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The C++ Programming Language

Fourth Edition

Bjarne Stroustrup

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Library of Congress Cataloging-in-Publication Data

Stroustrup, Bjarne.
     The C++ programming language / Bjarne Stroustrup.—Fourth edition.
         pages cm
     Includes bibliographical references and index.
     ISBN 978-0-321-56384-2 (pbk. : alk. paper)—ISBN 0-321-56384-0 (pbk. : alk. paper)
     1. C++ (Computer programming language) I. Title.

    QA76.73.C153 S77 2013
    005.13’3—dc23                                                                                           2013002159

Copyright © 2013 by Pearson Education, Inc.

All rights reserved. Printed in the United States of America. This publication is protected by copyright, and permission must be obtained from the publisher prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. To obtain permission to use material from this work, please submit a written request to Pearson Education, Inc., Permissions Department, One Lake Street, Upper Saddle River, New Jersey 07458, or you may fax your request to (201) 236-3290.

This book was typeset in Times and Helvetica by the author.

ISBN-13: 978-0-321-56384-2
ISBN-10:         0-321-56384-0

Text printed in the United States on recycled paper at Edwards Brothers Malloy in Ann Arbor, Michigan.
Second printing, June 2013

Preface

All problems in computer science can be solved by another level of indirection, except for the problem of too many layers of indirection.

– David J. Wheeler

C++ feels like a new language. That is, I can express my ideas more clearly, more simply, and more directly in C++11 than I could in C++98. Furthermore, the resulting programs are better checked by the compiler and run faster.

In this book, I aim for completeness. I describe every language feature and standard-library component that a professional programmer is likely to need. For each, I provide:

• Rationale: What kinds of problems is it designed to help solve? What principles underlie the design? What are the fundamental limitations?

• Specification: What is its definition? The level of detail is chosen for the expert programmer; the aspiring language lawyer can follow the many references to the ISO standard.

• Examples: How can it be used well by itself and in combination with other features? What are the key techniques and idioms? What are the implications for maintainability and performance?

The use of C++ has changed dramatically over the years and so has the language itself. From the point of view of a programmer, most of the changes have been improvements. The current ISO standard C++ (ISO/IEC 14882-2011, usually called C++11) is simply a far better tool for writing quality software than were previous versions. How is it a better tool? What kinds of programming styles and techniques does modern C++ support? What language and standard-library features support those techniques? What are the basic building blocks of elegant, correct, maintainable, and efficient C++ code? Those are the key questions answered by this book. Many answers are not the same as you would find with 1985, 1995, or 2005 vintage C++: progress happens.

C++ is a general-purpose programming language emphasizing the design and use of type-rich, lightweight abstractions. It is particularly suited for resource-constrained applications, such as those found in software infrastructures. C++ rewards the programmer who takes the time to master techniques for writing quality code. C++ is a language for someone who takes the task of programming seriously. Our civilization depends critically on software; it had better be quality software.

There are billions of lines of C++ deployed. This puts a premium on stability, so 1985 and 1995 C++ code still works and will continue to work for decades. However, for all applications, you can do better with modern C++; if you stick to older styles, you will be writing lower-quality and worse-performing code. The emphasis on stability also implies that standards-conforming code you write today will still work a couple of decades from now. All code in this book conforms to the 2011 ISO C++ standard.

This book is aimed at three audiences:

• C++ programmers who want to know what the latest ISO C++ standard has to offer,

• C programmers who wonder what C++ provides beyond C, and

• People with a background in application languages, such as Java, C#, Python, and Ruby, looking for something “closer to the machine” – something more flexible, something offering better compile-time checking, or something offering better performance.

Naturally, these three groups are not disjoint – a professional software developer masters more than just one programming language.

This book assumes that its readers are programmers. If you ask, “What’s a for-loop?” or “What’s a compiler?” then this book is not (yet) for you; instead, I recommend my Programming: Principles and Practice Using C++ to get started with programming and C++. Furthermore, I assume that readers have some maturity as software developers. If you ask “Why bother testing?” or say, “All languages are basically the same; just show me the syntax” or are confident that there is a single language that is ideal for every task, this is not the book for you.

What features does C++11 offer over and above C++98? A machine model suitable for modern computers with lots of concurrency. Language and standard-library facilities for doing systems-level concurrent programming (e.g., using multicores). Regular expression handling, resource management pointers, random numbers, improved containers (including, hash tables), and more. General and uniform initialization, a simpler for-statement, move semantics, basic Unicode support, lambdas, general constant expressions, control over class defaults, variadic templates, user-defined literals, and more. Please remember that those libraries and language features exist to support programming techniques for developing quality software. They are meant to be used in combination – as bricks in a building set – rather than to be used individually in relative isolation to solve a specific problem. A computer is a universal machine, and C++ serves it in that capacity. In particular, C++’s design aims to be sufficiently flexible and general to cope with future problems undreamed of by its designers.

Acknowledgments

In addition to the people mentioned in the acknowledgment sections of the previous editions, I would like to thank Pete Becker, Hans-J. Boehm, Marshall Clow, Jonathan Coe, Lawrence Crowl, Walter Daugherty, J. Daniel Garcia, Robert Harle, Greg Hickman, Howard Hinnant, Brian Kernighan, Daniel Krügler, Nevin Liber, Michel Michaud, Gary Powell, Jan Christiaan van Winkel, and Leor Zolman. Without their help this book would have been much poorer.

Thanks to Howard Hinnant for answering many questions about the standard library.

Andrew Sutton is the author of the Origin library, which was the testbed for much of the discussion of emulating concepts in the template chapters, and of the matrix library that is the topic of Chapter 29. The Origin library is open source and can be found by searching the Web for “Origin” and “Andrew Sutton.”

Thanks to my graduate design class for finding more problems with the “tour chapters” than anyone else.

Had I been able to follow every piece of advice of my reviewers, the book would undoubtedly have been much improved, but it would also have been hundreds of pages longer. Every expert reviewer suggested adding technical details, advanced examples, and many useful development conventions; every novice reviewer (or educator) suggested adding examples; and most reviewers observed (correctly) that the book may be too long.

Thanks to Princeton University’s Computer Science Department, and especially Prof. Brian Kernighan, for hosting me for part of the sabbatical that gave me time to write this book.

Thanks to Cambridge University’s Computer Lab, and especially Prof. Andy Hopper, for hosting me for part of the sabbatical that gave me time to write this book.

Thanks to my editor, Peter Gordon, and his production team at Addison-Wesley for their help and patience.

College Station, Texas

Bjarne Stroustrup

Preface to the Third Edition

Programming is understanding.

– Kristen Nygaard

I find using C++ more enjoyable than ever. C++’s support for design and programming has improved dramatically over the years, and lots of new helpful techniques have been developed for its use. However, C++ is not just fun. Ordinary practical programmers have achieved significant improvements in productivity, maintainability, flexibility, and quality in projects of just about any kind and scale. By now, C++ has fulfilled most of the hopes I originally had for it, and also succeeded at tasks I hadn’t even dreamt of.

This book introduces standard C++† and the key programming and design techniques supported by C++. Standard C++ is a far more powerful and polished language than the version of C++ introduced by the first edition of this book. New language features such as namespaces, exceptions, templates, and run-time type identification allow many techniques to be applied more directly than was possible before, and the standard library allows the programmer to start from a much higher level than the bare language.

† ISO/IEC 14882, Standard for the C++ Programming Language.

About a third of the information in the second edition of this book came from the first. This third edition is the result of a rewrite of even larger magnitude. It offers something to even the most experienced C++ programmer; at the same time, this book is easier for the novice to approach than its predecessors were. The explosion of C++ use and the massive amount of experience accumulated as a result makes this possible.

The definition of an extensive standard library makes a difference to the way C++ concepts can be presented. As before, this book presents C++ independently of any particular implementation, and as before, the tutorial chapters present language constructs and concepts in a “bottom up” order so that a construct is used only after it has been defined. However, it is much easier to use a well-designed library than it is to understand the details of its implementation. Therefore, the standard library can be used to provide realistic and interesting examples well before a reader can be assumed to understand its inner workings. The standard library itself is also a fertile source of programming examples and design techniques.

This book presents every major C++ language feature and the standard library. It is organized around language and library facilities. However, features are presented in the context of their use. That is, the focus is on the language as the tool for design and programming rather than on the language in itself. This book demonstrates key techniques that make C++ effective and teaches the fundamental concepts necessary for mastery. Except where illustrating technicalities, examples are taken from the domain of systems software. A companion, The Annotated C++ Language Standard, presents the complete language definition together with annotations to make it more comprehensible.

The primary aim of this book is to help the reader understand how the facilities offered by C++ support key programming techniques. The aim is to take the reader far beyond the point where he or she gets code running primarily by copying examples and emulating programming styles from other languages. Only a good understanding of the ideas behind the language facilities leads to mastery. Supplemented by implementation documentation, the information provided is sufficient for completing significant real-world projects. The hope is that this book will help the reader gain new insights and become a better programmer and designer.

Acknowledgments

In addition to the people mentioned in the acknowledgement sections of the first and second editions, I would like to thank Matt Austern, Hans Boehm, Don Caldwell, Lawrence Crowl, Alan Feuer, Andrew Forrest, David Gay, Tim Griffin, Peter Juhl, Brian Kernighan, Andrew Koenig, Mike Mowbray, Rob Murray, Lee Nackman, Joseph Newcomer, Alex Stepanov, David Vandevoorde, Peter Weinberger, and Chris Van Wyk for commenting on draft chapters of this third edition. Without their help and suggestions, this book would have been harder to understand, contained more errors, been slightly less complete, and probably been a little bit shorter.

I would also like to thank the volunteers on the C++ standards committees who did an immense amount of constructive work to make C++ what it is today. It is slightly unfair to single out individuals, but it would be even more unfair not to mention anyone, so I’d like to especially mention Mike Ball, Dag Brück, Sean Corfield, Ted Goldstein, Kim Knuttila, Andrew Koenig, Dmitry Lenkov, Nathan Myers, Martin O’Riordan, Tom Plum, Jonathan Shopiro, John Spicer, Jerry Schwarz, Alex Stepanov, and Mike Vilot, as people who each directly cooperated with me over some part of C++ and its standard library.

After the initial printing of this book, many dozens of people have mailed me corrections and suggestions for improvements. I have been able to accommodate many of their suggestions within the framework of the book so that later printings benefitted significantly. Translators of this book into many languages have also provided many clarifications. In response to requests from readers, I have added appendices D and E. Let me take this opportunity to thank a few of those who helped: Dave Abrahams, Matt Austern, Jan Bielawski, Janina Mincer Daszkiewicz, Andrew Koenig, Dietmar Kühl, Nicolai Josuttis, Nathan Myers, Paul E. Sevinç, Andy Tenne-Sens, Shoichi Uchida, Ping-Fai (Mike) Yang, and Dennis Yelle.

Murray Hill, New Jersey

Bjarne Stroustrup

Preface to the Second Edition

The road goes ever on and on.

– Bilbo Baggins

As promised in the first edition of this book, C++ has been evolving to meet the needs of its users. This evolution has been guided by the experience of users of widely varying backgrounds working in a great range of application areas. The C++ user-community has grown a hundredfold during the six years since the first edition of this book; many lessons have been learned, and many techniques have been discovered and/or validated by experience. Some of these experiences are reflected here.

The primary aim of the language extensions made in the last six years has been to enhance C++ as a language for data abstraction and object-oriented programming in general and to enhance it as a tool for writing high-quality libraries of user-defined types in particular. A “high-quality library,” is a library that provides a concept to a user in the form of one or more classes that are convenient, safe, and efficient to use. In this context, safe means that a class provides a specific type-safe interface between the users of the library and its providers; efficient means that use of the class does not impose significant overheads in run-time or space on the user compared with handwritten C code.

This book presents the complete C++ language. Chapters 1 through 10 give a tutorial introduction; Chapters 11 through 13 provide a discussion of design and software development issues; and, finally, the complete C++ reference manual is included. Naturally, the features added and resolutions made since the original edition are integral parts of the presentation. They include refined overloading resolution, memory management facilities, and access control mechanisms, type-safe linkage, const and static member functions, abstract classes, multiple inheritance, templates, and exception handling.

C++ is a general-purpose programming language; its core application domain is systems programming in the broadest sense. In addition, C++ is successfully used in many application areas that are not covered by this label. Implementations of C++ exist from some of the most modest microcomputers to the largest supercomputers and for almost all operating systems. Consequently, this book describes the C++ language itself without trying to explain a particular implementation, programming environment, or library.

This book presents many examples of classes that, though useful, should be classified as “toys.” This style of exposition allows general principles and useful techniques to stand out more clearly than they would in a fully elaborated program, where they would be buried in details. Most of the useful classes presented here, such as linked lists, arrays, character strings, matrices, graphics classes, associative arrays, etc., are available in “bulletproof” and/or “goldplated” versions from a wide variety of commercial and non-commercial sources. Many of these “industrial strength” classes and libraries are actually direct and indirect descendants of the toy versions found here.

This edition provides a greater emphasis on tutorial aspects than did the first edition of this book. However, the presentation is still aimed squarely at experienced programmers and endeavors not to insult their intelligence or experience. The discussion of design issues has been greatly expanded to reflect the demand for information beyond the description of language features and their immediate use. Technical detail and precision have also been increased. The reference manual, in particular, represents many years of work in this direction. The intent has been to provide a book with a depth sufficient to make more than one reading rewarding to most programmers. In other words, this book presents the C++ language, its fundamental principles, and the key techniques needed to apply it. Enjoy!

Acknowledgments

In addition to the people mentioned in the acknowledgements section in the preface to the first edition, I would like to thank Al Aho, Steve Buroff, Jim Coplien, Ted Goldstein, Tony Hansen, Lorraine Juhl, Peter Juhl, Brian Kernighan, Andrew Koenig, Bill Leggett, Warren Montgomery, Mike Mowbray, Rob Murray, Jonathan Shopiro, Mike Vilot, and Peter Weinberger for commenting on draft chapters of this second edition. Many people influenced the development of C++ from 1985 to 1991. I can mention only a few: Andrew Koenig, Brian Kernighan, Doug McIlroy, and Jonathan Shopiro. Also thanks to the many participants of the “external reviews” of the reference manual drafts and to the people who suffered through the first year of X3J16.

Murray Hill, New Jersey

Bjarne Stroustrup

Preface to the First Edition

Language shapes the way we think, and determines what we can think about.

– B.L.Whorf

C++ is a general purpose programming language designed to make programming more enjoyable for the serious programmer. Except for minor details, C++ is a superset of the C programming language. In addition to the facilities provided by C, C++ provides flexible and efficient facilities for defining new types. A programmer can partition an application into manageable pieces by defining new types that closely match the concepts of the application. This technique for program construction is often called data abstraction. Objects of some user-defined types contain type information. Such objects can be used conveniently and safely in contexts in which their type cannot be determined at compile time. Programs using objects of such types are often called object based. When used well, these techniques result in shorter, easier to understand, and easier to maintain programs.

The key concept in C++ is class. A class is a user-defined type. Classes provide data hiding, guaranteed initialization of data, implicit type conversion for user-defined types, dynamic typing, user-controlled memory management, and mechanisms for overloading operators. C++ provides much better facilities for type checking and for expressing modularity than C does. It also contains improvements that are not directly related to classes, including symbolic constants, inline substitution of functions, default function arguments, overloaded function names, free store management operators, and a reference type. C++ retains C’s ability to deal efficiently with the fundamental objects of the hardware (bits, bytes, words, addresses, etc.). This allows the user-defined types to be implemented with a pleasing degree of efficiency.

C++ and its standard libraries are designed for portability. The current implementation will run on most systems that support C. C libraries can be used from a C++ program, and most tools that support programming in C can be used with C++.

This book is primarily intended to help serious programmers learn the language and use it for nontrivial projects. It provides a complete description of C++, many complete examples, and many more program fragments.

Acknowledgments

C++ could never have matured without the constant use, suggestions, and constructive criticism of many friends and colleagues. In particular, Tom Cargill, Jim Coplien, Stu Feldman, Sandy Fraser, Steve Johnson, Brian Kernighan, Bart Locanthi, Doug McIlroy, Dennis Ritchie, Larry Rosler, Jerry Schwarz, and Jon Shopiro provided important ideas for development of the language. Dave Presotto wrote the current implementation of the stream I/O library.

In addition, hundreds of people contributed to the development of C++ and its compiler by sending me suggestions for improvements, descriptions of problems they had encountered, and compiler errors. I can mention only a few: Gary Bishop, Andrew Hume, Tom Karzes, Victor Milenkovic, Rob Murray, Leonie Rose, Brian Schmult, and Gary Walker.

Many people have also helped with the production of this book, in particular, Jon Bentley, Laura Eaves, Brian Kernighan, Ted Kowalski, Steve Mahaney, Jon Shopiro, and the participants in the C++ course held at Bell Labs, Columbus, Ohio, June 26-27, 1985.

Murray Hill, New Jersey

Bjarne Stroustrup

Part I: Introduction

This introduction gives an overview of the major concepts and features of the C++ programming language and its standard library. It also provides an overview of this book and explains the approach taken to the description of the language facilities and their use. In addition, the introductory chapters present some background information about C++, the design of C++, and the use of C++.

Chapters

1 Notes to the Reader

2 A Tour of C++: The Basics

3 A Tour of C++: Abstraction Mechanisms

4 A Tour of C++: Containers and Algorithms

5 A Tour of C++: Concurrency and Utilities

“... and you, Marcus, you have given me many things; now I shall give you this good advice. Be many people. Give up the game of being always Marcus Cocoza. You have worried too much about Marcus Cocoza, so that you have been really his slave and prisoner. You have not done anything without first considering how it would affect Marcus Cocoza’s happiness and prestige. You were always much afraid that Marcus might do a stupid thing, or be bored. What would it really have mattered? All over the world people are doing stupid things ... I should like you to be easy, your little heart to be light again. You must from now, be more than one, many people, as many as you can think of ...”

– Karen Blixen,
The Dreamers from Seven Gothic Tales (1934)

1. Notes to the Reader

Hurry Slowly (festina lente).

– Octavius, Caesar Augustus

• The Structure of This Book

Introduction; Basic Facilities; Abstraction Mechanisms; The Standard Library; Examples and References

• The Design of C++

Programming Styles; Type Checking; C Compatibility; Language, Libraries, and Systems

• Learning C++

Programming in C++; Suggestions for C++ Programmers; Suggestions for C Programmers; Suggestions for Java Programmers

• History

Timeline; The Early Years; The 1998 Standard; The 2011 Standard; What is C++ Used for?

• Advice

• References

1.1. The Structure of This Book

A pure tutorial sorts its topics so that no concept is used before it has been introduced; it must be read linearly starting with page one. Conversely, a pure reference manual can be accessed starting at any point; it describes each topic succinctly with references (forward and backward) to related topics. A pure tutorial can in principle be read without prerequisites – it carefully describes all. A pure reference can be used only by someone familiar with all fundamental concepts and techniques. This book combines aspects of both. If you know most concepts and techniques, you can access it on a per-chapter or even on a per-section basis. If not, you can start at the beginning, but try not to get bogged down in details. Use the index and the cross-references.

Making parts of the book relatively self-contained implies some repetition, but repetition also serves as review for people reading the book linearly. The book is heavily cross-referenced both to itself and to the ISO C++ standard. Experienced programmers can read the (relatively) quick “tour” of C++ to gain the overview needed to use the book as a reference. This book consists of four parts:

Part I

Introduction: Chapter 1 (this chapter) is a guide to this book and provides a bit of C++ background. Chapters 2-5 give a quick introduction to the C++ language and its standard library.

Part II

Basic Facilities: Chapters 6-15 describe C++’s built-in types and the basic facilities for constructing programs out of them.

Part III

Abstraction Mechanisms: Chapters 16-29 describe C++’s abstraction mechanisms and their use for object-oriented and generic programming.

Part IV

Chapters 30-44 provide an overview of the standard library and a discussion of compatibility issues.

1.1.1. Introduction

This chapter, Chapter 1, provides an overview of this book, some hints about how to use it, and some background information about C++ and its use. You are encouraged to skim through it, read what appears interesting, and return to it after reading other parts of the book. Please do not feel obliged to read it all carefully before proceeding.

The following chapters provide an overview of the major concepts and features of the C++ programming language and its standard library:

Chapter 2

A Tour of C++: The Basics describes C++’s model of memory, computation, and error handling.

Chapter 3

A Tour of C++: Abstraction Mechanisms presents the language features supporting data abstraction, object-oriented programming, and generic programming.

Chapter 4

A Tour of C++: Containers and Algorithms introduces strings, simple I/O, containers, and algorithms as provided by the standard library.

Chapter 5

A Tour of C++: Concurrency and Utilities outlines the standard-library utilities related to resource management, concurrency, mathematical computation, regular expressions, and more.

This whirlwind tour of C++’s facilities aims to give the reader a taste of what C++ offers. In particular, it should convince readers that C++ has come a long way since the first, second, and third editions of this book.

1.1.2. Basic Facilities

Part II focuses on the subset of C++ that supports the styles of programming traditionally done in C and similar languages. It introduces the notions of type, object, scope, and storage. It presents the fundamentals of computation: expressions, statements, and functions. Modularity – as supported by namespaces, source files, and exception handling – is also discussed:

Chapter 6

Types and Declarations: Fundamental types, naming, scopes, initialization, simple type deduction, object lifetimes, and type aliases

Chapter 7

Pointers, Arrays, and References

Chapter 8

Structures, Unions, and Enumerations

Chapter 9

Statements: Declarations as statements, selection statements (if and switch), iteration statements (for, while, and do), goto, and comments

Chapter 10

Expressions: A desk calculator example, survey of operators, constant expressions, and implicit type conversion.

Chapter 11

Select Operations: Logical operators, the conditional expression, increment and decrement, free store (new and delete), {}-lists, lambda expressions, and explicit type conversion (static_cast and const_cast)

Chapter 12

Functions: Function declarations and definitions, inline functions, constexpr functions, argument passing, overloaded functions, pre- and postconditions, pointers to functions, and macros

Chapter 13

Exception Handling: Styles of error handling, exception guarantees, resource management, enforcing invariants, throw and catch, a vector implementation

Chapter 14

Namespaces: namespace, modularization and interface, composition using namespaces

Chapter 15

Source Files and Programs: Separate compilation, linkage, using header files, and program start and termination

I assume that you are familiar with most of the programming concepts used in Part I. For example, I explain the C++ facilities for expressing recursion and iteration, but I do not go into technical details or spend much time explaining how these concepts are useful.

The exception to this rule is exceptions. Many programmers lack experience with exceptions or got their experience from languages (such as Java) where resource management and exception handling are not integrated. Consequently, the chapter on exception handling (Chapter 13) presents the basic philosophy of C++ exception handling and resource management. It goes into some detail about strategy with a focus on the “Resource Acquisition Is Initialization” technique (RAII).

1.1.3. Abstraction Mechanisms

Part III describes the C++ facilities supporting various forms of abstraction, including object-oriented and generic programming. The chapters fall into three rough categories: classes, class hierarchies, and templates.

The first four chapters concentrate of the classes themselves:

Chapter 16

Classes: The notion of a user-defined type, a class, is the foundation of all C++ abstraction mechanisms.

Chapter 17

Construction, Cleanup, Copy, and Move shows how a programmer can define the meaning of creation and initialization of objects of a class. Further, the meaning of copy, move, and destruction can be specified.

Chapter 18

Operator Overloading presents the rules for giving meaning to operators for user-defined types with an emphasis on conventional arithmetic and logical operators, such as +, *, and &.

Chapter 19

Special Operators discusses the use of user-defined operator for non-arithmetic purposes, such as [] for subscripting, () for function objects, and –> for “smart pointers.”

Classes can be organized into hierarchies:

Chapter 20

Derived Classes presents the basic language facilities for building hierarchies out of classes and the fundamental ways of using them. We can provide complete separation between an interface (an abstract class) and its implementations (derived classes); the connection between them is provided by virtual functions. The C++ model for access control (public, protected, and private) is presented.

Chapter 21

Class Hierarchies discusses ways of using class hierarchies effectively. It also presents the notion of multiple inheritance, that is, a class having more than one direct base class.

Chapter 22

Run-Time Type Information presents ways to navigate class hierarchies using data stored in objects. We can use dynamic_cast to inquire whether an object of a base class was defined as an object of a derived class and use the typeid to gain minimal information from an object (such as the name of its class).

Many of the most flexible, efficient, and useful abstractions involve the parameterization of types (classes) and algorithms (functions) with other types and algorithms:

Chapter 23

Templates presents the basic principles behind templates and their use. Class templates, function templates, and template aliases are presented.

Chapter 24

Generic Programming introduces the basic techniques for designing generic programs. The technique of lifting an abstract algorithm from a number of concrete code examples is central, as is the notion of concepts specifying a generic algorithm’s requirements on its arguments.

Chapter 25

Specialization describes how templates are used to generate classes and functions, specializations, given a set of template arguments.

Chapter 26

Instantiation focuses on the rules for name binding.

Chapter 27

Templates and Hierarchies explains how templates and class hierarchies can be used in combination.

Chapter 28

Metaprogramming explores how templates can be used to generate programs. Templates provide a Turing-complete mechanism for generating code.

Chapter 29

A Matrix Design gives a longish example to show how language features can be used in combination to solve a complex design problem: the design of an N-dimensional matrix with near-arbitrary element types.

The language features supporting abstraction techniques are described in the context of those techniques. The presentation technique in Part III differs from that of Part II in that I don’t assume that the reader knows the techniques described.

1.1.4. The Standard Library

The library chapters are less tutorial than the language chapters. In particular, they are meant to be read in any order and can be used as a user-level manual for the library components:

Chapter 30

Standard-Library Overview gives an overview of the standard library, lists the standard-library headers, and presents language support and diagnostics support, such as exception and system_error.

Chapter 31

STL Containers presents the containers from the iterators, containers, and algorithms framework (called the STL), including vector, map, and unordered_set.

Chapter 32

STL Algorithms presents the algorithms from the STL, including find(), sort(), and merge().

Chapter 33

STL Iterators presents iterators and other utilities from the STL, including reverse_iterator, move_iterator, and function.

Chapter 34

Memory and Resources presents utility components related to memory and resource management, such as array, bitset, pair, tuple, unique_ptr, shared_ptr, allocators, and the garbage collector interface.

Chapter 35

Utilities presents minor utility components, such as time utilities, type traits, and various type functions.

Chapter 36

Strings documents the string library, including the character traits that are the basis for the use of different character sets.

Chapter 37

Regular Expressions describes the regular expression syntax and the various ways of using it for string matching, including regex_match() for matching a complete string, regex_search() for finding a pattern in a string, regex_replace() for simple replacement, and regex_iterator for general traversal of a stream of characters.

Chapter 38

I/O Streams documents the stream I/O library. It describes formatted and unformatted input and output, error handling, and buffering.

Chapter 39

Locales describes class locale and its various facets that provide support for the handling of cultural differences in character sets, formatting of numeric values, formatting of date and time, and more.

Chapter 40

Numerics describes facilities for numerical computation (such as complex, valarray, random numbers, and generalized numerical algorithms).

Chapter 41

Concurrency presents the C++ basic memory model and the facilities offered for concurrent programming without locks.

Chapter 42

Threads and Tasks presents the classes providing threads-and-locks-style concurrent programming (such as thread, timed_mutex, lock_guard, and try_lock()) and the support for task-based concurrency (such as future and async()).

Chapter 43

The C Standard Library documents the C standard library (including printf() and clock()) as incorporated into the C++ standard library.

Chapter 44

Compatibility discusses the relation between C and C++ and between Standard C++ (also called ISO C++) and the versions of C++ that preceded it.

1.1.5. Examples and References

This book emphasizes program organization rather than the design of algorithms. Consequently, I avoid clever or harder-to-understand algorithms. A trivial algorithm is typically better suited to illustrate an aspect of the language definition or a point about program structure. For example, I use a Shell sort where, in real code, a quicksort would be better. Often, reimplementation with a more suitable algorithm is an exercise. In real code, a call of a library function is typically more appropriate than the code used here to illustrate language features.

Textbook examples necessarily give a warped view of software development. By clarifying and simplifying the examples, the complexities that arise from scale disappear. I see no substitute for writing realistically sized programs in order to get an impression of what programming and a programming language are really like. This book concentrates on the language features and the standard-library facilities. These are the basic techniques from which every program is composed. The rules and techniques for such composition are emphasized.

The selection of examples reflects my background in compilers, foundation libraries, and simulations. The emphasis reflects my interest in systems programming. Examples are simplified versions of what is found in real code. The simplification is necessary to keep programming language and design points from getting lost in details. My ideal is the shortest and clearest example that illustrates a design principle, a programming technique, a language construct, or a library feature. There are no “cute” examples without counterparts in real code. For purely language-technical examples, I use variables named x and y, types called A and B, and functions called f() and g().

Where possible, the C++ language and library features are presented in the context of their use rather than in the dry manner of a manual. The language features presented and the detail in which they are described roughly reflect my view of what is needed for effective use of C++. The purpose is to give you an idea of how a feature can be used, often in combination with other features. An understanding of every language-technical detail of a language feature or library component is neither necessary nor sufficient for writing good programs. In fact, an obsession with understanding every little detail is a prescription for awful – overelaborate and overly clever – code. What is needed is an understanding of design and programming techniques together with an appreciation of application domains.

I assume that you have access to online information sources. The final arbiter of language and standard-library rules is the ISO C++ standard [C++,2011].

References to parts of this book are of the form §2.3.4 (Chapter 2, section 3, subsection 4) and §iso.5.3.1 (ISO C++ standard, §5.3.1). Italics are used sparingly for emphasis (e.g., “a string literal is not acceptable”), for first occurrences of important concepts (e.g., polymorphism), and for comments in code examples.

To save a few trees and to simplify additions, the hundreds of exercises for this book have been moved to the Web. Look for them at www.stroustrup.com.

The language and library used in this book are “pure C++” as defined by the C++ standard [C++,2011]. Therefore, the examples should run on every up-to-date C++ implementation. The major program fragments in this book were tried using several C++ implementations. Examples using features only recently adopted into C++ didn’t compile on every implementation. However, I see no point in mentioning which implementations failed to compile which examples. Such information would soon be out of date because implementers are working hard to ensure that their implementations correctly accept every C++ feature. See Chapter 44 for suggestions on how to cope with older C++ compilers and with code written for C compilers.

I use C++11 features freely wherever I find them most appropriate. For example, I prefer {}-style initializers and using for type aliases. In places, that usage may startle “old timers.” However, being startled is often a good way to start reviewing material. On the other hand, I don’t use new features just because they are new; my ideal is the most elegant expression of the fundamental ideas – and that may very well be using something that has been in C++ or even in C for ages.

Obviously, if you have to use a pre-C++11 compiler (say, because some of your customers have not yet upgraded to the current standard), you have to refrain from using novel features. However, please don’t assume that “the old ways” are better or simpler just because they are old and familiar. §44.2 summarizes the differences between C++98 and C++11.

1.2. The Design of C++

The purpose of a programming language is to help express ideas in code. In that, a programming language performs two related tasks: it provides a vehicle for the programmer to specify actions to be executed by the machine, and it provides a set of concepts for the programmer to use when thinking about what can be done. The first purpose ideally requires a language that is “close to the machine” so that all important aspects of a machine are handled simply and efficiently in a way that is reasonably obvious to the programmer. The C language was primarily designed with this in mind. The second purpose ideally requires a language that is “close to the problem to be solved” so that the concepts of a solution can be expressed directly and concisely. The facilities added to C to create C++, such as function argument checking, const, classes, constructors and destructors, exceptions, and templates, were primarily designed with this in mind. Thus, C++ is based on the idea of providing both

• direct mappings of built-in operations and types to hardware to provide efficient memory use and efficient low-level operations, and

• affordable and flexible abstraction mechanisms to provide user-defined types with the same notational support, range of uses, and performance as built-in types.

This was initially achieved by applying ideas from Simula to C. Over the years, further application of these simple ideals resulted in a far more general, efficient, and flexible set of facilities. The result supports a synthesis of programming styles that can be simultaneously efficient and elegant.

The design of C++ has focused on programming techniques dealing with fundamental notions such as memory, mutability, abstraction, resource management, expression of algorithms, error handling, and modularity. Those are the most important concerns of a systems programmer and more generally of programmers of resource-constrained and high-performance systems.

By defining libraries of classes, class hierarchies, and templates, you can write C++ programs at a much higher level than the one presented in this book. For example, C++ is widely used in financial systems, for game development, and for scientific computation (§1.4.5). For high-level applications programming to be effective and convenient, we need libraries. Using just the bare language features makes almost all programming quite painful. That’s true for every general-purpose language. Conversely, given suitable libraries just about any programming task can be pleasant.

My standard introduction of C++ used to start:

• C++ is a general-purpose programming language with a bias toward systems programming.

This is still true. What has changed over the years is an increase in the importance, power, and flexibility of C++’s abstraction mechanisms:

• C++ is a general-purpose programming language providing a direct and efficient model of hardware combined with facilities for defining lightweight abstractions.

Or terser:

• C++ is a language for developing and using elegant and efficient abstractions.

By general-purpose programming language I mean a language designed to support a wide variety of uses. C++ has indeed been used for an incredible variety of uses (from microcontrollers to huge distributed commercial applications), but the key point is that C++ is not deliberately specialized for any given application area. No language is ideal for every application and every programmer, but the ideal for C++ is to support the widest possible range of application areas well.

By systems programming I mean writing code that directly uses hardware resources, has serious resource constraints, or closely interacts with code that does. In particular, the implementation of software infrastructure (e.g., device drivers, communications stacks, virtual machines, operating systems, operations systems, programming environments, and foundation libraries) is mostly systems programming. The importance of the “bias toward systems programming” qualification in my long-standing characterization of C++ is that C++ has not been simplified (compromised) by ejecting the facilities aimed at the expert-level use of hardware and systems resources in the hope of making it more suitable for other application areas.

Of course, you can also program in ways that completely hide hardware, use expensive abstractions (e.g., every object on the free store and every operation a virtual function), use inelegant styles (e.g., overabstraction), or use essentially no abstractions (“glorified assembly code”). However, many languages can do that, so those are not distinguishing characteristics of C++.

The Design and Evolution of C++ book [Stroustrup,1994] (known as D&E) outlines the ideas and design aims of C++ in greater detail, but two principles should be noted:

• Leave no room for a lower-level language below C++ (except for assembly code in rare cases). If you can write more efficient code in a lower-level language then that language will most likely become the systems programming language of choice.

• What you don’t use you don’t pay for. If programmers can hand-write reasonable code to simulate a language feature or a fundamental abstraction and provide even slightly better performance, someone will do so, and many will imitate. Therefore, a language feature and a fundamental abstraction must be designed not to waste a single byte or a single processor cycle compared to equivalent alternatives. This is known as the zero-overhead principle.

These are Draconian principles, but essential in some (but obviously not all) contexts. In particular, the zero-overhead principle repeatedly led C++ to simpler, more elegant, and more powerful facilities than were first envisioned. The STL is an example (§4.1.1, §4.4, §4.5, Chapter 31, Chapter 32, Chapter 33). These principles have been essential in the effort to raise the level of programming.

1.2.1. Programming Style

Languages features exist to provide support for programming styles. Please don’t look at an individual language feature as a solution, but as one building brick from a varied set which can be combined to express solutions.

The general ideals for design and programming can be expressed simply:

• Express ideas directly in code.

• Express independent ideas independently in code.

• Represent relationships among ideas directly in code.

• Combine ideas expressed in code freely – where and only where combinations make sense.

• Express simple ideas simply.

These are ideals shared by many people, but languages designed to support them can differ dramatically. A fundamental reason for that is that a language embodies a set of engineering tradeoffs reflecting differing needs, tastes, and histories of various individuals and communities. C++’s answers to the general design challenges were shaped by its origins in systems programming (going back to C and BCPL [Richards,1980]), its aim to address issues of program complexity through abstraction (going back to Simula), and its history.

The C++ language features most directly support four programming styles:

• Procedural programming

• Data abstraction

• Object-oriented programming

• Generic programming

However, the emphasis is on the support of effective combinations of those. The best (most maintainable, most readable, smallest, fastest, etc.) solution to most nontrivial problems tends to be one that combines aspects of these styles.

As is usual with important terms in the computing world, a wide variety of definitions of these terms are popular in various parts of the computing industry and academia. For example, what I refer to as a “programming style,” others call a “programming technique” or a “paradigm.” I prefer to use “programming technique” for something more limited and language-specific. I feel uncomfortable with the word “paradigm” as pretentious and (from Kuhn’s original definition) having implied claims of exclusivity.

My ideal is language facilities that can be used elegantly in combination to support a continuum of programming styles and a wide variety of programming techniques.

• Procedural programming: This is programming focused on processing and the design of suitable data structures. It is what C was designed to support (and Algol, and Fortran, as well as many other languages). C++’s support comes in the form of the built-in types, operators, statements, functions, structs, unions, etc. With minor exceptions, C is a subset of C++. Compared to C, C++ provides further support for procedural programming in the form of many additional language constructs and a stricter, more flexible, and more supportive type system.

• Data abstraction: This is programming focused on the design of interfaces, hiding implementation details in general and representations in particular. C++ supports concrete and abstract classes. The facilities for defining classes with private implementation details, constructors and destructors, and associated operations directly support this. The notion of an abstract class provides direct support for complete data hiding.

• Object-oriented programming: This is programming focused on the design, implementation, and use of class hierarchies. In addition to allowing the definition lattices of classes, C++ provides a variety of features for navigating class lattices and for simplifying the definition of a class out of existing ones. Class hierarchies provide run-time polymorphism (§20.3.2, §21.2) and encapsulation (§20.4, §20.5).

• Generic programming: This is programming focused on the design, implementation, and use of general algorithms. Here, “general” means that an algorithm can be designed to accept a wide variety of types as long as they meet the algorithm’s requirements on its arguments. The template is C++’s main support for generic programming. Templates provide (compile-time) parametric polymorphism.

Just about anything that increases the flexibility or efficiency of classes improves the support of all of those styles. Thus, C++ could be (and has been) called class oriented.

Each of these styles of design and programming has contributed to the synthesis that is C++. Focusing exclusively on one of these styles is a mistake: except for toy examples, doing so leads to wasted development effort and suboptimal (inflexible, verbose, poorly performing, unmaintainable, etc.) code.

I wince when someone characterizes C++ exclusively through one of these styles (e.g., “C++ is an object-oriented language”) or uses a term (e.g., “hybrid” or “mixed paradigm”) to imply that a more restrictive language would be preferable. The former misses the fact that all the styles mentioned have contributed something significant to the synthesis; the latter denies the validity of the synthesis. The styles mentioned are not distinct alternatives: each contributes techniques to a more expressive and effective style of programming, and C++ provides direct language support for their use in combination.

From its inception, the design of C++ aimed at a synthesis of programming and design styles. Even the earliest published account of C++ [Stroustrup,1982] presents examples that use these different styles in combination and presents language features aimed at supporting such combinations:

• Classes support all of the mentioned styles; all rely on the user representing ideas as user-defined types or objects of user-defined types.

• Public/private access control supports data abstraction and object-oriented programming by making a clear distinction between interface and implementation.

• Member functions, constructors, destructors, and user-defined assignment provide a clean functional interface to objects as needed by data abstraction and object-oriented programming. They also provide a uniform notation as needed for generic programming. More general overloading had to wait until 1984 and uniform initialization until 2010.

• Function declarations provide specific statically checked interfaces to member functions as well as freestanding functions, so they support all of the mentioned styles. They are necessary for overloading. At the time, C lacked “function prototypes” but Simula had function declarations as well as member functions.

• Generic functions and parameterized types (generated from functions and classes using macros) support generic programming. Templates had to wait until 1988.

• Base and derived classes provide the foundation for object-oriented programming and some forms of data abstraction. Virtual functions had to wait until 1983.

• Inlining made the use of these facilities affordable in systems programming and for building run-time and space efficient libraries.

These early features are general abstraction mechanisms, rather than support for disjoint programming styles. Today’s C++ provides much better support for design and programming based on lightweight abstraction, but the aim of elegant and efficient code was there from the very beginning. The developments since 1981 provide much better support for the synthesis of the programming styles (“paradigms”) originally considered and significantly improve their integration.

The fundamental object in C++ has identity; that is, it is located in a specific location in memory and can be distinguished from other objects with (potentially) the same value by comparing addresses. Expressions denoting such objects are called lvalues (§6.4). However, even from the earliest days of C++’s ancestors [Barron,1963] there have also been objects without identity (objects for which an address cannot be safely stored for later use). In C++11, this notion of rvalue has been developed into a notion of a value that can be moved around cheaply (§3.3.2, §6.4.1, §7.7.2). Such objects are the basis of techniques that resemble what is found in functional programming (where the notion of objects with identity is viewed with horror). This nicely complements the techniques and language features (e.g., lambda expressions) developed primarily for generic programming. It also solves classical problems related to “simple abstract data types,” such as how to elegantly and efficiently return a large matrix from an operation (e.g., a matrix +).

From the very earliest days, C++ programs and the design of C++ itself have been concerned about resource management. The ideal was (and is) for resource management to be

• simple (for implementers and especially for users),

• general (a resource is anything that has to be acquired from somewhere and later released),

• efficient (obey the zero-overhead principle; §1.2),

• perfect (no leaks are acceptable), and

• statically type-safe.

Many important C++ classes, such as the standard library’s vector, string, thread, mutex, unique_ptr, fstream, and regex, are resource handles. Foundation and application libraries beyond the standard provided many more examples, such as Matrix and Widget. The initial step in supporting the notion of resource handles was taken with the provision of constructors and destructors in the very first “C with Classes” draft. This was soon backed with the ability to control copy by defining assignment as well as copy constructors. The introduction of move constructors and move assignments (§3.3) in C++11 completes this line of thinking by allowing cheap movement of potentially large objects from scope to scope (§3.3.2) and to simply control the lifetime of polymorphic or shared objects (§5.2.1).

The facilities supporting resource management also benefit abstractions that are not resource handles. Any class that establishes and maintains an invariant relies on a subset of those features.

1.2.2. Type Checking

The connection between the language in which we think/program and the problems and solutions we can imagine is very close. For this reason, restricting language features with the intent of eliminating programmer errors is, at best, dangerous. A language provides a programmer with a set of conceptual tools; if these are inadequate for a task, they will be ignored. Good design and the absence of errors cannot be guaranteed merely by the presence or absence of specific language features. However, the language features and the type system are provided for the programmer to precisely and concisely represent a design in code.

The notion of static types and compile-time type checking is central to effective use of C++. The use of static types is key to expressiveness, maintainability, and performance. Following Simula, the design of user-defined types with interfaces that are checked at compile time is key to the expressiveness of C++. The C++ type system is extensible in nontrivial ways (Chapter 3, Chapter 16, Chapter 18, Chapter 19, Chapter 21, Chapter 23, Chapter 28, Chapter 29), aiming for equal support for built-in types and user-defined types.

C++ type-checking and data-hiding features rely on compile-time analysis of programs to prevent accidental corruption of data. They do not provide secrecy or protection against someone who is deliberately breaking the rules: C++ protects against accident, not against fraud. They can, however, be used freely without incurring run-time or space overheads. The idea is that to be useful, a language feature must not only be elegant, it must also be affordable in the context of a real-world program.

C++’s static type system is flexible, and the use of simple user-defined types implies little, if any overhead. The aim is to support a style of programming that represents distinct ideas as distinct types, rather than just using generalizations, such as integer, floating-point number, string, “raw memory,” and “object,” everywhere. A type-rich style of programming makes code more readable, maintainable, and analyzable. A trivial type system allows only trivial analysis, whereas a type-rich style of programming opens opportunities for nontrivial error detection and optimization. C++ compilers and development tools support such type-based analysis [Stroustrup,2012].

Maintaining most of C as a subset and preserving the direct mapping to hardware needed for the most demanding low-level systems programming tasks implies the ability to break the static type system. However, my ideal is (and always was) complete type safety. In this, I agree with Dennis Ritchie, who said, “C is a strongly typed, weakly checked language.” Note that Simula was both type-safe and flexible. In fact, my ideal when I started on C++ was “Algol68 with Classes” rather than “C with Classes.” However, the list of solid reasons against basing my work on type-safe Algol68 [Woodward,1974] was long and painful. So, perfect type safety is an ideal that C++ as a language can only approximate. But it is an ideal that C++ programmers (especially library builders) can strive for. Over the years, the set of language features, standard-library components, and techniques supporting that ideal has grown. Outside of low-level sections of code (hopefully isolated by type-safe interfaces), code that interfaces to code obeying different language conventions (e.g., an operating system call interface), and the implementations of fundamental abstractions (e.g., string and vector), there is now little need for type-unsafe code.

1.2.3. C Compatibility

C++ was developed from the C programming language and, with few exceptions, retains C as a subset. The main reasons for relying on C were to build on a proven set of low-level language facilities and to be part of a technical community. Great importance was attached to retaining a high degree of compatibility with C [Koenig,1989] [Stroustrup,1994] (Chapter 44); this (unfortunately) precluded cleaning up the C syntax. The continuing, more or less parallel evolution of C and C++ has been a constant source of concern and requires constant attention [Stroustrup,2002]. Having two committees devoted to keeping two widely used languages “as compatible as possible” is not a particularly good way of organizing work. In particular, there are differences in opinion as to the value of compatibility, differences in opinion on what constitutes good programming, and differences in opinion on what support is needed for good programming. Just keeping up communication between the committees is a large amount of work.

One hundred percent C/C++ compatibility was never a goal for C++ because that would compromise type safety and the smooth integration of user-defined and built-in types. However, the definition of C++ has been repeatedly reviewed to remove gratuitous incompatibilities; C++ is now more compatible with C than it was originally. C++98 adopted many details from C89 (§44.3.1). When C then evolved from C89 [C,1990] to C99 [C,1999], C++ adopted almost all of the new features, leaving out VLAs (variable-length arrays) as a misfeature and designated initializers as redundant. C’s facilities for low-level systems programming tasks are retained and enhanced; for example, see inlining (§3.2.1.1, §12.1.5, §16.2.8) and constexpr (§2.2.3, §10.4, §12.1.6).

Conversely, modern C has adopted (with varying degrees of faithfulness and effectiveness) many features from C++ (e.g., const, function prototypes, and inlining; see [Stroustrup,2002]).

The definition of C++ has been revised to ensure that a construct that is both legal C and legal C++ has the same meaning in both languages (§44.3).

One of the original aims for C was to replace assembly coding for the most demanding systems programming tasks. When C++ was designed, care was taken not to compromise the gains in this area. The difference between C and C++ is primarily in the degree of emphasis on types and structure. C is expressive and permissive. Through extensive use of the type system, C++ is even more expressive without loss of performance.

Knowing C is not a prerequisite for learning C++. Programming in C encourages many techniques and tricks that are rendered unnecessary by C++ language features. For example, explicit type conversion (casting) is less frequently needed in C++ than it is in C (§1.3.3). However, good C programs tend to be C++ programs. For example, every program in Kernighan and Ritchie, The C Programming Language, Second Edition [Kernighan,1988], is a C++ program. Experience with any statically typed language will be a help when learning C++.

1.2.4. Language, Libraries, and Systems

The C++ fundamental (built-in) types, operators, and statements are those that computer hardware deals with directly: numbers, characters, and addresses. C++ has no built-in high-level data types and no high-level primitive operations. For example, the C++ language does not provide a matrix type with an inversion operator or a string type with a concatenation operator. If a user wants such a type, it can be defined in the language itself. In fact, defining a new general-purpose or application-specific type is the most fundamental programming activity in C++. A well-designed user-defined type differs from a built-in type only in the way it is defined, not in the way it is used. The C++ standard library (Chapter 4, Chapter 5, Chapter 30, Chapter 31, etc.) provides many examples of such types and their uses. From a user’s point of view, there is little difference between a built-in type and a type provided by the standard library. Except for a few unfortunate and unimportant historical accidents, the C++ standard library is written in C++. Writing the C++ standard library in C++ is a crucial test of the C++ type system and abstraction mechanisms: they must be (and are) sufficiently powerful (expressive) and efficient (affordable) for the most demanding systems programming tasks. This ensures that they can be used in large systems that typically consist of layer upon layer of abstraction.

Features that would incur run-time or memory overhead even when not used were avoided. For example, constructs that would make it necessary to store “housekeeping information” in every object were rejected, so if a user declares a structure consisting of two 16-bit quantities, that structure will fit into a 32-bit register. Except for the new, delete, typeid, dynamic_cast, and throw operators, and the try-block, individual C++ expressions and statements need no run-time support. This can be essential for embedded and high-performance applications. In particular, this implies that the C++ abstraction mechanisms are usable for embedded, high-performance, high-reliability, and real-time applications. So, programmers of such applications don’t have to work with a low-level (error-prone, impoverished, and unproductive) set of language features.

C++ was designed to be used in a traditional compilation and run-time environment: the C programming environment on the UNIX system [UNIX,1985]. Fortunately, C++ was never restricted to UNIX; it simply used UNIX and C as a model for the relationships among language, libraries, compilers, linkers, execution environments, etc. That minimal model helped C++ to be successful on essentially every computing platform. There are, however, good reasons for using C++ in environments that provide significantly more run-time support. Facilities such as dynamic loading, incremental compilation, and a database of type definitions can be put to good use without affecting the language.

Not every piece of code can be well structured, hardware-independent, easy to read, etc. C++ possesses features that are intended for manipulating hardware facilities in a direct and efficient way without concerns for safety or ease of comprehension. It also possesses facilities for hiding such code behind elegant and safe interfaces.

Naturally, the use of C++ for larger programs leads to the use of C++ by groups of programmers. C++’s emphasis on modularity, strongly typed interfaces, and flexibility pays off here. However, as programs get larger, the problems associated with their development and maintenance shift from being language problems to being more global problems of tools and management.

This book emphasizes techniques for providing general-purpose facilities, generally useful types, libraries, etc. These techniques will serve programmers of small programs as well as programmers of large ones. Furthermore, because all nontrivial programs consist of many semi-independent parts, the techniques for writing such parts serve programmers of all applications.

I use the implementation and use of standard-library components, such as vector, as examples. This introduces library components and their underlying design concepts and implementation techniques. Such examples show how programmers might design and implement their own libraries. However, if the standard library provides a component that addresses a problem, it is almost always better to use that component than to build your own. Even if the standard component is arguably slightly inferior to a home-built component for a particular problem, the standard component is likely to be more widely applicable, more widely available, and more widely known. Over the longer term, the standard component (possibly accessed through a convenient custom interface) is likely to lower long-term maintenance, porting, tuning, and education costs.

You might suspect that specifying a program by using a more detailed type structure would increase the size of the program source text (or even the size of the generated code). With C++, this is not so. A C++ program declaring function argument types, using classes, etc., is typically a bit shorter than the equivalent C program not using these facilities. Where libraries are used, a C++ program will appear much shorter than its C equivalent, assuming, of course, that a functioning C equivalent could have been built.

C++ supports systems programming. This implies that C++ code is able to effectively interoperate with software written in other languages on a system. The idea of writing all software in a single language is a fantasy. From the beginning, C++ was designed to interoperate simply and efficiently with C, assembler, and Fortran. By that, I meant that a C++, C, assembler, or Fortran function could call functions in the other languages without extra overhead or conversion of data structures passed among them.

C++ was designed to operate within a single address space. The use of multiple processes and multiple address spaces relied on (extralinguistic) operating system support. In particular, I assumed that a C++ programmer would have the operating systems command language available for composing processes into a system. Initially, I relied on the UNIX Shell for that, but just about any “scripting language” will do. Thus, C++ provided no support for multiple address spaces and no support for multiple processes, but it was used for systems relying on those features from the earliest days. C++ was designed to be part of large, concurrent, multilanguage systems.

1.3. Learning C++

No programming language is perfect. Fortunately, a programming language does not have to be perfect to be a good tool for building great systems. In fact, a general-purpose programming language cannot be perfect for all of the many tasks to which it is put. What is perfect for one task is often seriously flawed for another because perfection in one area implies specialization. Thus, C++ was designed to be a good tool for building a wide variety of systems and to allow a wide variety of ideas to be expressed directly.

Not everything can be expressed directly using the built-in features of a language. In fact, that isn’t even the ideal. Language features exist to support a variety of programming styles and techniques. Consequently, the task of learning a language should focus on mastering the native and natural styles for that language – not on understanding of every little detail of every language feature. Writing programs is essential; understanding a programming language is not just an intellectual exercise. Practical application of ideas is necessary.

In practical programming, there is little advantage in knowing the most obscure language features or using the largest number of features. A single language feature in isolation is of little interest. Only in the context provided by techniques and by other features does the feature acquire meaning and interest. Thus, when reading the following chapters, please remember that the real purpose of examining the details of C++ is to be able to use language features and library facilities in concert to support good programming styles in the context of sound designs.

No significant system is built exclusively in terms of the language features themselves. We build and use libraries to simplify the task of programming and to increase the quality of our systems. We use libraries to improve maintainability, portability, and performance. Fundamental application concepts are represented as abstractions (e.g., classes, templates, and class hierarchies) in libraries. Many of the most fundamental programming concepts are represented in the standard library. Thus, learning the standard library is an integral part of learning C++. The standard library is the repository of much hard-earned knowledge of how to use C++ well.

C++ is widely used for teaching and research. This has surprised some who – correctly – point out that C++ isn’t the smallest or cleanest language ever designed. It is, however:

• Sufficiently clean for successfully teaching basic design and programming concepts

• Sufficiently comprehensive to be a vehicle for teaching advanced concepts and techniques

• Sufficiently realistic, efficient, and flexible for demanding projects

• Sufficiently commercial to be a vehicle for putting what is learned into nonacademic use

• Sufficiently available for organizations and collaborations relying on diverse development and execution environments

C++ is a language that you can grow with.

The most important thing to do when learning C++ is to focus on fundamental concepts (such as type safety, resource management, and invariants) and programming techniques (such as resource management using scoped objects and the use of iterators in algorithms) and not get lost in language-technical details. The purpose of learning a programming language is to become a better programmer, that is, to become more effective at designing and implementing new systems and at maintaining old ones. For this, an appreciation of programming and design techniques is far more important than understanding all the details. The understanding of technical details comes with time and practice.

C++ programming is based on strong static type checking, and most techniques aim at achieving a high level of abstraction and a direct representation of the programmer’s ideas. This can usually be done without compromising run-time and space efficiency compared to lower-level techniques. To gain the benefits of C++, programmers coming to it from a different language must learn and internalize idiomatic C++ programming style and technique. The same applies to programmers used to earlier and less expressive versions of C++.

Thoughtlessly applying techniques effective in one language to another typically leads to awkward, poorly performing, and hard-to-maintain code. Such code is also most frustrating to write because every line of code and every compiler error message reminds the programmer that the language used differs from “the old language.” You can write in the style of Fortran, C, Lisp, Java, etc., in any language, but doing so is neither pleasant nor economical in a language with a different philosophy. Every language can be a fertile source of ideas about how to write C++ programs. However, ideas must be transformed into something that fits with the general structure and type system of C++ in order to be effective in C++. Over the basic type system of a language, only Pyrrhic victories are possible.

In the continuing debate on whether one needs to learn C before C++, I am firmly convinced that it is best to go directly to C++. C++ is safer and more expressive, and it reduces the need to focus on low-level techniques. It is easier for you to learn the trickier parts of C that are needed to compensate for its lack of higher-level facilities after you have been exposed to the common subset of C and C++ and to some of the higher-level techniques supported directly in C++. Chapter 44 is a guide for programmers going from C++ to C, say, to deal with legacy code. My opinion on how to teach C++ to novices is represented by [Stroustrup,2008].

There are several independently developed implementations of C++. They are supported by a wealth of tools, libraries, and software development environments. To help master all of this you can find textbooks, manuals, and a bewildering variety of online resources. If you plan to use C++ seriously, I strongly suggest that you obtain access to several such sources. Each has its own emphasis and bias, so use at least two.

1.3.1. Programming in C++

The question “How does one write good programs in C++?” is very similar to the question “How does one write good English prose?” There are two answers: “Know what you want to say” and “Practice. Imitate good writing.” Both appear to be as appropriate for C++ as they are for English – and as hard to follow.

The main ideal for C++ programming – as for programming in most higher-level languages – is to express concepts (ideas, notions, etc.) from a design directly in code. We try to ensure that the concepts we talk about, represent with boxes and arrows on our whiteboard, and find in our (non-programming) textbooks have direct and obvious counterparts in our programs:

[1] Represent ideas directly in code.

[2] Represent relationships among ideas directly in code (e.g., hierarchical, parametric, and ownership relationships).

[3] Represent independent ideas independently in code.

[4] Keep simple things simple (without making complex things impossible).

More specifically:

[5] Prefer statically type-checked solutions (when applicable).

[6] Keep information local (e.g., avoid global variables, minimize the use of pointers).

[7] Don’t overabstract (i.e., don’t generalize, introduce class hierarchies, or parameterize beyond obvious needs and experience).

More specific suggestions are listed in §1.3.2.

1.3.2. Suggestions for C++ Programmers

By now, many people have been using C++ for a decade or two. Many more are using C++ in a single environment and have learned to live with the restrictions imposed by early compilers and first-generation libraries. Often, what an experienced C++ programmer has failed to notice over the years is not the introduction of new features as such, but rather the changes in relationships between features that make fundamental new programming techniques feasible. In other words, what you didn’t think of when first learning C++ or found impractical just might be a superior approach today. You find out only by reexamining the basics.

Read through the chapters in order. If you already know the contents of a chapter, you can be done in minutes. If you don’t already know the contents, you’ll have learned something unexpected. I learned a fair bit writing this book, and I suspect that hardly any C++ programmer knows every feature and technique presented. Furthermore, to use the language well, you need a perspective that brings order to the set of features and techniques. Through its organization and examples, this book offers such a perspective.

Take the opportunity offered by the new C++11 facilities to modernize your design and programming techniques:

[1] Use constructors to establish invariants (§2.4.3.2, §13.4, §17.2.1).

[2] Use constructor/destructor pairs to simplify resource management (RAII; §5.2, §13.3).

[3] Avoid “naked” new and delete (§3.2.1.2, §11.2.1).

[4] Use containers and algorithms rather than built-in arrays and ad hoc code (§4.4, §4.5, §7.4, Chapter 32).

[5] Prefer standard-library facilities to locally developed code (§1.2.4).

[6] Use exceptions, rather than error codes, to report errors that cannot be handled locally (§2.4.3, §13.1).

[7] Use move semantics to avoid copying large objects (§3.3.2, §17.5.2).

[8] Use unique_ptr to reference objects of polymorphic type (§5.2.1).

[9] Use shared_ptr to reference shared objects, that is, objects without a single owner that is responsible for their destruction (§5.2.1).

[10] Use templates to maintain static type safety (eliminate casts) and avoid unnecessary use of class hierarchies (§27.2).

It might also be a good idea to review the advice for C and Java programmers (§1.3.3, §1.3.4).

1.3.3. Suggestions for C Programmers

The better one knows C, the harder it seems to be to avoid writing C++ in C style, thereby losing many of the potential benefits of C++. Please take a look at Chapter 44, which describes the differences between C and C++.

[1] Don’t think of C++ as C with a few features added. C++ can be used that way, but only suboptimally. To get really major advantages from C++ as compared to C, you need to apply different design and implementation styles.

[2] Don’t write C in C++; that is often seriously suboptimal for both maintenance and performance.

[3] Use the C++ standard library as a teacher of new techniques and programming styles. Note the difference from the C standard library (e.g., = rather than strcpy() for copying and == rather than strcmp() for comparing).

[4] Macro substitution is almost never necessary in C++. Use const (§7.5), constexpr (§2.2.3, §10.4), enum or enum class (§8.4) to define manifest constants, inline (§12.1.5) to avoid function-calling overhead, templates (§3.4, Chapter 23) to specify families of functions and types, and namespaces (§2.4.2, §14.3.1) to avoid name clashes.

[5] Don’t declare a variable before you need it, and initialize it immediately. A declaration can occur anywhere a statement can (§9.3), in for-statement initializers (§9.5), and in conditions (§9.4.3).

[6] Don’t use malloc(). The new operator (§11.2) does the same job better, and instead of realloc(), try a vector (§3.4.2). Don’t just replace malloc() and free() with “naked” new and delete (§3.2.1.2, §11.2.1).

[7] Avoid void*, unions, and casts, except deep within the implementation of some function or class. Their use limits the support you can get from the type system and can harm performance. In most cases, a cast is an indication of a design error. If you must use an explicit type conversion, try using one of the named casts (e.g., static_cast; §11.5.2) for a more precise statement of what you are trying to do.

[8] Minimize the use of arrays and C-style strings. C++ standard-library strings (§4.2), arrays (§8.2.4), and vectors (§4.4.1) can often be used to write simpler and more maintainable code compared to the traditional C style. In general, try not to build yourself what has already been provided by the standard library.

[9] Avoid pointer arithmetic except in very specialized code (such as a memory manager) and for simple array traversal (e.g., ++p).

[10] Do not assume that something laboriously written in C style (avoiding C++ features such as classes, templates, and exceptions) is more efficient than a shorter alternative (e.g., using standard-library facilities). Often (but of course not always), the opposite is true.

To obey C linkage conventions, a C++ function must be declared to have C linkage (§15.2.5).

1.3.4. Suggestions for Java Programmers

C++ and Java are rather different languages with similar syntaxes. Their aims are significantly different and so are many of their application domains. Java is not a direct successor to C++ in the sense of a language that can do the same as its predecessor, but better and also more. To use C++ well, you need to adopt programming and design techniques appropriate to C++, rather than trying to write Java in C++. It is not just an issue of remembering to delete objects that you create with new because you can’t rely on the presence of a garbage collector:

[1] Don’t simply mimic Java style in C++; that is often seriously suboptimal for both maintainability and performance.

[2] Use the C++ abstraction mechanisms (e.g., classes and templates): don’t fall back to a C style of programming out of a false feeling of familiarity.

[3] Use the C++ standard library as a teacher of new techniques and programming styles.

[4] Don’t immediately invent a unique base for all of your classes (an Object class). Typically, you can do better without it for many/most classes.

[5] Minimize the use of reference and pointer variables: use local and member variables (§3.2.1.2, §5.2, §16.3.4, §17.1).

[6] Remember: a variable is never implicitly a reference.

[7] Think of pointers as C++’s equivalent to Java references (C++ references are more limited; there is no reseating of C++ references).

[8] A function is not virtual by default. Not every class is meant for inheritance.

[9] Use abstract classes as interfaces to class hierarchies; avoid “brittle base classes,” that is, base classes with data members.

[10] Use scoped resource management (“Resource Acquisition Is Initialization”; RAII) whenever possible.

[11] Use a constructor to establish a class invariant (and throw an exception if it can’t).

[12] If a cleanup action is needed when an object is deleted (e.g., goes out of scope), use a destructor for that. Don’t imitate finally (doing so is more ad hoc and in the longer run far more work than relying on destructors).

[13] Avoid “naked” new and delete; instead, use containers (e.g., vector, string, and map) and handle classes (e.g., lock and unique_ptr).

[14] Use freestanding functions (nonmember functions) to minimize coupling (e.g., see the standard algorithms), and use namespaces (§2.4.2, Chapter 14) to limit the scope of freestanding functions.

[15] Don’t use exception specifications (except noexcept; §13.5.1.1).

[16] A C++ nested class does not have access to an object of the enclosing class.

[17] C++ offers only the most minimal run-time reflection: dynamic_cast and typeid (Chapter 22). Rely more on compile-time facilities (e.g., compile-time polymorphism; Chapter 27, Chapter 28).

Most of this advice applies equally to C# programmers.

1.4. History

I invented C++, wrote its early definitions, and produced its first implementation. I chose and formulated the design criteria for C++, designed its major language features, developed or helped to develop many of the early libraries, and was responsible for the processing of extension proposals in the C++ standards committee.

C++ was designed to provide Simula’s facilities for program organization [Dahl,1970] [Dahl,1972] together with C’s efficiency and flexibility for systems programming [Kernighan,1978] [Kernighan,1988]. Simula is the initial source of C++’s abstraction mechanisms. The class concept (with derived classes and virtual functions) was borrowed from it. However, templates and exceptions came to C++ later with different sources of inspiration.

The evolution of C++ was always in the context of its use. I spent a lot of time listening to users and seeking out the opinions of experienced programmers. In particular, my colleagues at AT&T Bell Laboratories were essential for the growth of C++ during its first decade.

This section is a brief overview; it does not try to mention every language feature and library component. Furthermore, it does not go into details. For more information, and in particular for more names of people who contributed, see [Stroustrup,1993], [Stroustrup,2007], and [Stroustrup,1994]. My two papers from the ACM History of Programming Languages conference and my Design and Evolution of C++ book (known as “D&E”) describe the design and evolution of C++ in detail and document influences from other programming languages.

Most of the documents produced as part of the ISO C++ standards effort are available online [WG21]. In my FAQ, I try to maintain a connection between the standard facilities and the people who proposed and refined those facilities [Stroustrup,2010]. C++ is not the work of a faceless, anonymous committee or of a supposedly omnipotent “dictator for life”; it is the work of many dedicated, experienced, hard-working individuals.

1.4.1. Timeline

The work that led to C++ started in the fall of 1979 under the name “C with Classes.” Here is a simplified timeline:

1979

Work on “C with Classes” started. The initial feature set included classes and derived classes, public/private access control, constructors and destructors, and function declarations with argument checking. The first library supported non-preemptive concurrent tasks and random number generators.

1984

“C with Classes” was renamed to C++. By then, C++ had acquired virtual functions, function and operator overloading, references, and the I/O stream and complex number libraries.

1985

First commercial release of C++ (October 14). The library included I/O streams, complex numbers, and tasks (nonpreemptive scheduling).

1985

The C++ Programming Language (“TC++PL,” October 14) [Stroustrup,1986].

1989

The Annotated C++ Reference Manual (“the ARM”).

1991

The C++ Programming Language, Second Edition [Stroustrup,1991], presenting generic programming using templates and error handling based on exceptions (including the “Resource Acquisition Is Initialization” general resource management idiom).

1997

The C++ Programming Language, Third Edition [Stroustrup,1997] introduced ISO C++, including namespaces, dynamic_cast, and many refinements of templates. The standard library added the STL framework of generic containers and algorithms.

1998

ISO C++ standard.

2002

Work on a revised standard, colloquially named C++0x, started.

2003

A “bug fix” revision of the ISO C++ standard was issued. A C++ Technical Report introduced new standard-library components, such as regular expressions, unordered containers (hash tables), and resource management pointers, which later became part of C++0x.

2006

An ISO C++ Technical Report on Performance was issued to answer questions of cost, predictability, and techniques, mostly related to embedded systems programming.

2009

C++0x was feature complete. It provided uniform initialization, move semantics, variadic template arguments, lambda expressions, type aliases, a memory model suitable for concurrency, and much more. The standard library added several components, including threads, locks, and most of the components from the 2003 Technical Report.

2011

ISO C++11 standard was formally approved.

2012

The first complete C++11 implementations emerged.

2012

Work on future ISO C++ standards (referred to as C++14 and C++17) started.

2013

The C++ Programming Language, Fourth Edition introduced C++11.

During development, C++11 was known as C++0x. As is not uncommon in large projects, we were overly optimistic about the completion date.

1.4.2. The Early Years

I originally designed and implemented the language because I wanted to distribute the services of a UNIX kernel across multiprocessors and local-area networks (what are now known as multicores and clusters). For that, I needed some event-driven simulations for which Simula would have been ideal, except for performance considerations. I also needed to deal directly with hardware and provide high-performance concurrent programming mechanisms for which C would have been ideal, except for its weak support for modularity and type checking. The result of adding Simula-style classes to C, “C with Classes,” was used for major projects in which its facilities for writing programs that use minimal time and space were severely tested. It lacked operator overloading, references, virtual functions, templates, exceptions, and many, many details [Stroustrup,1982]. The first use of C++ outside a research organization started in July 1983.

The name C++ (pronounced “see plus plus”) was coined by Rick Mascitti in the summer of 1983 and chosen as the replacement for “C with Classes” by me. The name signifies the evolutionary nature of the changes from C; “++” is the C increment operator. The slightly shorter name “C+” is a syntax error; it had also been used as the name of an unrelated language. Connoisseurs of C semantics find C++ inferior to ++C. The language was not called D, because it was an extension of C, because it did not attempt to remedy problems by removing features, and because there already existed several would-be C successors named D. For yet another interpretation of the name C++, see the appendix of [Orwell,1949].

C++ was designed primarily so that my friends and I would not have to program in assembler, C, or various then-fashionable high-level languages. Its main purpose was to make writing good programs easier and more pleasant for the individual programmer. In the early years, there was no C++ paper design; design, documentation, and implementation went on simultaneously. There was no “C++ project” either, or a “C++ design committee.” Throughout, C++ evolved to cope with problems encountered by users and as a result of discussions among my friends, my colleagues, and me.

1.4.2.1. Language Features and Library Facilities

The very first design of C++ (then called “C with Classes”) included function declarations with argument type checking and implicit conversions, classes with the public/private distinction between the interface and the implementation, derived classes, and constructors and destructors. I used macros to provide primitive parameterization. This was in use by mid-1980. Late that year, I was able to present a set of language facilities supporting a coherent set of programming styles; see §1.2.1. In retrospect, I consider the introduction of constructors and destructors most significant. In the terminology of the time, “a constructor creates the execution environment for the member functions and the destructor reverses that.” Here is the root of C++’s strategies for resource management (causing a demand for exceptions) and the key to many techniques for making user code short and clear. If there were other languages at the time that supported multiple constructors capable of executing general code, I didn’t (and don’t) know of them. Destructors were new in C++.

C++ was released commercially in October 1985. By then, I had added inlining (§12.1.5, §16.2.8), consts (§2.2.3, §7.5, §16.2.9), function overloading (§12.3), references (§7.7), operator overloading (§3.2.1.1, Chapter 18, Chapter 19), and virtual functions (§3.2.3, §20.3.2). Of these features, support for run-time polymorphism in the form of virtual functions was by far the most controversial. I knew its worth from Simula but found it impossible to convince most people in the systems programming world of its value. Systems programmers tended to view indirect function calls with suspicion, and people acquainted with other languages supporting object-oriented programming had a hard time believing that virtual functions could be fast enough to be useful in systems code. Conversely, many programmers with an object-oriented background had (and many still have) a hard time getting used to the idea that you use virtual function calls only to express a choice that must be made at run time. The resistance to virtual functions may be related to a resistance to the idea that you can get better systems through more regular structure of code supported by a programming language. Many C programmers seem convinced that what really matters is complete flexibility and careful individual crafting of every detail of a program. My view was (and is) that we need every bit of help we can get from languages and tools: the inherent complexity of the systems we are trying to build is always at the edge of what we can express.

Much of the design of C++ was done on the blackboards of my colleagues. In the early years, the feedback from Stu Feldman, Alexander Fraser, Steve Johnson, Brian Kernighan, Doug McIlroy, and Dennis Ritchie was invaluable.

In the second half of the 1980s, I continued to add language features in response to user comments. The most important of those were templates [Stroustrup,1988] and exception handling [Koenig,1990], which were considered experimental at the time the standards effort started. In the design of templates, I was forced to decide among flexibility, efficiency, and early type checking. At the time, nobody knew how to simultaneously get all three, and to compete with C-style code for demanding systems applications, I felt that I had to choose the first two properties. In retrospect, I think the choice was the correct one, and the search for better type checking of templates continues [Gregor,2006] [Sutton,2011] [Stroustrup,2012a]. The design of exceptions focused on multilevel propagation of exceptions, the passing of arbitrary information to an error handler, and the integrations between exceptions and resource management by using local objects with destructors to represent and release resources (what I clumsily called “Resource Acquisition Is Initialization”; §13.3).

I generalized C++’s inheritance mechanisms to support multiple base classes [Stroustrup,1987a]. This was called multiple inheritance and was considered difficult and controversial. I considered it far less important than templates or exceptions. Multiple inheritance of abstract classes (often called interfaces) is now universal in languages supporting static type checking and object-oriented programming.

The C++ language evolved hand in hand with some of the key library facilities presented in this book. For example, I designed the complex [Stroustrup,1984], vector, stack, and (I/O) stream [Stroustrup,1985] classes together with the operator overloading mechanisms. The first string and list classes were developed by Jonathan Shopiro and me as part of the same effort. Jonathan’s string and list classes were the first to see extensive use as part of a library. The string class from the standard C++ library has its roots in these early efforts. The task library described in [Stroustrup,1987b] was part of the first “C with Classes” program ever written in 1980. I wrote it and its associated classes to support Simula-style simulations. Unfortunately, we had to wait until 2011 (30 years!) to get concurrency support standardized and universally available (§1.4.4.2, §5.3, Chapter 41). The development of the template facility was influenced by a variety of vector, map, list, and sort templates devised by Andrew Koenig, Alex Stepanov, me, and others.

C++ grew up in an environment with a multitude of established and experimental programming languages (e.g., Ada [Ichbiah,1979], Algol 68 [Woodward,1974], and ML [Paulson,1996]). At the time, I was comfortable in about 25 languages, and their influences on C++ are documented in [Stroustrup,1994] and [Stroustrup,2007]. However, the determining influences always came from the applications I encountered. That was a deliberate policy to have the development of C++ “problem driven” rather than imitative.

1.4.3. The 1998 Standard

The explosive growth of C++ use caused some changes. Sometime during 1987, it became clear that formal standardization of C++ was inevitable and that we needed to start preparing the ground for a standardization effort [Stroustrup,1994]. The result was a conscious effort to maintain contact between implementers of C++ compilers and major users. This was done through paper and electronic mail and through face-to-face meetings at C++ conferences and elsewhere.

AT&T Bell Labs made a major contribution to C++ and its wider community by allowing me to share drafts of revised versions of the C++ reference manual with implementers and users. Because many of those people worked for companies that could be seen as competing with AT&T, the significance of this contribution should not be underestimated. A less enlightened company could have caused major problems of language fragmentation simply by doing nothing. As it happened, about a hundred individuals from dozens of organizations read and commented on what became the generally accepted reference manual and the base document for the ANSI C++ standardization effort. Their names can be found in The Annotated C++ Reference Manual (“the ARM”) [Ellis,1989]. The X3J16 committee of ANSI was convened in December 1989 at the initiative of Hewlett-Packard. In June 1991, this ANSI (American national) standardization of C++ became part of an ISO (international) standardization effort for C++ and named WG21. From 1990, these joint C++ standards committees have been the main forum for the evolution of C++ and the refinement of its definition. I served on these committees throughout. In particular, as the chairman of the working group for extensions (later called the evolution group), I was directly responsible for handling proposals for major changes to C++ and the addition of new language features. An initial draft standard for public review was produced in April 1995. The first ISO C++ standard (ISO/IEC 14882-1998) [C++,1998] was ratified by a 22-0 national vote in 1998. A “bug fix release” of this standard was issued in 2003, so you sometimes hear people refer to C++03, but that is essentially the same language as C++98.

1.4.3.1. Language Features

By the time the ANSI and ISO standards efforts started, most major language features were in place and documented in the ARM [Ellis,1989]. Consequently, most of the work involved refinement of features and their specification. The template mechanisms, in particular, benefited from much detailed work. Namespaces were introduced to cope with the increased size of C++ programs and the increased number of libraries. At the initiative of Dmitry Lenkov from Hewett-Packard, minimal facilities to use run-time type information (RTTI; Chapter 22) were introduced. I had left such facilities out of C++ because I had found them seriously overused in Simula. I tried to get a facility for optional conservative garbage collection accepted, but failed. We had to wait until the 2011 standard for that.

Clearly, the 1998 language was far superior in features and in particular in the detail of specification to the 1989 language. However, not all changes were improvements. In addition to the inevitable minor mistakes, two major features were added that in retrospect should not have been:

• Exception specifications provide run-time enforcement of which exceptions a function is allowed to throw. They were added at the energetic initiative of people from Sun Microsystems. Exception specifications turned out to be worse than useless for improving readability, reliability, and performance. They are deprecated (scheduled for future removal) in the 2011 standard. The 2011 standard introduced noexcept (§13.5.1.1) as a simpler solution to many of the problems that exception specifications were supposed to address.

• It was always obvious that separate compilation of templates and their uses would be ideal [Stroustrup,1994]. How to achieve that under the constraints from real-world uses of templates was not at all obvious. After a long debate in the committee, a compromise was reached and something called export templates were specified as part of the 1998 standard. It was not an elegant solution to the problem, only one vendor implemented export (the Edison Design Group), and the feature was removed from the 2011 standard. We are still looking for a solution. My opinion is that the fundamental problem is not separate compilation in itself, but that the distinction between interface and implementation of a template is not well specified. Thus, export solved the wrong problem. In the future, language support for “concepts” (§24.3) may help by providing precise specification of template requirements. This is an area of active research and design [Sutton,2011] [Stroustrup,2012a].

1.4.3.2. The Standard Library

The greatest and most important innovation in the 1998 standard was the inclusion of the STL, a framework of algorithms and containers, in the standard library (§4.4, §4.5, Chapter 31, Chapter 32, Chapter 33). It was the work of Alex Stepanov (with Dave Musser, Meng Le, and others) based on more than a decade’s work on generic programming. Andrew Koenig, Beman Dawes, and I did much to help get the STL accepted [Stroustrup,2007]. The STL has been massively influential within the C++ community and beyond.

Except for the STL, the standard library was a bit of a hodgepodge of components, rather than a unified design. I had failed to ship a sufficiently large foundation library with Release 1.0 of C++ [Stroustrup,1993], and an unhelpful (non-research) AT&T manager had prevented my colleagues and me from rectifying that mistake for Release 2.0. That meant that every major organization (such as Borland, IBM, Microsoft, and Texas Instruments) had its own foundation library by the time the standards work started. Thus, the committee was limited to a patchwork of components based on what had always been available (e.g., the complex library), what could be added without interfering with the major vendor’s libraries, and what was needed to ensure cooperation among different nonstandard libraries.

The standard-library string (§4.2, Chapter 36) had its origins in early work by Jonathan Shopiro and me at Bell Labs but was revised and extended by several different individuals and groups during standardization. The valarray library for numerical computation (§40.5) is primarily the work of Kent Budge. Jerry Schwarz transformed my streams library (§1.4.2.1) into the iostreams library (§4.3, Chapter 38) using Andrew Koenig’s manipulator technique (§38.4.5.2) and other ideas. The iostreams library was further refined during standardization, where the bulk of the work was done by Jerry Schwarz, Nathan Myers, and Norihiro Kumagai.

By commercial standards the C++98 standard library is tiny. For example, there is no standard GUI, database access library, or Web application library. Such libraries are widely available but are not part of the ISO standard. The reasons for that are practical and commercial, rather than technical. However, the C standard library was (and is) many influential people’s measure of a standard library, and compared to that, the C++ standard library is huge.

1.4.4. The 2011 Standard

The current C++, C++11, known for years as C++0x, is the work of the members of WG21. The committee worked under increasingly onerous self-imposed processes and procedures. These processes probably led to a better (and more rigorous) specification, but they also limited innovation [Stroustrup,2007]. An initial draft standard for public review was produced in 2009. The second ISO C++ standard (ISO/IEC 14882-2011) [C++,2011] was ratified by a 21-0 national vote in August 2011.

One reason for the long gap between the two standards is that most members of the committee (including me) were under the mistaken impression that the ISO rules required a “waiting period” after a standard was issued before starting work on new features. Consequently, serious work on new language features did not start until 2002. Other reasons included the increased size of modern languages and their foundation libraries. In terms of pages of standards text, the language grew by about 30% and the standard library by about 100%. Much of the increase was due to more detailed specification, rather than new functionality. Also, the work on a new C++ standard obviously had to take great care not to compromise older code through incompatible changes. There are billions of lines of C++ code in use that the committee must not break.

The overall aims for the C++11 effort were:

• Make C++ a better language for systems programming and library building.

• Make C++ easier to teach and learn.

The aims are documented and detailed in [Stroustrup,2007].

A major effort was made to make concurrent systems programming type-safe and portable. This involved a memory model (§41.2) and a set of facilities for lock-free programming (§41.3), which is primarily the work of Hans Boehm, Brian McKnight, and others. On top of that, we added the threads library. Pete Becker, Peter Dimov, Howard Hinnant, William Kempf, Anthony Williams, and others did massive amounts of work on that. To provide an example of what can be achieved on top of the basic concurrency facilities, I proposed work on “a way to exchange information between tasks without explicit use of a lock,” which became futures and async() (§5.3.5); Lawrence Crowl and Detlef Vollmann did most of the work on that. Concurrency is an area where a complete and detailed listing of who did what and why would require a very long paper. Here, I can’t even try.

1.4.4.1. Language Features

The list of language features and standard-library facilities added to C++98 to get C++11 is presented in §44.2. With the exception of concurrency support, every addition to the language could be deemed “minor,” but doing so would miss the point: language features are meant to be used in combination to write better programs. By “better” I mean easier to read, easier to write, more elegant, less error-prone, more maintainable, faster-running, consuming fewer resources, etc.

Here are what I consider the most widely useful new “building bricks” affecting the style of C++11 code with references to the text and their primary authors:

• Control of defaults: =delete and =default: §3.3.4, §17.6.1, §17.6.4; Lawrence Crowl and Bjarne Stroustrup.

• Deducing the type of an object from its initializer, auto: §2.2.2, §6.3.6.1; Bjarne Stroustrup. I first designed and implemented auto in 1983 but had to remove it because of C compatibility problems.

• Generalized constant expression evaluation (including literal types), constexpr: §2.2.3, §10.4, §12.1.6; Gabriel Dos Reis and Bjarne Stroustrup [DosReis,2010].

• In-class member initializers: §17.4.4; Michael Spertus and Bill Seymour.

• Inheriting constructors: §20.3.5.1; Bjarne Stroustrup, Michael Wong, and Michel Michaud.

• Lambda expressions, a way of implicitly defining function objects at the point of their use in an expression: §3.4.3, §11.4; Jaakko Jarvi.

• Move semantics, a way of transmitting information without copying: §3.3.2, §17.5.2; Howard Hinnant.

• A way of stating that a function may not throw exceptions noexcept: §13.5.1.1; David Abrahams, Rani Sharoni, and Doug Gregor.

• A proper name for the null pointer, §7.2.2; Herb Sutter and Bjarne Stroustrup.

• The range-for statement: §2.2.5, §9.5.1; Thorsten Ottosen and Bjarne Stroustrup.

• Override controls: final and override: §20.3.4. Alisdair Meredith, Chris Uzdavinis, and Ville Voutilainen.

• Type aliases, a mechanism for providing an alias for a type or a template. In particular, a way of defining a template by binding some arguments of another template: §3.4.5, §23.6; Bjarne Stroustrup and Gabriel Dos Reis.

• Typed and scoped enumerations: enum class: §8.4.1; David E. Miller, Herb Sutter, and Bjarne Stroustrup.

• Universal and uniform initialization (including arbitrary-length initializer lists and protection against narrowing): §2.2.2, §3.2.1.3, §6.3.5, §17.3.1, §17.3.4; Bjarne Stroustrup and Gabriel Dos Reis.

• Variadic templates, a mechanism for passing an arbitrary number of arguments of arbitrary types to a template: §3.4.4, §28.6; Doug Gregor and Jaakko Jarvi.

Many more people than can be listed here deserve to be mentioned. The technical reports to the committee [WG21] and my C++11 FAQ [Stroustrup,2010a] give many of the names. The minutes of the committee’s working groups mention more still. The reason my name appears so often is (I hope) not vanity, but simply that I chose to work on what I consider important. These are features that will be pervasive in good code. Their major role is to flesh out the C++ feature set to better support programming styles (§1.2.1). They are the foundation of the synthesis that is C++11.

Much work went into a proposal that did not make it into the standard. “Concepts” was a facility for specifying and checking requirements for template arguments [Gregor,2006] based on previous research (e.g., [Stroustrup,1994] [Siek,2000] [DosReis,2006]) and extensive work in the committee. It was designed, specified, implemented, and tested, but by a large majority the committee decided that the proposal was not yet ready. Had we been able to refine “concepts,” it would have been the most important single feature in C++11 (its only competitor for that title is concurrency support). However, the committee decided against “concepts” on the grounds of complexity, difficulty of use, and compile-time performance [Stroustrup,2010b]. I think we (the committee) did the right thing with “concepts” for C++11, but this feature really was “the one that got away.” This is currently a field of active research and design [Sutton,2011] [Stroustrup,2012a].

1.4.4.2. Standard Library

The work on what became the C++11 standard library started with a standards committee technical report ("TR1"). Initially, Matt Austern was the head of the Library Working Group, and later Howard Hinnant took over until we shipped the final draft standard in 2011.

As for language features, I’ll only list a few standard-library components with references to the text and the names of the individuals most closely associated with them. For a more detailed list, see §44.2.2. Some components, such as unordered_map (hash tables), were ones we simply didn’t manage to finish in time for the C++98 standard. Many others, such as unique_ptr and function were part of a technical report (TR1) based on Boost libraries. Boost is a volunteer organization created to provide useful library components based on the STL [Boost].

• Hashed containers, such as unordered_map: §31.4.3; Matt Austern.

• The basic concurrency library components, such as thread, mutex, and lock: §5.3, §42.2; Pete Becker, Peter Dimov, Howard Hinnant, William Kempf, Anthony Williams, and more.

• Launching asynchronous computation and returning results, future, promise, and async(): §5.3.5, §42.4.6; Detlef Vollmann, Lawrence Crowl, Bjarne Stroustrup, and Herb Sutter.

• The garbage collection interface: §34.5; Michael Spertus and Hans Boehm.

• A regular expression library, regexp: §5.5, Chapter 37; John Maddock.

• A random number library: §5.6.3, §40.7; Jens Maurer and Walter Brown. It was about time. I shipped the first random number library with “C with Classes” in 1980.

Several utility components were tried out in Boost:

• A pointer for simply and efficiently passing resources, unique_ptr: §5.2.1, §34.3.1; Howard E. Hinnant. This was originally called move_ptr and is what auto_ptr should have been had we known how to do so for C++98.

• A pointer for representing shared ownership, shared_ptr: §5.2.1, §34.3.2; Peter Dimov. A successor to the C++98 counted_ptr proposal from Greg Colvin.

• The tuple library: §5.4.3, §28.5, §34.2.4.2; Jaakko Jarvi and Gary Powell. They credit a long list of contributors, including Doug Gregor, David Abrahams, and Jeremy Siek.

• The general bind(): §33.5.1; Peter Dimov. His acknowledgments list a veritable who’s who of Boost (including Doug Gregor, John Maddock, Dave Abrahams, and Jaakko Jarvi).

• The function type for holding callable objects: §33.5.3; Doug Gregor. He credits William Kempf and others with contributions.

1.4.5. What is C++ used for?

By now (2013), C++ is used just about everywhere: it is in your computer, your phone, your car, probably even in your camera. You don’t usually see it. C++ is a systems programming language, and its most pervasive uses are deep in the infrastructure where we, as users, never look.

C++ is used by millions of programmers in essentially every application domain. Billions (thousands of millions) of lines of C++ are currently deployed. This massive use is supported by half a dozen independent implementations, many thousands of libraries, hundreds of textbooks, and dozens of websites. Training and education at a variety of levels are widely available.

Early applications tended to have a strong systems programming flavor. For example, several early operating systems have been written in C++: [Campbell,1987] (academic), [Rozier,1988] (real time), [Berg,1995] (high-throughput I/O). Many current ones (e.g., Windows, Apple’s OS, Linux, and most portable-device OSs) have key parts done in C++. Your cellphone and Internet routers are most likely written in C++. I consider uncompromising low-level efficiency essential for C++. This allows us to use C++ to write device drivers and other software that rely on direct manipulation of hardware under real-time constraints. In such code, predictability of performance is at least as important as raw speed. Often, so is the compactness of the resulting system. C++ was designed so that every language feature is usable in code under severe time and space constraints (§1.2.4) [Stroustrup,1994,§4.5].

Some of today’s most visible and widely used systems have their critical parts written in C++. Examples are Amadeus (airline ticketing), Amazon (Web commerce), Bloomberg (financial information), Google (Web search), and Facebook (social media). Many other programming languages and technologies depend critically on C++’s performance and reliability in their implementation. Examples include the most widely used Java Virtual Machines (e.g., Oracle’s HotSpot), JavaScript interpreters (e.g., Google’s V8), browsers (e.g., Microsoft’s Internet Explorer, Mozilla’s Firefox, Apple’s Safari, and Google’s Chrome), and application frameworks (e.g., Microsoft’s .NET Web services framework). I consider C++ to have unique strengths in the area of infrastructure software [Stroustrup,2012a].

Most applications have sections of code that are critical for acceptable performance. However, the largest amount of code is not in such sections. For most code, maintainability, ease of extension, and ease of testing are key. C++’s support for these concerns has led to its widespread use in areas where reliability is a must and where requirements change significantly over time. Examples are financial systems, telecommunications, device control, and military applications. For decades, the central control of the U.S. long-distance telephone system has relied on C++, and every 800 call (i.e., a call paid for by the called party) has been routed by a C++ program [Kamath,1993]. Many such applications are large and long-lived. As a result, stability, compatibility, and scalability have been constant concerns in the development of C++. Multimillion-line C++ programs are common.

Games is another area where a multiplicity of languages and tools need to coexist with a language providing uncompromising efficiency (often on “unusual” hardware). Thus, games has been another major applications area for C++.

What used to be called systems programming is widely found in embedded systems, so it is not surprising to find massive use of C++ in demanding embedded systems projects, including computer tomography (CAT scanners), flight control software (e.g., Lockheed-Martin), rocket control, ship’s engines (e.g., the control of the world’s largest marine diesel engines from MAN), automobile software (e.g., BMW), and wind turbine control (e.g., Vesta).

C++ wasn’t specifically designed with numerical computation in mind. However, much numerical, scientific, and engineering computation is done in C++. A major reason for this is that traditional numerical work must often be combined with graphics and with computations relying on data structures that don’t fit into the traditional Fortran mold (e.g., [Root,1995]). I am particularly pleased to see C++ used in major scientific endeavors, such as the Human Genome Project, NASA’s Mars Rovers, CERN’s search for the fundamentals of the universe, and many others.

C++’s ability to be used effectively for applications that require work in a variety of application areas is an important strength. Applications that involve local- and wide-area networking, numerics, graphics, user interaction, and database access are common. Traditionally, such application areas were considered distinct and were served by distinct technical communities using a variety of programming languages. However, C++ is widely used in all of those areas, and more. It is designed so that C++ code can coexist with code written in other languages. Here, again, C++’s stability over decades is important. Furthermore, no really major system is written 100% in a single language. Thus, C++’s original design aim of interoperability becomes significant.

Major applications are not written in just the raw language. C++ is supported by a variety of libraries (beyond the ISO C++ standard library) and tool sets, such as Boost [Boost] (portable foundation libraries), POCO (Web development), QT (cross-platform application development), wxWidgets (a cross-platform GUI library), WebKit (a layout engine library for Web browsers), CGAL (computational geometry), QuickFix (Financial Information eXchange), OpenCV (real-time image processing), and Root [Root,1995] (High-Energy Physics). There are many thousands of C++ libraries, so keeping up with them all is impossible.

1.5. Advice

Each chapter contains an “Advice” section with a set of concrete recommendations related to its contents. Such advice consists of rough rules of thumb, not immutable laws. A piece of advice should be applied only where reasonable. There is no substitute for intelligence, experience, common sense, and good taste.

I find rules of the form “never do this” unhelpful. Consequently, most advice is phrased as suggestions for what to do. Negative suggestions tend not to be phrased as absolute prohibitions and I try to suggest alternatives. I know of no major feature of C++ that I have not seen put to good use. The “Advice” sections do not contain explanations. Instead, each piece of advice is accompanied by a reference to an appropriate section of the book.

For starters, here are a few high-level recommendations derived from the sections on design, learning, and history of C++:

[1] Represent ideas (concepts) directly in code, for example, as a function, a class, or an enumeration; §1.2.

[2] Aim for your code to be both elegant and efficient; §1.2.

[3] Don’t overabstract; §1.2.

[4] Focus design on the provision of elegant and efficient abstractions, possibly presented as libraries; §1.2.

[5] Represent relationships among ideas directly in code, for example, through parameterization or a class hierarchy; §1.2.1.

[6] Represent independent ideas separately in code, for example, avoid mutual dependencies among classes; §1.2.1.

[7] C++ is not just object-oriented; §1.2.1.

[8] C++ is not just for generic programming; §1.2.1.

[9] Prefer solutions that can be statically checked; §1.2.1.

[10] Make resources explicit (represent them as class objects); §1.2.1, §1.4.2.1.

[11] Express simple ideas simply; §1.2.1.

[12] Use libraries, especially the standard library, rather than trying to build everything from scratch; §1.2.1.

[13] Use a type-rich style of programming; §1.2.2.

[14] Low-level code is not necessarily efficient; don’t avoid classes, templates, and standard-library components out of fear of performance problems; §1.2.4, §1.3.3.

[15] If data has an invariant, encapsulate it; §1.3.2.

[16] C++ is not just C with a few extensions; §1.3.3.

In general: To write a good program takes intelligence, taste, and patience. You are not going to get it right the first time. Experiment!

1.6. References

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D. Dechev, P. Pirkelbauer, and B. Stroustrup: Understanding and Effectively Preventing the ABA Problem in Descriptor-based Lock-free Designs. 13th IEEE Computer Society ISORC 2010 Symposium. May 2010.

[DosReis,2006]

Gabriel Dos Reis and Bjarne Stroustrup: Specifying C++ Concepts. POPL06. January 2006.

[DosReis,2010]

Gabriel Dos Reis and Bjarne Stroustrup: General Constant Expressions for System Programming Languages. SAC-2010. The 25th ACM Symposium On Applied Computing. March 2010.

[DosReis,2011]

Gabriel Dos Reis and Bjarne Stroustrup: A Principled, Complete, and Efficient Representation of C++. Journal of Mathematics in Computer Science. Vol. 5, Issue 3. 2011.

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Margaret A. Ellis and Bjarne Stroustrup: The Annotated C++ Reference Manual. Addison-Wesley. Reading, Mass. 1990. ISBN 0-201-51459-1.

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Len Freeman and Chris Phillips: Parallel Numerical Algorithms. Prentice Hall. Englewood Cliffs, New Jersey. 1992. ISBN 0-13-651597-5.

[Friedl,1997]:

Jeffrey E. F. Friedl: Mastering Regular Expressions. O’Reilly Media. Sebastopol, California. 1997. ISBN 978-1565922570.

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Erich Gamma et al.: Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley. Reading, Massachusetts. 1994. ISBN 0-201-63361-2.

[Gregor,2006]

Douglas Gregor et al.: Concepts: Linguistic Support for Generic Programming in C++. OOPSLA’06.

[Hennessy,2011]

John L. Hennessy and David A. Patterson: Computer Architecture, Fifth Edition: A Quantitative Approach. Morgan Kaufmann. San Francisco, California. 2011. ISBN 978-0123838728.

[Ichbiah,1979]

Jean D. Ichbiah et al.: Rationale for the Design of the ADA Programming Language. SIGPLAN Notices. Vol. 14, No. 6. June 1979.

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Yogeesh H. Kamath, Ruth E. Smilan, and Jean G. Smith: Reaping Benefits with Object-Oriented Technology. AT&T Technical Journal. Vol. 72, No. 5. September/October 1993.

[Kernighan,1978]

Brian W. Kernighan and Dennis M. Ritchie: The C Programming Language. Prentice Hall. Englewood Cliffs, New Jersey. 1978.

[Kernighan,1988]

Brian W. Kernighan and Dennis M. Ritchie: The C Programming Language, Second Edition. Prentice-Hall. Englewood Cliffs, New Jersey. 1988. ISBN 0-13-110362-8.

[Knuth,1968]

Donald E. Knuth: The Art of Computer Programming. Addison-Wesley. Reading, Massachusetts. 1968.

[Koenig,1989]

Andrew Koenig and Bjarne Stroustrup: C++: As close to C as possible – but no closer. The C++ Report. Vol. 1, No. 7. July 1989.

[Koenig,1990]

A. R. Koenig and B. Stroustrup: Exception Handling for C++ (revised). Proc USENIX C++ Conference. April 1990.

[Kolecki,2002]

Joseph C. Kolecki: An Introduction to Tensors for Students of Physics and Engineering. NASA/TM-2002-211716.

[Langer,2000]

Angelika Langer and Klaus Kreft: Standard C++ IOStreams and Locales: Advanced Programmer’s Guide and Reference. Addison-Wesley. 2000. ISBN 978-0201183955.

[McKenney]

Paul E. McKenney: Is Parallel Programming Hard, And, If So, What Can You Do About It? kernel.org. Corvallis, Oregon. 2012. http://kernel.org/pub/linux/kernel/people/paulmck/perfbook/perfbook.html.

[Maddock,2009]

John Maddock: Boost.Regex. www.boost.org. 2009.

[Orwell,1949]

George Orwell: 1984. Secker and Warburg. London. 1949.

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Larry C. Paulson: ML for the Working Programmer. Cambridge University Press. Cambridge. 1996. ISBN 0-521-56543-X.

[Pirkelbauer,2009]

P. Pirkelbauer, Y. Solodkyy, and B. Stroustrup: Design and Evaluation of C++ Open Multi-Methods. Science of Computer Programming. Elsevier Journal. June 2009. doi:10.1016/j.scico.2009.06.002.

[Richards,1980]

Martin Richards and Colin Whitby-Strevens: BCPL – The Language and Its Compiler. Cambridge University Press. Cambridge. 1980. ISBN 0-521-21965-5.

[Root,1995]

ROOT: A Data Analysis Framework. root.cern.ch. It seems appropriate to represent a tool from CERN, the birthplace of the World Wide Web, by a Web address.

[Rozier,1988]

M. Rozier et al.: CHORUS Distributed Operating Systems. Computing Systems. Vol. 1, No. 4. Fall 1988.

[Siek,2000]

Jeremy G. Siek and Andrew Lumsdaine: Concept checking: Binding parametric polymorphism in C++. Proc. First Workshop on C++ Template Programming. Erfurt, Germany. 2000.

[Solodkyy,2012]

Y. Solodkyy, G. Dos Reis, and B. Stroustrup: Open and Efficient Type Switch for C++. Proc. OOPSLA’12.

[Stepanov,1994]

Alexander Stepanov and Meng Lee: The Standard Template Library. HP Labs Technical Report HPL-94-34 (R. 1). 1994.

[Stewart,1998]

G. W. Stewart: Matrix Algorithms, Volume I. Basic Decompositions. SIAM. Philadelphia, Pennsylvania. 1998.

[Stroustrup,1982]

B. Stroustrup: Classes: An Abstract Data Type Facility for the C Language. Sigplan Notices. January 1982. The first public description of “C with Classes.”

[Stroustrup,1984]

B. Stroustrup: Operator Overloading in C++. Proc. IFIP WG2.4 Conference on System Implementation Languages: Experience & Assessment. September 1984.

[Stroustrup,1985]

B. Stroustrup: An Extensible I/O Facility for C++. Proc. Summer 1985 USENIX Conference.

[Stroustrup,1986]

B. Stroustrup: The C++ Programming Language. Addison-Wesley. Reading, Massachusetts. 1986. ISBN 0-201-12078-X.

[Stroustrup,1987]

B. Stroustrup: Multiple Inheritance for C++. Proc. EUUG Spring Conference. May 1987.

[Stroustrup,1987b]

B. Stroustrup and J. Shopiro: A Set of C Classes for Co-Routine Style Programming. Proc. USENIX C++ Conference. Santa Fe, New Mexico. November 1987.

[Stroustrup,1988]

B. Stroustrup: Parameterized Types for C++. Proc. USENIX C++ Conference, Denver. 1988.

[Stroustrup,1991]

B. Stroustrup: The C++ Programming Language (Second Edition). Addison-Wesley. Reading, Massachusetts. 1991. ISBN 0-201-53992-6.

[Stroustrup,1993]

B. Stroustrup: A History of C++: 1979-1991. Proc. ACM History of Programming Languages conference (HOPL-2). ACM Sigplan Notices. Vol 28, No 3. 1993.

[Stroustrup,1994]

B. Stroustrup: The Design and Evolution of C++. Addison-Wesley. Reading, Mass. 1994. ISBN 0-201-54330-3.

[Stroustrup,1997]

B. Stroustrup: The C++ Programming Language, Third Edition. Addison-Wesley. Reading, Massachusetts. 1997. ISBN 0-201-88954-4. Hardcover (“Special”) Edition. 2000. ISBN 0-201-70073-5.

[Stroustrup,2002]

B. Stroustrup: C and C++: Siblings, C and C++: A Case for Compatibility, and C and C++: Case Studies in Compatibility. The C/C++ Users Journal. July-September 2002. www.stroustrup.com/papers.html.

[Stroustrup,2007]

B. Stroustrup: Evolving a language in and for the real world: C++ 1991-2006. ACM HOPL-III. June 2007.

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B. Stroustrup: Programming – Principles and Practice Using C++. Addison-Wesley. 2009. ISBN 0-321-54372-6.

[Stroustrup,2010a]

B. Stroustrup: The C++11 FAQ. www.stroustrup.com/C++11FAQ.html.

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2. A Tour of C++: The Basics

The first thing we do, let’s kill all the language lawyers.

– Henry VI, Part II

• Introduction

• The Basics

Hello, World!; Types, Variables, and Arithmetic; Constants; Tests and Loops; Pointers, Arrays, and Loops

• User-Defined Types

Structures; Classes; Enumerations

• Modularity

Separate Compilation; Namespaces; Error Handling

• Postscript

• Advice

2.1. Introduction

The aim of this chapter and the next three is to give you an idea of what C++ is, without going into a lot of details. This chapter informally presents the notation of C++, C++’s model of memory and computation, and the basic mechanisms for organizing code into a program. These are the language facilities supporting the styles most often seen in C and sometimes called procedural programming. Chapter 3 follows up by presenting C++’s abstraction mechanisms. Chapter 4 and Chapter 5 give examples of standard-library facilities.

The assumption is that you have programmed before. If not, please consider reading a textbook, such as Programming: Principles and Practice Using C++ [Stroustrup,2009], before continuing here. Even if you have programmed before, the language you used or the applications you wrote may be very different from the style of C++ presented here. If you find this “lightning tour” confusing, skip to the more systematic presentation starting in Chapter 6.

This tour of C++ saves us from a strictly bottom-up presentation of language and library facilities by enabling the use of a rich set of facilities even in early chapters. For example, loops are not discussed in detail until Chapter 10, but they will be used in obvious ways long before that. Similarly, the detailed description of classes, templates, free-store use, and the standard library are spread over many chapters, but standard-library types, such as vector, string, complex, map, unique_ptr, and ostream, are used freely where needed to improve code examples.

As an analogy, think of a short sightseeing tour of a city, such as Copenhagen or New York. In just a few hours, you are given a quick peek at the major attractions, told a few background stories, and usually given some suggestions about what to see next. You do not know the city after such a tour. You do not understand all you have seen and heard. To really know a city, you have to live in it, often for years. However, with a bit of luck, you will have gained a bit of an overview, a notion of what is special about the city, and ideas of what might be of interest to you. After the tour, the real exploration can begin.

This tour presents C++ as an integrated whole, rather than as a layer cake. Consequently, it does not identify language features as present in C, part of C++98, or new in C++11. Such historical information can be found in §1.4 and Chapter 44.

2.2. The Basics

C++ is a compiled language. For a program to run, its source text has to be processed by a compiler, producing object files, which are combined by a linker yielding an executable program. A C++ program typically consists of many source code files (usually simply called source files).

An executable program is created for a specific hardware/system combination; it is not portable, say, from a Mac to a Windows PC. When we talk about portability of C++ programs, we usually mean portability of source code; that is, the source code can be successfully compiled and run on a variety of systems.

The ISO C++ standard defines two kinds of entities:

• Core language features, such as built-in types (e.g., char and int) and loops (e.g., for-statements and while-statements)

• Standard-library components, such as containers (e.g., vector and map) and I/O operations (e.g., << and getline())

The standard-library components are perfectly ordinary C++ code provided by every C++ implementation. That is, the C++ standard library can be implemented in C++ itself (and is with very minor uses of machine code for things such as thread context switching). This implies that C++ is sufficiently expressive and efficient for the most demanding systems programming tasks.

C++ is a statically typed language. That is, the type of every entity (e.g., object, value, name, and expression) must be known to the compiler at its point of use. The type of an object determines the set of operations applicable to it.

2.2.1. Hello, World!

The minimal C++ program is

int main() { }     // the minimal C++ program

This defines a function called main, which takes no arguments and does nothing (§15.4).

Curly braces, { }, express grouping in C++. Here, they indicate the start and end of the function body. The double slash, //, begins a comment that extends to the end of the line. A comment is for the human reader; the compiler ignores comments.

Every C++ program must have exactly one global function named main(). The program starts by executing that function. The int value returned by main(), if any, is the program’s return value to “the system.” If no value is returned, the system will receive a value indicating successful completion. A nonzero value from main() indicates failure. Not every operating system and execution environment make use of that return value: Linux/Unix-based environments often do, but Windows-based environments rarely do.

Typically, a program produces some output. Here is a program that writes Hello, World!:

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#include <iostream>

int main()
{
     std::cout << "Hello, World!\n";
}

The line #include <iostream> instructs the compiler to include the declarations of the standard stream I/O facilities as found in iostream. Without these declarations, the expression

std::cout << "Hello, World!\n"

would make no sense. The operator << (“put to”) writes its second argument onto its first. In this case, the string literal "Hello, World!\n" is written onto the standard output stream std::cout. A string literal is a sequence of characters surrounded by double quotes. In a string literal, the backslash character \ followed by another character denotes a single “special character.” In this case, \n is the newline character, so that the characters written are Hello, World! followed by a newline.

The std:: specifies that the name cout is to be found in the standard-library namespace (§2.4.2, Chapter 14). I usually leave out the std:: when discussing standard features; §2.4.2 shows how to make names from a namespace visible without explicit qualification.

Essentially all executable code is placed in functions and called directly or indirectly from main(). For example:

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#include <iostream>
using namespace std;       // make names from std visible without std:: (§2.4.2)

double square(double x)    // square a double precision floating-point number
{
    return x*x;
}

void print_square(double x)
{
     cout << "the square of " << x << " is " << square(x) << "\n";
}

int main()
{
     print_square(1.234);      // print: the square of 1.234 is 1.52276
}

A “return type” void indicates that a function does not return a value.

2.2.2. Types, Variables, and Arithmetic

Every name and every expression has a type that determines the operations that may be performed on it. For example, the declaration

int inch;

specifies that inch is of type int; that is, inch is an integer variable.

A declaration is a statement that introduces a name into the program. It specifies a type for the named entity:

• A type defines a set of possible values and a set of operations (for an object).

• An object is some memory that holds a value of some type.

• A value is a set of bits interpreted according to a type.

• A variable is a named object.

C++ offers a variety of fundamental types. For example:

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bool     // Boolean, possible values are true and false
char     // character, for example, 'a', ' z', and '9'
int      // integer, for example, 1, 42, and 1066
double   // double-precision floating-point number, for example, 3.14 and 299793.0

Each fundamental type corresponds directly to hardware facilities and has a fixed size that determines the range of values that can be stored in it:

A char variable is of the natural size to hold a character on a given machine (typically an 8-bit byte), and the sizes of other types are quoted in multiples of the size of a char. The size of a type is implementation-defined (i.e., it can vary among different machines) and can be obtained by the sizeof operator; for example, sizeof(char) equals 1 and sizeof(int) is often 4.

The arithmetic operators can be used for appropriate combinations of these types:

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x+y      // plus
+x       // unary plus
x–y      // minus
–x       // unary minus
x*y      // multiply
x/y      // divide
x%y      // remainder (modulus) for integers

So can the comparison operators:

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x==y     // equal
x!=y     // not equal
x<y      // less than
x>y      // greater than
x<=y     // less than or equal
x>=y     // greater than or equal

In assignments and in arithmetic operations, C++ performs all meaningful conversions (§10.5.3) between the basic types so that they can be mixed freely:

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void some_function()       // function that doesn't return a value
{
     double d = 2.2;       // initialize floating-point number
     int i = 7;            // initialize integer
     d = d+i;              // assign sum to d
     i = d*i;              // assign product to i (truncating the double d*i to an int)
}

Note that = is the assignment operator and == tests equality.

C++ offers a variety of notations for expressing initialization, such as the = used above, and a universal form based on curly-brace-delimited initializer lists:

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double d1 = 2.3;
double d2 {2.3};

complex<double> z = 1;           // a complex number with double-precision floating-point scalars
complex<double> z2 {d1,d2};
complex<double> z3 = {1,2};      // the = is optional with { ... }

vector<int> v {1,2,3,4,5,6};     // a vector of ints

The = form is traditional and dates back to C, but if in doubt, use the general {}-list form (§6.3.5.2). If nothing else, it saves you from conversions that lose information (narrowing conversions; §10.5):

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int i1 = 7.2;       // i1 becomes 7
int i2 {7.2};       // error: floating-point to integer conversion
int i3 = {7.2};     // error: floating-point to integer conversion (the = is redundant)

A constant (§2.2.3) cannot be left uninitialized and a variable should only be left uninitialized in extremely rare circumstances. Don’t introduce a name until you have a suitable value for it. User-defined types (such as string, vector, Matrix, Motor_controller, and Orc_warrior) can be defined to be implicitly initialized (§3.2.1.1).

When defining a variable, you don’t actually need to state its type explicitly when it can be deduced from the initializer:

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auto b = true;     // a bool
auto ch = 'x';     // a char
auto i = 123;      // an int
auto d = 1.2;      // a double
auto z = sqrt(y);  // z has the type of whatever sqrt(y) returns

With auto, we use the = syntax because there is no type conversion involved that might cause problems (§6.3.6.2).

We use auto where we don’t have a specific reason to mention the type explicitly. “Specific reasons” include:

• The definition is in a large scope where we want to make the type clearly visible to readers of our code.

• We want to be explicit about a variable’s range or precision (e.g., double rather than float).

Using auto, we avoid redundancy and writing long type names. This is especially important in generic programming where the exact type of an object can be hard for the programmer to know and the type names can be quite long (§4.5.1).

In addition to the conventional arithmetic and logical operators (§10.3), C++ offers more specific operations for modifying a variable:

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x+=y    // x = x+y
++x     // increment: x = x+1
x–=y    // x = x-y
––x     // decrement: x = x-1
x*=y    // scaling: x = x*y
x/=y    // scaling: x = x/y
x%=y    // x = x%y

These operators are concise, convenient, and very frequently used.

2.2.3. Constants

C++ supports two notions of immutability (§7.5):

• const: meaning roughly “I promise not to change this value” (§7.5). This is used primarily to specify interfaces, so that data can be passed to functions without fear of it being modified. The compiler enforces the promise made by const.

• constexpr: meaning roughly “to be evaluated at compile time” (§10.4). This is used primarily to specify constants, to allow placement of data in memory where it is unlikely to be corrupted, and for performance.

For example:

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const int dmv = 17;                         // dmv is a named constant
int var = 17;                               // var is not a constant
constexpr double max1 = 1.4*square(dmv);    // OK if square(17) is a constant expression
constexpr double max2 = 1.4*square(var);    // error: var is not a constant expression
const double max3 = 1.4*square(var);        // OK, may be evaluated at run time
double sum(const vector<double>&);          // sum will not modify its argument (§2.2.5)
vector<double> v {1.2, 3.4, 4.5};           // v is not a constant
const double s1 = sum(v);                   // OK: evaluated at run time
constexpr double s2 = sum(v);               // error: sum(v) not constant expression

For a function to be usable in a constant expression, that is, in an expression that will be evaluated by the compiler, it must be defined constexpr. For example:

constexpr double square(double x) { return x*x; }

To be constexpr, a function must be rather simple: just a return-statement computing a value. A constexpr function can be used for non-constant arguments, but when that is done the result is not a constant expression. We allow a constexpr function to be called with non-constant-expression arguments in contexts that do not require constant expressions, so that we don’t have to define essentially the same function twice: once for constant expressions and once for variables.

In a few places, constant expressions are required by language rules (e.g., array bounds (§2.2.5, §7.3), case labels (§2.2.4, §9.4.2), some template arguments (§25.2), and constants declared using constexpr). In other cases, compile-time evaluation is important for performance. Independently of performance issues, the notion of immutability (of an object with an unchangeable state) is an important design concern (§10.4).

2.2.4. Tests and Loops

C++ provides a conventional set of statements for expressing selection and looping. For example, here is a simple function that prompts the user and returns a Boolean indicating the response:

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bool accept()
{
     cout << "Do you want to proceed (y or n)?\n";    // write question

     char answer = 0;
     cin >> answer;                                   // read answer

     if (answer == 'y') return true;
     return false;
}

To match the << output operator (“put to”), the >> operator (“get from”) is used for input; cin is the standard input stream. The type of the right-hand operand of >> determines what input is accepted, and its right-hand operand is the target of the input operation. The \n character at the end of the output string represents a newline (§2.2.1).

The example could be improved by taking an n (for “no”) answer into account:

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bool accept2()
{
     cout << "Do you want to proceed (y or n)?\n"; // write question

     char answer = 0;
     cin >> answer;                                // read answer
     switch (answer) {
     case 'y':
          return true;
     case 'n':
          return false;
     default:
          cout << "I'll take that for a no.\n";
          return false;
     }
}

A switch-statement tests a value against a set of constants. The case constants must be distinct, and if the value tested does not match any of them, the default is chosen. If no default is provided, no action is taken if the value doesn’t match any case constant.

Few programs are written without loops. For example, we might like to give the user a few tries to produce acceptable input:

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bool accept3()
{
     int tries = 1;
     while (tries<4) {
         cout << "Do you want to proceed (y or n)?\n";  // write question
         char answer = 0;
         cin >> answer;                                 // read answer

         switch (answer) {
         case 'y':
              return true;
         case 'n':
              return false;
         default:
              cout << "Sorry, I don't understand that.\n";
              ++tries; // increment
         }
     }
     cout << "I'll take that for a no.\n";
     return false;
}

The while-statement executes until its condition becomes false.

2.2.5. Pointers, Arrays, and Loops

An array of elements of type char can be declared like this:

char v[6];       // array of 6 characters

Similarly, a pointer can be declared like this:

char* p;         // pointer to character

In declarations, [] means “array of” and * means “pointer to.” All arrays have 0 as their lower bound, so v has six elements, v[0] to v[5]. The size of an array must be a constant expression (§2.2.3). A pointer variable can hold the address of an object of the appropriate type:

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char* p = &v[3];          // p points to v's fourth element
char x = *p;              // *p is the object that p points to

In an expression, prefix unary * means “contents of” and prefix unary & means “address of.” We can represent the result of that initialized definition graphically:

Consider copying ten elements from one array to another:

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void copy_fct()
{
     int v1[10] = {0,1,2,3,4,5,6,7,8,9};
     int v2[10];                // to become a copy of v1

     for (auto i=0; i!=10; ++i) // copy elements
          v2[i]=v1[i];
     // ...
}

This for-statement can be read as “set i to zero; while i is not 10, copy the ith element and increment i.” When applied to an integer variable, the increment operator, ++, simply adds 1. C++ also offers a simpler for-statement, called a range-for-statement, for loops that traverse a sequence in the simplest way:

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void print()
{
     int v[] = {0,1,2,3,4,5,6,7,8,9};

     for (auto x : v)            // for each x in v
           cout << x << '\n';

     for (auto x : {10,21,32,43,54,65})
           cout << x << '\n';
     // ...
}

The first range-for-statement can be read as “for every element of v, from the first to the last, place a copy in x and print it.” Note that we don’t have to specify an array bound when we initialize it with a list. The range-for-statement can be used for any sequence of elements (§3.4.1).

If we didn’t want to copy the values from v into the variable x, but rather just have x refer to an element, we could write:

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void increment()
{
     int v[] = {0,1,2,3,4,5,6,7,8,9};

     for (auto& x : v)
           ++x;
     // ...
}

In a declaration, the unary suffix & means “reference to.” A reference is similar to a pointer, except that you don’t need to use a prefix* to access the value referred to by the reference. Also, a reference cannot be made to refer to a different object after its initialization. When used in declarations, operators (such as &, *, and []) are called declarator operators:

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T a[n];   // T[n]: array of n Ts (§7.3)
T* p;     // T*: pointer to T (§7.2)
T& r;     // T&: reference to T (§7.7)
T f(A);   // T(A): function taking an argument of type A returning a result of type T (§2.2.1)

We try to ensure that a pointer always points to an object, so that dereferencing it is valid. When we don’t have an object to point to or if we need to represent the notion of “no object available” (e.g., for an end of a list), we give the pointer the value nullptr (“the null pointer”). There is only one nullptr shared by all pointer types:

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double* pd = nullptr;
Link<Record>* lst = nullptr; // pointer to a Link to a Record
int x = nullptr;             // error: nullptr is a pointer not an integer

It is often wise to check that a pointer argument that is supposed to point to something, actually points to something:

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int count_x(char* p, char x)
     // count the number of occurrences of x in p[]
     // p is assumed to point to a zero-terminated array of char (or to nothing)
{
     if (p==nullptr) return 0;
     int count = 0;
     for (; *p!=0; ++p)
           if (*p==x)
                 ++count;
     return count;
}

Note how we can move a pointer to point to the next element of an array using ++ and that we can leave out the initializer in a for-statement if we don’t need it.

The definition of count_x() assumes that the char* is a C-style string, that is, that the pointer points to a zero-terminated array of char.

In older code, 0 or NULL is typically used instead of nullptr (§7.2.2). However, using nullptr eliminates potential confusion between integers (such as 0 or NULL) and pointers (such as nullptr).

2.3. User-Defined Types

We call the types that can be built from the fundamental types (§2.2.2), the const modifier (§2.2.3), and the declarator operators (§2.2.5) built-in types. C++’s set of built-in types and operations is rich, but deliberately low-level. They directly and efficiently reflect the capabilities of conventional computer hardware. However, they don’t provide the programmer with high-level facilities to conveniently write advanced applications. Instead, C++ augments the built-in types and operations with a sophisticated set of abstraction mechanisms out of which programmers can build such high-level facilities. The C++ abstraction mechanisms are primarily designed to let programmers design and implement their own types, with suitable representations and operations, and for programmers to simply and elegantly use such types. Types built out of the built-in types using C++’s abstraction mechanisms are called user-defined types. They are referred to as classes and enumerations. Most of this book is devoted to the design, implementation, and use of user-defined types. The rest of this chapter presents the simplest and most fundamental facilities for that. Chapter 3 is a more complete description of the abstraction mechanisms and the programming styles they support. Chapter 4 and Chapter 5 present an overview of the standard library, and since the standard library mainly consists of user-defined types, they provide examples of what can be built using the language facilities and programming techniques presented in Chapter 2 and Chapter 3.

2.3.1. Structures

The first step in building a new type is often to organize the elements it needs into a data structure, a struct:

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struct Vector {
     int sz;       // number of elements
     double* elem; // pointer to elements
};

This first version of Vector consists of an int and a double*.

A variable of type Vector can be defined like this:

Vector v;

However, by itself that is not of much use because v’s elem pointer doesn’t point to anything. To be useful, we must give v some elements to point to. For example, we can construct a Vector like this:

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void vector_init(Vector& v, int s)
{
     v.elem = new double[s]; // allocate an array of s doubles
     v.sz = s;
}

That is, v’s elem member gets a pointer produced by the new operator and v’s size member gets the number of elements. The & in Vector& indicates that we pass v by non-const reference (§2.2.5, §7.7); that way, vector_init() can modify the vector passed to it.

The new operator allocates memory from an area called the free store (also known as dynamic memory and heap; §11.2).

A simple use of Vector looks like this:

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double read_and_sum(int s)
    // read s integers from cin and return their sum; s is assumed to be positive
{
    Vector v;
    vector_init(v,s);           // allocate s elements for v
    for (int i=0; i!=s; ++i)
          cin>>v.elem[i];       // read into elements

    double sum = 0;
    for (int i=0; i!=s; ++i)
          sum+=v.elem[i];       // take the sum of the elements
    return sum;
}

There is a long way to go before our Vector is as elegant and flexible as the standard-library vector. In particular, a user of Vector has to know every detail of Vector’s representation. The rest of this chapter and the next gradually improve Vector as an example of language features and techniques. Chapter 4 presents the standard-library vector, which contains many nice improvements, and Chapter 31 presents the complete vector in the context of other standard-library facilities.

I use vector and other standard-library components as examples

• to illustrate language features and design techniques, and

• to help you learn and use the standard-library components.

Don’t reinvent standard-library components, such as vector and string; use them.

We use . (dot) to access struct members through a name (and through a reference) and –> to access struct members through a pointer. For example:

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void f(Vector v, Vector& rv, Vector* pv)
{
     int i1 = v.sz;     // access through name
     int i2 = rv.sz;    // access through reference
     int i4 = pv–>sz;   // access through pointer
}

2.3.2. Classes

Having the data specified separately from the operations on it has advantages, such as the ability to use the data in arbitrary ways. However, a tighter connection between the representation and the operations is needed for a user-defined type to have all the properties expected of a “real type.” In particular, we often want to keep the representation inaccessible to users, so as to ease use, guarantee consistent use of the data, and allow us to later improve the representation. To do that we have to distinguish between the interface to a type (to be used by all) and its implementation (which has access to the otherwise inaccessible data). The language mechanism for that is called a class. A class is defined to have a set of members, which can be data, function, or type members. The interface is defined by the public members of a class, and private members are accessible only through that interface. For example:

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class Vector {
public:
     Vector(int s) :elem{new double[s]}, sz{s} { } // construct a Vector
     double& operator[](int i) { return elem[i]; } // element access: subscripting
     int size() { return sz; }
private:
     double* elem; // pointer to the elements
     int sz;       // the number of elements
};

Given that, we can define a variable of our new type Vector:

Vector v(6);      // a Vector with 6 elements

We can illustrate a Vector object graphically:

Basically, the Vector object is a “handle” containing a pointer to the elements (elem) plus the number of elements (sz). The number of elements (6 in the example) can vary from Vector object to Vector object, and a Vector object can have a different number of elements at different times (§3.2.1.3). However, the Vector object itself is always the same size. This is the basic technique for handling varying amounts of information in C++: a fixed-size handle referring to a variable amount of data “elsewhere” (e.g., on the free store allocated by new; §11.2). How to design and use such objects is the main topic of Chapter 3.

Here, the representation of a Vector (the members elem and sz) is accessible only through the interface provided by the public members: Vector(), operator[](), and size(). The read_and_sum() example from §2.3.1 simplifies to:

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double read_and_sum(int s)
{
    Vector v(s);                     // make a vector of s elements
    for (int i=0; i!=v.size(); ++i)
          cin>>v[i];                 // read into elements

    double sum = 0;
    for (int i=0; i!=v.size(); ++i)
          sum+=v[i];                 // take the sum of the elements
    return sum;
}

A “function” with the same name as its class is called a constructor, that is, a function used to construct objects of a class. So, the constructor, Vector(), replaces vector_init() from §2.3.1. Unlike an ordinary function, a constructor is guaranteed to be used to initialize objects of its class. Thus, defining a constructor eliminates the problem of uninitialized variables for a class.

Vector(int) defines how objects of type Vector are constructed. In particular, it states that it needs an integer to do that. That integer is used as the number of elements. The constructor initializes the Vector members using a member initializer list:

:elem{new double[s]}, sz{s}

That is, we first initialize elem with a pointer to s elements of type double obtained from the free store. Then, we initialize sz to s.

Access to elements is provided by a subscript function, called operator[]. It returns a reference to the appropriate element (a double&).

The size() function is supplied to give users the number of elements.

Obviously, error handling is completely missing, but we’ll return to that in §2.4.3. Similarly, we did not provide a mechanism to “give back” the array of doubles acquired by new; §3.2.1.2 shows how to use a destructor to elegantly do that.

2.3.3. Enumerations

In addition to classes, C++ supports a simple form of user-defined type for which we can enumerate the values:

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enum class Color { red, blue, green };
enum class Traffic_light { green, yellow, red };

Color col = Color::red;
Traffic_light light = Traffic_light::red;

Note that enumerators (e.g., red) are in the scope of their enum class, so that they can be used repeatedly in different enum classes without confusion. For example, Color::red is Color’s red which is different from Traffic_light::red.

Enumerations are used to represent small sets of integer values. They are used to make code more readable and less error-prone than it would have been had the symbolic (and mnemonic) enumerator names not been used.

The class after the enum specifies that an enumeration is strongly typed and that its enumerators are scoped. Being separate types, enum classes help prevent accidental misuses of constants. In particular, we cannot mix Traffic_light and Color values:

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Color x = red;                 // error: which red?
Color y = Traffic_light::red;  // error: that red is not a Color
Color z = Color::red;          // OK

Similarly, we cannot implicitly mix Color and integer values:

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int i = Color::red;        // error: Color::red is not an int
Color c = 2;               // error: 2 is not a Color

If you don’t want to explicitly qualify enumerator names and want enumerator values to be ints (without the need for an explicit conversion), you can remove the class from enum class to get a “plain enum” (§8.4.2).

By default, an enum class has only assignment, initialization, and comparisons (e.g., == and <; §2.2.2) defined. However, an enumeration is a user-defined type so we can define operators for it:

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Traffic_light& operator++(Traffic_light& t)
      // prefix increment: ++
{
      switch (t) {
      case Traffic_light::green:    return t=Traffic_light::yellow;
      case Traffic_light::yellow:   return t=Traffic_light::red;
      case Traffic_light::red:      return t=Traffic_light::green;
      }
}

Traffic_light next = ++light;       // next becomes Traffic_light::green

C++ also offers a less strongly typed “plain” enum (§8.4.2).

2.4. Modularity

A C++ program consists of many separately developed parts, such as functions (§2.2.1, Chapter 12), user-defined types (§2.3, §3.2, Chapter 16), class hierarchies (§3.2.4, Chapter 20), and templates (§3.4, Chapter 23). The key to managing this is to clearly define the interactions among those parts. The first and most important step is to distinguish between the interface to a part and its implementation. At the language level, C++ represents interfaces by declarations. A declaration specifies all that’s needed to use a function or a type. For example:

Click here to view code image

double sqrt(double);    // the square root function takes a double and returns a double

class Vector {
public:
     Vector(int s);
     double& operator[](int i);
     int size();
private:
     double* elem; // elem points to an array of sz doubles
     int sz;
};

The key point here is that the function bodies, the function definitions, are “elsewhere.” For this example, we might like for the representation of Vector to be “elsewhere” also, but we will deal with that later (abstract types; §3.2.2). The definition of sqrt() will look like this:

Click here to view code image

double sqrt(double d)     // definition of sqrt()
{
    // ... algorithm as found in math textbook ...
}

For Vector, we need to define all three member functions:

Click here to view code image

Vector::Vector(int s)               // definition of the constructor
    :elem{new double[s]}, sz{s}     // initialize members
{
}

double& Vector::operator[](int i)   // definition of subscripting
{
    return elem[i];
}

int Vector::size()                  // definition of size()
{
    return sz;
}

We must define Vector’s functions, but not sqrt() because it is part of the standard library. However, that makes no real difference: a library is simply some “other code we happen to use” written with the same language facilities as we use.

2.4.1. Separate Compilation

C++ supports a notion of separate compilation where user code sees only declarations of types and functions used. The definitions of those types and functions are in separate source files and compiled separately. This can be used to organize a program into a set of semi-independent code fragments. Such separation can be used to minimize compilation times and to strictly enforce separation of logically distinct parts of a program (thus minimizing the chance of errors). A library is often a separately compiled code fragments (e.g., functions).

Typically, we place the declarations that specify the interface to a module in a file with a name indicating its intended use. For example:

Click here to view code image

// Vector.h:

class Vector {
public:
     Vector(int s);
     double& operator[](int i);
     int size();
private:
     double* elem;    // elem points to an array of sz doubles
     int sz;
};

This declaration would be placed in a file Vector.h, and users will include that file, called a header file, to access that interface. For example:

Click here to view code image

// user.cpp:

#include "Vector.h"       // get Vector's interface
#include <cmath>          // get the the standard-library math function interface including sqrt()
using namespace std;      // make std members visible (§2.4.2)

double sqrt_sum(Vector& v)
{
    double sum = 0;
    for (int i=0; i!=v.size(); ++i)
          sum+=sqrt(v[i]);             // sum of square roots
    return sum;
}

To help the compiler ensure consistency, the .cpp file providing the implementation of Vector will also include the .h file providing its interface:

Click here to view code image

// Vector.cpp:

#include "Vector.h" // get the interface

Vector::Vector(int s)
    :elem{new double[s]}, sz{s}
{
}

double& Vector::operator[](int i)
{
    return elem[i];
}

int Vector::size()
{
    return sz;
}

The code in user.cpp and Vector.cpp shares the Vector interface information presented in Vector.h, but the two files are otherwise independent and can be separately compiled. Graphically, the program fragments can be represented like this:

Strictly speaking, using separate compilation isn’t a language issue; it is an issue of how best to take advantage of a particular language implementation. However, it is of great practical importance. The best approach is to maximize modularity, represent that modularity logically through language features, and then exploit the modularity physically through files for effective separate compilation (Chapter 14, Chapter 15).

2.4.2. Namespaces

In addition to functions (§2.2.1, Chapter 12), classes (Chapter 16), and enumerations (§2.3.3, §8.4), C++ offers namespaces (Chapter 14) as a mechanism for expressing that some declarations belong together and that their names shouldn’t clash with other names. For example, I might want to experiment with my own complex number type (§3.2.1.1, §18.3, §40.4):

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namespace My_code {
   class complex { /* ... */ };
   complex sqrt(complex);
   // ...
   int main();
}

int My_code::main()
{
   complex z {1,2};
   auto z2 = sqrt(z);
   std::cout << '{' << z2.real() << ',' << z2.imag() << "}\n";
   // ...
};

int main()
{
   return My_code::main();
}

By putting my code into the namespace My_code, I make sure that my names do not conflict with the standard-library names in namespace std (§4.1.2). The precaution is wise, because the standard library does provide support for complex arithmetic (§3.2.1.1, §40.4).

The simplest way to access a name in another namespace is to qualify it with the namespace name (e.g., std::cout and My_code::main). The “real main()” is defined in the global namespace, that is, not local to a defined namespace, class, or function. To gain access to names in the standard-library namespace, we can use a using-directive (§14.2.3):

using namespace std;

Namespaces are primarily used to organize larger program components, such as libraries. They simplify the composition of a program out of separately developed parts.

2.4.3. Error Handling

Error handling is a large and complex topic with concerns and ramifications that go far beyond language facilities into programming techniques and tools. However, C++ provides a few features to help. The major tool is the type system itself. Instead of painstakingly building up our applications from the built-in types (e.g., char, int, and double) and statements (e.g., if, while, and for), we build more types that are appropriate for our applications (e.g., string, map, and regex) and algorithms (e.g., sort(), find_if(), and draw_all()). Such higher level constructs simplify our programming, limit our opportunities for mistakes (e.g., you are unlikely to try to apply a tree traversal to a dialog box), and increase the compiler’s chances of catching such errors. The majority of C++ constructs are dedicated to the design and implementation of elegant and efficient abstractions (e.g., user-defined types and algorithms using them). One effect of this modularity and abstraction (in particular, the use of libraries) is that the point where a run-time error can be detected is separated from the point where it can be handled. As programs grow, and especially when libraries are used extensively, standards for handling errors become important.

2.4.3.1. Exceptions

Consider again the Vector example. What ought to be done when we try to access an element that is out of range for the vector from §2.3.2?

• The writer of Vector doesn’t know what the user would like to have done in this case (the writer of Vector typically doesn’t even know in which program the vector will be running).

• The user of Vector cannot consistently detect the problem (if the user could, the out-of-range access wouldn’t happen in the first place).

The solution is for the Vector implementer to detect the attempted out-of-range access and then tell the user about it. The user can then take appropriate action. For example, Vector::operator[]() can detect an attempted out-of-range access and throw an out_of_range exception:

Click here to view code image

double& Vector::operator[](int i)
{
    if (i<0 || size()<=i) throw out_of_range{"Vector::operator[]"};
    return elem[i];
}

The throw transfers control to a handler for exceptions of type out_of_range in some function that directly or indirectly called Vector::operator[](). To do that, the implementation will unwind the function call stack as needed to get back to the context of that caller (§13.5.1). For example:

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void f(Vector& v)
{
     // ...
     try { // exceptions here are handled by the handler defined below

         v[v.size()] = 7; // try to access beyond the end of v
     }
     catch (out_of_range) { // oops: out_of_range error
         // ... handle range error ...
     }
     // ...
}

We put code for which we are interested in handling exceptions into a try-block. That attempted assignment to v[v.size()] will fail. Therefore, the catch-clause providing a handler for out_of_range will be entered. The out_of_range type is defined in the standard library and is in fact used by some standard-library container access functions.

Use of the exception-handling mechanisms can make error handling simpler, more systematic, and more readable. See Chapter 13 for further discussion, details, and examples.

2.4.3.2. Invariants

The use of exceptions to signal out-of-range access is an example of a function checking its argument and refusing to act because a basic assumption, a precondition, didn’t hold. Had we formally specified Vector’s subscript operator, we would have said something like “the index must be in the [0:size()) range,” and that was in fact what we tested in our operator[](). Whenever we define a function, we should consider what its preconditions are and if feasible test them (see §12.4, §13.4).

However, operator[]() operates on objects of type Vector and nothing it does makes any sense unless the members of Vector have “reasonable” values. In particular, we did say “elem points to an array of sz doubles” but we only said that in a comment. Such a statement of what is assumed to be true for a class is called a class invariant, or simply an invariant. It is the job of a constructor to establish the invariant for its class (so that the member functions can rely on it) and for the member functions to make sure that the invariant holds when they exit. Unfortunately, our Vector constructor only partially did its job. It properly initialized the Vector members, but it failed to check that the arguments passed to it made sense. Consider:

Vector v(–27);

This is likely to cause chaos.

Here is a more appropriate definition:

Click here to view code image

Vector::Vector(int s)
{
    if (s<0) throw length_error{};
    elem = new double[s];
    sz = s;
}

I use the standard-library exception length_error to report a non-positive number of elements because some standard-library operations use that exception to report problems of this kind. If operator new can’t find memory to allocate, it throws a std::bad_alloc. We can now write:

Click here to view code image

void test()
{
     try {
         Vector v(–27);
     }
     catch (std::length_error) {
         // handle negative size
     }
     catch (std::bad_alloc) {
         // handle memory exhaustion
     }
}

You can define your own classes to be used as exceptions and have them carry arbitrary information from a point where an error is detected to a point where it can be handled (§13.5).

Often, a function has no way of completing its assigned task after an exception is thrown. Then, “handling” an exception simply means doing some minimal local cleanup and rethrowing the exception (§13.5.2.1).

The notion of invariants is central to the design of classes, and preconditions serve a similar role in the design of functions. Invariants

• helps us to understand precisely what we want

• forces us to be specific; that gives us a better chance of getting our code correct (after debugging and testing).

The notion of invariants underlies C++’s notions of resource management supported by constructors (§2.3.2) and destructors (§3.2.1.2, §5.2). See also §13.4, §16.3.1, and §17.2.

2.4.3.3. Static Assertions

Exceptions report errors found at run time. If an error can be found at compile time, it is usually preferable to do so. That’s what much of the type system and the facilities for specifying the interfaces to user-defined types are for. However, we can also perform simple checks on other properties that are known at compile time and report failures as compiler error messages. For example:

static_assert(4<=sizeof(int), "integers are too small"); // check integer size

This will write integers are too small if 4<=sizeof(int) does not hold, that is, if an int on this system does not have at least 4 bytes. We call such statements of expectations assertions.

The static_assert mechanism can be used for anything that can be expressed in terms of constant expressions (§2.2.3, §10.4). For example:

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constexpr double C = 299792.458;                        // km/s

void f(double speed)
{
     const double local_max = 160.0/(60*60);            // 160 km/h == 160.0/(60*60) km/s

     static_assert(speed<C,"can't go that fast");       // error: speed must be a constant
     static_assert(local_max<C,"can't go that fast");   // OK

     // ...
}

In general, static_assert(A,S) prints S as a compiler error message if A is not true.

The most important uses of static_assert come when we make assertions about types used as parameters in generic programming (§5.4.2, §24.3).

For runtime-checked assertions, see §13.4.

2.5. Postscript

The topics covered in this chapter roughly correspond to the contents of Part II (Chapters 6–15). Those are the parts of C++ that underlie all programming techniques and styles supported by C++. Experienced C and C++ programmers, please note that this foundation does not closely correspond to the C or C++98 subsets of C++ (that is, C++11).

2.6. Advice

[1] Don’t panic! All will become clear in time; §2.1.

[2] You don’t have to know every detail of C++ to write good programs; §1.3.1.

[3] Focus on programming techniques, not on language features; §2.1.

3. A Tour of C++: Abstraction Mechanisms

Don’t Panic!

– Douglas Adams

• Introduction

• Classes

Concrete Types; Abstract Types; Virtual Functions; Class Hierarchies

• Copy and Move

Copying Containers; Moving Containers; Resource Management; Suppressing Operations

• Templates

Parameterized Types; Function Templates; Function Objects; Variadic Templates; Aliases

• Advice

3.1. Introduction

This chapter aims to give you an idea of C++’s support for abstraction and resource management without going into a lot of detail. It informally presents ways of defining and using new types (user-defined types). In particular, it presents the basic properties, implementation techniques, and language facilities used for concrete classes, abstract classes, and class hierarchies. Templates are introduced as a mechanism for parameterizing types and algorithms with (other) types and algorithms. Computations on user-defined and built-in types are represented as functions, sometimes generalized to template functions and function objects. These are the language facilities supporting the programming styles known as object-oriented programming and generic programming. The next two chapters follow up by presenting examples of standard-library facilities and their use.

The assumption is that you have programmed before. If not, please consider reading a textbook, such as Programming: Principles and Practice Using C++ [Stroustrup,2009], before continuing here. Even if you have programmed before, the language you used or the applications you wrote may be very different from the style of C++ presented here. If you find this “lightning tour” confusing, skip to the more systematic presentation starting in Chapter 6.

As in Chapter 2, this tour presents C++ as an integrated whole, rather than as a layer cake. Consequently, it does not identify language features as present in C, part of C++98, or new in C++11. Such historical information can be found in §1.4 and Chapter 44.

3.2. Classes

The central language feature of C++ is the class. A class is a user-defined type provided to represent a concept in the code of a program. Whenever our design for a program has a useful concept, idea, entity, etc., we try to represent it as a class in the program so that the idea is there in the code, rather than just in our head, in a design document, or in some comments. A program built out of a well chosen set of classes is far easier to understand and get right than one that builds everything directly in terms of the built-in types. In particular, classes are often what libraries offer.

Essentially all language facilities beyond the fundamental types, operators, and statements exist to help define better classes or to use them more conveniently. By “better,” I mean more correct, easier to maintain, more efficient, more elegant, easier to use, easier to read, and easier to reason about. Most programming techniques rely on the design and implementation of specific kinds of classes. The needs and tastes of programmers vary immensely. Consequently, the support for classes is extensive. Here, we will just consider the basic support for three important kinds of classes:

• Concrete classes (§3.2.1)

• Abstract classes (§3.2.2)

• Classes in class hierarchies (§3.2.4)

An astounding number of useful classes turn out to be of these three kinds. Even more classes can be seen as simple variants of these kinds or are implemented using combinations of the techniques used for these.

3.2.1. Concrete Types

The basic idea of concrete classes is that they behave “just like built-in types.” For example, a complex number type and an infinite-precision integer are much like built-in int, except of course that they have their own semantics and sets of operations. Similarly, a vector and a string are much like built-in arrays, except that they are better behaved (§4.2, §4.3.2, §4.4.1).

The defining characteristic of a concrete type is that its representation is part of its definition. In many important cases, such as a vector, that representation is only one or more pointers to more data stored elsewhere, but it is present in each object of a concrete class. That allows implementations to be optimally efficient in time and space. In particular, it allows us to

• place objects of concrete types on the stack, in statically allocated memory, and in other objects (§6.4.2);

• refer to objects directly (and not just through pointers or references);

• initialize objects immediately and completely (e.g., using constructors; §2.3.2); and

• copy objects (§3.3).

The representation can be private (as it is for Vector; §2.3.2) and accessible only through the member functions, but it is present. Therefore, if the representation changes in any significant way, a user must recompile. This is the price to pay for having concrete types behave exactly like built-in types. For types that don’t change often, and where local variables provide much-needed clarity and efficiency, this is acceptable and often ideal. To increase flexibility, a concrete type can keep major parts of its representation on the free store (dynamic memory, heap) and access them through the part stored in the class object itself. That’s the way vector and string are implemented; they can be considered resource handles with carefully crafted interfaces.

3.2.1.1. An Arithmetic Type

The “classical user-defined arithmetic type” is complex:

Click here to view code image

class complex {
     double re, im; // representation: two doubles
public:
     complex(double r, double i) :re{r}, im{i} {}  // construct complex from two scalars
     complex(double r) :re{r}, im{0} {}            // construct complex from one scalar
     complex() :re{0}, im{0} {}                    // default complex: {0,0}

     double real() const { return re; }
     void real(double d) { re=d; }
     double imag() const { return im; }
     void imag(double d) { im=d; }

     complex& operator+=(complex z) { re+=z.re, im+=z.im; return *this; } // add to re and im
                                                                          // and return the result
     complex& operator–=(complex z) { re–=z.re, im–=z.im; return *this; }

     complex& operator*=(complex);    // defined out-of-class somewhere
     complex& operator/=(complex);    // defined out-of-class somewhere
};

This is a slightly simplified version of the standard-library complex (§40.4). The class definition itself contains only the operations requiring access to the representation. The representation is simple and conventional. For practical reasons, it has to be compatible with what Fortran provided 50 years ago, and we need a conventional set of operators. In addition to the logical demands, complex must be efficient or it will remain unused. This implies that simple operations must be inlined. That is, simple operations (such as constructors, +=, and imag()) must be implemented without function calls in the generated machine code. Functions defined in a class are inlined by default. An industrial-strength complex (like the standard-library one) is carefully implemented to do appropriate inlining.

A constructor that can be invoked without an argument is called a default constructor. Thus, complex() is complex’s default constructor. By defining a default constructor you eliminate the possibility of uninitialized variables of that type.

The const specifiers on the functions returning the real and imaginary parts indicate that these functions do not modify the object for which they are called.

Many useful operations do not require direct access to the representation of complex, so they can be defined separately from the class definition:

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complex operator+(complex a, complex b) { return a+=b; }
complex operator–(complex a, complex b) { return a–=b; }
complex operator–(complex a) { return {–a.real(), –a.imag()}; }    // unary minus
complex operator*(complex a, complex b) { return a*=b; }
complex operator/(complex a, complex b) { return a/=b; }

Here, I use the fact that an argument passed by value is copied, so that I can modify an argument without affecting the caller’s copy, and use the result as the return value.

The definitions of == and != are straightforward:

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bool operator==(complex a, complex b)          // equal
{
     return a.real()==b.real() && a.imag()==b.imag();
}

bool operator!=(complex a, complex b)          // not equal
{
     return !(a==b);
}

complex sqrt(complex);

// ...

Class complex can be used like this:

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void f(complex z)
{
     complex a {2.3};       // construct {2.3,0.0} from 2.3
     complex b {1/a};
     complex c {a+z*complex{1,2.3}};
     // ...
     if (c != b)
            c = –(b/a)+2*b;
}

The compiler converts operators involving complex numbers into appropriate function calls. For example, c!=b means operator!=(c,b) and 1/a means operator/(complex{1},a).

User-defined operators (“overloaded operators”) should be used cautiously and conventionally. The syntax is fixed by the language, so you can’t define a unary /. Also, it is not possible to change the meaning of an operator for built-in types, so you can’t redefine + to subtract ints.

3.2.1.2. A Container

A container is an object holding a collection of elements, so we call Vector a container because it is the type of objects that are containers. As defined in §2.3.2, Vector isn’t an unreasonable container of doubles: it is simple to understand, establishes a useful invariant (§2.4.3.2), provides range-checked access (§2.4.3.1), and provides size() to allow us to iterate over its elements. However, it does have a fatal flaw: it allocates elements using new but never deallocates them. That’s not a good idea because although C++ defines an interface for a garbage collector (§34.5), it is not guaranteed that one is available to make unused memory available for new objects. In some environments you can’t use a collector, and sometimes you prefer more precise control of destruction (§13.6.4) for logical or performance reasons. We need a mechanism to ensure that the memory allocated by the constructor is deallocated; that mechanism is a destructor:

Click here to view code image

class Vector {
private:
     double* elem;        // elem points to an array of sz doubles
     int sz;
public:
     Vector(int s) :elem{new double[s]}, sz{s}         // constructor: acquire resources
     {
         for (int i=0; i!=s; ++i) elem[i]=0;           // initialize elements
     }

     ~Vector() { delete[] elem; }                      // destructor: release resources

     double& operator[](int i);
     int size() const;
};

The name of a destructor is the complement operator, ~, followed by the name of the class; it is the complement of a constructor. Vector’s constructor allocates some memory on the free store (also called the heap or dynamic store) using the new operator. The destructor cleans up by freeing that memory using the delete operator. This is all done without intervention by users of Vector. The users simply create and use Vectors much as they would variables of built-in types. For example:

void fct(int n)
{
     Vector v(n);

     // ... use v ...

     {
           Vector v2(2*n);
           // ... use v and v2 ...
     } // v2 is destroyed here

     // ... use v ..

} // v is destroyed here

Vector obeys the same rules for naming, scope, allocation, lifetime, etc., as does a built-in type, such as int and char. For details on how to control the lifetime of an object, see §6.4. This Vector has been simplified by leaving out error handling; see §2.4.3.

The constructor/destructor combination is the basis of many elegant techniques. In particular, it is the basis for most C++ general resource management techniques (§5.2, §13.3). Consider a graphical illustration of a Vector:

The constructor allocates the elements and initializes the Vector members appropriately. The destructor deallocates the elements. This handle-to-data model is very commonly used to manage data that can vary in size during the lifetime of an object. The technique of acquiring resources in a constructor and releasing them in a destructor, known as Resource Acquisition Is Initialization or RAII, allows us to eliminate “naked new operations,” that is, to avoid allocations in general code and keep them buried inside the implementation of well-behaved abstractions. Similarly, “naked delete operations” should be avoided. Avoiding naked new and naked delete makes code far less error-prone and far easier to keep free of resource leaks (§5.2).

3.2.1.3. Initializing Containers

A container exists to hold elements, so obviously we need convenient ways of getting elements into a container. We can handle that by creating a Vector with an appropriate number of elements and then assigning to them, but typically other ways are more elegant. Here, I just mention two favorites:

• Initializer-list constructor: Initialize with a list of elements.

• push_back(): Add a new element at the end (at the back of) the sequence.

These can be declared like this:

Click here to view code image

class Vector {
public:
     Vector(std::initializer_list<double>);     // initialize with a list
     // ...
     void push_back(double);                    // add element at end increasing the size by one
     // ...
};

The push_back() is useful for input of arbitrary numbers of elements. For example:

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Vector read(istream& is)
{
    Vector v;
    for (double d; is>>d;)     // read floating-point values into d
          v.push_back(d);      // add d to v
    return v;
}

The input loop is terminated by an end-of-file or a formatting error. Until that happens, each number read is added to the Vector so that at the end, v’s size is the number of elements read. I used a for-statement rather than the more conventional while-statement to keep the scope of d limited to the loop. The implementation of push_back() is discussed in §13.6.4.3. The way to provide Vector with a move constructor, so that returning a potentially huge amount of data from read() is cheap, is explained in §3.3.2.

The std::initializer_list used to define the initializer-list constructor is a standard-library type known to the compiler: when we use a {}-list, such as {1,2,3,4}, the compiler will create an object of type initializer_list to give to the program. So, we can write:

Click here to view code image

Vector v1 = {1,2,3,4,5};            // v1 has 5 elements
Vector v2 = {1.23, 3.45, 6.7, 8};   // v2 has 4 elements

Vector’s initializer-list constructor might be defined like this:

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Vector::Vector(std::initializer_list<double> lst)    // initialize with a list
    :elem{new double[lst.size()]}, sz{lst.size()}
{
    copy(lst.begin(),lst.end(),elem);          // copy from lst into elem
}

3.2.2. Abstract Types

Types such as complex and Vector are called concrete types because their representation is part of their definition. In that, they resemble built-in types. In contrast, an abstract type is a type that completely insulates a user from implementation details. To do that, we decouple the interface from the representation and give up genuine local variables. Since we don’t know anything about the representation of an abstract type (not even its size), we must allocate objects on the free store (§3.2.1.2, §11.2) and access them through references or pointers (§2.2.5, §7.2, §7.7).

First, we define the interface of a class Container which we will design as a more abstract version of our Vector:

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class Container {
public:
     virtual double& operator[](int) = 0;     // pure virtual function
     virtual int size() const = 0;            // const member function (§3.2.1.1)
     virtual ~Container() {}                  // destructor (§3.2.1.2)
};

This class is a pure interface to specific containers defined later. The word virtual means “may be redefined later in a class derived from this one.” Unsurprisingly, a function declared virtual is called a virtual function. A class derived from Container provides an implementation for the Container interface. The curious =0 syntax says the function is pure virtual; that is, some class derived from Container must define the function. Thus, it is not possible to define an object that is just a Container; a Container can only serve as the interface to a class that implements its operator[]() and size() functions. A class with a pure virtual function is called an abstract class.

This Container can be used like this:

void use(Container& c)
{
     const int sz = c.size();

     for (int i=0; i!=sz; ++i)
           cout << c[i] << '\n';
}

Note how use() uses the Container interface in complete ignorance of implementation details. It uses size() and [] without any idea of exactly which type provides their implementation. A class that provides the interface to a variety of other classes is often called a polymorphic type (§20.3.2).

As is common for abstract classes, Container does not have a constructor. After all, it does not have any data to initialize. On the other hand, Container does have a destructor and that destructor is virtual. Again, that is common for abstract classes because they tend to be manipulated through references or pointers, and someone destroying a Container through a pointer has no idea what resources are owned by its implementation; see also §3.2.4.

A container that implements the functions required by the interface defined by the abstract class Container could use the concrete class Vector:

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class Vector_container : public Container {   // Vector_container implements Container
     Vector v;
public:
     Vector_container(int s) : v(s) { }  // Vector of s elements
     ~Vector_container() {}

     double& operator[](int i) { return v[i]; }
     int size() const { return v.size(); }
};

The :public can be read as “is derived from” or “is a subtype of.” Class Vector_container is said to be derived from class Container, and class Container is said to be a base of class Vector_container. An alternative terminology calls Vector_container and Container subclass and superclass, respectively. The derived class is said to inherit members from its base class, so the use of base and derived classes is commonly referred to as inheritance.

The members operator[]() and size() are said to override the corresponding members in the base class Container (§20.3.2). The destructor (~Vector_container()) overrides the base class destructor (~Container()). Note that the member destructor (~Vector()) is implicitly invoked by its class’s destructor (~Vector_container()).

For a function like use(Container&) to use a Container in complete ignorance of implementation details, some other function will have to make an object on which it can operate. For example:

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void g()
{
     Vector_container vc {10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0};
     use(vc);
}

Since use() doesn’t know about Vector_containers but only knows the Container interface, it will work just as well for a different implementation of a Container. For example:

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class List_container : public Container { // List_container implements Container
     std::list<double> ld;     // (standard-library) list of doubles (§4.4.2)
public:
     List_container() { }      // empty List
     List_container(initializer_list<double> il) : ld{il} { }
     ~List_container() {}
     double& operator[](int i);
     int size() const { return ld.size(); }
};

double& List_container::operator[](int i)
{
     for (auto& x : ld) {
           if (i==0) return x;
           ––i;
     }
     throw out_of_range("List container");
}

Here, the representation is a standard-library list<double>. Usually, I would not implement a container with a subscript operation using a list, because performance of list subscripting is atrocious compared to vector subscripting. However, here I just wanted to show an implementation that is radically different from the usual one.

A function can create a List_container and have use() use it:

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void h()
{
     List_container lc = { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
     use(lc);
}

The point is that use(Container&) has no idea if its argument is a Vector_container, a List_container, or some other kind of container; it doesn’t need to know. It can use any kind of Container. It knows only the interface defined by Container. Consequently, use(Container&) needn’t be recompiled if the implementation of List_container changes or a brand-new class derived from Container is used.

The flip side of this flexibility is that objects must be manipulated through pointers or references (§3.3, §20.4).

3.2.3. Virtual Functions

Consider again the use of Container:

void use(Container& c)
{
     const int sz = c.size();

     for (int i=0; i!=sz; ++i)
           cout << c[i] << '\n';
}

How is the call c[i] in use() resolved to the right operator[]()? When h() calls use(), List_container’s operator[]() must be called. When g() calls use(), Vector_container’s operator[]() must be called. To achieve this resolution, a Container object must contain information to allow it to select the right function to call at run time. The usual implementation technique is for the compiler to convert the name of a virtual function into an index into a table of pointers to functions. That table is usually called the virtual function table or simply the vtbl. Each class with virtual functions has its own vtbl identifying its virtual functions. This can be represented graphically like this:

The functions in the vtbl allow the object to be used correctly even when the size of the object and the layout of its data are unknown to the caller. The implementation of the caller needs only to know the location of the pointer to the vtbl in a Container and the index used for each virtual function. This virtual call mechanism can be made almost as efficient as the “normal function call” mechanism (within 25%). Its space overhead is one pointer in each object of a class with virtual functions plus one vtbl for each such class.

3.2.4. Class Hierarchies

The Container example is a very simple example of a class hierarchy. A class hierarchy is a set of classes ordered in a lattice created by derivation (e.g., : public). We use class hierarchies to represent concepts that have hierarchical relationships, such as “A fire engine is a kind of a truck which is a kind of a vehicle” and “A smiley face is a kind of a circle which is a kind of a shape.” Huge hierarchies, with hundreds of classes, that are both deep and wide are common. As a semi-realistic classic example, let’s consider shapes on a screen:

The arrows represent inheritance relationships. For example, class Circle is derived from class Shape. To represent that simple diagram in code, we must first specify a class that defines the general properties of all shapes:

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class Shape {
public:
     virtual Point center() const =0;     // pure virtual
     virtual void move(Point to) =0;

     virtual void draw() const = 0;       // draw on current "Canvas"
     virtual void rotate(int angle) = 0;

     virtual ~Shape() {}                  // destructor
     // ...
};

Naturally, this interface is an abstract class: as far as representation is concerned, nothing (except the location of the pointer to the vtbl) is common for every Shape. Given this definition, we can write general functions manipulating vectors of pointers to shapes:

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void rotate_all(vector<Shape*>& v, int angle) // rotate v's elements by angle degrees
{
     for (auto p : v)
           p–>rotate(angle);
}

To define a particular shape, we must say that it is a Shape and specify its particular properties (including its virtual functions):

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class Circle : public Shape {
public:
     Circle(Point p, int rr);         // constructor

     Point center() const { return x; }
     void move(Point to) { x=to; }

     void draw() const;
     void rotate(int) {}              // nice simple algorithm
private:
     Point x;  // center
     int r;    // radius
};

So far, the Shape and Circle example provides nothing new compared to the Container and Vector_container example, but we can build further:

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class Smiley : public Circle { // use the circle as the base for a face
public:
     Smiley(Point p, int r) : Circle{p,r}, mouth{nullptr} { }

     ~Smiley()
     {
          delete mouth;
          for (auto p : eyes) delete p;
     }
     void move(Point to);

     void draw() const;
     void rotate(int);

     void add_eye(Shape* s) { eyes.push_back(s); }
     void set_mouth(Shape* s);
     virtual void wink(int i);    // wink eye number i

     // ...

private:
     vector<Shape*> eyes;         // usually two eyes
     Shape* mouth;
};

The push_back() member function adds its argument to the vector (here, eyes), increasing that vector’s size by one.

We can now define Smiley::draw() using calls to Smiley’s base and member draw()s:

void Smiley::draw()
{
     Circle::draw();
     for (auto p : eyes)
           p–>draw();
     mouth–>draw();
}

Note the way that Smiley keeps its eyes in a standard-library vector and deletes them in its destructor. Shape’s destructor is virtual and Smiley’s destructor overrides it. A virtual destructor is essential for an abstract class because an object of a derived class is usually manipulated through the interface provided by its abstract base class. In particular, it may be deleted through a pointer to a base class. Then, the virtual function call mechanism ensures that the proper destructor is called. That destructor then implicitly invokes the destructors of its bases and members.

In this simplified example, it is the programmer’s task to place the eyes and mouth appropriately within the circle representing the face.

We can add data members, operations, or both as we define a new class by derivation. This gives great flexibility with corresponding opportunities for confusion and poor design. See Chapter 21. A class hierarchy offers two kinds of benefits:

• Interface inheritance: An object of a derived class can be used wherever an object of a base class is required. That is, the base class acts as an interface for the derived class. The Container and Shape classes are examples. Such classes are often abstract classes.

• Implementation inheritance: A base class provides functions or data that simplifies the implementation of derived classes. Smiley’s uses of Circle’s constructor and of Circle::draw() are examples. Such base classes often have data members and constructors.

Concrete classes – especially classes with small representations – are much like built-in types: we define them as local variables, access them using their names, copy them around, etc. Classes in class hierarchies are different: we tend to allocate them on the free store using new, and we access them through pointers or references. For example, consider a function that reads data describing shapes from an input stream and constructs the appropriate Shape objects:

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enum class Kind { circle, triangle, smiley };

Shape* read_shape(istream& is)       // read shape descriptions from input stream is
{
    // ... read shape header from is and find its Kind k ...

    switch (k) {
    case Kind::circle:
         // read circle data {Point,int} into p and r
         return new Circle{p,r};
    case Kind::triangle:
         // read triangle data {Point,Point,Point} into p1, p2, and p3
         return new Triangle{p1,p2,p3};
    case Kind::smiley:
         // read smiley data {Point,int,Shape,Shape,Shape} into p, r, e1 ,e2, and m
         Smiley* ps = new Smiley{p,r};
         ps–>add_eye(e1);
         ps–>add_eye(e2);
         ps–>set_mouth(m);
         return ps;
    }
}

A program may use that shape reader like this:

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void user()
{
     std::vector<Shape*>v;
     while (cin)
          v.push_back(read_shape(cin));
     draw_all(v);                // call draw() for each element
     rotate_all(v,45);           // call rotate(45) for each element
     for (auto p : v) delete p;  // remember to delete elements
}

Obviously, the example is simplified – especially with respect to error handling – but it vividly illustrates that user() has absolutely no idea of which kinds of shapes it manipulates. The user() code can be compiled once and later used for new Shapes added to the program. Note that there are no pointers to the shapes outside user(), so user() is responsible for deallocating them. This is done with the delete operator and relies critically on Shape’s virtual destructor. Because that destructor is virtual, delete invokes the destructor for the most derived class. This is crucial because a derived class may have acquired all kinds of resources (such as file handles, locks, and output streams) that need to be released. In this case, a Smiley deletes its eyes and mouth objects.

Experienced programmers will notice that I left open two obvious opportunities for mistakes:

• A user might fail to delete the pointer returned by read_shape().

• The owner of a container of Shape pointers might not delete the objects pointed to.

In that sense, functions returning a pointer to an object allocated on the free store are dangerous. One solution to both problems is to return a standard-library unique_ptr (§5.2.1) rather than a “naked pointer” and store unique_ptrs in the container:

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unique_ptr<Shape> read_shape(istream& is) // read shape descriptions from input stream is
{
     // read shape header from is and find its Kind k

     switch (k) {
     case Kind::circle:
          // read circle data {Point,int} into p and r
          return unique_ptr<Shape>{new Circle{p,r}};      // §5.2.1
     // ...
}

void user()
{
     vector<unique_ptr<Shape>> v;
     while (cin)
           v.push_back(read_shape(cin));
     draw_all(v);            // call draw() for each element
     rotate_all(v,45);               // call rotate(45) for each element
} // all Shapes implicitly destroyed

Now the object is owned by the unique_ptr which will delete the object when it is no longer needed, that is, when its unique_ptr goes out of scope.

For the unique_ptr version of user() to work, we need versions of draw_all() and rotate_all() that accept vector<unique_ptr<Shape>>s. Writing many such _all() functions could become tedious, so §3.4.3 shows an alternative.

3.3. Copy and Move

By default, objects can be copied. This is true for objects of user-defined types as well as for builtin types. The default meaning of copy is memberwise copy: copy each member. For example, using complex from §3.2.1.1:

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void test(complex z1)
{
     complex z2 {z1};   // copy initialization
     complex z3;
     z3 = z2;           // copy assignment
     // ...
}

Now z1, z2, and z3 have the same value because both the assignment and the initialization copied both members.

When we design a class, we must always consider if and how an object might be copied. For simple concrete types, memberwise copy is often exactly the right semantics for copy. For some sophisticated concrete types, such as Vector, memberwise copy is not the right semantics for copy, and for abstract types it almost never is.

3.3.1. Copying Containers

When a class is a resource handle, that is, it is responsible for an object accessed through a pointer, the default memberwise copy is typically a disaster. Memberwise copy would violate the resource handle’s invariant (§2.4.3.2). For example, the default copy would leave a copy of a Vector referring to the same elements as the original:

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void bad_copy(Vector v1)
{
     Vector v2 = v1;    // copy v1's representation into v2
     v1[0] = 2;         // v2[0] is now also 2!
     v2[1] = 3;         // v1[1] is now also 3!
}

Assuming that v1 has four elements, the result can be represented graphically like this:

Fortunately, the fact that Vector has a destructor is a strong hint that the default (memberwise) copy semantics is wrong and the compiler should at least warn against this example (§17.6). We need to define better copy semantics.

Copying of an object of a class is defined by two members: a copy constructor and a copy assignment:

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class Vector {
private:
     double* elem; // elem points to an array of sz doubles
     int sz;
public:
     Vector(int s);                       // constructor: establish invariant, acquire resources
     ~Vector() { delete[] elem; }         // destructor: release resources

     Vector(const Vector& a);             // copy constructor
     Vector& operator=(const Vector& a);  // copy assignment

     double& operator[](int i);
     const double& operator[](int i) const;

     int size() const;
};

A suitable definition of a copy constructor for Vector allocates the space for the required number of elements and then copies the elements into it, so that after a copy each Vector has its own copy of the elements:

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Vector::Vector(const Vector& a)      // copy constructor
    :elem{new double[sz]},           // allocate space for elements
    sz{a.sz}
{
    for (int i=0; i!=sz; ++i)        // copy elements
          elem[i] = a.elem[i];
}

The result of the v2=v1 example can now be presented as:

Of course, we need a copy assignment in addition to the copy constructor:

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Vector& Vector::operator=(const Vector& a)   // copy assignment
{
    double* p = new double[a.sz];
    for (int i=0; i!=a.sz; ++i)
          p[i] = a.elem[i];
    delete[] elem;         // delete old elements
    elem = p;
    sz = a.sz;
    return *this;
}

The name this is predefined in a member function and points to the object for which the member function is called.

A copy constructor and a copy assignment for a class X are typically declared to take an argument of type const X&.

3.3.2. Moving Containers

We can control copying by defining a copy constructor and a copy assignment, but copying can be costly for large containers. Consider:

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Vector operator+(const Vector& a, const Vector& b)
{
    if (a.size()!=b.size())
          throw Vector_size_mismatch{};

    Vector res(a.size());
    for (int i=0; i!=a.size(); ++i)
          res[i]=a[i]+b[i];
    return res;
}

Returning from a + involves copying the result out of the local variable res and into some place where the caller can access it. We might use this + like this:

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void f(const Vector& x, const Vector& y, const Vector& z)
{
     Vector r;
     // ...
     r = x+y+z;
     // ...
}

That would be copying a Vector at least twice (one for each use of the + operator). If a Vector is large, say, 10,000 doubles, that could be embarrassing. The most embarrassing part is that res in operator+() is never used again after the copy. We didn’t really want a copy; we just wanted to get the result out of a function: we wanted to move a Vector rather than to copy it. Fortunately, we can state that intent:

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class Vector {
     // ...

     Vector(const Vector& a);          // copy constructor
     Vector& operator=(const Vector& a);     // copy assignment

     Vector(Vector&& a);               // move constructor
     Vector& operator=(Vector&& a);          // move assignment
};

Given that definition, the compiler will choose the move constructor to implement the transfer of the return value out of the function. This means that r=x+y+z will involve no copying of Vectors. Instead, Vectors are just moved.

As is typical, Vector’s move constructor is trivial to define:

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Vector::Vector(Vector&& a)
    :elem{a.elem},      // "grab the elements" from a
    sz{a.sz}
{
    a.elem = nullptr;         // now a has no elements
    a.sz = 0;
}

The && means “rvalue reference” and is a reference to which we can bind an rvalue (§6.4.1). The word “rvalue” is intended to complement “lvalue,” which roughly means “something that can appear on the left-hand side of an assignment.” So an rvalue is – to a first approximation – a value that you can’t assign to, such as an integer returned by a function call, and an rvalue reference is a reference to something that nobody else can assign to. The res local variable in operator+() for Vectors is an example.

A move constructor does not take a const argument: after all, a move constructor is supposed to remove the value from its argument. A move assignment is defined similarly.

A move operation is applied when an rvalue reference is used as an initializer or as the right-hand side of an assignment.

After a move, a moved-from object should be in a state that allows a destructor to be run. Typically, we should also allow assignment to a moved-from object (§17.5, §17.6.2).

Where the programmer knows that a value will not be used again, but the compiler can’t be expected to be smart enough to figure that out, the programmer can be specific:

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Vector f()
{
    Vector x(1000);
    Vector y(1000);
    Vector z(1000);
    // ...
    z = x;             // we get a copy
    y = std::move(x);  // we get a move
    // ...
    return z;          // we get a move
};

The standard-library function move() returns an rvalue reference to its argument.

Just before the return we have:

When z is destroyed, it too has been moved from (by the return) so that, like x, it is empty (it holds no elements).

3.3.3. Resource Management

By defining constructors, copy operations, move operations, and a destructor, a programmer can provide complete control of the lifetime of a contained resource (such as the elements of a container). Furthermore, a move constructor allows an object to move simply and cheaply from one scope to another. That way, objects that we cannot or would not want to copy out of a scope can be simply and cheaply moved out instead. Consider a standard-library thread representing a concurrent activity (§5.3.1) and a Vector of a million doubles. We can’t copy the former and don’t want to copy the latter.

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std::vector<thread> my_threads;

Vector init(int n)
{
    thread t {heartbeat};               // run heartbeat concurrently (on its own thread)
    my_threads.push_back(move(t));      // move t into my_threads
    // ... more initialization ...
    Vector vec(n);
    for (int i=0; i<vec.size(); ++i) vec[i] = 777;
    return vec;                         // move res out of init()
}

auto v = init(); // start heartbeat and initialize v

This makes resource handles, such as Vector and thread, an alternative to using pointers in many cases. In fact, the standard-library “smart pointers,” such as unique_ptr, are themselves resource handles (§5.2.1).

I used the standard-library vector to hold the threads because we don’t get to parameterize Vector with an element type until §3.4.1.

In very much the same way as new and delete disappear from application code, we can make pointers disappear into resource handles. In both cases, the result is simpler and more maintainable code, without added overhead. In particular, we can achieve strong resource safety; that is, we can eliminate resource leaks for a general notion of a resource. Examples are vectors holding memory, threads holding system threads, and fstreams holding file handles.

3.3.4. Suppressing Operations

Using the default copy or move for a class in a hierarchy is typically a disaster: given only a pointer to a base, we simply don’t know what members the derived class has (§3.2.2), so we can’t know how to copy them. So, the best thing to do is usually to delete the default copy and move operations, that is, to eliminate the default definitions of those two operations:

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class Shape {
public:
     Shape(const Shape&) =delete;             // no copy operations
     Shape& operator=(const Shape&) =delete;

     Shape(Shape&&) =delete;                  // no move operations
     Shape& operator=(Shape&&) =delete;

     ~Shape();
     // ...
};

Now an attempt to copy a Shape will be caught by the compiler. If you need to copy an object in a class hierarchy, write some kind of clone function (§22.2.4).

In this particular case, if you forgot to delete a copy or move operation, no harm is done. A move operation is not implicitly generated for a class where the user has explicitly declared a destructor. Furthermore, the generation of copy operations is deprecated in this case (§44.2.3). This can be a good reason to explicitly define a destructor even where the compiler would have implicitly provided one (§17.2.3).

A base class in a class hierarchy is just one example of an object we wouldn’t want to copy. A resource handle generally cannot be copied just by copying its members (§5.2, §17.2.2).

The =delete mechanism is general, that is, it can be used to suppress any operation (§17.6.4).

3.4. Templates

Someone who wants a vector is unlikely always to want a vector of doubles. A vector is a general concept, independent of the notion of a floating-point number. Consequently, the element type of a vector ought to be represented independently. A template is a class or a function that we parameterize with a set of types or values. We use templates to represent concepts that are best understood as something very general from which we can generate specific types and functions by specifying arguments, such as the element type double.

3.4.1. Parameterized Types

We can generalize our vector-of-doubles type to a vector-of-anything type by making it a template and replacing the specific type double with a parameter. For example:

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template<typename T>
class Vector {
private:
     T* elem; // elem points to an array of sz elements of type T
     int sz;
public:
     Vector(int s);                  // constructor: establish invariant, acquire resources
     ~Vector() { delete[] elem; }    // destructor: release resources

     // ... copy and move operations ...

     T& operator[](int i);
     const T& operator[](int i) const;
     int size() const { return sz; }
};

The template<typename T> prefix makes T a parameter of the declaration it prefixes. It is C++’s version of the mathematical “for all T” or more precisely “for all types T.”

The member functions might be defined similarly:

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template<typename T>
Vector<T>::Vector(int s)
{
    if (s<0) throw Negative_size{};
    elem = new T[s];
    sz = s;
}

template<typename T>
const T& Vector<T>::operator[](int i) const
{
    if (i<0 || size()<=i)
          throw out_of_range{"Vector::operator[]"};
    return elem[i];
}

Given these definitions, we can define Vectors like this:

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Vector<char> vc(200);      // vector of 200 characters
Vector<string> vs(17);     // vector of 17 strings
Vector<list<int>> vli(45); // vector of 45 lists of integers

The >> in Vector<list<int>> terminates the nested template arguments; it is not a misplaced input operator. It is not (as in C++98) necessary to place a space between the two >s.

We can use Vectors like this:

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void write(const Vector<string>& vs)      // Vector of some strings
{
     for (int i = 0; i!=vs.size(); ++i)
            cout << vs[i] << '\n';
}

To support the range-for loop for our Vector, we must define suitable begin() and end() functions:

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template<typename T>
T* begin(Vector<T>& x)
{
    return &x[0];          // pointer to first element
}

template<typename T>
T* end(Vector<T>& x)
{
    return x.begin()+x.size(); // pointer to one-past-last element
}

Given those, we can write:

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void f2(const Vector<string>& vs) // Vector of some strings
{
     for (auto& s : vs)
           cout << s << '\n';
}

Similarly, we can define lists, vectors, maps (that is, associative arrays), etc., as templates (§4.4, §23.2, Chapter 31).

Templates are a compile-time mechanism, so their use incurs no run-time overhead compared to “handwritten code” (§23.2.2).

3.4.2. Function Templates

Templates have many more uses than simply parameterizing a container with an element type. In particular, they are extensively used for parameterization of both types and algorithms in the standard library (§4.4.5, §4.5.5). For example, we can write a function that calculates the sum of the element values of any container like this:

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template<typename Container, typename Value>
Value sum(const Container& c, Value v)
{
    for (auto x : c)
          v+=x;
    return v;
}

The Value template argument and the function argument v are there to allow the caller to specify the type and initial value of the accumulator (the variable in which to accumulate the sum):

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void user(Vector<int>& vi, std::list<double>& ld, std::vector<complex<double>>& vc)
{
     int x = sum(vi,0);                  // the sum of a vector of ints (add ints)
     double d = sum(vi,0.0);             // the sum of a vector of ints (add doubles)
     double dd = sum(ld,0.0);            // the sum of a list of doubles
     auto z = sum(vc,complex<double>{}); // the sum of a vector of complex<double>
                                         // the initial value is {0.0,0.0}
}

The point of adding ints in a double would be to gracefully handle a number larger than the largest int. Note how the types of the template arguments for sum<T,V> are deduced from the function arguments. Fortunately, we do not need to explicitly specify those types.

This sum() is a simplified version of the standard-library accumulate() (§40.6).

3.4.3. Function Objects

One particularly useful kind of template is the function object (sometimes called a functor), which is used to define objects that can be called like functions. For example:

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template<typename T>
class Less_than {
     const T val;     // value to compare against
public:
     Less_than(const T& v) :val(v) { }
     bool operator()(const T& x) const { return x<val; } // call operator
};

The function called operator() implements the “function call,” “call,” or “application” operator ().

We can define named variables of type Less_than for some argument type:

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Less_than<int> lti {42};          // lti(i) will compare i to 42 using < (i<42)
Less_than<string> lts {"Backus"}; // lts(s) will compare s to "Backus" using < (s<"Backus")

We can call such an object, just as we call a function:

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void fct(int n, const string & s)
{
     bool b1 = lti(n);    // true if n<42
     bool b2 = lts(s);    // true if s<"Backus"
     // ...
}

Such function objects are widely used as arguments to algorithms. For example, we can count the occurrences of values for which a predicate returns true:

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template<typename C, typename P>
int count(const C& c, P pred)
{
     int cnt = 0;
     for (const auto& x : c)
           if (pred(x))
                 ++cnt;
     return cnt;
}

A predicate is something that we can invoke to return true or false. For example:

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void f(const Vector<int>& vec, const list<string>& lst, int x, const string& s)
{
     cout << "number of values less than " << x
          << ": " << count(vec,Less_than<int>{x})
          << '\n';
     cout << "number of values less than " << s
          << ": " << count(lst,Less_than<string>{s})
          << '\n';
}

Here, Less_than<int>{x} constructs an object for which the call operator compares to the int called x; Less_than<string>{s} constructs an object that compares to the string called s. The beauty of these function objects is that they carry the value to be compared against with them. We don’t have to write a separate function for each value (and each type), and we don’t have to introduce nasty global variables to hold values. Also, for a simple function object like Less_than inlining is simple, so that a call of Less_than is far more efficient than an indirect function call. The ability to carry data plus their efficiency make function objects particularly useful as arguments to algorithms.

Function objects used to specify the meaning of key operations of a general algorithm (such as Less_than for count()) are often referred to as policy objects.

We have to define Less_than separately from its use. That could be seen as inconvenient. Consequently, there is a notation for implicitly generating function objects:

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void f(const Vector<int>& vec, const list<string>& lst, int x, const string& s)
{
     cout << "number of values less than " << x
          << ": " << count(vec,[&](int a){ return a<x; })
          << '\n';
     cout << "number of values less than " << s
          << ": " << count(lst,[&](const string& a){ return a<s; })
          << '\n';
}

The notation [&](int a){ return a<x; } is called a lambda expression (§11.4). It generates a function object exactly like Less_than<int>{x}. The [&] is a capture list specifying that local names used (such as x) will be passed by reference. Had we wanted to “capture” only x, we could have said so: [&x]. Had we wanted to give the generated object a copy of x, we could have said so: [=x]. Capture nothing is [], capture all local names used by reference is [&], and capture all local names used by value is [=].

Using lambdas can be convenient and terse, but also obscure. For nontrivial actions (say, more than a simple expression), I prefer to name the operation so as to more clearly state its purpose and to make it available for use in several places in a program.

In §3.2.4, we noticed the annoyance of having to write many functions to perform operations on elements of vectors of pointers and unique_ptrs, such as draw_all() and rotate_all(). Function objects (in particular, lambdas) can help by allowing us to separate the traversal of the container from the specification of what is to be done with each element.

First, we need a function that applies an operation to each object pointed to by the elements of a container of pointers:

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template<class C, class Oper>
void for_all(C& c, Oper op)       // assume that C is a container of pointers
{
     for (auto& x : c)
           op(*x);     // pass op() a reference to each element pointed to
}

Now, we can write a version of user() from §3.2.4 without writing a set of _all functions:

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void user()
{
     vector<unique_ptr<Shape>> v;
     while (cin)
           v.push_back(read_shape(cin));
     for_all(v,[](Shape& s){ s.draw(); });      // draw_all()
     for_all(v,[](Shape& s){ s.rotate(45); });  // rotate_all(45)
}

I pass a reference to Shape to a lambda so that the lambda doesn’t have to care exactly how the objects are stored in the container. In particular, those for_all() calls would still work if I changed v to a vector<Shape*>.

3.4.4. Variadic Templates

A template can be defined to accept an arbitrary number of arguments of arbitrary types. Such a template is called a variadic template. For example:

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template<typename T, typename... Tail>
void f(T head, Tail... tail)
{
     g(head);    // do something to head
     f(tail...); // try again with tail
}

void f() { }     // do nothing

The key to implementing a variadic template is to note that when you pass a list of arguments to it, you can separate the first argument from the rest. Here, we do something to the first argument (the head) and then recursively call f() with the rest of the arguments (the tail). The ellipsis, ..., is used to indicate “the rest” of a list. Eventually, of course, tail will become empty and we need a separate function to deal with that.

We can call this f() like this:

int main()
{
     cout << "first: ";
     f(1,2.2,"hello");

     cout << "\nsecond: "
     f(0.2,'c',"yuck!",0,1,2);
     cout << "\n";
}

This would call f(1,2.2,"hello"), which will call f(2.2,"hello"), which will call f("hello"), which will call f(). What might the call g(head) do? Obviously, in a real program it will do whatever we wanted done to each argument. For example, we could make it write its argument (here, head) to output:

template<typename T>
void g(T x)
{
     cout << x << " ";
}

Given that, the output will be:

first: 1 2.2 hello
second: 0.2 c yuck! 0 1 2

It seems that f() is a simple variant of printf() printing arbitrary lists or values – implemented in three lines of code plus their surrounding declarations.

The strength of variadic templates (sometimes just called variadics) is that they can accept any arguments you care to give them. The weakness is that the type checking of the interface is a possibly elaborate template program. For details, see §28.6. For examples, see §34.2.4.2 (N-tuples) and Chapter 29 (N-dimensional matrices).

3.4.5. Aliases

Surprisingly often, it is useful to introduce a synonym for a type or a template (§6.5). For example, the standard header <cstddef> contains a definition of the alias size_t, maybe:

using size_t = unsigned int;

The actual type named size_t is implementation-dependent, so in another implementation size_t may be an unsigned long. Having the alias size_t allows the programmer to write portable code.

It is very common for a parameterized type to provide an alias for types related to their template arguments. For example:

template<typename T>
class Vector {
public:
     using value_type = T;
    // ...
};

In fact, every standard-library container provides value_type as the name of its value type (§31.3.1). This allows us to write code that will work for every container that follows this convention. For example:

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template<typename C>
using Element_type = typename C::value_type;

template<typename Container>
void algo(Container& c)
{
     Vector<Element_type<Container>> vec; // keep results here
     // ...
}

The aliasing mechanism can be used to define a new template by binding some or all template arguments. For example:

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template<typename Key, typename Value>
class Map {
     // ...
};

template<typename Value>
using String_map = Map<string,Value>;

String_map<int> m; // m is a Map<string,int>

See §23.6.

3.5. Advice

[1] Express ideas directly in code; §3.2.

[2] Define classes to represent application concepts directly in code; §3.2.

[3] Use concrete classes to represent simple concepts and performance-critical components; §3.2.1.

[4] Avoid “naked” new and delete operations; §3.2.1.2.

[5] Use resource handles and RAII to manage resources; §3.2.1.2.

[6] Use abstract classes as interfaces when complete separation of interface and implementation is needed; §3.2.2.

[7] Use class hierarchies to represent concepts with inherent hierarchical structure; §3.2.4.

[8] When designing a class hierarchy, distinguish between implementation inheritance and interface inheritance; §3.2.4.

[9] Control construction, copy, move, and destruction of objects; §3.3.

[10] Return containers by value (relying on move for efficiency); §3.3.2.

[11] Provide strong resource safety; that is, never leak anything that you think of as a resource; §3.3.3.

[12] Use containers, defined as resource handle templates, to hold collections of values of the same type; §3.4.1.

[13] Use function templates to represent general algorithms; §3.4.2.

[14] Use function objects, including lambdas, to represent policies and actions; §3.4.3.

[15] Use type and template aliases to provide a uniform notation for types that may vary among similar types or among implementations; §3.4.5.

4. A Tour of C++: Containers and Algorithms

Why waste time learning when ignorance is instantaneous?

– Hobbes

• Libraries

Standard-Library Overview; The Standard-Library Headers and Namespace

• Strings

• Stream I/O

Output; Input; I/O of User-Defined Types

• Containers

vector; list; map; unordered_map; Container Overview

• Algorithms

Use of Iterators; Iterator Types; Stream Iterators; Predicates; Algorithm Overview; Container Algorithms

• Advice

4.1. Libraries

No significant program is written in just a bare programming language. First, a set of libraries is developed. These then form the basis for further work. Most programs are tedious to write in the bare language, whereas just about any task can be rendered simple by the use of good libraries.

Continuing from Chapters 2 and 3, this chapter and the next give a quick tour of key standard-library facilities. I assume that you have programmed before. If not, please consider reading a textbook, such as Programming: Principles and Practice Using C++ [Stroustrup,2009], before continuing. Even if you have programmed before, the libraries you used or the applications you wrote may be very different from the style of C++ presented here. If you find this “lightning tour” confusing, you might skip to the more systematic and bottom-up language presentation starting in Chapter 6. Similarly, a more systematic description of the standard library starts in Chapter 30.

I very briefly present useful standard-library types, such as string, ostream, vector, map (this chapter), unique_ptr, thread, regex, and complex (Chapter 5), as well as the most common ways of using them. Doing this allows me to give better examples in the following chapters. As in Chapter 2 and Chapter 3, you are strongly encouraged not to be distracted or discouraged by an incomplete understanding of details. The purpose of this chapter is to give you a taste of what is to come and to convey a basic understanding of the most useful library facilities.

The specification of the standard library is almost two thirds of the ISO C++ standard. Explore it, and prefer it to home-made alternatives. Much though have gone into its design, more still into its implementations, and much effort will go into its maintenance and extension.

The standard-library facilities described in this book are part of every complete C++ implementation. In addition to the standard-library components, most implementations offer “graphical user interface” systems (GUIs), Web interfaces, database interfaces, etc. Similarly, most application development environments provide “foundation libraries” for corporate or industrial “standard” development and/or execution environments. Here, I do not describe such systems and libraries. The intent is to provide a self-contained description of C++ as defined by the standard and to keep the examples portable, except where specifically noted. Naturally, a programmer is encouraged to explore the more extensive facilities available on most systems.

4.1.1. Standard-Library Overview

The facilities provided by the standard library can be classified like this:

• Run-time language support (e.g., for allocation and run-time type information); see §30.3.

• The C standard library (with very minor modifications to minimize violations of the type system); see Chapter 43.

• Strings and I/O streams (with support for international character sets and localization); see Chapter 36, Chapter 38, and Chapter 39. I/O streams is an extensible framework to which users can add their own streams, buffering strategies, and character sets.

• A framework of containers (such as vector and map) and algorithms (such as find(), sort(), and merge()); see §4.4, §4.5, Chapters 31-33. This framework, conventionally called the STL [Stepanov,1994], is extensible so users can add their own containers and algorithms.

• Support for numerical computation (such as standard mathematical functions, complex numbers, vectors with arithmetic operations, and random number generators); see §3.2.1.1 and Chapter 40.

• Support for regular expression matching; see §5.5 and Chapter 37.

• Support for concurrent programming, including threads and locks; see §5.3 and Chapter 41. The concurrency support is foundational so that users can add support for new models of concurrency as libraries.

• Utilities to support template metaprogramming (e.g., type traits; §5.4.2, §28.2.4, §35.4), STL-style generic programming (e.g., pair; §5.4.3, §34.2.4.1), and general programming (e.g., clock; §5.4.1, §35.2).

• “Smart pointers” for resource management (e.g., unique_ptr and shared_ptr; §5.2.1, §34.3) and an interface to garbage collectors (§34.5).

• Special-purpose containers, such as array (§34.2.1), bitset (§34.2.2), and tuple (§34.2.4.2).

The main criteria for including a class in the library were that:

• it could be helpful to almost every C++ programmer (both novices and experts),

• it could be provided in a general form that did not add significant overhead compared to a simpler version of the same facility, and

• that simple uses should be easy to learn (relative to the inherent complexity of their task).

Essentially, the C++ standard library provides the most common fundamental data structures together with the fundamental algorithms used on them.

4.1.2. The Standard-library Headers and Namespace

Every standard-library facility is provided through some standard header. For example:

#include<string>
#include<list>

This makes the standard string and list available.

The standard library is defined in a namespace (§2.4.2, §14.3.1) called std. To use standard library facilities, the std:: prefix can be used:

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std::string s {"Four legs Good; two legs Baaad!"};
std::list<std::string> slogans {"War is peace", "Freedom is Slavery", "Ignorance is Strength"};

For simplicity, I will rarely use the std:: prefix explicitly in examples. Neither will I always #include the necessary headers explicitly. To compile and run the program fragments here, you must #include the appropriate headers (as listed in §4.4.5, §4.5.5, and §30.2) and make the names they declare accessible. For example:

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#include<string>          // make the standard string facilities accessible
using namespace std;      // make std names available without std:: prefix

string s {"C++ is a general–purpose programming language"};  // OK: string is std::string

It is generally in poor taste to dump every name from a namespace into the global namespace. However, in this book, I use the standard library almost exclusively and it is good to know what it offers. So, I don’t prefix every use of a standard library name with std::. Nor do I #include the appropriate headers in every example. Assume that done.

Here is a selection of standard-library headers, all supplying declarations in namespace std:

This listing is far from complete; see §30.2 for more information.

4.2. Strings

The standard library provides a string type to complement the string literals. The string type provides a variety of useful string operations, such as concatenation. For example:

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string compose(const string& name, const string& domain)
{
     return name + '@' + domain;
}

auto addr = compose("dmr","bell–labs.com");

Here, addr is initialized to the character sequence dmr@bell–labs.com. “Addition” of strings means concatenation. You can concatenate a string, a string literal, a C-style string, or a character to a string. The standard string has a move constructor so returning even long strings by value is efficient (§3.3.2).

In many applications, the most common form of concatenation is adding something to the end of a string. This is directly supported by the += operation. For example:

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void m2(string& s1, string& s2)
{
     s1 = s1 + '\n';   // append newline
     s2 += '\n';       // append newline
}

The two ways of adding to the end of a string are semantically equivalent, but I prefer the latter because it is more explicit about what it does, more concise, and possibly more efficient.

A string is mutable. In addition to = and +=, subscripting (using []) and substring operations are supported. The standard-library string is described in Chapter 36. Among other useful features, it provides the ability to manipulate substrings. For example:

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string name = "Niels Stroustrup";

void m3()
{
     string s = name.substr(6,10);    // s = "Stroustrup"
     name.replace(0,5,"nicholas");    // name becomes "nicholas Stroustrup"
     name[0] = toupper(name[0]);      // name becomes "Nicholas Stroustrup"
}

The substr() operation returns a string that is a copy of the substring indicated by its arguments. The first argument is an index into the string (a position), and the second is the length of the desired substring. Since indexing starts from 0, s gets the value Stroustrup.

The replace() operation replaces a substring with a value. In this case, the substring starting at 0 with length 5 is Niels; it is replaced by nicholas. Finally, I replace the initial character with its uppercase equivalent. Thus, the final value of name is Nicholas Stroustrup. Note that the replacement string need not be the same size as the substring that it is replacing.

Naturally, strings can be compared against each other and against string literals. For example:

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string incantation;

void respond(const string& answer)
{
     if (answer == incantation) {
           // perform magic
     }
     else if (answer == "yes") {
           // ...
     }
     // ...
}

The string library is described in Chapter 36. The most common techniques for implementing string are presented in the String example (§19.3).

4.3. Stream I/O

The standard library provides formatted character input and output through the iostream library. The input operations are typed and extensible to handle user-defined types. This section is a very brief introduction to the use of iostreams; Chapter 38 is a reasonably complete description of the iostream library facilities.

Other forms of user interaction, such as graphical I/O, are handled through libraries that are not part of the ISO standard and therefore not described here.

4.3.1. Output

The I/O stream library defines output for every built-in type. Further, it is easy to define output of a user-defined type (§4.3.3). The operator << (“put to”) is used as an output operator on objects of type ostream; cout is the standard output stream and cerr is the standard stream for reporting errors. By default, values written to cout are converted to a sequence of characters. For example, to output the decimal number 10, we can write:

void f()
{
     cout << 10;
}

This places the character 1 followed by the character 0 on the standard output stream.

Equivalently, we could write:

void g()
{
     int i {10};
     cout << i;
}

Output of different types can be combined in the obvious way:

void h(int i)
{
     cout << "the value of i is ";
     cout << i;
     cout << '\n';
}

For h(10), the output will be:

the value of i is 10

People soon tire of repeating the name of the output stream when outputting several related items. Fortunately, the result of an output expression can itself be used for further output. For example:

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void h2(int i)
{
     cout << "the value of i is " << i << '\n';
}

This h2() produces the same output as h().

A character constant is a character enclosed in single quotes. Note that a character is output as a character rather than as a numerical value. For example:

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void k()
{
     int b = 'b';   // note: char implicitly converted to int
     char c = 'c';
     cout << 'a' << b << c;
}

The integer value of the character 'b' is 98 (in the ASCII encoding used on the C++ implementation that I used), so this will output a98c.

4.3.2. Input

The standard library offers istreams for input. Like ostreams, istreams deal with character string representations of built-in types and can easily be extended to cope with user-defined types.

The operator >> (“get from”) is used as an input operator; cin is the standard input stream. The type of the right-hand operand of >> determines what input is accepted and what is the target of the input operation. For example:

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void f()
{
     int i;
     cin >> i;      // read an integer into i

     double d;
     cin >> d;      // read a double-precision floating-point number into d
}

This reads a number, such as 1234, from the standard input into the integer variable i and a floating-point number, such as 12.34e5, into the double-precision floating-point variable d.

Often, we want to read a sequence of characters. A convenient way of doing that is to read into a string. For example:

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void hello()
{
     cout << "Please enter your name\n";
     string str;
     cin >> str;
     cout << "Hello, " << str << "!\n";
}

If you type in Eric the response is:

Hello, Eric!

By default, a whitespace character (§7.3.2), such as a space, terminates the read, so if you enter Eric Bloodaxe pretending to be the ill-fated king of York, the response is still:

Hello, Eric!

You can read a whole line (including the terminating newline character) using the getline() function. For example:

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void hello_line()
{
     cout << "Please enter your name\n";
     string str;
     getline(cin,str);
     cout << "Hello, " << str << "!\n";
}

With this program, the input Eric Bloodaxe yields the desired output:

Hello, Eric Bloodaxe!

The newline that terminated the line is discarded, so cin is ready for the next input line.

The standard strings have the nice property of expanding to hold what you put in them; you don’t have to precalculate a maximum size. So, if you enter a couple of megabytes of semicolons, the program will echo pages of semicolons back at you.

4.3.3. I/O of User-Defined Types

In addition to the I/O of built-in types and standard strings, the iostream library allows programmers to define I/O for their own types. For example, consider a simple type Entry that we might use to represent entries in a telephone book:

struct Entry {
     string name;
     int number;
};

We can define a simple output operator to write an Entry using a {”name”,number} format similar to the one we use for initialization in code:

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ostream& operator<<(ostream& os, const Entry& e)
{
     return os << "{\"" << e.name << "\", " << e.number << "}";
}

A user-defined output operator takes its output stream (by reference) as its first argument and returns it as its result. See §38.4.2 for details.

The corresponding input operator is more complicated because it has to check for correct formatting and deal with errors:

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istream& operator>>(istream& is, Entry& e)
     // read { "name" , number } pair. Note: formatted with { " " , and }
{
     char c, c2;
     if (is>>c && c=='{' && is>>c2 && c2=="") { // start with a { "
            string name;                   // the default value of a string is the empty string: ""
            while (is.get(c) && c!='"')    // anything before a " is part of the name
                  name+=c;

            if (is>>c && c==',') {
                  int number = 0;
                  if (is>>number>>c && c=='}') { // read the number and a }
                         e = {name,number};      // assign to the entry
                         return is;
                  }
             }
     }
     is.setf(ios_base::failbit);     // register the failure in the stream
     return is;
}

An input operation returns a reference to its istream which can be used to test if the operation succeeded. For example, when used as a condition, is>>c means “Did we succeed at reading from is into c?”

The is>>c skips whitespace by default, but is.get(c) does not, so that this Entry-input operator ignores (skips) whitespace outside the name string, but not within it. For example:

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{ "John Marwood Cleese" , 123456   }
{"Michael Edward Palin",987654}

We can read such a pair of values from input into an Entry like this:

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for (Entry ee; cin>>ee; )  // read from cin into ee
     cout << ee << '\n';   // write ee to cout

The output is:

{"John Marwood Cleese", 123456}
{"Michael Edward Palin", 987654}

See §38.4.1 for more technical details and techniques for writing input operators for user-defined types. See §5.5 and Chapter 37 for a more systematic technique for recognizing patterns in streams of characters (regular expression matching).

4.4. Containers

Most computing involves creating collections of values and then manipulating such collections. Reading characters into a string and printing out the string is a simple example. A class with the main purpose of holding objects is commonly called a container. Providing suitable containers for a given task and supporting them with useful fundamental operations are important steps in the construction of any program.

To illustrate the standard-library containers, consider a simple program for keeping names and telephone numbers. This is the kind of program for which different approaches appear “simple and obvious” to people of different backgrounds. The Entry class from §4.3.3 can be used to hold a simple phone book entry. Here, we deliberately ignore many real-world complexities, such as the fact that many phone numbers do not have a simple representation as a 32-bit int.

4.4.1. vector

The most useful standard-library container is vector. A vector is a sequence of elements of a given type. The elements are stored contiguously in memory:

The Vector examples in §3.2.2 and §3.4 give an idea of the implementation of vector and §13.6 and §31.4 provide an exhaustive discussion.

We can initialize a vector with a set of values of its element type:

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vector<Entry> phone_book = {
     {"David Hume",123456},
     {"Karl Popper",234567},
     {"Bertrand Arthur William Russell",345678}
};

Elements can be accessed through subscripting:

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void print_book(const vector<Entry>& book)
{
     for (int i = 0; i!=book.size(); ++i)
           cout << book[i] << '\n';
}

As usual, indexing starts at 0 so that book[0] holds the entry for David Hume. The vector member function size() gives the number of elements.

The elements of a vector constitute a range, so we can use a range-for loop (§2.2.5):

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void print_book(const vector<Entry>& book)
{
     for (const auto& x : book)   // for "auto" see §2.2.2
           cout << x << '\n';
}

When we define a vector, we give it an initial size (initial number of elements):

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vector<int> v1 = {1, 2, 3, 4};     // sizeis4
vector<string> v2;                 // sizeis0
vector<Shape*> v3(23);             // size is 23; initial element value: nullptr
vector<double> v4(32,9.9);         // size is 32; initial element value: 9.9

An explicit size is enclosed in ordinary parentheses, for example, (23), and by default the elements are initialized to the element type’s default value (e.g., nullptr for pointers and 0 for numbers). If you don’t want the default value, you can specify one as a second argument (e.g., 9.9 for the 32 elements of v4).

The initial size can be changed. One of the most useful operations on a vector is push_back(), which adds a new element at the end of a vector, increasing its size by one. For example:

void input()
{
     for (Entry e; cin>>e;)
           phone_book.push_back(e);
}

This reads Entrys from the standard input into phone_book until either the end-of-input (e.g., the end of a file) is reached or the input operation encounters a format error. The standard-library vector is implemented so that growing a vector by repeated push_back()s is efficient.

A vector can be copied in assignments and initializations. For example:

vector<Entry> book2 = phone_book;

Copying and moving of vectors are implemented by constructors and assignment operators as described in §3.3. Assigning a vector involves copying its elements. Thus, after the initialization of book2, book2 and phone_book hold separate copies of every Entry in the phone book. When a vector holds many elements, such innocent-looking assignments and initializations can be expensive. Where copying is undesirable, references or pointers (§7.2, §7.7) or move operations (§3.3.2, §17.5.2) should be used.

4.4.1.1. Elements

Like all standard-library containers, vector is a container of elements of some type T, that is, a vector<T>. Just about any type qualifies as an element type: built-in numeric types (such as char, int, and double), user-defined types (such as string, Entry, list<int>, and Matrix<double,2>), and pointers (such as const char*, Shape*, and double*). When you insert a new element, its value is copied into the container. For example, when you put an integer with the value 7 into a container, the resulting element really has the value 7. The element is not a reference or a pointer to some object containing 7. This makes for nice compact containers with fast access. For people who care about memory sizes and run-time performance this is critical.

4.4.1.2. Range Checking

The standard-library vector does not guarantee range checking (§31.2.2). For example:

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void silly(vector<Entry>& book)
{
     int i = book[ph.size()].number;    // book.size() is out of range
     // ...
}

That initialization is likely to place some random value in i rather than giving an error. This is undesirable, and out-of-range errors are a common problem. Consequently, I often use a simple range-checking adaptation of vector:

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template<typename T>
class Vec : public std::vector<T> {
public:
     using vector<T>::vector; // use the constructors from vector (under the name Vec); see §20.3.5.1

     T& operator[](int i)                // range check
         { return vector<T>::at(i); }

     const T& operator[](int i) const         // range check const objects; §3.2.1.1
         { return vector<T>::at(i); }
};

Vec inherits everything from vector except for the subscript operations that it redefines to do range checking. The at() operation is a vector subscript operation that throws an exception of type out_of_range if its argument is out of the vector’s range (§2.4.3.1, §31.2.2).

For Vec, an out-of-range access will throw an exception that the user can catch. For example:

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void checked(Vec<Entry>& book)
{
     try {
           book[book.size()] = {"Joe",999999};  // will throw an exception
           // ...
     }
     catch (out_of_range) {
           cout << "range error\n";
     }
}

The exception will be thrown, and then caught (§2.4.3.1, Chapter 13). If the user doesn’t catch an exception, the program will terminate in a well-defined manner rather than proceeding or failing in an undefined manner. One way to minimize surprises from uncaught exceptions is to use a main() with a try-block as its body. For example:

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int main()
try {
     // your code
}
catch (out_of_range) {
     cerr << "range error\n";
}
catch (...) {
     cerr << "unknown exception thrown\n";
}

This provides default exception handlers so that if we fail to catch some exception, an error message is printed on the standard error-diagnostic output stream cerr (§38.1).

Some implementations save you the bother of defining Vec (or equivalent) by providing a range-checked version of vector (e.g., as a compiler option).

4.4.2. list

The standard library offers a doubly-linked list called list:

We use a list for sequences where we want to insert and delete elements without moving other elements. Insertion and deletion of phone book entries could be common, so a list could be appropriate for representing a simple phone book. For example:

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list<Entry> phone_book = {
     {"David Hume",123456},
     {"Karl Popper",234567},
     {"Bertrand Arthur William Russell",345678}
};

When we use a linked list, we tend not to access elements using subscripting the way we commonly do for vectors. Instead, we might search the list looking for an element with a given value. To do this, we take advantage of the fact that a list is a sequence as described in §4.5:

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int get_number(const string& s)
{
     for (const auto& x : phone_book)
            if (x.name==s)
                  return x.number;
     return 0; // use 0 to represent "number not found"
}

The search for s starts at the beginning of the list and proceeds until s is found or the end of phone_book is reached.

Sometimes, we need to identify an element in a list. For example, we may want to delete it or insert a new entry before it. To do that we use an iterator: a list iterator identifies an element of a list and can be used to iterate through a list (hence its name). Every standard-library container provides the functions begin() and end(), which return an iterator to the first and to one-past-the-last element, respectively (§4.5, §33.1.1). Using iterators explicitly, we can – less elegantly – write the get_number() function like this:

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int get_number(const string& s)
{
     for (auto p = phone_book.begin(); p!=phone_book.end(); ++p)
           if (p–>name==s)
                 return p–>number;
     return 0; // use 0 to represent "number not found"
}

In fact, this is roughly the way the terser and less error-prone range-for loop is implemented by the compiler. Given an iterator p, *p is the element to which it refers, ++p advances p to refer to the next element, and when p refers to a class with a member m, then p–>m is equivalent to (*p).m.

Adding elements to a list and removing elements from a list is easy:

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void f(const Entry& ee, list<Entry>::iterator p, list<Entry>::iterator q)
{
     phone_book.insert(p,ee);       // add ee before the element referred to by p
     phone_book.erase(q);           // remove the element referred to by q
}

For a more complete description of insert() and erase(), see §31.3.7.

These list examples could be written identically using vector and (surprisingly, unless you understand machine architecture) perform better with a small vector than with a small list. When all we want is a sequence of elements, we have a choice between using a vector and a list. Unless you have a reason not to, use a vector. A vector performs better for traversal (e.g., find() and count()) and for sorting and searching (e.g., sort() and binary_search()).

4.4.3. map

Writing code to look up a name in a list of (name,number) pairs is quite tedious. In addition, a linear search is inefficient for all but the shortest lists. The standard library offers a search tree (a red-black tree) called map:

In other contexts, a map is known as an associative array or a dictionary. It is implemented as a balanced binary tree.

The standard-library map (§31.4.3) is a container of pairs of values optimized for lookup. We can use the same initializer as for vector and list (§4.4.1, §4.4.2):

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map<string,int> phone_book {
    {"David Hume",123456},
    {"Karl Popper",234567},
    {"Bertrand Arthur William Russell",345678}
};

When indexed by a value of its first type (called the key), a map returns the corresponding value of the second type (called the value or the mapped type). For example:

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int get_number(const string& s)
{
     return phone_book[s];
}

In other words, subscripting a map is essentially the lookup we called get_number(). If a key isn’t found, it is entered into the map with a default value for its value. The default value for an integer type is 0; the value I just happened to choose represents an invalid telephone number.

If we wanted to avoid entering invalid numbers into our phone book, we could use find() and insert() instead of [] (§31.4.3.1).

4.4.4. unordered_map

The cost of a map lookup is O(log(n)) where n is the number of elements in the map. That’s pretty good. For example, for a map with 1,000,000 elements, we perform only about 20 comparisons and indirections to find an element. However, in many cases, we can do better by using a hashed lookup rather than comparison using an ordering function, such as <. The standard-library hashed containers are referred to as “unordered” because they don’t require an ordering function:

For example, we can use an unordered_map from <unordered_map> for our phone book:

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unordered_map<string,int> phone_book {
    {"David Hume",123456},
    {"Karl Popper",234567},
    {"Bertrand Arthur William Russell",345678}
};

As for a map, we can subscript an unordered_map:

int get_number(const string& s)
{
     return phone_book[s];
}

The standard-library unordered_map provides a default hash function for strings. If necessary, you can provide your own (§31.4.3.4).

4.4.5. Container Overview

The standard library provides some of the most general and useful container types to allow the programmer to select a container that best serves the needs of an application:

The unordered containers are optimized for lookup with a key (often a string); in other words, they are implemented using hash tables.

The standard containers are described in §31.4. The containers are defined in namespace std and presented in headers <vector>, <list>, <map>, etc. (§4.1.2, §30.2). In addition, the standard library provides container adaptors queue<T> (§31.5.2), stack<T> (§31.5.1), deque<T> (§31.4), and priority_queue<T> (§31.5.3). The standard library also provides more specialized container-like types, such as a fixed-size array array<T,N> (§34.2.1) and bitset<N> (§34.2.2).

The standard containers and their basic operations are designed to be similar from a notational point of view. Furthermore, the meanings of the operations are equivalent for the various containers. Basic operations apply to every kind of container for which they make sense and can be efficiently implemented. For example:

• begin() and end() give iterators to the first and one-beyond-the-last elements, respectively.

• push_back() can be used (efficiently) to add elements to the end of a vector, forward_list, list, and other containers.

• size() returns the number of elements.

This notational and semantic uniformity enables programmers to provide new container types that can be used in a very similar manner to the standard ones. The range-checked vector, Vector (§2.3.2, §2.4.3.1), is an example of that. The uniformity of container interfaces also allows us to specify algorithms independently of individual container types. However, each has strengths and weaknesses. For example, subscripting and traversing a vector is cheap and easy. On the other hand, vector elements are moved when we insert or remove elements; list has exactly the opposite properties. Please note that a vector is usually more efficient than a list for short sequences of small elements (even for insert() and erase()). I recommend the standard-library vector as the default type for sequences of elements: you need a reason to choose another.

4.5. Algorithms

A data structure, such as a list or a vector, is not very useful on its own. To use one, we need operations for basic access such as adding and removing elements (as is provided for list and vector). Furthermore, we rarely just store objects in a container. We sort them, print them, extract subsets, remove elements, search for objects, etc. Consequently, the standard library provides the most common algorithms for containers in addition to providing the most common container types. For example, the following sorts a vector and places a copy of each unique vector element on a list:

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bool operator<(const Entry& x, const Entry& y)  // less than
{
     return x.name<y.name;        // order Entrys by their names
}
void f(vector<Entry>& vec, list<Entry>& lst)
{
     sort(vec.begin(),vec.end());                      // use < for order
     unique_copy(vec.begin(),vec.end(),lst.begin());   // don't copy adjacent equal elements
}

The standard algorithms are described in Chapter 32. They are expressed in terms of sequences of elements. A sequence is represented by a pair of iterators specifying the first element and the one-beyond-the-last element:

In the example, sort() sorts the sequence defined by the pair of iterators vec.begin() and vec.end() – which just happens to be all the elements of a vector. For writing (output), you need only to specify the first element to be written. If more than one element is written, the elements following that initial element will be overwritten. Thus, to avoid errors, lst must have at least as many elements as there are unique values in vec.

If we wanted to place the unique elements in a new container, we could have written:

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list<Entry> f(vector<Entry>& vec)
{
     list<Entry> res;
     sort(vec.begin(),vec.end());
     unique_copy(vec.begin(),vec.end(),back_inserter(res)); // append to res
     return res;
}

A back_inserter() adds elements at the end of a container, extending the container to make room for them (§33.2.2). Thus, the standard containers plus back_inserter()s eliminate the need to use error-prone, explicit C-style memory management using realloc() (§31.5.1). The standard-library list has a move constructor (§3.3.2, §17.5.2) that makes returning res by value efficient (even for lists of thousands of elements).

If you find the pair-of-iterators style of code, such as sort(vec.begin(),vec.end()), tedious, you can define container versions of the algorithms and write sort(vec) (§4.5.6).

4.5.1. Use of Iterators

When you first encounter a container, a few iterators referring to useful elements can be obtained; begin() and end() are the best examples of this. In addition, many algorithms return iterators. For example, the standard algorithm find looks for a value in a sequence and returns an iterator to the element found:

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bool has_c(const string& s, char c)    // does s contain the character c?
{
     auto p = find(s.begin(),s.end(),c);
     if (p!=s.end())
           return true;
     else
           return false;
}

Like many standard-library search algorithms, find returns end() to indicate “not found.” An equivalent, shorter, definition of has_c() is:

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bool has_c(const string& s, char c)     // does s contain the character c?
{
     return find(s.begin(),s.end(),c)!=s.end();
}

A more interesting exercise would be to find the location of all occurrences of a character in a string. We can return the set of occurrences as a vector of string iterators. Returning a vector is efficient because of vector provides move semantics (§3.3.1). Assuming that we would like to modify the locations found, we pass a non-const string:

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vector<string::iterator> find_all(string& s, char c)   // find all occurrences of c in s
{
     vector<string::iterator> res;
     for (auto p = s.begin(); p!=s.end(); ++p)
           if (*p==c)
                 res.push_back(p);
     return res;
}

We iterate through the string using a conventional loop, moving the iterator p forward one element at a time using ++ and looking at the elements using the dereference operator *. We could test find_all() like this:

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void test()
{
     string m {"Mary had a little lamb"};
     for (auto p : find_all(m,'a'))
           if (*p!='a')
                 cerr << "a bug!\n";
}

That call of find_all() could be graphically represented like this:

Iterators and standard algorithms work equivalently on every standard container for which their use makes sense. Consequently, we could generalize find_all():

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template<typename C, typename V>
vector<typename C::iterator> find_all(C& c, V v)     // find all occurrences of v in c
{
     vector<typename C::iterator> res;
     for (auto p = c.begin(); p!=c.end(); ++p)
           if (*p==v)
                 res.push_back(p);
     return res;
}

The typename is needed to inform the compiler that C’s iterator is supposed to be a type and not a value of some type, say, the integer 7. We can hide this implementation detail by introducing a type alias (§3.4.5) for Iterator:

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template<typename T>
using Iterator<T> = typename T::iterator;

template<typename C, typename V>
vector<Iterator<C>> find_all(C& c, V v)    // find all occurrences of v in c
{
     vector<Iterator<C>>res;
     for (auto p = c.begin(); p!=c.end(); ++p)
           if (*p==v)
                 res.push_back(p);
     return res;
}

We can now write:

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void test()
{
     string m {"Mary had a little lamb"};
     for (auto p : find_all(m,'a'))             // p is a string::iterator
           if (*p!='a')
                 cerr << "string bug!\n";

     list<double> ld {1.1, 2.2, 3.3, 1.1};
     for (auto p : find_all(ld,1.1))
           if (*p!=1.1)
                 cerr << "list bug!\n";

     vector<string> vs { "red", "blue", "green", "green", "orange", "green" };
     for (auto p : find_all(vs,"green"))
           if (*p!="green")
                 cerr << "vector bug!\n";

     for (auto p : find_all(vs,"green"))
           *p = "vert";
}

Iterators are used to separate algorithms and containers. An algorithm operates on its data through iterators and knows nothing about the container in which the elements are stored. Conversely, a container knows nothing about the algorithms operating on its elements; all it does is to supply iterators upon request (e.g., begin() and end()). This model of separation between data storage and algorithm delivers very general and flexible software.

4.5.2. Iterator Types

What are iterators really? Any particular iterator is an object of some type. There are, however, many different iterator types, because an iterator needs to hold the information necessary for doing its job for a particular container type. These iterator types can be as different as the containers and the specialized needs they serve. For example, a vector’s iterator could be an ordinary pointer, because a pointer is quite a reasonable way of referring to an element of a vector:

Alternatively, a vector iterator could be implemented as a pointer to the vector plus an index:

Using such an iterator would allow range checking.

A list iterator must be something more complicated than a simple pointer to an element because an element of a list in general does not know where the next element of that list is. Thus, a list iterator might be a pointer to a link:

What is common for all iterators is their semantics and the naming of their operations. For example, applying ++ to any iterator yields an iterator that refers to the next element. Similarly, * yields the element to which the iterator refers. In fact, any object that obeys a few simple rules like these is an iterator (§33.1.4). Furthermore, users rarely need to know the type of a specific iterator; each container “knows” its iterator types and makes them available under the conventional names iterator and const_iterator. For example, list<Entry>::iterator is the general iterator type for list<Entry>. We rarely have to worry about the details of how that type is defined.

4.5.3. Stream Iterators

Iterators are a general and useful concept for dealing with sequences of elements in containers. However, containers are not the only place where we find sequences of elements. For example, an input stream produces a sequence of values, and we write a sequence of values to an output stream. Consequently, the notion of iterators can be usefully applied to input and output.

To make an ostream_iterator, we need to specify which stream will be used and the type of objects written to it. For example:

ostream_iterator<string> oo {cout};     // write strings to cout

The effect of assigning to *oo is to write the assigned value to cout. For example:

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int main()
{
     *oo = "Hello, ";    // meaning cout<<"Hello, "
     ++oo;
     *oo = "world!\n";   // meaning cout<<"world!\n"
}

This is yet another way of writing the canonical message to standard output. The ++oo is done to mimic writing into an array through a pointer.

Similarly, an istream_iterator is something that allows us to treat an input stream as a read-only container. Again, we must specify the stream to be used and the type of values expected:

istream_iterator<string> ii {cin};

Input iterators are used in pairs representing a sequence, so we must provide an istream_iterator to indicate the end of input. This is the default istream_iterator:

istream_iterator<string> eos {};

Typically, istream_iterators and ostream_iterators are not used directly. Instead, they are provided as arguments to algorithms. For example, we can write a simple program to read a file, sort the words read, eliminate duplicates, and write the result to another file:

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int main()
{
     string from, to;
     cin >> from >> to;                     // get source and target file names

     ifstream is {from};                    // input stream for file "from"
     istream_iterator<string> ii {is};      // input iterator for stream
     istream_iterator<string> eos {};       // input sentinel

     ofstream os{to};                       // output stream for file "to"
     ostream_iterator<string> oo {os,"\n"}; // output iterator for stream

     vector<string> b {ii,eos};             // b is a vector initialized from input [ii:eos)
     sort(b.begin(),b.end());               // sort the buffer

     unique_copy(b.begin(),b.end(),oo);     // copy buffer to output, discard replicated values
     return !is.eof() || !os;               // return error state (§2.2.1, §38.3)
}

An ifstream is an istream that can be attached to a file, and an ofstream is an ostream that can be attached to a file. The ostream_iterator’s second argument is used to delimit output values.

Actually, this program is longer than it needs to be. We read the strings into a vector, then we sort() them, and then we write them out, eliminating duplicates. A more elegant solution is not to store duplicates at all. This can be done by keeping the strings in a set, which does not keep duplicates and keeps its elements in order (§31.4.3). That way, we could replace the two lines using a vector with one using a set and replace unique_copy() with the simpler copy():

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     set<string> b {ii,eos};         // collect strings from input
     copy(b.begin(),b.end(),oo);     // copy buffer to output

We used the names ii, eos, and oo only once, so we could further reduce the size of the program:

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int main()
{
     string from, to;
     cin >> from >> to;        // get source and target file names

     ifstream is {from};       // input stream for file "from"
     ofstream os {to};         // output stream for file "to"

     set<string> b {istream_iterator<string>{is},istream_iterator<string>{}}; // read input
     copy(b.begin(),b.end(),ostream_iterator<string>{os,"\n"});               // copy to output

     return !is.eof() || !os;         // return error state (§2.2.1, §38.3)
}

It is a matter of taste and experience whether or not this last simplification improves readability.

4.5.4. Predicates

In the examples above, the algorithms have simply “built in” the action to be done for each element of a sequence. However, we often want to make that action a parameter to the algorithm. For example, the find algorithm (§32.4) provides a convenient way of looking for a specific value. A more general variant looks for an element that fulfills a specified requirement, a predicate (§3.4.2). For example, we might want to search a map for the first value larger than 42. A map allows us to access its elements as a sequence of (key,value) pairs, so we can search a map<string,int>’s sequence for a pair<const string,int> where the int is greater than 42:

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void f(map<string,int>& m)
{
     auto p = find_if(m.begin(),m.end(),Greater_than{42});
     // ...
}

Here, Greater_than is a function object (§3.4.3) holding the value (42) to be compared against:

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struct Greater_than {
     int val;
     Greater_than(int v) : val{v} { }
     bool operator()(const pair<string,int>& r) { return r.second>val; }
};

Alternatively, we could use a lambda expression (§3.4.3):

int cxx = count_if(m.begin(), m.end(), [](const pair<string,int>& r) { return r.second>42; });

4.5.5. Algorithm Overview

A general definition of an algorithm is “a finite set of rules which gives a sequence of operations for solving a specific set of problems [and] has five important features: Finiteness ... Definiteness ... Input ... Output ... Effectiveness” [Knuth,1968,§1.1]. In the context of the C++ standard library, an algorithm is a function template operating on sequences of elements.

The standard library provides dozens of algorithms. The algorithms are defined in namespace std and presented in the <algorithm> header. These standard-library algorithms all take sequences as inputs (§4.5). A half-open sequence from b to e is referred to as [b:e). Here are a few I have found particularly useful:

These algorithms, and many more (see Chapter 32), can be applied to elements of containers, strings, and built-in arrays.

4.5.6. Container Algorithms

A sequence is defined by a pair of iterators [begin:end). This is general and flexible, but most often, we apply an algorithm to a sequence that is the contents of a container. For example:

sort(v.begin(),v.end());

Why don’t we just say sort(v)? We can easily provide that shorthand:

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namespace Estd {
   using namespace std;

   template<class C>
   void sort(C& c)
   {
        sort(c.begin(),c.end());
   }
   template<class C, class Pred>
   void sort(C& c, Pred p)
   {
        sort(c.begin(),c.end(),p);
   }

   // ...
}

I put the container versions of sort() (and other algorithms) into their own namespace Estd (“extended std”) to avoid interfering with other programmers’ uses of namespace std.

4.6. Advice

[1] Don’t reinvent the wheel; use libraries; §4.1.

[2] When you have a choice, prefer the standard library over other libraries; §4.1.

[3] Do not think that the standard library is ideal for everything; §4.1.

[4] Remember to #include the headers for the facilities you use; §4.1.2.

[5] Remember that standard-library facilities are defined in namespace std; §4.1.2.

[6] Prefer strings over C-style strings (a char*; §2.2.5); §4.2, §4.3.2.

[7] iostreams are type sensitive, type-safe, and extensible; §4.3.

[8] Prefer vector<T>, map<K,T>, and unordered_map<K,T> over T[]; §4.4.

[9] Know your standard containers and their tradeoffs; §4.4.

[10] Use vector as your default container; §4.4.1.

[11] Prefer compact data structures; §4.4.1.1.

[12] If in doubt, use a range-checked vector (such as Vec); §4.4.1.2.

[13] Use push_back() or back_inserter() to add elements to a container; §4.4.1, §4.5.

[14] Use push_back() on a vector rather than realloc() on an array; §4.5.

[15] Catch common exceptions in main(); §4.4.1.2.

[16] Know your standard algorithms and prefer them over handwritten loops; §4.5.5.

[17] If iterator use gets tedious, define container algorithms; §4.5.6.

5. A Tour of C++: Concurrency and Utilities

When you wish to instruct, be brief.

– Cicero

• Introduction

• Resource Management

unique_ptr and shared_ptr

• Concurrency

Tasks and threads; Passing Arguments; Returning Results; Sharing Data; Communicating Tasks

• Small Utility Components

Time; Type Functions; pair and tuple

• Regular Expressions

• Math

Mathematical Functions and Algorithms; Complex Numbers; Random Numbers; Vector Arithmetic; Numeric Limits

• Advice

5.1. Introduction

From an end-user’s perspective, the ideal standard library would provide components directly supporting essentially every need. For a given application domain, a huge commercial library can come close to that ideal. However, that is not what the C++ standard library is trying to do. A manageable, universally available, library cannot be everything to everybody. Instead, the C++ standard library aims to provide components that are useful to most people in most application areas. That is, it aims to serve the intersection of all needs rather than their union. In addition, support for a few widely important application areas, such as mathematical computation and text manipulation, have crept in.

5.2. Resource Management

One of the key tasks of any nontrivial program is to manage resources. A resource is something that must be acquired and later (explicitly or implicitly) released. Examples are memory, locks, sockets, thread handles, and file handles. For a long-running program, failing to release a resource in a timely manner (“a leak”) can cause serious performance degradation and possibly even a miserable crash. Even for short programs, a leak can become an embarrassment, say by a resource shortage increasing the run time by orders of magnitude.

The standard library components are designed not to leak resources. To do this, they rely on the basic language support for resource management using constructor/destructor pairs to ensure that a resource doesn’t outlive an object responsible for it. The use of a constructor/destructor pair in Vector to manage the lifetime of its elements is an example (§3.2.1.2) and all standard-library containers are implemented in similar ways. Importantly, this approach interacts correctly with error handling using exceptions. For example, the technique is used for the standard-library lock classes:

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mutex m; // used to protect access to shared data
// ...
void f()
{
     unique_lock<mutex> lck {m}; // acquire the mutex m
     // ... manipulate shared data ...
}

A thread will not proceed until lck’s constructor has acquired its mutex, m (§5.3.4). The corresponding destructor releases the resource. So, in this example, unique_lock’s destructor releases the mutex when the thread of control leaves f() (through a return, by “falling off the end of the function,” or through an exception throw).

This is an application of the “Resource Acquisition Is Initialization” technique (RAII; §3.2.1.2, §13.3). This technique is fundamental to the idiomatic handling of resources in C++. Containers (such as vector and map), string, and iostream manage their resources (such as file handles and buffers) similarly.

5.2.1. unique_ptr and shared_ptr

The examples so far take care of objects defined in a scope, releasing the resources they acquire at the exit from the scope, but what about objects allocated on the free store? In <memory>, the standard library provides two “smart pointers” to help manage objects on the free store:

[1] unique_ptr to represent unique ownership (§34.3.1)

[2] shared_ptr to represent shared ownership (§34.3.2)

The most basic use of these “smart pointers” is to prevent memory leaks caused by careless programming. For example:

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void f(int i, int j) // X* vs. unique_ptr<X>
{
     X* p = new X;                 // allocate a new X
     unique_ptr<X> sp {new X};     // allocate a new X and give its pointer to unique_ptr
     // ...
     if (i<99) throw Z{};          // may throw an exception
     if (j<77) return;             // may return "early"
     p–>do_something();            // may throw an exception
     sp–>do_something();           // may throw an exception
     // ...
     delete p;                     // destroy *p
}

Here, we “forgot” to delete p if i<99 or if j<77. On the other hand, unique_ptr ensures that its object is properly destroyed whichever way we exit f() (by throwing an exception, by executing return, or by “falling off the end”). Ironically, we could have solved the problem simply by not using a pointer and not using new:

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void f(int i, int j)     // use a local variable
{
     X x;
     // ...
}

Unfortunately, overuse of new (and of pointers and references) seems to be an increasing problem.

However, when you really need the semantics of pointers, unique_ptr is a very lightweight mechanism with no space or time overhead compared to correct use of a built-in pointer. Its further uses include passing free-store allocated objects in and out of functions:

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unique_ptr<X> make_X(int i)
    // make an X and immediately give it to a unique_ptr
{
    // ... check i, etc. ...
    return unique_ptr<X>{new X{i}};
}

A unique_ptr is a handle to an individual object (or an array) in much the same way that a vector is a handle to a sequence of objects. Both control the lifetime of other objects (using RAII) and both rely on move semantics to make return simple and efficient.

The shared_ptr is similar to unique_ptr except that shared_ptrs are copied rather than moved. The shared_ptrs for an object share ownership of an object and that object is destroyed when the last of its shared_ptrs is destroyed. For example:

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void f(shared_ptr<fstream>);
void g(shared_ptr<fstream>);

void user(const string& name, ios_base::openmode mode)
{
     shared_ptr<fstream> fp {new fstream(name,mode)};
     if (!*fp) throw No_file{}; // make sure the file was properly opened

     f(fp);
     g(fp);
     // ...
}

Now, the file opened by fp’s constructor will be closed by the last function to (explicitly or implicitly) destroy a copy of fp. Note that f() or g() may spawn a task holding a copy of fp or in some other way store a copy that outlives user(). Thus, shared_ptr provides a form of garbage collection that respects the destructor-based resource management of the memory-managed objects. This is neither cost free nor exorbitantly expensive, but does make the lifetime of the shared object hard to predict. Use shared_ptr only if you actually need shared ownership.

Given unique_ptr and shared_ptr, we can implement a complete “no naked new” policy (§3.2.1.2) for many programs. However, these “smart pointers” are still conceptually pointers and therefore only my second choice for resource management – after containers and other types that manage their resources at a higher conceptual level. In particular, shared_ptrs do not in themselves provide any rules for which of their owners can read and/or write the shared object. Data races (§41.2.4) and other forms of confusion are not addressed simply by eliminating the resource management issues.

Where do we use “smart pointers” (such as unique_ptr) rather than resource handles with operations designed specifically for the resource (such as vector or thread)? Unsurprisingly, the answer is “when we need pointer semantics.”

• When we share an object, we need pointers (or references) to refer to the shared object, so a shared_ptr becomes the obvious choice (unless there is an obvious single owner).

• When we refer to a polymorphic object, we need a pointer (or a reference) because we don’t know the exact type of the object referred to or even its size), so a unique_ptr becomes the obvious choice.

• A shared polymorphic object typically requires shared_ptrs.

We do not need to use a pointer to return a collection of objects from a function; a container that is a resource handle will do that simply and efficiently (§3.3.2).

5.3. Concurrency

Concurrency – the execution of several tasks simultaneously – is widely used to improve throughput (by using several processors for a single computation) or to improve responsiveness (by allowing one part of a program to progress while another is waiting for a response). All modern programming languages provide support for this. The support provided by the C++ standard library is a portable and type-safe variant of what has been used in C++ for more than 20 years and is almost universally supported by modern hardware. The standard-library support is primarily aimed at supporting systems-level concurrency rather than directly providing sophisticated higher-level concurrency models; those can be supplied as libraries built using the standard-library facilities.

The standard library directly supports concurrent execution of multiple threads in a single address space. To allow that, C++ provides a suitable memory model (§41.2) and a set of atomic operations (§41.3). However, most users will see concurrency only in terms of the standard library and libraries built on top of that. This section briefly gives examples of the main standard-library concurrency support facilities: threads, mutexes, lock() operations, packaged_tasks, and futures. These features are built directly upon what operating systems offer and do not incur performance penalties compared with those.

5.3.1. Tasks and threads

We call a computation that can potentially be executed concurrently with other computations a task. A thread is the system-level representation of a task in a program. A task to be executed concurrently with other tasks is launched by constructing a std::thread (found in <thread>) with the task as its argument. A task is a function or a function object:

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void f();                // function

struct F {               // function object
     void operator()();  // F's call operator (§3.4.3)
};

void user()
{
     thread t1 {f};      // f() executes in separate thread
     thread t2 {F()};    // F()() executes in separate thread

     t1.join();          // wait for t1
     t2.join();          // wait for t2
}

The join()s ensure that we don’t exit user() until the threads have completed. To “join” means to “wait for the thread to terminate.”

Threads of a program share a single address space. In this, threads differ from processes, which generally do not directly share data. Since threads share an address space, they can communicate through shared objects (§5.3.4). Such communication is typically controlled by locks or other mechanisms to prevent data races (uncontrolled concurrent access to a variable).

Programming concurrent tasks can be very tricky. Consider possible implementations of the tasks f (a function) and F (a function object):

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void f() { cout << "Hello "; }

struct F {
     void operator()() { cout << "Parallel World!\n"; }
};

This is an example of a bad error: Here, f and F() each use the object cout without any form of synchronization. The resulting output would be unpredictable and could vary between different executions of the program because the order of execution of the individual operations in the two tasks is not defined. The program may produce “odd” output, such as

PaHerallllel o World!

When defining tasks of a concurrent program, our aim is to keep tasks completely separate except where they communicate in simple and obvious ways. The simplest way of thinking of a concurrent task is as a function that happens to run concurrently with its caller. For that to work, we just have to pass arguments, get a result back, and make sure that there is no use of shared data in between (no data races).

5.3.2. Passing Arguments

Typically, a task needs data to work upon. We can easily pass data (or pointers or references to the data) as arguments. Consider:

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void f(vector<double>& v);    // function do something with v

struct F {                    // function object: do something with v
     vector<double>& v;
     F(vector<double>& vv) :v{vv} { }
     void operator()();       // application operator; §3.4.3
};

int main()
{
     vector<double> some_vec {1,2,3,4,5,6,7,8,9};
     vector<double> vec2 {10,11,12,13,14};

     thread t1 {f,some_vec};  // f(some_vec) executes in a separate thread
     thread t2 {F{vec2}};     // F(vec2)() executes in a separate thread

     t1.join();
     t2.join();
}

Obviously, F{vec2} saves a reference to the argument vector in F. F can now use that array and hopefully no other task accesses vec2 while F is executing. Passing vec2 by value would eliminate that risk.

The initialization with {f,some_vec} uses a thread variadic template constructor that can accept an arbitrary sequence of arguments (§28.6). The compiler checks that the first argument can be invoked given the following arguments and builds the necessary function object to pass to the thread. Thus, if F::operator()() and f() perform the same algorithm, the handling of the two tasks are roughly equivalent: in both cases, a function object is constructed for the thread to execute.

5.3.3. Returning Results

In the example in §5.3.2, I pass the arguments by non-const reference. I only do that if I expect the task to modify the value of the data referred to (§7.7). That’s a somewhat sneaky, but not uncommon, way of returning a result. A less obscure technique is to pass the input data by const reference and to pass the location of a place to deposit the result as a separate argument:

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void f(const vector<double>& v, double* res);// take input from v; place result in *res

class F {
public:
     F(const vector<double>& vv, double* p) :v{vv}, res{p} { }
     void operator()();          // place result in *res
private:
     const vector<double>& v;         // source of input
     double* res;               // target for output
};

int main()
{
     vector<double> some_vec;
     vector<double> vec2;
     // ...

     double res1;
     double res2;

     thread t1 {f,some_vec,&res1}; // f(some_vec,&res1) executes in a separate thread
     thread t2 {F{vec2,&res2}};          // F{vec2,&res2}() executes in a separate thread

     t1.join();
     t2.join();

     cout << res1 << ' ' << res2 << '\n';
}

I don’t consider returning results through arguments particularly elegant, so I return to this topic in §5.3.5.1.

5.3.4. Sharing Data

Sometimes tasks need to share data. In that case, the access has to be synchronized so that at most one task at a time has access. Experienced programmers will recognize this as a simplification (e.g., there is no problem with many tasks simultaneously reading immutable data), but consider how to ensure that at most one task at a time has access to a given set of objects.

The fundamental element of the solution is a mutex, a “mutual exclusion object.” A thread acquires a mutex using a lock() operation:

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mutex m; // controlling mutex
int sh;  // shared data

void f()
{
     unique_lock<mutex> lck {m}; // acquire mutex
     sh += 7;                    // manipulate shared data
}    // release mutex implicitly

The unique_lock’s constructor acquires the mutex (through a call m.lock()). If another thread has already acquired the mutex, the thread waits (“blocks”) until the other thread completes its access. Once a thread has completed its access to the shared data, the unique_lock releases the mutex (with a call m.unlock()). The mutual exclusion and locking facilities are found in <mutex>.

The correspondence between the shared data and a mutex is conventional: the programmer simply has to know which mutex is supposed to correspond to which data. Obviously, this is error-prone, and equally obviously we try to make the correspondence clear through various language means. For example:

class Record {
public:
     mutex rm;
     // ...
};

It doesn’t take a genius to guess that for a Record called rec, rec.rm is a mutex that you are supposed to acquire before accessing the other data of rec, though a comment or a better name might have helped a reader.

It is not uncommon to need to simultaneously access several resources to perform some action. This can lead to deadlock. For example, if thread1 acquires mutex1 and then tries to acquire mutex2 while thread2 acquires mutex2 and then tries to acquire mutex1, then neither task will ever proceed further. The standard library offers help in the form of an operation for acquiring several locks simultaneously:

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void f()
{
     // ...
     unique_lock<mutex> lck1 {m1,defer_lock};    // defer_lock: don't yet try to acquire the mutex
     unique_lock<mutex> lck2 {m2,defer_lock};
     unique_lock<mutex> lck3 {m3,defer_lock};
     // ...
     lock(lck1,lck2,lck3);                       // acquire all three locks
     // ... manipulate shared data ...
} // implicitly release all mutexes

This lock() will only proceed after acquiring all its mutex arguments and will never block (“go to sleep”) while holding a mutex. The destructors for the individual unique_locks ensure that the mutexes are released when a thread leaves the scope.

Communicating through shared data is pretty low level. In particular, the programmer has to devise ways of knowing what work has and has not been done by various tasks. In that regard, use of shared data is inferior to the notion of call and return. On the other hand, some people are convinced that sharing must be more efficient than copying arguments and returns. That can indeed be so when large amounts of data are involved, but locking and unlocking are relatively expensive operations. On the other hand, modern machines are very good at copying data, especially compact data, such as vector elements. So don’t choose shared data for communication because of “efficiency” without thought and preferably not without measurement.

5.3.4.1. Waiting for Events

Sometimes, a thread needs to wait for some kind of external event, such as another thread completing a task or a certain amount of time having passed. The simplest “event” is simply time passing. Consider:

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using namespace std::chrono; // see §35.2

auto t0 = high_resolution_clock::now();
this_thread::sleep_for(milliseconds{20});
auto t1 = high_resolution_clock::now();
cout << duration_cast<nanoseconds>(t1–t0).count() << " nanoseconds passed\n";

Note that I didn’t even have to launch a thread; by default, this_thread refers to the one and only thread (§42.2.6).

I used duration_cast to adjust the clock’s units to the nanoseconds I wanted. See §5.4.1 and §35.2 before trying anything more complicated than this with time. The time facilities are found in <chrono>.

The basic support for communicating using external events is provided by condition_variables found in <condition_variable> (§42.3.4). A condition_variable is a mechanism allowing one thread to wait for another. In particular, it allows a thread to wait for some condition (often called an event) to occur as the result of work done by other threads.

Consider the classical example of two threads communicating by passing messages through a queue. For simplicity, I declare the queue and the mechanism for avoiding race conditions on that queue global to the producer and consumer:

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class Message {   // object to be communicated
     // ...
};

queue<Message> mqueue;          // the queue of messages
condition_variable mcond;       // the variable communicating events
mutex mmutex;                   // the locking mechanism

The types queue, condition_variable, and mutex are provided by the standard library.

The consumer() reads and processes Messages:

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void consumer()
{
     while(true) {
          unique_lock<mutex> lck{mmutex};             // acquire mmutex
          while (mcond.wait(lck)) /* do nothing */;   // release lck and wait;
                                                      // re-acquire lck upon wakeup
          auto m = mqueue.front();                    // get the message
          mqueue.pop();
          lck.unlock();                               // release lck
          // ... process m ...
     }
}

Here, I explicitly protect the operations on the queue and on the condition_variable with a unique_lock on the mutex. Waiting on condition_variable releases its lock argument until the wait is over (so that the queue is non-empty) and then reacquires it.

The corresponding producer looks like this:

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void producer()
{
     while(true) {
          Message m;
          // ... fill the message ...
          unique_lock<mutex> lck {mmutex};  // protect operations
          mqueue.push(m);
          mcond.notify_one();               // notify
     }                                      // release lock (at end of scope)
}

Using condition_variables supports many forms of elegant and efficient sharing, but can be rather tricky (§42.3.4).

5.3.5. Communicating Tasks

The standard library provides a few facilities to allow programmers to operate at the conceptual level of tasks (work to potentially be done concurrently) rather than directly at the lower level of threads and locks:

[1] future and promise for returning a value from a task spawned on a separate thread

[2] packaged_task to help launch tasks and connect up the mechanisms for returning a result

[3] async() for launching of a task in a manner very similar to calling a function.

These facilities are found in <future>.

5.3.5.1. future and promise

The important point about future and promise is that they enable a transfer of a value between two tasks without explicit use of a lock; “the system” implements the transfer efficiently. The basic idea is simple: When a task wants to pass a value to another, it puts the value into a promise. Somehow, the implementation makes that value appear in the corresponding future, from which it can be read (typically by the launcher of the task). We can represent this graphically:

If we have a future<X> called fx, we can get() a value of type X from it:

X v = fx.get(); // if necessary, wait for the value to get computed

If the value isn’t there yet, our thread is blocked until it arrives. If the value couldn’t be computed, get() might throw an exception (from the system or transmitted from the task from which we were trying to get() the value).

The main purpose of a promise is to provide simple “put” operations (called set_value() and set_exception()) to match future’s get(). The names “future” and “promise” are historical; please don’t blame me. They are yet another fertile source of puns.

If you have a promise and need to send a result of type X to a future, you can do one of two things: pass a value or pass an exception. For example:

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void f(promise<X>& px) // a task: place the result in px
{
     // ...
     try {
          X res;
          // ... compute a value for res ...
          px.set_value(res);
     }
     catch (...) {      // oops: couldn't compute res
          // pass the exception to the future's thread:
          px.set_exception(current_exception());
     }
}

The current_exception() refers to the caught exception (§30.4.1.2).

To deal with an exception transmitted through a future, the caller of get() must be prepared to catch it somewhere. For example:

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void g(future<X>& fx)           // a task: get the result from fx
{
     // ...
     try {
          X v = fx.get();  // if necessary, wait for the value to get computed
          // ... use v ...
     }
     catch (...) {         // oops: someone couldn't compute v
          // ... handle error ...
     }
}

5.3.5.2. packaged_task

How do we get a future into the task that needs a result and the corresponding promise into the thread that should produce that result? The packaged_task type is provided to simplify setting up tasks connected with futures and promises to be run on threads. A packaged_task provides wrapper code to put the return value or exception from the task into a promise (like the code shown in §5.3.5.1). If you ask it by calling get_future, a packaged_task will give you the future corresponding to its promise. For example, we can set up two tasks to each add half of the elements of a vector<double> using the standard-library accumulate() (§3.4.2, §40.6):

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double accum(double* beg, double * end, double init)
     // compute the sum of [beg:end) starting with the initial value init
{
     return accumulate(beg,end,init);
}

double comp2(vector<double>& v)
{
     using Task_type = double(double*,double*,double);   // type of task

     packaged_task<Task_type> pt0 {accum};               // package the task (i.e., accum)
     packaged_task<Task_type> pt1 {accum};

     future<double> f0 {pt0.get_future()};               // get hold of pt0's future
     future<double> f1 {pt1.get_future()};               // get hold of pt1's future

     double* first = &v[0];
     thread t1 {move(pt0),first,first+v.size()/2,0};     // start a thread for pt0
     thread t2 {move(pt1),first+v.size()/2,first+v.size(),0};                                                   // start a thread for pt1

     // ...

     return f0.get()+f1.get();       // get the results
}

The packaged_task template takes the type of the task as its template argument (here Task_type, an alias for double(double*,double*,double)) and the task as its constructor argument (here, accum). The move() operations are needed because a packaged_task cannot be copied.

Please note the absence of explicit mention of locks in this code: we are able to concentrate on tasks to be done, rather than on the mechanisms used to manage their communication. The two tasks will be run on separate threads and thus potentially in parallel.

5.3.5.3. async()

The line of thinking I have pursued in this chapter is the one I believe to be the simplest yet still among the most powerful: Treat a task as a function that may happen to run concurrently with other tasks. It is far from the only model supported by the C++ standard library, but it serves well for a wide range of needs. More subtle and tricky models, e.g., styles of programming relying on shared memory, can be used as needed.

To launch tasks to potentially run asynchronously, we can use async():

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double comp4(vector<double>& v)
    // spawn many tasks if v is large enough
{
    if (v.size()<10000) return accum(v.begin(),v.end(),0.0);

    auto v0 = &v[0];
    auto sz = v.size();

    auto f0 = async(accum,v0,v0+sz/4,0.0);         // first quarter
    auto f1 = async(accum,v0+sz/4,v0+sz/2,0.0);    // second quarter
    auto f2 = async(accum,v0+sz/2,v0+sz*3/4,0.0);  // third quarter
    auto f3 = async(accum,v0+sz*3/4,v0+sz,0.0);    // fourth quarter

    return f0.get()+f1.get()+f2.get()+f3.get();  // collect and combine the results
}

Basically, async() separates the “call part” of a function call from the “get the result part,” and separates both from the actual execution of the task. Using async(), you don’t have to think about threads and locks. Instead, you think just in terms of tasks that potentially compute their results asynchronously. There is an obvious limitation: Don’t even think of using async() for tasks that share resources needing locking – with async() you don’t even know how many threads will be used because that’s up to async() to decide based on what it knows about the system resources available at the time of a call. For example, async() may check whether any idle cores (processors) are available before deciding how many threads to use.

Please note that async() is not just a mechanism specialized for parallel computation for increased performance. For example, it can also be used to spawn a task for getting information from a user, leaving the “main program” active with something else (§42.4.6).

5.4. Small Utility Components

Not all standard-library components come as part of obviously labeled facilities, such as “containers” or “I/O.” This section gives a few examples of small, widely useful components:

• clock and duration for measuring time.

• Type functions, such as iterator_traits and is_arithmetic, for gaining information about types.

• pair and tuple for representing small potentially heterogeneous sets of values.

The point here is that a function or a type need not be complicated or closely tied to a mass of other functions and types to be useful. Such library components mostly act as building blocks for more powerful library facilities, including other components of the standard library.

5.4.1. Time

The standard library provides facilities for dealing with time. For example, here is the basic way of timing something:

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using namespace std::chrono;      // see §35.2

auto t0 = high_resolution_clock::now();
do_work();
auto t1 = high_resolution_clock::now();
cout << duration_cast<milliseconds>(t1–t0).count() << "msec\n";

The clock returns a time_point (a point in time). Subtracting two time_points gives a duration (a period of time). Various clocks give their results in various units of time (the clock I used measures nanoseconds), so it is usually a good idea to convert a duration into a known unit. That’s what duration_cast does.

The standard-library facilities for dealing with time are found in the subnamespace std::chrono in <chrono> (§35.2).

Don’t make statements about “efficiency” of code without first doing time measurements. Guesses about performance are most unreliable.

5.4.2. Type Functions

A type function is a function that is evaluated at compile-time given a type as its argument or returning a type. The standard library provides a variety of type functions to help library implementers and programmers in general to write code that take advantage of aspects of the language, the standard library, and code in general.

For numerical types, numeric_limits from <limits> presents a variety of useful information (§5.6.5). For example:

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constexpr float min = numeric_limits<float>::min();    // smallest positive float (§40.2)

Similarly, object sizes can be found by the built-in sizeof operator (§2.2.2). For example:

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constexpr int szi = sizeof(int); // the number of bytes in an int

Such type functions are part of C++’s mechanisms for compile-time computation that allow tighter type checking and better performance than would otherwise have been possible. Use of such features is often called metaprogramming or (when templates are involved) template metaprogramming (Chapter 28). Here, I just present two facilities provided by the standard library: iterator_traits (§5.4.2.1) and type predicates (§5.4.2.2).

5.4.2.1. iterator_traits

The standard-library sort() takes a pair of iterators supposed to define a sequence (§4.5). Furthermore, those iterators must offer random access to that sequence, that is, they must be random-access iterators. Some containers, such as forward_list, do not offer that. In particular, a forward_list is a singly-linked list so subscripting would be expensive and there is no reasonable way to refer back to a previous element. However, like most containers, forward_list offers forward iterators that can be used to traverse the sequence by algorithms and for-statements (§33.1.1).

The standard library provides a mechanism, iterator_traits that allows us to check which kind of iterator is supported. Given that, we can improve the range sort() from §4.5.6 to accept either a vector or a forward_list. For example:

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void test(vector<string>& v, forward_list<int>& lst)
{
     sort(v);    // sort the vector
     sort(lst);  // sort the singly-linked list
}

The techniques needed to make that work are generally useful.

First, I write two helper functions that take an extra argument indicating whether they are to be used for random-access iterators or forward iterators. The version taking random-access iterator arguments is trivial:

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template<typename Ran>                                              // for random-access iterators
void sort_helper(Ran beg, Ran end, random_access_iterator_tag)      // we can subscript into [beg:end)
{
     sort(beg,end);     // just sort it
}

The version for forward iterators is almost as simple; just copy the list into a vector, sort, and copy back again:

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template<typename For>                                       // for forward iterators
void sort_helper(For beg, For end, forward_iterator_tag)     // we can traverse [beg:end)
{
     vector<decltype(*beg)> v {beg,end};    // initialize a vector from [beg:end)
     sort(v.begin(),v.end());
     copy(v.begin(),v.end(),beg);           // copy the elements back
}

The decltype() is a built-in type function that returns the declared type of its argument (§6.3.6.3). Thus, v is a vector<X> where X is the element type of the input sequence.

The real “type magic” is in the selection of helper functions:

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template<typname C>
void sort(C& c)
{
     using Iter = Iterator_type<C>;
     sort_helper(c.begin(),c.end(),Iterator_category<Iter>{});
}

Here, I use two type functions: Iterator_type<C> returns the iterator type of C (that is, C::iterator) and then Iterator_category<Iter>{} constructs a “tag” value indicating the kind of iterator provided:

• std::random_access_iterator_tag if C’s iterator supports random access.

• std::forward_iterator_tag if C’s iterator supports forward iteration.

Given that, we can select between the two sorting algorithms at compile time. This technique, called tag dispatch is one of several used in the standard library and elsewhere to improve flexibility and performance.

The standard-library support for techniques for using iterators, such as tag dispatch, comes in the form of a simple class template iterator_traits from <iterator> (§33.1.3). This allows simple definitions of the type functions used in sort():

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template<typename C>
    using Iterator_type = typename C::iterator;   // C's iterator type

template<typename Iter>
    using Iterator_category = typename std::iterator_traits<Iter>::iterator_category;  // Iter's category

If you don’t want to know what kind of “compile-time type magic” is used to provide the standard-library features, you are free to ignore facilities such as iterator_traits. But then you can’t use the techniques they support to improve your own code.

5.4.2.2. Type Predicates

A standard-library type predicate is a simple type function that answers a fundamental question about types. For example:

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bool b1 = Is_arithmetic<int>();     // yes, int is an arithmetic type
bool b2 = Is_arithmetic<string>();  // no, std::string is not an arithmetic type

These predicates are found in <type_traits> and described in §35.4.1. Other examples are is_class, is_pod, is_literal_type, has_virtual_destructor, and is_base_of. They are most useful when we write templates. For example:

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template<typename Scalar>
class complex {
     Scalar re, im;
public:
     static_assert(Is_arithmetic<Scalar>(), "Sorry, I only support complex of arithmetic types");
     // ...
};

To improve readability compared to using the standard library directly, I defined a type function:

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template<typename T>
constexpr bool Is_arithmetic()
{
     return std::is_arithmetic<T>::value ;
}

Older programs use ::value directly instead of (), but I consider that quite ugly and it exposes implementation details.

5.4.3. pair and tuple

Often, we need some data that is just data; that is, a collection of values, rather than an object of a class with a well-defined semantics and an invariant for its value (§2.4.3.2, §13.4). In such cases, we could define a simple struct with an appropriate set of appropriately named members. Alternatively, we could let the standard library write the definition for us. For example, the standard-library algorithm equal_range (§32.6.1) returns a pair of iterators specifying a sub-sequence meeting a predicate:

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template<typename Forward_iterator, typename T, typename Compare>
    pair<Forward_iterator,Forward_iterator>
    equal_range(Forward_iterator first, Forward_iterator last, const T& val, Compare cmp);

Given a sorted sequence [first:last), equal_range() will return the pair representing the subsequence that matches the predicate cmp. We can use that to search in a sorted sequence of Records:

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auto rec_eq = [](const Record& r1, const Record& r2) { return r1.name<r2.name;};// compare names

void f(const vector<Record>& v)     // assume that v is sorted on its "name" field
{
     auto er = equal_range(v.begin(),v.end(),Record{"Reg"},rec_eq);
     for (auto p = er.first; p!=er.second; ++p)    // print all equal records
           cout << *p;                             // assume that << is defined for Record
}

The first member of a pair is called first and the second member is called second. This naming is not particularly creative and may look a bit odd at first, but such consistent naming is a boon when we want to write generic code.

The standard-library pair (from <utility>) is quite frequently used in the standard library and elsewhere. A pair provides operators, such as =, ==, and <, if its elements do. The make_pair() function makes it easy to create a pair without explicitly mentioning its type (§34.2.4.1). For example:

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void f(vector<string>& v)
{
     auto pp = make_pair(v.begin(),2);    // pp is a pair<vector<string>::iterator,int>
     // ...
}

If you need more than two elements (or less), you can use tuple (from <utility>; §34.2.4.2). A tuple is a heterogeneous sequence of elements; for example:

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tuple<string,int,double> t2("Sild",123, 3.14); // the type is explicitly specified

auto t = make_tuple(string("Herring"),10, 1.23); // the type is deduced
                                                 // t is a tuple<string,int,double>

string s = get<0>(t); // get first element of tuple
int x = get<1>(t);
double d = get<2>(t);

The elements of a tuple are numbered (starting with zero), rather than named the way elements of pairs are (first and second). To get compile-time selection of elements, I must unfortunately use the ugly get<1>(t), rather than get(t,1) or t[1] (§28.5.2).

Like pairs, tuples can be assigned and compared if their elements can be.

A pair is common in interfaces because often we want to return more than one value, such as a result and an indicator of the quality of that result. It is less common to need three or more parts to a result, so tuples are more often found in the implementations of generic algorithms.

5.5. Regular Expressions

Regular expressions are a powerful tool for text processing. They provide a way to simply and tersely describe patterns in text (e.g., a U.S. ZIP code such as TX 77845, or an ISO-style date, such as 2009–06–07) and to efficiently find such patterns in text. In <regex>, the standard library provides support for regular expressions in the form of the std::regex class and its supporting functions. To give a taste of the style of the regex library, let us define and print a pattern:

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regex pat (R"(\w{2}\s*\d{5}(–\d{4})?)"); // ZIP code pattern: XXddddd-dddd and variants
cout << "pattern: " << pat << '\n';

People who have used regular expressions in just about any language will find \w{2}\s*\d{5}(–\d{4})? familiar. It specifies a pattern starting with two letters \w{2} optionally followed by some space \s* followed by five digits \d{5} and optionally followed by a dash and four digits –\d{4}. If you are not familiar with regular expressions, this may be a good time to learn about them ([Stroustrup,2009], [Maddock,2009], [Friedl,1997]). Regular expressions are summarized in §37.1.1.

To express the pattern, I use a raw string literal (§7.3.2.1) starting with R"( and terminated by )". This allows backslashes and quotes to be used directly in the string.

The simplest way of using a pattern is to search for it in a stream:

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int lineno = 0;
for (string line; getline(cin,line);) {           // read into line buffer
      ++lineno;
      smatch matches;                             // matched strings go here
      if (regex_search(line,matches,pat))         // search for pat in line
            cout << lineno << ": " << matches[0] << '\n';
}

The regex_search(line,matches,pat) searches the line for anything that matches the regular expression stored in pat and if it finds any matches, it stores them in matches. If no match was found, regex_search(line,matches,pat) returns false. The matches variable is of type smatch. The “s” stands for “sub” and an smatch is a vector of sub-matches. The first element, here matches[0], is the complete match.

For a more complete description see Chapter 37.

5.6. Math

C++ wasn’t designed primarily with numerical computation in mind. However, C++ is heavily used for numerical computation and the standard library reflects that.

5.6.1. Mathematical Functions and Algorithms

In <cmath>, we find the “usual mathematical functions,” such as sqrt(), log(), and sin() for arguments of type float, double, and long double (§40.3). Complex number versions of these functions are found in <complex> (§40.4).

In <numeric>, we find a small set of generalized numerical algorithms, such as accumulate(). For example:

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void f()
{
     list<double> lst {1, 2, 3, 4, 5, 9999.99999};
     auto s = accumulate(lst.begin(),lst.end(),0.0); // calculate the sum
     cout << s << '\n';                              // print 10014.9999
}

These algorithms work for every standard-library sequence and can have operations supplied as arguments (§40.6).

5.6.2. Complex Numbers

The standard library supports a family of complex number types along the lines of the complex class described in §2.3. To support complex numbers where the scalars are single-precision floating-point numbers (floats), double-precision floating-point numbers (doubles), etc., the standard library complex is a template:

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template<typename Scalar>
class complex {
public:
     complex(const Scalar& re ={}, const Scalar& im ={});
     // ...
};

The usual arithmetic operations and the most common mathematical functions are supported for complex numbers. For example:

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void f(complex<float> fl, complex<double> db)
{
     complex<long double> ld {fl+sqrt(db)};
     db += fl*3;
     fl = pow(1/fl,2);
     // ...
}

The sqrt() and pow() (exponentiation) functions are among the usual mathematical functions defined in <complex>. For more details, see §40.4.

5.6.3. Random Numbers

Random numbers are useful in many contexts, such as testing, games, simulation, and security. The diversity of application areas is reflected in the wide selection of random number generators provided by the standard library in <random>. A random number generator consists of two parts:

[1] an engine that produces a sequence of random or pseudo-random values.

[2] a distribution that maps those values into a mathematical distribution in a range.

Examples of distributions are uniform_int_distribution (where all integers produced are equally likely), normal_distribution (“the bell curve”), and exponential_distribution (exponential growth); each for some specified range. For example:

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using my_engine = default_random_engine;            // type of engine
using my_distribution = uniform_int_distribution<>; // type of distribution

my_engine re {};                                    // the default engine
my_distribution one_to_six {1,6};                   // distribution that maps to the ints 1..6
auto die = bind(one_to_six,re);                     // make a generator

int x = die();                                      // roll the die: x becomes a value in [1:6]

The standard-library function bind() makes a function object that will invoke its first argument (here, one_to_six) given its second argument (here, re) as its argument (§33.5.1). Thus a call die() is equivalent to a call one_to_six(re).

Thanks to its uncompromising attention to generality and performance one expert has deemed the standard-library random number component “what every random number library wants to be when it grows up.” However, it can hardly be deemed “novice friendly.” The using statements makes what is being done a bit more obvious. Instead, I could just have written:

auto die = bind(uniform_int_distribution<>{1,6}, default_random_engine{});

Which version is the more readable depends entirely on the context and the reader.

For novices (of any background) the fully general interface to the random number library can be a serious obstacle. A simple uniform random number generator is often sufficient to get started. For example:

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Rand_int rnd {1,10};               // make a random number generator for [1:10]
int x = rnd();      // x is a number in [1:10]

So, how could we get that? We have to get something like die() inside a class Rand_int:

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class Rand_int {
public:
     Rand_int(int low, int high) :dist{low,high} { }
     int operator()() { return dist(re); }     // draw an int
private:
     default_random_engine re;
     uniform_int_distribution<> dist;
};

That definition is still “expert level,” but the use of Rand_int() is manageable in the first week of a C++ course for novices. For example:

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int main()
{
     Rand_int rnd {0,4}; // make a uniform random number generator

     vector<int> histogram(5);             // make a vector of size 5
     for (int i=0; i!=200; ++i)
           ++histogram[rnd()];             // fill histogram with the frequencies of numbers [0:4]

     for (int i = 0; i!=mn.size(); ++i) {  // write out a bar graph
           cout << i << '\t';
           for (int j=0; j!=mn[i]; ++j) cout << '*';
           cout << endl;
     }
}

The output is a (reassuringly boring) uniform distribution (with reasonable statistical variation):

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0   ********************************************
1   ******************************************
2   *******************************
3   ******************************************
4   *****************************************

There is no standard graphics library for C++, so I use “ASCII graphics.” Obviously, there are lots of open source and commercial graphics and GUI libraries for C++, but in this book I’ll restrict myself to ISO standard facilities.

For more information about random numbers, see §40.7.

5.6.4. Vector Arithmetic

The vector described in §4.4.1 was designed to be a general mechanism for holding values, to be flexible, and to fit into the architecture of containers, iterators, and algorithms. However, it does not support mathematical vector operations. Adding such operations to vector would be easy, but its generality and flexibility precludes optimizations that are often considered essential for serious numerical work. Consequently, the standard library provides (in <valarray>) a vector-like template, called valarray, that is less general and more amenable to optimization for numerical computation:

template<typename T>
class valarray {
    // ...
};

The usual arithmetic operations and the most common mathematical functions are supported for valarrays. For example:

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void f(valarray<double>& a1, valarray<double>& a2)
{
     valarray<double> a = a1*3.14+a2/a1;      // numeric array operators *, +, /, and =
     a2 += a1*3.14;
     a = abs(a);
     double d = a2[7];
     // ...
}

For more details, see §40.5. In particular, valarray offers stride access to help implement multidimensional computations.

5.6.5. Numeric Limits

In <limits>, the standard library provides classes that describe the properties of built-in types – such as the maximum exponent of a float or the number of bytes in an int; see §40.2. For example, we can assert that a char is signed:

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static_assert(numeric_limits<char>::is_signed,"unsigned characters!");
static_assert(100000<numeric_limits<int>::max(),"small ints!");

Note that the second assert (only) works because numeric_limits<int>::max() is a constexpr function (§2.2.3, §10.4).

5.7. Advice

[1] Use resource handles to manage resources (RAII); §5.2.

[2] Use unique_ptr to refer to objects of polymorphic type; §5.2.1.

[3] Use shared_ptr to refer to shared objects; §5.2.1.

[4] Use type-safe mechanisms for concurrency; §5.3.

[5] Minimize the use of shared data; §5.3.4.

[6] Don’t choose shared data for communication because of “efficiency” without thought and preferably not without measurement; §5.3.4.

[7] Think in terms of concurrent tasks, rather than threads; §5.3.5.

[8] A library doesn’t have to be large or complicated to be useful; §5.4.

[9] Time your programs before making claims about efficiency; §5.4.1.

[10] You can write code to explicitly depend on properties of types; §5.4.2.

[11] Use regular expressions for simple pattern matching; §5.5.

[12] Don’t try to do serious numeric computation using only the language; use libraries; §5.6.

[13] Properties of numeric types are accessible through numeric_limits; §5.6.5.

Part II: Basic Facilities

This part describes C++’s built-in types and the basic facilities for constructing programs out of them. The C subset of C++ is presented together with C++’s additional support for traditional styles of programming. It also discusses the basic facilities for composing a C++ program out of logical and physical parts.

Chapters

6 Types and Declarations

7 Pointers, Arrays, and References

8 Structures, Unions, and Enumerations

9 Statements

10 Expressions

11 Select Operations

12 Functions

13 Exception Handling

14 Namespaces

15 Source Files and Programs

“... I have long entertained a suspicion, with regard to the decisions of philosophers upon all subjects, and found in myself a greater inclination to dispute, than assent to their conclusions. There is one mistake, to which they seem liable, almost without exception; they confine too much their principles, and make no account of that vast variety, which nature has so much affected in all her operations. When a philosopher has once laid hold of a favourite principle, which perhaps accounts for many natural effects, he extends the same principle over the whole creation, and reduces to it every phænomenon, though by the most violent and absurd reasoning. ...”

– David Hume,
Essays, Moral, Political, and Literary. PART I. (1752)

6. Types and Declarations

Perfection is achieved only on the point of collapse.

– C. N. Parkinson

• The ISO C++ Standard

Implementations; The Basic Source Character Set

• Types

Fundamental Types; Booleans; Character Types; Integer Types; Floating-Point Types; Prefixes and Suffixes; void; Sizes; Alignment

• Declarations

The Structure of Declarations; Declaring Multiple Names; Names; Scope; Initialization; Deducing a Type: auto and decltype()

• Objects and Values

Lvalues and Rvalues; Lifetimes of Objects

• Type Aliases

• Advice

6.1. The ISO C++ Standard

The C++ language and standard library are defined by their ISO standard: ISO/IEC 14882:2011. In this book, references to the standard are of the form §iso.23.3.6.1. In cases where the text of this book is considered imprecise, incomplete, or possibly wrong, consult the standard. But don’t expect the standard to be a tutorial or to be easily accessible by non-experts.

Strictly adhering to the C++ language and library standard doesn’t by itself guarantee good code or even portable code. The standard doesn’t say whether a piece of code is good or bad; it simply says what a programmer can and cannot rely on from an implementation. It is easy to write perfectly awful standard-conforming programs, and most real-world programs rely on features that the standard does not guarantee to be portable. They do so to access system interfaces and hardware features that cannot be expressed directly in C++ or require reliance on specific implementation details.

Many important things are deemed implementation-defined by the standard. This means that each implementation must provide a specific, well-defined behavior for a construct and that behavior must be documented. For example:

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unsigned char c1 = 64;       // well defined: a char has at least 8 bits and can always hold 64
unsigned char c2 = 1256;     // implementation-defined: truncation if a char has only 8 bits

The initialization of c1 is well defined because a char must be at least 8 bits. However, the behavior of the initialization of c2 is implementation-defined because the number of bits in a char is implementation-defined. If the char has only 8 bits, the value 1256 will be truncated to 232 (§10.5.2.1). Most implementation-defined features relate to differences in the hardware used to run a program.

Other behaviors are unspecified; that is, a range of possible behaviors are acceptable, but the implementer is not obliged to specify which actually occur. Usually, the reason for deeming something unspecified is that the exact behavior is unpredictable for fundamental reasons. For example, the exact value returned by new is unspecified. So is the value of a variable assigned to from two threads unless some synchronization mechanism has been employed to prevent a data race (§41.2).

When writing real-world programs, it is usually necessary to rely on implementation-defined behavior. Such behavior is the price we pay for the ability to operate effectively on a large range of systems. For example, C++ would have been much simpler if all characters had been 8 bits and all pointers 32 bits. However, 16-bit and 32-bit character sets are not uncommon, and machines with 16-bit and 64-bit pointers are in wide use.

To maximize portability, it is wise to be explicit about what implementation-defined features we rely on and to isolate the more subtle examples in clearly marked sections of a program. A typical example of this practice is to present all dependencies on hardware sizes in the form of constants and type definitions in some header file. To support such techniques, the standard library provides numeric_limits (§40.2). Many assumptions about implementation-defined features can be checked by stating them as static assertions (§2.4.3.3). For example:

static_assert(4<=sizeof(int),"sizeof(int) too small");

Undefined behavior is nastier. A construct is deemed undefined by the standard if no reasonable behavior is required by an implementation. Typically, some obvious implementation technique will cause a program using an undefined feature to behave very badly. For example:

const int size = 4*1024;
char page[size];

void f()
{
     page[size+size] = 7; // undefined
}

Plausible outcomes of this code fragment include overwriting unrelated data and triggering a hardware error/exception. An implementation is not required to choose among plausible outcomes. Where powerful optimizers are used, the actual effects of undefined behavior can become quite unpredictable. If a set of plausible and easily implementable alternatives exist, a feature is deemed unspecified or implementation-defined rather than undefined.

It is worth spending considerable time and effort to ensure that a program does not use something deemed unspecified or undefined by the standard. In many cases, tools exist to help do this.

6.1.1. Implementations

A C++ implementation can be either hosted or freestanding (§iso.17.6.1.3). A hosted implementation includes all the standard-library facilities as described in the standard (§30.2) and in this book. A freestanding implementation may provide fewer standard-library facilities, as long as the following are provided:

Freestanding implementations are meant for code running with only the most minimal operating system support. Many implementations also provide a (non-standard) option for not using exceptions for really minimal, close-to-the-hardware, programs.

6.1.2. The Basic Source Character Set

The C++ standard and the examples in this book are written using the basic source character set consisting of the letters, digits, graphical characters, and whitespace characters from the U.S. variant of the international 7-bit character set ISO 646-1983 called ASCII (ANSI3.4-1968). This can cause problems for people who use C++ in an environment with a different character set:

• ASCII contains punctuation characters and operator symbols (such as ], {, and !) that are not available in some character sets.

• We need a notation for characters that do not have a convenient character representation (such as newline and “the character with value 17”).

• ASCII doesn’t contain characters (such as ñ, þ, and Æ) that are used for writing languages other than English.

To use an extended character set for source code, a programming environment can map the extended character set into the basic source character set in one of several ways, for example, by using universal character names (§6.2.3.2).

6.2. Types

Consider:

x = y+f(2);

For this to make sense in a C++ program, the names x, y, and f must be suitably declared. That is, the programmer must specify that entities named x, y, and f exist and that they are of types for which = (assignment), + (addition), and () (function call), respectively, are meaningful.

Every name (identifier) in a C++ program has a type associated with it. This type determines what operations can be applied to the name (that is, to the entity referred to by the name) and how such operations are interpreted. For example:

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float x;            // x is a floating-point variable
int y = 7;          // y is an integer variable with the initial value 7
float f(int);       // f is a function taking an argument of type int and returning a floating-point number

These declarations would make the example meaningful. Because y is declared to be an int, it can be assigned to, used as an operand for +, etc. On the other hand, f is declared to be a function that takes an int as its argument, so it can be called given the interger 2.

This chapter presents fundamental types (§6.2.1) and declarations (§6.3). Its examples just demonstrate language features; they are not intended to do anything useful. More extensive and realistic examples are saved for later chapters. This chapter simply provides the most basic elements from which C++ programs are constructed. You must know these elements, plus the terminology and simple syntax that go with them, in order to complete a real project in C++ and especially to read code written by others. However, a thorough understanding of every detail mentioned in this chapter is not a requirement for understanding the following chapters. Consequently, you may prefer to skim through this chapter, observing the major concepts, and return later as the need for understanding more details arises.

6.2.1. Fundamental Types

C++ has a set of fundamental types corresponding to the most common basic storage units of a computer and the most common ways of using them to hold data:

§6.2.2 A Boolean type (bool)

§6.2.3 Character types (such as char and wchar_t)

§6.2.4 Integer types (such as int and long long)

§6.2.5 Floating-point types (such as double and long double)

§6.2.7 A type, void, used to signify the absence of information

From these types, we can construct other types using declarator operators:

§7.2 Pointer types (such as int*)

§7.3 Array types (such as char[])

§7.7 Reference types (such as double& and vector<int>&&)

In addition, a user can define additional types:

§8.2 Data structures and classes (Chapter 16)

§8.4 Enumeration types for representing specific sets of values (enum and enum class)

The Boolean, character, and integer types are collectively called integral types. The integral and floating-point types are collectively called arithmetic types. Enumerations and classes (Chapter 16) are called user-defined types because they must be defined by users rather than being available for use without previous declaration, the way fundamental types are. In contrast, fundamental types, pointers, and references are collectively referred to as built-in types. The standard library provides many user-defined types (Chapter 4, Chapter 5).

The integral and floating-point types are provided in a variety of sizes to give the programmer a choice of the amount of storage consumed, the precision, and the range available for computations (§6.2.8). The assumption is that a computer provides bytes for holding characters, words for holding and computing integer values, some entity most suitable for floating-point computation, and addresses for referring to those entities. The C++ fundamental types together with pointers and arrays present these machine-level notions to the programmer in a reasonably implementation-independent manner.

For most applications, we could use bool for logical values, char for characters, int for integer values, and double for floating-point values. The remaining fundamental types are variations for optimizations, special needs, and compatibility that are best ignored until such needs arise.

6.2.2. Booleans

A Boolean, bool, can have one of the two values true or false. A Boolean is used to express the results of logical operations. For example:

void f(int a, int b)
{
     bool b1 {a==b};
     // ...
}

If a and b have the same value, b1 becomes true; otherwise, b1 becomes false.

A common use of bool is as the type of the result of a function that tests some condition (a predicate). For example:

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bool is_open(File*);

bool greater(int a, int b) { return a>b; }

By definition, true has the value 1 when converted to an integer and false has the value 0. Conversely, integers can be implicitly converted to bool values: nonzero integers convert to true and 0 converts to false. For example:

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bool b1 = 7;      // 7!=0, so b becomes true
bool b2 {7};      // error: narrowing (§2.2.2, §10.5)

int i1 = true;    // i1 becomes 1
int i2 {true};    // i2 becomes 1

If you prefer to use the {}-initializer syntax to prevent narrowing, yet still want to convert an int to a bool, you can be explicit:

void f(int i)
{
     bool b {i!=0};
     // ...
};

In arithmetic and logical expressions, bools are converted to ints; integer arithmetic and logical operations are performed on the converted values. If the result needs to be converted back to bool, a 0 is converted to false and a nonzero value is converted to true. For example:

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bool a = true;
bool b = true;

bool x = a+b;   // a+b is 2, so x becomes true
bool y = a||b;  // a||b is 1, so y becomes true ("||" means "or")
bool z = a–b;   // a-b is 0, so z becomes false

A pointer can be implicitly converted to a bool (§10.5.2.5). A non-null pointer converts to true; pointers with the value nullptr convert to false. For example:

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void g(int* p)
{
     bool b = p;              // narrows to true or false
     bool b2 {p!=nullptr};    // explicit test against nullptr

     if (p) {  // equivalent to p!=nullptr
           // ...
     }
}

I prefer if (p) over if (p!=nullptr) because it more directly expresses the notion “if p is valid” and also because it is shorter. The shorter form leaves fewer opportunities for mistakes.

6.2.3. Character Types

There are many character sets and character set encodings in use. C++ provides a variety of character types that reflect that – often bewildering – variety:

• char: The default character type, used for program text. A char is used for the implementation’s character set and is usually 8 bits.

• signed char: Like char, but guaranteed to be signed, that is, capable of holding both positive and negative values.

• unsigned char: Like char, but guaranteed to be unsigned.

• wchar_t: Provided to hold characters of a larger character set such as Unicode (see §7.3.2.2). The size of wchar_t is implementation-defined and large enough to hold the largest character set supported by the implementation’s locale (Chapter 39).

• char16_t: A type for holding 16-bit character sets, such as UTF-16.

• char32_t: A type for holding 32-bit character sets, such as UTF-32.

These are six distinct types (despite the fact that the _t suffix is often used to denote aliases; §6.5). On each implementation, the char type will be identical to that of either signed char or unsigned char, but these three names are still considered separate types.

A char variable can hold a character of the implementation’s character set. For example:

char ch = 'a';

Almost universally, a char has 8 bits so that it can hold one of 256 different values. Typically, the character set is a variant of ISO-646, for example ASCII, thus providing the characters appearing on your keyboard. Many problems arise from the fact that this set of characters is only partially standardized.

Serious variations occur between character sets supporting different natural languages and between character sets supporting the same natural language in different ways. Here, we are interested only in how such differences affect the rules of C++. The larger and more interesting issue of how to program in a multilingual, multi-character-set environment is beyond the scope of this book, although it is alluded to in several places (§6.2.3, §36.2.1, Chapter 39).

It is safe to assume that the implementation character set includes the decimal digits, the 26 alphabetic characters of English, and some of the basic punctuation characters. It is not safe to assume that:

• There are no more than 127 characters in an 8-bit character set (e.g., some sets provide 255 characters).

• There are no more alphabetic characters than English provides (most European languages provide more, e.g., æ, þ, and ß).

• The alphabetic characters are contiguous (EBCDIC leaves a gap between 'i' and 'j').

• Every character used to write C++ is available (e.g., some national character sets do not provide {, }, [, ], |, and \).

• A char fits in 1 byte. There are embedded processors without byte accessing hardware for which a char is 4 bytes. Also, one could reasonably use a 16-bit Unicode encoding for the basic chars.

Whenever possible, we should avoid making assumptions about the representation of objects. This general rule applies even to characters.

Each character has an integer value in the character set used by the implementation. For example, the value of 'b' is 98 in the ASCII character set. Here is a loop that outputs the the integer value of any character you care to input:

Click here to view code image

void intval()
{
     for (char c; cin >> c; )
           cout << "the value of '" << c << "' is " << int{c} << '\n';
}

The notation int{c} gives the integer value for a character c (“the int we can construct from c”). The possibility of converting a char to an integer raises the question: is a char signed or unsigned? The 256 values represented by an 8-bit byte can be interpreted as the values 0 to 255 or as the values –127 to 127. No, not –128 to 127 as one might expect: the C++ standard leaves open the possibility of one’s-complement hardware and that eliminates one value; thus, a use of –128 is nonportable. Unfortunately, the choice of signed or unsigned for a plain char is implementation-defined. C++ provides two types for which the answer is definite: signed char, which can hold at least the values –127 to 127, and unsigned char, which can hold at least the values 0 to 255. Fortunately, the difference matters only for values outside the 0 to 127 range, and the most common characters are within that range.

Values outside that range stored in a plain char can lead to subtle portability problems. See §6.2.3.1 if you need to use more than one type of char or if you store integers in char variables.

Note that the character types are integral types (§6.2.1) so that arithmetic and bitwise logical operations (§10.3) apply. For example:

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void digits()
{
     for (int i=0; i!=10; ++i)
           cout << static_cast<char>('0'+i);
}

This is a way of writing the ten digits to cout. The character literal '0' is converted to its integer value and i is added. The resulting int is then converted to a char and written to cout. Plain '0'+i is an int, so if I had left out the static_cast<char>, the output would have been something like 48, 49, and so on, rather than 0, 1, and so on.

6.2.3.1. Signed and Unsigned Characters

It is implementation-defined whether a plain char is considered signed or unsigned. This opens the possibility for some nasty surprises and implementation dependencies. For example:

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char c = 255; //  255 is "all ones," hexadecimal 0xFF
int i = c;

What will be the value of i? Unfortunately, the answer is undefined. On an implementation with 8-bit bytes, the answer depends on the meaning of the “all ones” char bit pattern when extended into an int. On a machine where a char is unsigned, the answer is 255. On a machine where a char is signed, the answer is –1. In this case, the compiler might warn about the conversion of the literal 255 to the char value –1. However, C++ does not offer a general mechanism for detecting this kind of problem. One solution is to avoid plain char and use the specific char types only. Unfortunately, some standard-library functions, such as strcmp(), take plain chars only (§43.4).

A char must behave identically to either a signed char or an unsigned char. However, the three char types are distinct, so you can’t mix pointers to different char types. For example:

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void f(char c, signed char sc, unsigned char uc)
{
     char* pc = &uc;               // error: no pointer conversion
     signed char* psc = pc;        // error: no pointer conversion
     unsigned char* puc = pc;      // error: no pointer conversion
     psc = puc;                    // error: no pointer conversion
}

Variables of the three char types can be freely assigned to each other. However, assigning a toolarge value to a signed char (§10.5.2.1) is still undefined. For example:

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void g(char c, signed char sc, unsigned char uc)
{
     c = 255;   // implementation-defined if plain chars are signed and have 8 bits
     c = sc;    // OK
     c = uc;    // implementation-defined if plain chars are signed and if uc's value is too large
     sc = uc;   // implementation defined if uc's value is too large
     uc = sc;   // OK: conversion to unsigned
     sc = c;    // implementation-defined if plain chars are unsigned and if c's value is too large
     uc = c;    // OK: conversion to unsigned
}

To be concrete, assume that a char is 8 bits:

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signed char sc = –160;
unsigned char uc = sc;   // uc == 116 (because 256-160==116)
cout << uc;              // print 't'

char count[256];         // assume 8-bit chars
++count[sc];             // likely disaster: out-of-range access
++count[uc];             // OK

None of these potential problems and confusions occur if you use plain char throughout and avoid negative character values.

6.2.3.2. Character Literals

A character literal is a single character enclosed in single quotes, for example, 'a' and '0'. The type of a character literal is char. A character literal can be implicitly converted to its integer value in the character set of the machine on which the C++ program is to run. For example, if you are running on a machine using the ASCII character set, the value of '0' is 48. The use of character literals rather than decimal notation makes programs more portable.

A few characters have standard names that use the backslash, \ , as an escape character:

Despite their appearance, these are single characters.

We can represent a character from the implementation character set as a one-, two-, or three-digit octal number (\ followed by octal digits) or as a hexadecimal number (\x followed by hexadecimal digits). There is no limit to the number of hexadecimal digits in the sequence. A sequence of octal or hexadecimal digits is terminated by the first character that is not an octal digit or a hexadecimal digit, respectively. For example:

This makes it possible to represent every character in the machine’s character set and, in particular, to embed such characters in character strings (see §7.3.2). Using any numeric notation for characters makes a program nonportable across machines with different character sets.

It is possible to enclose more than one character in a character literal, for example, 'ab'. Such uses are archaic, implementation-dependent, and best avoided. The type of such a multicharacter literal is int.

When embedding a numeric constant in a string using the octal notation, it is wise always to use three digits for the number. The notation is hard enough to read without having to worry about whether or not the character after a constant is a digit. For hexadecimal constants, use two digits. Consider these examples:

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char v1[] = "a\xah\129";     // 6 chars: 'a' '\xa' 'h' '\12' '9' '\0'
char v2[] = "a\xah\127";     // 5 chars: 'a' '\xa' 'h' '\127' '\0'
char v3[] = "a\xad\127";     // 4 chars: 'a' '\xad' '\127' '\0'
char v4[] = "a\xad\0127";    // 5 chars: 'a' '\xad' '\012' '7' '\0'

Wide character literals are of the form L'ab' and are of type wchar_t. The number of characters between the quotes and their meanings are implementation-defined.

A C++ program can manipulate character sets that are much richer than the 127-character ASCII set, such as Unicode. Literals of such larger character sets are presented as sequences of four or eight hexadecimal digits preceded by a U or a u. For example:

U'\UFADEBEEF'
u'\uDEAD'
u'\xDEAD'

The shorter notation u'\uXXXX' is equivalent to U'\U0000XXXX' for any hexadecimal digit X. A number of hexadecimal digits different from four or eight is a lexical error. The meaning of the hexadecimal number is defined by the ISO/IEC 10646 standard and such values are called universal character names. In the C++ standard, universal character names are described in §iso.2.2, §iso.2.3, §iso.2.14.3, §iso.2.14.5, and §iso.E.

6.2.4. Integer Types

Like char, each integer type comes in three forms: “plain” int, signed int, and unsigned int. In addition, integers come in four sizes: short int, “plain” int, long int, and long long int. A long int can be referred to as plain long, and a long long int can be referred to as plain long long. Similarly, short is a synonym for short int, unsigned for unsigned int, and signed for signed int. No, there is no long short int equivalent to int.

The unsigned integer types are ideal for uses that treat storage as a bit array. Using an unsigned instead of an int to gain one more bit to represent positive integers is almost never a good idea. Attempts to ensure that some values are positive by declaring variables unsigned will typically be defeated by the implicit conversion rules (§10.5.1, §10.5.2.1).

Unlike plain chars, plain ints are always signed. The signed int types are simply more explicit synonyms for their plain int counterparts, rather than different types.

If you need more detailed control over integer sizes, you can use aliases from <cstdint> (§43.7), such as int64_t (a signed integer with exactly 64 bits), uint_fast16_t (an unsigned integer with exactly 8 bits, supposedly the fastest such integer), and int_least32_t (a signed integer with at least 32 bits, just like plain int). The plain integer types have well-defined minimal sizes (§6.2.8), so the <cstdint> are sometimes redundant and can be overused.

In addition to the standard integer types, an implementation may provide extended integer types (signed and unsigned). These types must behave like integers and are considered integer types when considering conversions and integer literal values, but they usually have greater range (occupy more space).

6.2.4.1. Integer Literals

Integer literals come in three guises: decimal, octal, and hexadecimal. Decimal literals are the most commonly used and look as you would expect them to:

7  1234  976  12345678901234567890

The compiler ought to warn about literals that are too long to represent, but an error is only guaranteed for {} initializers (§6.3.5).

A literal starting with zero followed by x or X (0x or 0X) is a hexadecimal (base 16) number. A literal starting with zero but not followed by x or X is an octal (base 8) number. For example:

The letters a, b, c, d, e, and f, or their uppercase equivalents, are used to represent 10, 11, 12, 13, 14, and 15, respectively. Octal and hexadecimal notations are most useful for expressing bit patterns. Using these notations to express genuine numbers can lead to surprises. For example, on a machine on which an int is represented as a two’s complement 16-bit integer, 0xffff is the negative decimal number –1. Had more bits been used to represent an integer, it would have been the positive decimal number 65535.

The suffix U can be used to write explicitly unsigned literals. Similarly, the suffix L can be used to write explicitly long literals. For example, 3 is an int, 3U is an unsigned int, and 3L is a long int.

Combinations of suffixes are allowed. For example:

cout << 0xF0UL << ' ' << 0LU << '\n';

If no suffix is provided, the compiler gives an integer literal a suitable type based on its value and the implementation’s integer sizes (§6.2.4.2).

It is a good idea to limit the use of nonobvious constants to a few well-commented const (§7.5), constexpr (§10.4), and enumerator (§8.4) initializers.

6.2.4.2. Types of Integer Literals

In general, the type of an integer literal depends on its form, value, and suffix:

• If it is decimal and has no suffix, it has the first of these types in which its value can be represented: int, long int, long long int.

• If it is octal or hexadecimal and has no suffix, it has the first of these types in which its value can be represented: int, unsigned int, long int, unsigned long int, long long int, unsigned long long int.

• If it is suffixed by u or U, its type is the first of these types in which its value can be represented: unsigned int, unsigned long int, unsigned long long int.

• If it is decimal and suffixed by l or L, its type is the first of these types in which its value can be represented: long int, long long int.

• If it is octal or hexadecimal and suffixed by l or L, its type is the first of these types in which its value can be represented: long int, unsigned long int, long long int, unsigned long long int.

• If it is suffixed by ul, lu, uL, Lu, Ul, lU, UL, or LU, its type is the first of these types in which its value can be represented: unsigned long int, unsigned long long int.

• If it is decimal and is suffixed by ll or LL, its type is long long int.

• If it is octal or hexadecimal and is suffixed by ll or LL, its type is the first of these types in which its value can be represented: long long int, unsigned long long int.

• If it is suffixed by llu, llU, ull, Ull, LLu, LLU, uLL, or ULL, its type is unsigned long long int.

For example, 100000 is of type int on a machine with 32-bit ints but of type long int on a machine with 16-bit ints and 32-bit longs. Similarly, 0XA000 is of type int on a machine with 32-bit ints but of type unsigned int on a machine with 16-bit ints. These implementation dependencies can be avoided by using suffixes: 100000L is of type long int on all machines and 0XA000U is of type unsigned int on all machines.

6.2.5. Floating-Point Types

The floating-point types represent floating-point numbers. A floating-point number is an approximation of a real number represented in a fixed amount of memory. There are three floating-point types: float (single-precision), double (double-precision), and long double (extended-precision).

The exact meaning of single-, double-, and extended-precision is implementation-defined. Choosing the right precision for a problem where the choice matters requires significant understanding of floating-point computation. If you don’t have that understanding, get advice, take the time to learn, or use double and hope for the best.

6.2.5.1. Floating-Point Literals

By default, a floating-point literal is of type double. Again, a compiler ought to warn about floating-point literals that are too large to be represented. Here are some floating-point literals:

1.23  .23  0.23  1.  1.0  1.2e10  1.23e–15

Note that a space cannot occur in the middle of a floating-point literal. For example, 65.43 e–21 is not a floating-point literal but rather four separate lexical tokens (causing a syntax error):

65.43 e – 21

If you want a floating-point literal of type float, you can define one using the suffix f or F:

3.14159265f  2.0f  2.997925F  2.9e–3f

If you want a floating-point literal of type long double, you can define one using the suffix l or L:

3.14159265L  2.0L  2.997925L  2.9e–3L

6.2.6. Prefixes and Suffixes

There is a minor zoo of suffixes indicating types of literals and also a few prefixes:

Note that “string” here means “string literal” (§7.3.2) rather than “of type std::string.”

Obviously, we could also consider . and e as infix and R" and u8" as the first part of a set of delimiters. However, I consider the nomenclature less important than giving an overview of the bewildering variety of literals.

The suffixes l and L can be combined with the suffixes u and U to express unsigned long types. For example:

1LU       // unsigned long
2UL       // unsigned long
3ULL      // unsigned long long
4LLU      // unsigned long long
5LUL      // error

The suffixes l and L can be used for floating-point literals to express long double. For example:

1L        // long int
1.0L      // long double

Combinations of R, L, and u prefixes are allowed, for example, uR"**(foo\(bar))**". Note the dramatic difference in the meaning of a U prefix for a character (unsigned) and for a string UTF-32 encoding (§7.3.2.2).

In addition, a user can define new suffixes for user-defined types. For example, by defining a user-defined literal operator (§19.2.6), we can get

Click here to view code image

"foo bar"s     // a literal of type std::string
123_km         // a literal of type Distance

Suffixes not starting with _ are reserved for the standard library.

6.2.7. void

The type void is syntactically a fundamental type. It can, however, be used only as part of a more complicated type; there are no objects of type void. It is used either to specify that a function does not return a value or as the base type for pointers to objects of unknown type. For example:

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void x;      // error: there are no void objects
void& r;     // error: there are no references to void
void f();    // function f does not return a value (§12.1.4)
void* pv;    // pointer to object of unknown type (§7.2.1)

When declaring a function, you must specify the type of the value returned. Logically, you would expect to be able to indicate that a function didn’t return a value by omitting the return type. However, that would make a mess of the grammar (§iso.A). Consequently, void is used as a “pseudo return type” to indicate that a function doesn’t return a value.

6.2.8. Sizes

Some of the aspects of C++’s fundamental types, such as the size of an int, are implementation-defined (§6.1). I point out these dependencies and often recommend avoiding them or taking steps to minimize their impact. Why should you bother? People who program on a variety of systems or use a variety of compilers care a lot because if they don’t, they are forced to waste time finding and fixing obscure bugs. People who claim they don’t care about portability usually do so because they use only a single system and feel they can afford the attitude that “the language is what my compiler implements.” This is a narrow and shortsighted view. If your program is a success, it will be ported, so someone will have to find and fix problems related to implementation-dependent features. In addition, programs often need to be compiled with other compilers for the same system, and even a future release of your favorite compiler may do some things differently from the current one. It is far easier to know and limit the impact of implementation dependencies when a program is written than to try to untangle the mess afterward.

It is relatively easy to limit the impact of implementation-dependent language features. Limiting the impact of system-dependent library facilities is far harder. Using standard-library facilities wherever feasible is one approach.

The reason for providing more than one integer type, more than one unsigned type, and more than one floating-point type is to allow the programmer to take advantage of hardware characteristics. On many machines, there are significant differences in memory requirements, memory access times, and computation speed among the different varieties of fundamental types. If you know a machine, it is usually easy to choose, for example, the appropriate integer type for a particular variable. Writing truly portable low-level code is harder.

Here is a graphical representation of a plausible set of fundamental types and a sample string literal (§7.3.2):

On the same scale (.2 inch to a byte), a megabyte of memory would stretch about 3 miles (5 km) to the right.

Sizes of C++ objects are expressed in terms of multiples of the size of a char, so by definition the size of a char is 1. The size of an object or type can be obtained using the sizeof operator (§10.3). This is what is guaranteed about sizes of fundamental types:

• 1 ≡ sizeof(char) ≤ sizeof(short) ≤ sizeof(int) ≤ sizeof(long) ≤ sizeof(long long)

• 1 ≤ sizeof(bool) ≤ sizeof(long)

• sizeof(char) ≤ sizeof(wchar_t) ≤ sizeof(long)

• sizeof(float) ≤ sizeof(double) ≤ sizeof(long double)

• sizeof(N) ≡ sizeof(signed N) ≡ sizeof(unsigned N)

In that last line, N can be char, short, int, long, or long long. In addition, it is guaranteed that a char has at least 8 bits, a short at least 16 bits, and a long at least 32 bits. A char can hold a character of the machine’s character set. The char type is supposed to be chosen by the implementation to be the most suitable type for holding and manipulating characters on a given computer; it is typically an 8-bit byte. Similarly, the int type is supposed to be chosen to be the most suitable for holding and manipulating integers on a given computer; it is typically a 4-byte (32-bit) word. It is unwise to assume more. For example, there are machines with 32-bit chars. It is extremely unwise to assume that the size of an int is the same as the size of a pointer; many machines (“64-bit architectures”) have pointers that are larger than integers. Note that it is not guaranteed that sizeof(long)<sizeof(long long) or that sizeof(double)<sizeof(long double).

Some implementation-defined aspects of fundamental types can be found by a simple use of sizeof, and more can be found in <limits>. For example:

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#include <limits>  // §40.2
#include <iostream>

int main()
{
     cout << "size of long " << sizeof(1L) << '\n';
     cout << "size of long long " << sizeof(1LL) << '\n';

     cout << "largest float == " << std::numeric_limits<float>::max() << '\n';
     cout << "char is signed == " << std::numeric_limits<char>::is_signed << '\n';
}

The functions in <limits> (§40.2) are constexpr (§10.4) so that they can be used without run-time overhead and in contexts that require a constant expression.

The fundamental types can be mixed freely in assignments and expressions. Wherever possible, values are converted so as not to lose information (§10.5).

If a value v can be represented exactly in a variable of type T, a conversion of v to T is value-preserving. Conversions that are not value-preserving are best avoided (§2.2.2, §10.5.2.6).

If you need a specific size of integer, say, a 16-bit integer, you can #include the standard header <cstdint> that defines a variety of types (or rather type aliases; §6.5). For example:

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int16_t x {0xaabb};                 // 2 bytes
int64_t xxxx {0xaaaabbbbccccdddd};  // 8 bytes
int_least16_t y;                    // at least 2 bytes (just like int)
int_least32_t yy                    // at least 4 bytes (just like long)
int_fast32_t z;                     // the fastest int type with at least 4 bytes

The standard header <cstddef> defines an alias that is very widely used in both standard-library declarations and user code: size_t is an implementation-defined unsigned integer type that can hold the size in bytes of every object. Consequently, it is used where we need to hold an object size. For example:

void* allocate(size_t n);    // get n bytes

Similarly, <cstddef> defines the signed integer type ptrdiff_t for holding the result of subtracting two pointers to get a number of elements.

6.2.9. Alignment

An object doesn’t just need enough storage to hold its representation. In addition, on some machine architectures, the bytes used to hold it must have proper alignment for the hardware to access it efficiently (or in extreme cases to access it at all). For example, a 4-byte int often has to be aligned on a word (4-byte) boundary, and sometimes an 8-byte double has to be aligned on a word (8-byte) boundary. Of course, this is all very implementation specific, and for most programmers completely implicit. You can write good C++ code for decades without needing to be explicit about alignment. Where alignment most often becomes visible is in object layouts: sometimes structs contain “holes” to improve alignment (§8.2.1).

The alignof() operator returns the alignment of its argument expression. For example:

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auto ac = alignof('c');    // the alignment of a char
auto ai = alignof(1);      // the alignment of an int
auto ad = alignof(2.0);    // the alignment of a double

int a[20];
auto aa = alignof(a);      // the alignment of an int

Sometimes, we have to use alignment in a declaration, where an expression, such as alignof(x+y) is not allowed. Instead, we can use the type specifier alignas: alignas(T) means “align just like a T.” For example, we can set aside uninitialized storage for some type X like this:

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void user(const vector<X>& vx)
{
     constexpr int bufmax = 1024;
     alignas(X) buffer[bufmax];  // uninitialized

     const int max = min(vx.size(),bufmax/sizeof(X));
     uninitialized_copy(vx.begin(),vx.begin()+max,buffer);
     // ...
}

6.3. Declarations

Before a name (identifier) can be used in a C++ program, it must be declared. That is, its type must be specified to inform the compiler what kind of entity the name refers to. For example:

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char ch;
string s;
auto count = 1;
const double pi {3.1415926535897};
extern int error_number;

const char* name = "Njal";
const char* season[] = { "spring", "summer", "fall", "winter" };
vector<string> people { name, "Skarphedin", "Gunnar" };

struct Date
{ int d, m, y; }; int day(Date* p) { return p–>d; }
double sqrt(double);
template<class T> T abs(T a) { return a<0 ? –a: a; }

constexpr int fac(int n) { return (n<2)?1:n* fac(n–1); }   // possible compile-time evaluation (§2.2.3)
constexpr double zz { ii*fac(7) };                         // compile-time initialization

using Cmplx = std::complex<double>;                        // type alias (§3.4.5, §6.5)
struct User;                                               // type name
enum class Beer { Carlsberg, Tuborg, Thor };
namespace NS { int a; }

As can be seen from these examples, a declaration can do more than simply associate a type with a name. Most of these declarations are also definitions. A definition is a declaration that supplies all that is needed in a program for the use of an entity. In particular, if it takes memory to represent something, that memory is set aside by its definition. A different terminology deems declarations parts of an interface and definitions parts of an implementation. When taking that view, we try to compose interfaces out of declarations that can be replicated in separate files (§15.2.2); definitions that set aside memory do not belong in interfaces.

Assuming that these declarations are in the global scope (§6.3.4), we have:

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char ch;                               // set aside memory for a char and initialize it to 0
auto count = 1;                        // set aside memory for an int initialized to 1
const char* name = "Njal";             // set aside memory for a pointer to char
                                       // set aside memory for a string literal "Njal"
                                       // initialize the pointer with the address of that string literal

struct Date { int d, m, y; };          // Date is a struct with three members
int day(Date* p) { return p–>d; }      // day is a function that executes the specified code

using Point = std::complex<short>;// Point is a name for std::complex<short>

Of the declarations above, only three are not also definitions:

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double sqrt(double);          // function declaration
extern int error_number;      // variable declaration
struct User;                  // type name declaration

That is, if used, the entity they refer to must be defined elsewhere. For example:

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double sqrt(double d) { /* ... */ }
int error_number = 1;
struct User { /* ... */ };

There must always be exactly one definition for each name in a C++ program (for the effects of #include, see §15.2.3). However, there can be many declarations.

All declarations of an entity must agree on its type. So, this fragment has two errors:

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int count;
int count;       // error: redefinition
extern int error_number;
extern short error_number;      // error: type mismatch

This has no errors (for the use of extern, see §15.2):

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extern int error_number;
extern int error_number; // OK: redeclaration

Some definitions explicitly specify a “value” for the entities they define. For example:

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struct Date { int d, m, y; };
using Point = std::complex<short>;     // Point is a name for std::complex<short>
int day(Date* p) { return p–>d; }
const double pi {3.1415926535897};

For types, aliases, templates, functions, and constants, the “value” is permanent. For non-const data types, the initial value may be changed later. For example:

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void f()
{
     int count {1};                // initialize count to 1
     const char* name {"Bjarne"};  // name is a variable that points to a constant (§7.5)
     count = 2;                    // assign 2 to count
     name = "Marian";
}

Of the definitions, only two do not specify values:

char ch;
string s;

See §6.3.5 and §17.3.3 for explanations of how and when a variable is assigned a default value. Any declaration that specifies a value is a definition.

6.3.1. The Structure of Declarations

The structure of a declaration is defined by the C++ grammar (§iso.A). This grammar evolved over four decades, starting with the early C grammars, and is quite complicated. However, without too many radical simplifications, we can consider a declaration as having five parts (in order):

• Optional prefix specifiers (e.g., static or virtual)

• A base type (e.g., vector<double> or const int)

• A declarator optionally including a name (e.g., p[7], n, or *(*)[])

• Optional suffix function specifiers (e.g., const or noexcept)

• An optional initializer or function body (e.g., ={7,5,3} or {return x;})

Except for function and namespace definitions, a declaration is terminated by a semicolon. Consider a definition of an array of C-style strings:

const char* kings[] = { "Antigonus", "Seleucus", "Ptolemy" };

Here, the base type is const char, the declarator is * kings[], and the initializer is the = followed by the {}-list.

A specifier is an initial keyword, such as virtual (§3.2.3, §20.3.2), extern (§15.2), or constexpr (§2.2.3), that specifies some non-type attribute of what is being declared.

A declarator is composed of a name and optionally some declarator operators. The most common declarator operators are:

Their use would be simple if they were all either prefix or postfix. However, *, [], and () were designed to mirror their use in expressions (§10.3). Thus, * is prefix and [] and () are postfix. The postfix declarator operators bind tighter than the prefix ones. Consequently, char*kings[] is an array of pointers to char, whereas char(*kings)[] is a pointer to an array of char. We have to use parentheses to express types such as “pointer to array” and “pointer to function”; see the examples in §7.2.

Note that the type cannot be left out of a declaration. For example:

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const c = 7;     // error: no type

gt(int a, int b) // error: no return type
{
     return (a>b) ? a : b;
}

unsigned ui;     // OK: "unsigned" means"unsigned int"
long li;         // OK: "long" means "long int"

In this, standard C++ differs from early versions of C and C++ that allowed the first two examples by considering int to be the type when none was specified (§44.3). This “implicit int” rule was a source of subtle errors and much confusion.

Some types have names composed out of multiple keywords, such as long long and volatile int. Some type names don’t even look much like names, such as decltype(f(x)) (the return type of a call f(x); §6.3.6.3).

The volatile specifier is described in §41.4.

The alignas() specifier is described in §6.2.9.

6.3.2. Declaring Multiple Names

It is possible to declare several names in a single declaration. The declaration simply contains a list of comma-separated declarators. For example, we can declare two integers like this:

int x, y;       // int x; int y;

Operators apply to individual names only – and not to any subsequent names in the same declaration. For example:

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int* p, y;       // int* p; int y;  NOT int* y;
int x, *q;       // int x; int* q;
int v[10], *pv;  // int v[10]; int* pv;

Such declarations with multiple names and nontrivial declarators make a program harder to read and should be avoided.

6.3.3. Names

A name (identifier) consists of a sequence of letters and digits. The first character must be a letter. The underscore character, _, is considered a letter. C++ imposes no limit on the number of characters in a name. However, some parts of an implementation are not under the control of the compiler writer (in particular, the linker), and those parts, unfortunately, sometimes do impose limits. Some run-time environments also make it necessary to extend or restrict the set of characters accepted in an identifier. Extensions (e.g., allowing the character $ in a name) yield nonportable programs. A C++ keyword (§6.3.3.1), such as new or int, cannot be used as a name of a user-defined entity. Examples of names are:

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hello      this_is_a_most_unusually_long_identifier_that_is_better_avoided
DEFINED    foO       bAr          u_name          HorseSense
var0       var1      CLASS        _class          ___

Examples of character sequences that cannot be used as identifiers are:

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012          a fool      $sys      class      3var
pay.due      foo~bar     .name     if

Nonlocal names starting with an underscore are reserved for special facilities in the implementation and the run-time environment, so such names should not be used in application programs. Similarly, names starting with a double underscore (__) or an underscore followed by an uppercase letter (e.g., _Foo) are reserved (§iso.17.6.4.3).

When reading a program, the compiler always looks for the longest string of characters that could make up a name. Hence, var10 is a single name, not the name var followed by the number 10. Also, elseif is a single name, not the keyword else followed by the keyword if.

Uppercase and lowercase letters are distinct, so Count and count are different names, but it is often unwise to choose names that differ only by capitalization. In general, it is best to avoid names that differ only in subtle ways. For example, in some fonts, the uppercase “o” (O) and zero (0) can be hard to tell apart, as can the lowercase “L” (l), uppercase “i” (I), and one (1). Consequently, l0, lO, l1, ll, and I1l are poor choices for identifier names. Not all fonts have the same problems, but most have some.

Names from a large scope ought to have relatively long and reasonably obvious names, such as vector, Window_with_border, and Department_number. However, code is clearer if names used only in a small scope have short, conventional names such as x, i, and p. Functions (Chapter 12), classes (Chapter 16), and namespaces (§14.3.1) can be used to keep scopes small. It is often useful to keep frequently used names relatively short and reserve really long names for infrequently used entities.

Choose names to reflect the meaning of an entity rather than its implementation. For example, phone_book is better than number_vector even if the phone numbers happen to be stored in a vector (§4.4). Do not encode type information in a name (e.g., pcname for a name that’s a char* or icount for a count that’s an int) as is sometimes done in languages with dynamic or weak type systems:

• Encoding types in names lowers the abstraction level of the program; in particular, it prevents generic programming (which relies on a name being able to refer to entities of different types).

• The compiler is better at keeping track of types than you are.

• If you want to change the type of a name (e.g., use a std::string to hold the name), you’ll have to change every use of the name (or the type encoding becomes a lie).

• Any system of type abbreviations you can come up with will become overelaborate and cryptic as the variety of types you use increases.

Choosing good names is an art.

Try to maintain a consistent naming style. For example, capitalize names of user-defined types and start names of non-type entities with a lowercase letter (for example, Shape and current_token). Also, use all capitals for macros (if you must use macros (§12.6); for example, HACK) and never for non-macros (not even for non-macro constants). Use underscores to separate words in an identifier; number_of_elements is more readable than numberOfElements. However, consistency is hard to achieve because programs are typically composed of fragments from different sources and several different reasonable styles are in use. Be consistent in your use of abbreviations and acronyms. Note that the language and the standard library use lowercase for types; this can be seen as a hint that they are part of the standard.

6.3.3.1. Keywords

The C++ keywords are:

In addition, the word export is reserved for future use.

6.3.4. Scope

A declaration introduces a name into a scope; that is, a name can be used only in a specific part of the program text.

• Local scope: A name declared in a function (Chapter 12) or lambda (§11.4) is called a local name. Its scope extends from its point of declaration to the end of the block in which its declaration occurs. A block is a section of code delimited by a {} pair. Function and lambda parameter names are considered local names in the outermost block of their function or lambda.

• Class scope: A name is called a member name (or a class member name) if it is defined in a class outside any function, class (Chapter 16), enum class (§8.4.1), or other namespace. Its scope extends from the opening { of the class declaration to the end of the class declaration.

• Namespace scope: A name is called a namespace member name if it is defined in a namespace (§14.3.1) outside any function, lambda (§11.4), class (Chapter 16), enum class (§8.4.1), or other namespace. Its scope extends from the point of declaration to the end of its namespace. A namespace name may also be accessible from other translation units (§15.2).

• Global scope: A name is called a global name if it is defined outside any function, class (Chapter 16), enum class (§8.4.1), or namespace (§14.3.1). The scope of a global name extends from the point of declaration to the end of the file in which its declaration occurs. A global name may also be accessible from other translation units (§15.2). Technically, the global namespace is considered a namespace, so a global name is an example of a namespace member name.

• Statement scope: A name is in a statement scope if it is defined within the () part of a for-, while-, if-, or switch-statement. Its scope extends from its point of declaration to the end of its statement. All names in statement scope are local names.

• Function scope: A label (§9.6) is in scope from its point of declaration until the end of the function.

A declaration of a name in a block can hide a declaration in an enclosing block or a global name. That is, a name can be redefined to refer to a different entity within a block. After exit from the block, the name resumes its previous meaning. For example:

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int x;              // global x

void f()
{
     int x;         // local x hides global x
     x = 1;         // assign to local x
     {
          int x;    // hides first local x
          x = 2;    // assign to second local x
     }
     x = 3;         // assign to first local x
}

int* p = & x;       // take address of global x

Hiding names is unavoidable when writing large programs. However, a human reader can easily fail to notice that a name has been hidden (also known as shadowed). Because such errors are relatively rare, they can be very difficult to find. Consequently, name hiding should be minimized. Using names such as i and x for global variables or for local variables in a large function is asking for trouble.

A hidden global name can be referred to using the scope resolution operator, ::. For example:

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int x;

void f2()
{
     int x = 1; // hide global x
     ::x = 2;   // assign to global x
     x = 2;     // assign to local x
     // ...
}

There is no way to use a hidden local name.

The scope of a name that is not a class member starts at its point of declaration, that is, after the complete declarator and before the initializer. This implies that a name can be used even to specify its own initial value. For example:

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int x = 97;

void f3()
{
     int x = x;     // perverse: initialize x with its own (uninitialized) value
}

A good compiler warns if a variable is used before it has been initialized.

It is possible to use a single name to refer to two different objects in a block without using the :: operator. For example:

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int x = 11;

void f4()           // perverse: use of two different objects both called x in a single scope
{
     int y = x;     // use global x: y = 11
     int x = 22;
     y = x;         // use local x: y = 22
}

Again, such subtleties are best avoided.

The names of function arguments are considered declared in the outermost block of a function. For example:

void f5(int x)
{
     int x;     // error
}

This is an error because x is defined twice in the same scope.

Names introduced in a for-statement are local to that statement (in statement scope). This allows us to use conventional names for loop variables repeatedly in a function. For example:

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void f(vector<string>& v, list<int>& lst)
{
     for (const auto& x : v) cout << x << '\n';
     for (auto x : lst) cout << x << '\n';
     for (int i = 0, i!=v.size(), ++i) cout << v[i] << '\n';
     for (auto i : {1, 2, 3, 4, 5, 6, 7}) cout << i << '\n';
}

This contains no name clashes.

A declaration is not allowed as the only statement on the branch of an if-statement (§9.4.1).

6.3.5. Initialization

If an initializer is specified for an object, that initializer determines the initial value of an object. An initializer can use one of four syntactic styles:

X a1 {v};
X a2 = {v};
X a3 = v;
X a4(v);

Of these, only the first can be used in every context, and I strongly recommend its use. It is clearer and less error-prone than the alternatives. However, the first form (used for a1) is new in C++11, so the other three forms are what you find in older code. The two forms using = are what you use in C. Old habits die hard, so I sometimes (inconsistently) use = when initializing a simple variable with a simple value. For example:

int x1 = 0;
char c1 = 'z';

However, anything much more complicated than that is better done using {}. Initialization using {}, list initialization, does not allow narrowing (§iso.8.5.4). That is:

• An integer cannot be converted to another integer that cannot hold its value. For example, char to int is allowed, but not int to char.

• A floating-point value cannot be converted to another floating-point type that cannot hold its value. For example, float to double is allowed, but not double to float.

• A floating-point value cannot be converted to an integer type.

• An integer value cannot be converted to a floating-point type.

For example:

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void f(double val, int val2)
{
     int x2 = val;        // if val==7.9, x2 becomes 7
     char c2 = val2;      // if val2==1025, c2 becomes 1

     int x3 {val};        // error: possible truncation
     char c3 {val2};      // error: possible narrowing

     char c4 {24};        // OK: 24 can be represented exactly as a char
     char c5 {264};       // error (assuming 8-bit chars): 264 cannot be represented as a char

     int x4 {2.0};        // error: no double to int value conversion

     // ...
}

See §10.5 for the conversion rules for built-in types.

There is no advantage to using {} initialization, and one trap, when using auto to get the type determined by the initializer. The trap is that if the initializer is a {}-list, we may not want its type deduced (§6.3.6.2). For example:

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auto z1 {99};   // z1 is an initializer_list<int>
auto z2 = 99;   // z2 is an int

So prefer = when using auto.

It is possible to define a class so that an object can be initialized by a list of values and alternatively be constructed given a couple of arguments that are not simply values to be stored. The classical example is a vector of integers:

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vector<int> v1 {99};    // v1 is a vector of 1 element with the value 99
vector<int> v2(99);     // v2 is a vector of 99 elements each with the default value 0

I use the explicit invocation of a constructor, (99), to get the second meaning. Most types do not offer such confusing alternatives – even most vectors do not; for example:

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vector<string> v1{"hello!"};      // v1 is a vector of 1 element with the value "hello!"
vector<string> v2("hello!");      // error: no vector constructor takes a string literal

So, prefer {} initialization over alternatives unless you have a strong reason not to.

The empty initializer list, {}, is used to indicate that a default value is desired. For example:

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int x4 {};          // x4 becomes 0
double d4 {};       // d4 becomes 0.0
char* p {};         // p becomes nullptr
vector<int> v4{};   // v4 becomes the empty vector
string s4 {};       // s4 becomes ""

Most types have a default value. For integral types, the default value is a suitable representation of zero. For pointers, the default value is nullptr (§7.2.2). For user-defined types, the default value (if any) is determined by the type’s constructors (§17.3.3).

For user-defined types, there can be a distinction between direct initialization (where implicit conversions are allowed) and copy initialization (where they are not); see §16.2.6.

Initialization of particular kinds of objects is discussed where appropriate:

• Pointers: §7.2.2, §7.3.2, §7.4

• References: §7.7.1 (lvalues), §7.7.2 (rvalues)

• Arrays: §7.3.1, §7.3.2

• Constants: §10.4

• Classes: §17.3.1 (not using constructors), §17.3.2 (using constructors), §17.3.3 (default), §17.4 (member and base), §17.5 (copy and move)

• User-defined containers: §17.3.4

6.3.5.1. Missing Initializers

For many types, including all built-in types, it is possible to leave out the initializer. If you do that – and that has unfortunately been common – the situation is more complicated. If you don’t like the complications, just initialize consistently. The only really good case for an uninitialized variable is a large input buffer. For example:

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constexpr int max = 1024*1024;
char buf[max];
some_stream.get(buf,max);    // read at most max characters into buf

We could easily have initialized buf:

char buf[max] {};     // initialize every char to 0

By redundantly initializing, we would have suffered a performance hit which just might have been significant. Avoid such low-level use of buffers where you can, and don’t leave such buffers uninitialized unless you know (e.g., from measurement) that the optimization compared to using an initialized array is significant.

If no initializer is specified, a global (§6.3.4), namespace (§14.3.1), local static (§12.1.8), or static member (§16.2.12) (collectively called static objects) is initialized to {} of the appropriate type. For example:

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int a;     // means "int a{};" so that a becomes 0
double d;  // means "double d{};" so that d becomes 0.0

Local variables and objects created on the free store (sometimes called dynamic objects or heap objects; §11.2) are not initialized by default unless they are of user-defined types with a default constructor (§17.3.3). For example:

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void f()
{
     int x;                      // x does not have a well-defined value
     char buf[1024];             // buf[i] does not have a well-defined value

     int* p {new int};           // *p does not have a well-defined value
     char* q {new char[1024]};   // q[i] does not have a well-defined value

     string s;                   // s=="" because of string's default constructor
     vector<char> v;             // v=={} because of vector's default constructor

     string* ps {new string};    // *ps is "" because of string's default constructor
     // ...
}

If you want initialization of local variables of built-in type or objects of built-in type created with new, use {}. For example:

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void ff()
{
     int x {};                     // x becomes 0
     char buf[1024]{};             // buf[i] becomes 0 for all i

     int* p {new int{10}};         // *p becomes 10
     char* q {new char[1024]{}};   // q[i] becomes 0 for all i

     // ...
}

A member of an array or a class is default initialized if the array or structure is.

6.3.5.2. Initializer Lists

So far, we have considered the cases of no initializer and one initializer value. More complicated objects can require more than one value as an initializer. This is primarily handled by initializer lists delimited by { and }. For example:

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int a[] = { 1, 2 };                         // array initializer
struct S { int x, string s };
S s = { 1, "Helios" };                      // struct initializer
complex<double> z = { 0, pi };              // use constructor
vector<double> v = { 0.0, 1.1, 2.2, 3.3 };  // use list constructor

For C-style initialization of arrays, see §7.3.1. For C-style structures, see §8.2. For user-defined types with constructors, see §2.3.2 or §16.2.5. For initializer-list constructors, see §17.3.4.

In the cases above, the = is redundant. However, some prefer to add it to emphasize that a set of values are used to initialize a set of member variables.

In some cases, function-style argument lists can also be used (§2.3, §16.2.5). For example:

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complex<double> z(0,pi);      // use constructor
vector<double> v(10,3.3);     // use constructor: v gets 10 elements initialized to 3.3

In a declaration, an empty pair of parentheses, (), always means “function” (§12.1). So, if you want to be explicit about “use default initialization” you need {}. For example:

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complex<double> z1(1,2);        // function-style initializer (initialization by constructor)
complex<double> f1();           // function declaration

complex<double> z2 {1,2};       // initialization by constructor to {1,2}
complex<double> f2 {};          // initialization by constructor to the default value {0,0}

Note that initialization using the {} notation does not narrow (§6.3.5).

When using auto, a {}-list has its type deduced to std::initializer_list<T>. For example:

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auto x1 {1,2,3,4};          // x1 is an initializer_list<int>
auto x2 {1.0, 2.25, 3.5 };  // x2 is an initializer_list of<double>
auto x3 {1.0,2};            // error: cannot deduce the type of {1.0,2} (§6.3.6.2)

6.3.6. Deducing a Type: auto and decltype()

The language provides two mechanisms for deducing a type from an expression:

• auto for deducing a type of an object from its initializer; the type can be the type of a variable, a const, or a constexpr.

• decltype(expr) for deducing the type of something that is not a simple initializer, such as the return type for a function or the type of a class member.

The deduction done here is very simple: auto and decltype() simply report the type of an expression already known to the compiler.

6.3.6.1. The auto Type Specifier

When a declaration of a variable has an initializer, we don’t need to explicitly specify a type. Instead, we can let the variable have the type of its initializer. Consider:

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int a1 = 123;
char a2 = 123;
auto a3 = 123;  // the type of a3 is "int"

The type of the integer literal 123 is int, so a3 is an int. That is, auto is a placeholder for the type of the initializer.

There is not much advantage in using auto instead of int for an expression as simple as 123. The harder the type is to write and the harder the type is to know, the more useful auto becomes. For example:

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template<class T> void f1(vector<T>& arg)
{
     for (vector<T>::iterator p = arg.begin(); p!=arg.end(); ++p)
          *p = 7;

     for (auto p = arg.begin(); p!=arg.end(); ++p)
          *p = 7;
}

The loop using auto is the more convenient to write and the easier to read. Also, it is more resilient to code changes. For example, if I changed arg to be a list, the loop using auto would still work correctly whereas the first loop would need to be rewritten. So, unless there is a good reason not to, use auto in small scopes.

If a scope is large, mentioning a type explicitly can help localize errors. That is, compared to using a specific type, using auto can delay the detection of type errors. For example:

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void f(double d)
{
     constexpr auto max = d+7;
     int a[max];       // error: array bound not an integer
     // ...
}

If auto causes surprises, the best cure is typically to make functions smaller, which most often is a good idea anyway (§12.1).

We can decorate a deduced type with specifiers and modifiers (§6.3.1), such as const and & (reference; §7.7). For example:

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void f(vector<int>& v)
{
     for (const auto& x : v) { // x is a const int&
           // ...
     }
}

Here, auto is determined by the element type of v, that is, int.

Note that the type of an expression is never a reference because references are implicitly dereferenced in expressions (§7.7). For example:

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void g(int& v)
{
     auto x = v;    // x is an int (not an int&)
     auto& y = v;   // y is an int&
}

6.3.6.2. auto and {}-lists

When we explicitly mention the type of an object we are initializing, we have two types to consider: the type of the object and the type of the initializer. For example:

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char v1 = 12345;     // 12345 is an int
int v2 = 'c';        // 'c' is a char
T v3 = f();

By using the {}-initializer syntax for such definitions, we minimize the chances for unfortunate conversions:

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char v1 {12345};     // error: narrowing
int v2 {'c'};        // fine: implicit char->int conversion
T v3 {f()};          // works if and only if the type of f() can be implicitly converted to a T

When we use auto, there is only one type involved, the type of the initializer, and we can safely use the = syntax:

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auto v1 = 12345;      // v1 is an int
auto v2 = 'c';        // v2 is a char
auto v3 = f();        // v3 is of some appropriate type

In fact, it can be an advantage to use the = syntax with auto, because the {}-list syntax might surprise someone:

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auto v1 {12345};       // v1 is a list of int
auto v2 {'c'};         // v2 is a list of char
auto v3 {f()};         // v3 is a list of some appropriate type

This is logical. Consider:

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auto x0 {};         // error: cannot deduce a type
auto x1 {1};        // list of int with one element
auto x2 {1,2};      // list of int with two elements
auto x3 {1,2,3};    // list of int with three elements

The type of a homogeneous list of elements of type T is taken to be of type initializer_list<T> (§3.2.1.3, §11.3.3). In particular, the type of x1 is not deduced to be int. Had it been, what would be the types of x2 and x3?

Consequently, I recommend using = rather than {} for objects specified auto whenever we don’t mean “list.”

6.3.6.3. The decltype() Specifier

We can use auto when we have a suitable initializer. But sometimes, we want to have a type deduced without defining an initialized variable. Then, we can use a declaration type specifier: decltype(expr) is the declared type of expr. This is mostly useful in generic programming. Consider writing a function that adds two matrices with potentially different element types. What should be the type of the result of the addition? A matrix, of course, but what might its element type be? The obvious answer is that the element type of the sum is the type of the sum of the elements. So, I can declare:

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template<class T, class U>
auto operator+(const Matrix<T>& a, const Matrix<U>& b) –> Matrix<decltype(T{}+U{})>;

I use the suffix return type syntax (§12.1) to be able to express the return type in terms of the arguments: Matrix<decltype(T{}+U{})>. That is, the result is a Matrix with the element type being what you get from adding a pair of elements from the argument Matrixes: T{}+U{}.

In the definition, I again need decltype() to express Matrix’s element type:

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template<class T, class U>
auto operator+(const Matrix<T>& a, const Matrix<U>& b) –> Matrix<decltype(T{}+U{})>
{
     Matrix<decltype(T{}+U{})> res;
     for (int i=0; i!=a.rows(); ++i)
           for (int j=0; j!=a.cols(); ++j)
                 res(i,j) += a(i,j) + b(i,j);
     return res;
}

6.4. Objects and Values

We can allocate and use objects that do not have names (e.g., created using new), and it is possible to assign to strange-looking expressions (e.g., *p[a+10]=7). Consequently, we need a name for “something in memory.” This is the simplest and most fundamental notion of an object. That is, an object is a contiguous region of storage; an lvalue is an expression that refers to an object. The word “lvalue” was originally coined to mean “something that can be on the left-hand side of an assignment.” However, not every lvalue may be used on the left-hand side of an assignment; an lvalue can refer to a constant (§7.7). An lvalue that has not been declared const is often called a modifiable lvalue. This simple and low-level notion of an object should not be confused with the notions of class object and object of polymorphic type (§3.2.2, §20.3.2).

6.4.1. Lvalues and Rvalues

To complement the notion of an lvalue, we have the notion of an rvalue. Roughly, rvalue means “a value that is not an lvalue,” such as a temporary value (e.g., the value returned by a function).

If you need to be more technical (say, because you want to read the ISO C++ standard), you need a more refined view of lvalue and rvalue. There are two properties that matter for an object when it comes to addressing, copying, and moving:

• Has identity: The program has the name of, pointer to, or reference to the object so that it is possible to determine if two objects are the same, whether the value of the object has changed, etc.

• Movable: The object may be moved from (i.e., we are allowed to move its value to another location and leave the object in a valid but unspecified state, rather than copying; §17.5).

It turns out that three of the four possible combinations of those two properties are needed to precisely describe the C++ language rules (we have no need for objects that do not have identity and cannot be moved). Using “m for movable” and “i for has identity,” we can represent this classification of expressions graphically:

So, a classical lvalue is something that has identity and cannot be moved (because we could examine it after a move), and a classical rvalue is anything that we are allowed to move from. The other alternatives are prvalue (“pure rvalue”), glvalue (“generalized lvalue”), and xvalue (“x” for “extraordinary” or “expert only”; the suggestions for the meaning of this “x” have been quite imaginative). For example:

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void f(vector<string>& vs)
{
     vector<string>& v2 = std::move(vs);    // move vs to v2
     // ...
}

Here, std::move(vs) is an xvalue: it clearly has identity (we can refer to it as vs), but we have explicitly given permission for it to be moved from by calling std::move() (§3.3.2, §35.5.1).

For practical programming, thinking in terms of rvalue and lvalue is usually sufficient. Note that every expression is either an lvalue or an rvalue, but not both.

6.4.2. Lifetimes of Objects

The lifetime of an object starts when its constructor completes and ends when its destructor starts executing. Objects of types without a declared constructor, such as an int, can be considered to have default constructors and destructors that do nothing.

We can classify objects based on their lifetimes:

• Automatic: Unless the programmer specifies otherwise (§12.1.8, §16.2.12), an object declared in a function is created when its definition is encountered and destroyed when its name goes out of scope. Such objects are sometimes called automatic objects. In a typical implementation, automatic objects are allocated on the stack; each call of the function gets its own stack frame to hold its automatic objects.

• Static: Objects declared in global or namespace scope (§6.3.4) and statics declared in functions (§12.1.8) or classes (§16.2.12) are created and initialized once (only) and “live” until the program terminates (§15.4.3). Such objects are called static objects. A static object has the same address throughout the life of a program execution. Static objects can cause serious problems in a multi-threaded program because they are shared among all threads and typically require locking to avoid data races (§5.3.1, §42.3).

• Free store: Using the new and delete operators, we can create objects whose lifetimes are controlled directly (§11.2).

• Temporary objects (e.g., intermediate results in a computation or an object used to hold a value for a reference to const argument): their lifetime is determined by their use. If they are bound to a reference, their lifetime is that of the reference; otherwise, they “live” until the end of the full expression of which they are part. A full expression is an expression that is not part of another expression. Typically, temporary objects are automatic.

• Thread-local objects; that is, objects declared thread_local (§42.2.8): such objects are created when their thread is and destroyed when their thread is.

Static and automatic are traditionally referred to as storage classes.

Array elements and nonstatic class members have their lifetimes determined by the object of which they are part.

6.5. Type Aliases

Sometimes, we need a new name for a type. Possible reasons include:

• The original name is too long, complicated, or ugly (in some programmer’s eyes).

• A programming technique requires different types to have the same name in a context.

• A specific type is mentioned in one place only to simplify maintenance.

For example:

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using Pchar = char*;        // pointer to character
using PF = int(*)(double);  // pointer to function taking a double and returning an int

Similar types can define the same name as a member alias:

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template<class T>
class vector {
     using value_type = T;    // every container has a value_type
     // ...
};

template<class T>
class list {
     using value_type = T;    // every container has a value_type
     // ...
};

For good and bad, type aliases are synonyms for other types rather than distinct types. That is, an alias refers to the type for which it is an alias. For example:

Pchar p1 = nullptr;     // p1 is a char*
char* p3 = p1;          // fine

People who would like to have distinct types with identical semantics or identical representation should look at enumerations (§8.4) and classes (Chapter 16).

An older syntax using the keyword typedef and placing the name being declared where it would have been in a declaration of a variable can equivalently be used in many contexts. For example:

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typedef int int32_t;       // equivalent to "using int32_t = int;"
typedef short int16_t;     // equivalent to "using int16_t = short;"
typedef void(*PtoF)(int);  // equivalent to "using PtoF = void(*)(int);"

Aliases are used when we want to insulate our code from details of the underlying machine. The name int32_t indicates that we want it to represent a 32-bit integer. Having written our code in terms of int32_t, rather than “plain int,” we can port our code to a machine with sizeof(int)==2 by redefining the single occurrence of int32_t in our code to use a longer integer:

using int32_t = long;

The _t suffix is conventional for aliases (“typedefs”). The int16_t, int32_t, and other such aliases can be found in <stdint> (§43.7). Note that naming a type after its representation rather than its purpose is not necessarily a good idea (§6.3.3).

The using keyword can also be used to introduce a template alias (§23.6). For example:

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template<typename T>
     using Vector = std::vector<T, My_allocator<T>>;

We cannot apply type specifiers, such as unsigned, to an alias. For example:

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using Char = char;
using Uchar = unsigned Char;     // error
using Uchar = unsigned char;     // OK

6.6. Advice

[1] For the final word on language definition issues, see the ISO C++ standard; §6.1.

[2] Avoid unspecified and undefined behavior; §6.1.

[3] Isolate code that must depend on implementation-defined behavior; §6.1.

[4] Avoid unnecessary assumptions about the numeric value of characters; §6.2.3.2, §10.5.2.1.

[5] Remember that an integer starting with a 0 is octal; §6.2.4.1.

[6] Avoid “magic constants”; §6.2.4.1.

[7] Avoid unnecessary assumptions about the size of integers; §6.2.8.

[8] Avoid unnecessary assumptions about the range and precision of floating-point types; §6.2.8.

[9] Prefer plain char over signed char and unsigned char; §6.2.3.1.

[10] Beware of conversions between signed and unsigned types; §6.2.3.1.

[11] Declare one name (only) per declaration; §6.3.2.

[12] Keep common and local names short, and keep uncommon and nonlocal names longer; §6.3.3.

[13] Avoid similar-looking names; §6.3.3.

[14] Name an object to reflect its meaning rather than its type; §6.3.3.

[15] Maintain a consistent naming style; §6.3.3.

[16] Avoid ALL_CAPS names; §6.3.3.

[17] Keep scopes small; §6.3.4.

[18] Don’t use the same name in both a scope and an enclosing scope; §6.3.4.

[19] Prefer the {}-initializer syntax for declarations with a named type; §6.3.5.

[20] Prefer the = syntax for the initialization in declarations using auto; §6.3.5.

[21] Avoid uninitialized variables; §6.3.5.1.

[22] Use an alias to define a meaningful name for a built-in type in cases in which the built-in type used to represent a value might change; §6.5.

[23] Use an alias to define synonyms for types; use enumerations and classes to define new types; §6.5.

7. Pointers, Arrays, and References

The sublime and the ridiculous are often so nearly related that it is difficult to class them separately.

– Thomas Paine

• Introduction

• Pointers

void*; nullptr

• Arrays

Array Initializers; String Literals

• Pointers into Arrays

Navigating Arrays; Multidimensional Arrays; Passing Arrays

• Pointers and const

• Pointers and Ownership

• References

Lvalue References; Rvalue References; References to References; Pointers and References

• Advice

7.1. Introduction

This chapter deals with the basic language mechanisms for referring to memory. Obviously, we can refer to an object by name, but in C++ (most) objects “have identity.” That is, they reside at a specific address in memory, and an object can be accessed if you know its address and its type. The language constructs for holding and using addresses are pointers and references.

7.2. Pointers

For a type T, T * is the type “pointer to T.” That is, a variable of type T* can hold the address of an object of type T. For example:

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char c = 'a';
char* p = &c;        // p holds the address of c; & is the address-of operator

or graphically:

The fundamental operation on a pointer is dereferencing, that is, referring to the object pointed to by the pointer. This operation is also called indirection. The dereferencing operator is (prefix) unary *. For example:

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char c = 'a';
char* p = &c;  // p holds the address of c; & is the address-of operator
char c2 = *p;  // c2 == 'a'; * is the dereference operator

The object pointed to by p is c, and the value stored in c is 'a', so the value of *p assigned to c2 is 'a'.

It is possible to perform some arithmetic operations on pointers to array elements (§7.4).

The implementation of pointers is intended to map directly to the addressing mechanisms of the machine on which the program runs. Most machines can address a byte. Those that can’t tend to have hardware to extract bytes from words. On the other hand, few machines can directly address an individual bit. Consequently, the smallest object that can be independently allocated and pointed to using a built-in pointer type is a char. Note that a bool occupies at least as much space as a char (§6.2.8). To store smaller values more compactly, you can use the bitwise logical operations (§11.1.1), bit-fields in structures (§8.2.7), or a bitset (§34.2.2).

The *, meaning “pointer to,” is used as a suffix for a type name. Unfortunately, pointers to arrays and pointers to functions need a more complicated notation:

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int* pi;             // pointer to int
char* ppc;           // pointer to pointer to char
int* ap[15];         // array of 15 pointers to ints
int (*fp)(char*);    // pointer to function taking a char* argument; returns an int
int* f(char*);       // function taking a char* argument; returns a pointer to int

See §6.3.1 for an explanation of the declaration syntax and §iso.A for the complete grammar.

Pointers to functions can be useful; they are discussed in §12.5. Pointers to class members are presented in §20.6.

7.2.1. void*

In low-level code, we occasionally need to store or pass along an address of a memory location without actually knowing what type of object is stored there. A void* is used for that. You can read void* as “pointer to an object of unknown type.”

A pointer to any type of object can be assigned to a variable of type void*, but a pointer to function (§12.5) or a pointer to member (§20.6) cannot. In addition, a void* can be assigned to another void*, void*s can be compared for equality and inequality, and a void* can be explicitly converted to another type. Other operations would be unsafe because the compiler cannot know what kind of object is really pointed to. Consequently, other operations result in compile-time errors. To use a void*, we must explicitly convert it to a pointer to a specific type. For example:

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void f(int* pi)
{
    void* pv = pi;  // ok: implicit conversion of int* to void*
    *pv;            // error: can't dereference void*
    ++pv;           // error: can't increment void* (the size of the object pointed to is unknown)

    int* pi2 = static_cast<int* >(pv);          // explicit conversion back to int*

    double* pd1 = pv;                           // error
    double* pd2 = pi;                           // error
    double* pd3 = static_cast<double*>(pv);     // unsafe (§11.5.2)
}

In general, it is not safe to use a pointer that has been converted (“cast”) to a type that differs from the type of the object pointed to. For example, a machine may assume that every double is allocated on an 8-byte boundary. If so, strange behavior could arise if pi pointed to an int that wasn’t allocated that way. This form of explicit type conversion is inherently unsafe and ugly. Consequently, the notation used, static_cast (§11.5.2), was designed to be ugly and easy to find in code.

The primary use for void* is for passing pointers to functions that are not allowed to make assumptions about the type of the object and for returning untyped objects from functions. To use such an object, we must use explicit type conversion.

Functions using void* pointers typically exist at the very lowest level of the system, where real hardware resources are manipulated. For example:

void* my_alloc(size_t n);      // allocate n bytes from my special heap

Occurrences of void*s at higher levels of the system should be viewed with great suspicion because they are likely indicators of design errors. Where used for optimization, void* can be hidden behind a type-safe interface (§27.3.1).

Pointers to functions (§12.5) and pointers to members (§20.6) cannot be assigned to void*s.

7.2.2. nullptr

The literal nullptr represents the null pointer, that is, a pointer that does not point to an object. It can be assigned to any pointer type, but not to other built-in types:

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int* pi = nullptr;
double* pd = nullptr;
int i = nullptr;       // error: i is not a pointer

There is just one nullptr, which can be used for every pointer type, rather than a null pointer for each pointer type.

Before nullptr was introduced, zero (0) was used as a notation for the null pointer. For example:

int* x = 0; // x gets the value nullptr

No object is allocated with the address 0, and 0 (the all-zeros bit pattern) is the most common representation of nullptr. Zero (0) is an int. However, the standard conversions (§10.5.2.3) allow 0 to be used as a constant of pointer or pointer-to-member type.

It has been popular to define a macro NULL to represent the null pointer. For example:

int* p = NULL; // using the macro NULL

However, there are differences in the definition of NULL in different implementations; for example, NULL might be 0 or 0L. In C, NULL is typically (void*)0, which makes it illegal in C++ (§7.2.1):

int* p = NULL; // error: can't assign a void* to an int*

Using nullptr makes code more readable than alternatives and avoids potential confusion when a function is overloaded to accept either a pointer or an integer (§12.3.1).

7.3. Arrays

For a type T, T[size] is the type “array of size elements of type T.” The elements are indexed from 0 to size–1. For example:

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float v[3];     // an array of three floats: v[0], v[1], v[2]
char* a[32];    // an array of 32 pointers to char: a[0] .. a[31]

You can access an array using the subscript operator, [], or through a pointer (using operator * []; or operator []; §7.4). For example:

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void f()
{
     int aa[10];
     aa[6] = 9;       // assign to aa's 7th element
     int x = aa[99];  // undefined behavior
}

Access out of the range of an array is undefined and usually disastrous. In particular, run-time range checking is neither guaranteed nor common.

The number of elements of the array, the array bound, must be a constant expression (§10.4). If you need variable bounds, use a vector (§4.4.1, §31.4). For example:

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void f(int n)
{
     int v1[n];          // error: array size not a constant expression
     vector<int> v2(n);  // OK: vector with n int elements
}

Multidimensional arrays are represented as arrays of arrays (§7.4.2).

An array is C++’s fundamental way of representing a sequence of objects in memory. If what you want is a simple fixed-length sequence of objects of a given type in memory, an array is the ideal solution. For every other need, an array has serious problems.

An array can be allocated statically, on the stack, and on the free store (§6.4.2). For example:

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int a1[10];                // 10 ints in static storage

void f()
{
     int a2 [20];          // 20 ints on the stack
     int*p = new int[40];  // 40 ints on the free store
     // ...
}

The C++ built-in array is an inherently low-level facility that should primarily be used inside the implementation of higher-level, better-behaved, data structures, such as the standard-library vector or array. There is no array assignment, and the name of an array implicitly converts to a pointer to its first element at the slightest provocation (§7.4). In particular, avoid arrays in interfaces (e.g., as function arguments; §7.4.3, §12.2.2) because the implicit conversion to pointer is the root cause of many common errors in C code and C-style C++ code. If you allocate an array on the free store, be sure to delete[] its pointer once only and only after its last use (§11.2.2). That’s most easily and most reliably done by having the lifetime of the free-store array controlled by a resource handle (e.g., string (§19.3, §36.3), vector (§13.6, §34.2), or unique_ptr (§34.3.1)). If you allocate an array statically or on the stack, be sure never to delete[] it. Obviously, C programmers cannot follow these pieces of advice because C lacks the ability to encapsulate arrays, but that doesn’t make the advice bad in the context of C++.

One of the most widely used kinds of arrays is a zero-terminated array of char. That’s the way C stores strings, so a zero-terminated array of char is often called a C-style string. C++ string literals follow that convention (§7.3.2), and some standard-library functions (e.g., strcpy() and strcmp(); §43.4) rely on it. Often, a char* or a const char* is assumed to point to a zero-terminated sequence of characters.

7.3.1. Array Initializers

An array can be initialized by a list of values. For example:

int v1[] = { 1, 2, 3, 4 };
char v2[] = { 'a', 'b', 'c', 0 };

When an array is declared without a specific size, but with an initializer list, the size is calculated by counting the elements of the initializer list. Consequently, v1 and v2 are of type int[4] and char[4], respectively. If a size is explicitly specified, it is an error to give surplus elements in an initializer list. For example:

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char v3[2] = { 'a', 'b', 0 };       // error: too many initializers
char v4[3] = { 'a', 'b', 0 };       // OK

If the initializer supplies too few elements for an array, 0 is used for the rest. For example:

int v5[8] = { 1, 2, 3, 4 };

is equivalent to

int v5[] = { 1, 2, 3, 4 , 0, 0, 0, 0 };

There is no built-in copy operation for arrays. You cannot initialize one array with another (not even of exactly the same type), and there is no array assignment:

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int v6[8] = v5;  // error: can't copy an array (cannot assign an int* to an array)
v6 = v5;         // error: no array assignment

Similarly, you can’t pass arrays by value. See also §7.4.

When you need assignment to a collection of objects, use a vector (§4.4.1, §13.6, §34.2), an array (§8.2.4), or a valarray (§40.5) instead.

An array of characters can be conveniently initialized by a string literal (§7.3.2).

7.3.2. String Literals

A string literal is a character sequence enclosed within double quotes:

"this is a string"

A string literal contains one more character than it appears to have; it is terminated by the null character, '\0', with the value 0. For example:

sizeof("Bohr")==5

The type of a string literal is “array of the appropriate number of const characters,” so "Bohr" is of type const char[5].

In C and in older C++ code, you could assign a string literal to a non-const char*:

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void f()
{
    char* p = "Plato";  // error, but accepted in pre-C++11-standard code
    p[4] = 'e';         // error: assignment to const
}

It would obviously be unsafe to accept that assignment. It was (and is) a source of subtle errors, so please don’t grumble too much if some old code fails to compile for this reason. Having string literals immutable is not only obvious but also allows implementations to do significant optimizations in the way string literals are stored and accessed.

If we want a string that we are guaranteed to be able to modify, we must place the characters in a non-const array:

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void f()
{
    char p[] = "Zeno";  // p is an array of 5 char
    p[0] = 'R';         // OK
}

A string literal is statically allocated so that it is safe to return one from a function. For example:

const char* error_message(int i)
{
    // ...
    return "range error";
}

The memory holding "range error" will not go away after a call of error_message().

Whether two identical string literals are allocated as one array or as two is implementation-defined (§6.1). For example:

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const char* p = "Heraclitus";
const char* q = "Heraclitus";

void g()
{
     if (p == q) cout << "one!\n";        // the result is implementation-defined
     // ...
}

Note that == compares addresses (pointer values) when applied to pointers, and not the values pointed to.

The empty string is written as a pair of adjacent double quotes, "", and has the type const char[1]. The one character of the empty string is the terminating '\0'.

The backslash convention for representing nongraphic characters (§6.2.3.2) can also be used within a string. This makes it possible to represent the double quote (") and the escape character backslash (\) within a string. The most common such character by far is the newline character, '\n'. For example:

cout<<"beep at end of message\a\n";

The escape character, '\a', is the ASCII character BEL (also known as alert), which causes a sound to be emitted.

It is not possible to have a “real” newline in a (nonraw) string literal:

"this is not a string
but a syntax error"

Long strings can be broken by whitespace to make the program text neater. For example:

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char alpha[] = "abcdefghijklmnopqrstuvwxyz"
               "ABCDEFGHIJKLMNOPQRSTUVWXYZ";

The compiler will concatenate adjacent strings, so alpha could equivalently have been initialized by the single string

"abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ";

It is possible to have the null character in a string, but most programs will not suspect that there are characters after it. For example, the string "Jens\000Munk" will be treated as "Jens" by standard-library functions such as strcpy() and strlen(); see §43.4.

7.3.2.1. Raw Character Strings

To represent a backslash (\) or a double quote (") in a string literal, we have to precede it with a backslash. That’s logical and in most cases quite simple. However, if we need a lot of backslashes and a lot of quotes in string literals, this simple technique becomes unmanageable. In particular, in regular expressions a backslash is used both as an escape character and to introduce characters representing character classes (§37.1.1). This is a convention shared by many programming languages, so we can’t just change it. Therefore, when you write regular expressions for use with the standard regex library (Chapter 37), the fact that a backslash is an escape character becomes a notable source of errors. Consider how to write the pattern representing two words separated by a backslash (\):

string s = "\\w\\\\w";    // I hope I got that right

To prevent the frustration and errors caused by this clash of conventions, C++ provides raw string literals. A raw string literal is a string literal where a backslash is just a backslash (and a double quote is just a double quote) so that our example becomes:

string s = R"(\w\\w)";    // I'm pretty sure I got that right

Raw string literals use the R"(ccc)" notation for a sequence of characters ccc. The initial R is there to distinguish raw string literals from ordinary string literals. The parentheses are there to allow (“unescaped”) double quotes. For example:

R"("quoted string")"      // the string is "quoted string"

So, how do we get the character sequence )" into a raw string literal? Fortunately, that’s a rare problem, but "( and )" is only the default delimiter pair. We can add delimiters before the ( and after the ) in "(...)". For example:

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R"***("quoted string containing the usual terminator ("))")***"
     // "quoted string containing the usual terminator ("))"

The character sequence after the ) must be identical to the sequence before the (. This way we can cope with (almost) arbitrarily complicated patterns.

Unless you work with regular expressions, raw string literals are probably just a curiosity (and one more thing to learn), but regular expressions are useful and widely used. Consider a real-world example:

"('(?:[^\\\\']|\\\\.)*'|\"(?:[^\\\\\"]|\\\\.)*\")|"    // Are the five backslashes correct or not?

With examples like that, even experts easily become confused, and raw string literals provide a significant service.

In contrast to nonraw string literals, a raw string literal can contain a newline. For example:

string counts {R"(1
22
333)"};

is equivalent to

string x {"1\n22\n333"};

7.3.2.2. Larger Character Sets

A string with the prefix L, such as L"angst", is a string of wide characters (§6.2.3). Its type is const wchar_t[]. Similarly, a string with the prefix LR, such as LR"(angst)", is a raw string (§7.3.2.1) of wide characters of type const wchar_t[]. Such a string is terminated by a L'\0' character.

There are six kinds of character literals supporting Unicode (Unicode literals). This sounds excessive, but there are three major encodings of Unicode: UTF-8, UTF-16, and UTF-32. For each of these three alternatives, both raw and “ordinary” strings are supported. All three UTF encodings support all Unicode characters, so which you use depends on the system you need to fit into. Essentially all Internet applications (e.g., browsers and email) rely on one or more of these encodings.

UTF-8 is a variable-width encoding: common characters fit into 1 byte, less frequently used characters (by some estimate of use) into 2 bytes, and rarer characters into 3 or 4 bytes. In particular, the ASCII characters fit into 1 byte with the same encodings (integer values) in UTF-8 as in ASCII. The various Latin alphabets, Greek, Cyrillic, Hebrew, Arabic, and more fit into 2 bytes.

A UTF-8 string is terminated by '\0', a UTF-16 string by u'\0', and a UTF-32 string by U'\0'.

We can represent an ordinary English character string in a variety of ways. Consider a file name using a backslash as the separator:

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"folder\\file"       // implementation character set string
R"(folder\file)"     // implementation character raw set string
u8"folder\\file"     // UTF-8 string
u8R"(folder\file)"   // UTF-8 raw string
u"folder\\file"      // UTF-16 string
uR"(folder\file)"         // UTF-16 raw string
U"folder\\file"      // UTF-32 string
UR"(folder\file)"         // UTF-32 raw string

If printed, these strings will all look the same, but except for the “plain” and UTF-8 strings their internal representations are likely to differ.

Obviously, the real purpose of Unicode strings is to be able to put Unicode characters into them. For example:

u8"The official vowels in Danish are: a, e, i, o, u, \u00E6, \u00F8, \u00E5 and y."

Printing that string appropriately gives you

The official vowels in Danish are: a, e, i, o, u, æ, ø, å and y.

The hexadecimal number after the \u is a Unicode code point (§iso.2.14.3) [Unicode,1996]. Such a code point is independent of the encoding used and will in fact have different representations (as bits in bytes) in different encodings. For example, u'0430' (Cyrillic lowercase letter “a”) is the 2-byte hexadecimal value D0B0 in UTF-8, the 2-byte hexadecimal value 0403 in UTF-16, and the 4-byte hexadecimal value 00000403 in UTF-32. These hexadecimal values are referred to as universal character names.

The order of the us and Rs and their cases are significant: RU and Ur are not valid string prefixes.

7.4. Pointers into Arrays

In C++, pointers and arrays are closely related. The name of an array can be used as a pointer to its initial element. For example:

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int v[] = { 1, 2, 3, 4 };
int* p1 = v;            // pointer to initial element (implicit conversion)
int* p2 = &v[0];        // pointer to initial element
int* p3 = v+4;          // pointer to one-beyond-last element

or graphically:

Taking a pointer to the element one beyond the end of an array is guaranteed to work. This is important for many algorithms (§4.5, §33.1). However, since such a pointer does not in fact point to an element of the array, it may not be used for reading or writing. The result of taking the address of the element before the initial element or beyond one-past-the-last element is undefined and should be avoided. For example:

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int* p4 = v–1; // before the beginning, undefined: don't do it
int* p5 = v+7; // beyond the end, undefined: don't do it

The implicit conversion of an array name to a pointer to the initial element of the array is extensively used in function calls in C-style code. For example:

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extern "C" int strlen(const char*);       // from <string.h>

void f()
{
     char v[] = "Annemarie";
     char* p = v;   // implicit conversion of char[] to char*
     strlen(p);
     strlen(v);     // implicit conversion of char[] to char*
     v = p;         // error: cannot assign to array
}

The same value is passed to the standard-library function strlen() in both calls. The snag is that it is impossible to avoid the implicit conversion. In other words, there is no way of declaring a function so that the array v is copied when the function is called. Fortunately, there is no implicit or explicit conversion from a pointer to an array.

The implicit conversion of the array argument to a pointer means that the size of the array is lost to the called function. However, the called function must somehow determine the size to perform a meaningful operation. Like other C standard-library functions taking pointers to characters, strlen() relies on zero to indicate end-of-string; strlen(p) returns the number of characters up to and not including the terminating 0. This is all pretty low-level. The standard-library vector (§4.4.1, §13.6, §31.4), array (§8.2.4, §34.2.1), and string (§4.2) don’t suffer from this problem. These library types give their number of elements as their size() without having to count elements each time.

7.4.1. Navigating Arrays

Efficient and elegant access to arrays (and similar data structures) is the key to many algorithms (see §4.5, Chapter 32). Access can be achieved either through a pointer to an array plus an index or through a pointer to an element. For example:

void fi(char v[])
{
     for (int i = 0; v[i]!=0; ++i)
           use(v[i]);
}

void fp(char v[])
{
     for (char* p = v; *p!=0; ++p)
           use(*p);
}

The prefix * operator dereferences a pointer so that *p is the character pointed to by p, and ++ increments the pointer so that it refers to the next element of the array.

There is no inherent reason why one version should be faster than the other. With modern compilers, identical code should be (and usually is) generated for both examples. Programmers can choose between the versions on logical and aesthetic grounds.

Subscripting a built-in array is defined in terms of the pointer operations + and *. For every built-in array a and integer j within the range of a, we have:

a[j] == *(&a[0]+j) == *(a+j) == *(j+a) == j[a]

It usually surprises people to find that a[j]==j[a]. For example, 3["Texas"]=="Texas"[3]=='a'. Such cleverness has no place in production code. These equivalences are pretty low-level and do not hold for standard-library containers, such as array and vector.

The result of applying the arithmetic operators +, –, ++, or –– to pointers depends on the type of the object pointed to. When an arithmetic operator is applied to a pointer p of type T*, p is assumed to point to an element of an array of objects of type T; p+1 points to the next element of that array, and p–1 points to the previous element. This implies that the integer value of p+1 will be sizeof(T) larger than the integer value of p. For example:

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template<typename T>
int byte_diff(T* p, T *q)
{
     return reinterpret_cast<char *>(q)–reinterpret_cast<char*>(p);
}

void diff_test()
{
     int vi[10];
     short vs[10];
     cout << vi << ' ' << &vi[1] << ' ' << &vi[1]–&vi[0] << ' ' << byte_diff(&vi[0],&vi[1]) << '\n';
     cout << vs << ' ' << &vs[1] << ' ' << &vs[1]–&vs[0] << ' ' << byte_diff(&vs[0],&vs[1]) << '\n';
}

This produced:

0x7fffaef0 0x7fffaef4 1 4
0x7fffaedc 0x7fffaede 1 2

The pointer values were printed using the default hexadecimal notation. This shows that on my implementation, sizeof(short) is 2 and sizeof(int) is 4.

Subtraction of pointers is defined only when both pointers point to elements of the same array (although the language has no fast way of ensuring that is the case). When subtracting a pointer p from another pointer q, q–p, the result is the number of array elements in the sequence [p:q) (an integer). One can add an integer to a pointer or subtract an integer from a pointer; in both cases, the result is a pointer value. If that value does not point to an element of the same array as the original pointer or one beyond, the result of using that value is undefined. For example:

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void f()
{
     int v1[10];
     int v2[10];

     int i1 = &v1[5]–&v1[3];    // i1 = 2
     int i2 = &v1[5]–&v2[3];    // result undefined

     int* p1 = v2+2;            // p1 = &v2[2]
     int* p2 = v2–2;            // *p2 undefined
}

Complicated pointer arithmetic is usually unnecessary and best avoided. Addition of pointers makes no sense and is not allowed.

Arrays are not self-describing because the number of elements of an array is not guaranteed to be stored with the array. This implies that to traverse an array that does not contain a terminator the way C-style strings do, we must somehow supply the number of elements. For example:

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void fp(char v[], int size)
{
     for (int i=0; i!=size; ++i)
           use(v[i]);             // hope that v has at least size elements
     for (int x : v)
           use(x);                // error: range-for does not work for pointers

     const int N = 7;
     char v2[N];
     for (int i=0; i!=N; ++i)
           use(v2[i]);
     for (int x : v2)
           use(x);                // range-for works for arrays of known size
}

This array concept is inherently low-level. Most advantages of the built-in array and few of the disadvantages can be obtained through the use of the standard-library container array (§8.2.4, §34.2.1). Some C++ implementations offer optional range checking for arrays. However, such checking can be quite expensive, so it is often used only as a development aid (rather than being included in production code). If you are not using range checking for individual accesses, try to maintain a consistent policy of accessing elements only in well-defined ranges. That is best done when arrays are manipulated through the interface of a higher-level container type, such as vector, where it is harder to get confused about the range of valid elements.

7.4.2. Multidimensional Arrays

Multidimensional arrays are represented as arrays of arrays; a 3-by-5 array is declared like this:

int ma[3][5];   // 3 arrays with 5 ints each

We can initialize ma like this:

void init_ma()
{
     for (int i = 0; i!=3; i++)
          for (int j = 0; j!=5; j++)
                ma[i][j] = 10*i+j;
}

or graphically:

The array ma is simply 15 ints that we access as if it were 3 arrays of 5 ints. In particular, there is no single object in memory that is the matrix ma – only the elements are stored. The dimensions 3 and 5 exist in the compiler source only. When we write code, it is our job to remember them somehow and supply the dimensions where needed. For example, we might print ma like this:

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void print_ma()
{
     for (int i = 0; i!=3; i++) {
          for (int j = 0; j!=5; j++)
                cout << ma[i][j] << '\t';
          cout << '\n';
    }
}

The comma notation used for array bounds in some languages cannot be used in C++ because the comma (,) is a sequencing operator (§10.3.2). Fortunately, most mistakes are caught by the compiler. For example:

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int bad[3,5];            // error: comma not allowed in constant expression
int good[3][5];          // 3 arrays with 5 ints each
int ouch = good[1,4];    // error: int initialized by int* (good[1,4] means good[4], which is an int*)
int nice = good[1][4];

7.4.3. Passing Arrays

Arrays cannot directly be passed by value. Instead, an array is passed as a pointer to its first element. For example:

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void comp(double arg[10])          // arg is a double*
{
     for (int i=0; i!=10; ++i)
           arg[i]+=99;
}

void f()
{
     double a1[10];
     double a2[5];
     double a3[100];

     comp(a1);
     comp(a2);     // disaster!
     comp(a3);     // uses only the first 10 elements
};

This code looks sane, but it is not. The code compiles, but the call comp(a2) will write beyond the bounds of a2. Also, anyone who guessed that the array was passed by value will be disappointed: the writes to arg[i] are writes directly to the elements of comp()’s argument, rather than to a copy. The function could equivalently have been written as

void comp(double* arg)
{
     for (int i=0; i!=10; ++i)
           arg[i]+=99;
}

Now the insanity is (hopefully) obvious. When used as a function argument, the first dimension of an array is simply treated as a pointer. Any array bound specified is simply ignored. This implies that if you want to pass a sequence of elements without losing size information, you should not pass a built-in array. Instead, you can place the array inside a class as a member (as is done for std::array) or define a class that acts as a handle (as is done for std::string and std::vector).

If you insist on using arrays directly, you will have to deal with bugs and confusion without getting noticeable advantages in return. Consider defining a function to manipulate a two-dimensional matrix. If the dimensions are known at compile time, there is no problem:

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void print_m35(int m[3][5])
{
     for (int i = 0; i!=3; i++) {
           for (int j = 0; j!=5; j++)
                 cout << m[i][j] << '\t';
           cout << '\n';
     }
}

A matrix represented as a multidimensional array is passed as a pointer (rather than copied; §7.4). The first dimension of an array is irrelevant to finding the location of an element; it simply states how many elements (here, 3) of the appropriate type (here, int[5]) are present. For example, look at the layout of ma above and note that by knowing only that the second dimension is 5, we can locate ma[i][5] for any i. The first dimension can therefore be passed as an argument:

void print_mi5(int m[][5], int dim1)
{
     for (int i = 0; i!=dim1; i++) {
           for (int j = 0; j!=5; j++)
                 cout << m[i][j] << '\t';
           cout << '\n';
     }
}

When both dimensions need to be passed, the “obvious solution” does not work:

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void print_mij(int m[][], int dim1, int dim2)     // doesn't behave as most people would think
{
     for (int i = 0; i!=dim1; i++) {
           for (int j = 0; j!=dim2; j++)
                 cout << m[i][j] << '\t';    // surprise!
           cout << '\n';
     }
}

Fortunately, the argument declaration m[][] is illegal because the second dimension of a multidimensional array must be known in order to find the location of an element. However, the expression m[i][j] is (correctly) interpreted as *(*(m+i)+j), although that is unlikely to be what the programmer intended. A correct solution is:

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void print_mij(int* m, int dim1, int dim2)
{
    for (int i = 0; i!=dim1; i++) {
          for (int j = 0; j!=dim2; j++)
                cout << m[i*dim2+j] << '\t'; // obscure
          cout << '\n';
    }
}

The expression used for accessing the members in print_mij() is equivalent to the one the compiler generates when it knows the last dimension.

To call this function, we pass a matrix as an ordinary pointer:

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int test()
{
    int v[3][5] = {
          {0,1,2,3,4}, {10,11,12,13,14}, {20,21,22,23,24}
    };
    print_m35(v);
    print_mi5(v,3);
    print_mij(&v[0][0],3,5);
}

Note the use of &v[0][0] for the last call; v[0] would do because it is equivalent, but v would be a type error. This kind of subtle and messy code is best hidden. If you must deal directly with multidimensional arrays, consider encapsulating the code relying on it. In that way, you might ease the task of the next programmer to touch the code. Providing a multidimensional array type with a proper subscripting operator saves most users from having to worry about the layout of the data in the array (§29.2.2, §40.5.2).

The standard vector (§31.4) doesn’t suffer from these problems.

7.5. Pointers and const

C++ offers two related meanings of “constant”:

• constexpr: Evaluate at compile time (§2.2.3, §10.4).

• const: Do not modify in this scope (§2.2.3).

Basically, constexpr’s role is to enable and ensure compile-time evaluation, whereas const’s primary role is to specify immutability in interfaces. This section is primarily concerned with the second role: interface specification.

Many objects don’t have their values changed after initialization:

• Symbolic constants lead to more maintainable code than using literals directly in code.

• Many pointers are often read through but never written through.

• Most function parameters are read but not written to.

To express this notion of immutability after initialization, we can add const to the definition of an object. For example:

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const int model = 90;                // model is a const
const int v[] = { 1, 2, 3, 4 };      // v[i] is a const
const int x;                         // error: no initializer

Because an object declared const cannot be assigned to, it must be initialized.

Declaring something const ensures that its value will not change within its scope:

void f()
{
     model = 200;     // error
     v[2] = 3;        // error
}

Note that const modifies a type; it restricts the ways in which an object can be used, rather than specifying how the constant is to be allocated. For example:

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void g(const X* p)
{
     // can't modify *p here
}

void h()
{
     X val;       // val can be modified here
     g(&val);
     // ...
}

When using a pointer, two objects are involved: the pointer itself and the object pointed to. “Prefixing” a declaration of a pointer with const makes the object, but not the pointer, a constant. To declare a pointer itself, rather than the object pointed to, to be a constant, we use the declarator operator *const instead of plain *. For example:

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void f1(char* p)
{
     char s[] = "Gorm";

     const char* pc = s;           // pointer to constant
     pc[3] = 'g';                  // error: pc points to constant
     pc = p;                       // OK

     char *const cp = s;           // constant pointer
     cp[3] = 'a';                  // OK
     cp = p;                       // error: cp is constant

     const char *const cpc = s;    // const pointer to const
     cpc[3] = 'a';                 // error: cpc points to constant
     cpc = p;                      // error: cpc is constant
}

The declarator operator that makes a pointer constant is *const. There is no const* declarator operator, so a const appearing before the * is taken to be part of the base type. For example:

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char *const cp;         // const pointer to char
char const* pc;         // pointer to const char
const char* pc2;        // pointer to const char

Some people find it helpful to read such declarations right-to-left, for example, “cp is a const pointer to a char” and “pc2 is a pointer to a char const.”

An object that is a constant when accessed through one pointer may be variable when accessed in other ways. This is particularly useful for function arguments. By declaring a pointer argument const, the function is prohibited from modifying the object pointed to. For example:

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const char* strchr(const char* p, char c);    // find first occurrence of c in p
char* strchr(char* p, char c);                // find first occurrence of c in p

The first version is used for strings where the elements mustn’t be modified and returns a pointer to const that does not allow modification. The second version is used for mutable strings.

You can assign the address of a non-const variable to a pointer to constant because no harm can come from that. However, the address of a constant cannot be assigned to an unrestricted pointer because this would allow the object’s value to be changed. For example:

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void f4()
{
     int a = 1;
     const int c = 2;
     const int* p1 = &c; // OK
     const int* p2 = &a; // OK
     int* p3 = &c;       // error: initialization of int* with const int*
     *p3 = 7;            // try to change the value of c
}

It is possible, but typically unwise, to explicitly remove the restrictions on a pointer to const by explicit type conversion (§16.2.9, §11.5).

7.6. Pointers and Ownership

A resource is something that has to be acquired and later released (§5.2). Memory acquired by new and released by delete (§11.2) and files opened by fopen() and closed by fclose() (§43.2) are examples of resources where the most direct handle to the resource is a pointer. This can be most confusing because a pointer is easily passed around in a program, and there is nothing in the type system that distinguishes a pointer that owns a resource from one that does not. Consider:

void confused(int* p)
{
     // delete p?
}

int global {7};

void f()
{
     X* pn = new int{7};
     int i {7};
     int q = &i;
     confused(pn);
     confused(q);
     confused(&global);
}

If confused() deletes p the program will seriously misbehave for the second two calls because we may not delete objects not allocated by new (§11.2). If confused() does not delete p the program leaks (§11.2.1). In this case, obviously f() must manage the lifetime of the object it creates on the free store, but in general keeping track of what needs to be deleted in a large program requires a simple and consistent strategy.

It is usually a good idea to immediately place a pointer that represents ownership in a resource handle class, such as vector, string, and unique_ptr. That way, we can assume that every pointer that is not within a resource handle is not an owner and must not be deleted. Chapter 13 discusses resource management in greater detail.

7.7. References

A pointer allows us to pass potentially large amounts of data around at low cost: instead of copying the data we simply pass its address as a pointer value. The type of the pointer determines what can be done to the data through the pointer. Using a pointer differs from using the name of an object in a few ways:

• We use a different syntax, for example, *p instead of obj and p–>m rather than obj.m.

• We can make a pointer point to different objects at different times.

• We must be more careful when using pointers than when using an object directly: a pointer may be a nullptr or point to an object that wasn’t the one we expected.

These differences can be annoying; for example, some programmers find f(&x) ugly compared to f(x). Worse, managing pointer variables with varying values and protecting code against the possibility of nullptr can be a significant burden. Finally, when we want to overload an operator, say +, we want to write x+y rather than &x+&y. The language mechanism addressing these problems is called a reference. Like a pointer, a reference is an alias for an object, is usually implemented to hold a machine address of an object, and does not impose performance overhead compared to pointers, but it differs from a pointer in that:

• You access a reference with exactly the same syntax as the name of an object.

• A reference always refers to the object to which it was initialized.

• There is no “null reference,” and we may assume that a reference refers to an object (§7.7.4).

A reference is an alternative name for an object, an alias. The main use of references is for specifying arguments and return values for functions in general and for overloaded operators (Chapter 18) in particular. For example:

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template<class T>
class vector {
     T* elem;
     // ...
public:
     T& operator[](int i) { return elem[i]; }             // return reference to element
     const T& operator[](int i) const { return elem[i]; } // return reference to const element

     void push_back(const T& a);                          // pass element to be added by reference
     // ...
};

void f(const vector<double>& v)
{
     double d1 = v[1];   // copy the value of the double referred to by v.operator[](1) into d1
     v[2] = 7;           // place 7 in the double referred to by the result of v.operator[](2)

     v.push_back(d1);    // give push_back() a reference to d1 to work with
}

The idea of passing function arguments by reference is as old as high-level programming languages (the first version of Fortran used that).

To reflect the lvalue/rvalue and const/non-const distinctions, there are three kinds of references:

• lvalue references: to refer to objects whose value we want to change

• const references: to refer to objects whose value we do not want to change (e.g., a constant)

• rvalue references: to refer to objects whose value we do not need to preserve after we have used it (e.g., a temporary)

Collectively, they are called references. The first two are both called lvalue references.

7.7.1. Lvalue References

In a type name, the notation X& means “reference to X.” It is used for references to lvalues, so it is often called an lvalue reference. For example:

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void f()
{
     int var = 1;
     int& r {var};    // r and var now refer to the same int
     int x = r;       // x becomes 1

     r = 2;           // var becomes 2
}

To ensure that a reference is a name for something (that is, that it is bound to an object), we must initialize the reference. For example:

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int var = 1;
int& r1 {var};      // OK: r1 initialized
int& r2;            // error: initializer missing
extern int& r3;     // OK: r3 initialized elsewhere

Initialization of a reference is something quite different from assignment to it. Despite appearances, no operator operates on a reference. For example:

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void g()
{
     int var = 0;
     int& rr {var};
     ++rr;               // var is incremented to 1
     int* pp = &rr;      // pp points to var
}

Here, ++rr does not increment the reference rr; rather, ++ is applied to the int to which rr refers, that is, to var. Consequently, the value of a reference cannot be changed after initialization; it always refers to the object it was initialized to denote. To get a pointer to the object denoted by a reference rr, we can write &rr. Thus, we cannot have a pointer to a reference. Furthermore, we cannot define an array of references. In that sense, a reference is not an object.

The obvious implementation of a reference is as a (constant) pointer that is dereferenced each time it is used. It doesn’t do much harm to think about references that way, as long as one remembers that a reference isn’t an object that can be manipulated the way a pointer is:

In some cases, the compiler can optimize away a reference so that there is no object representing that reference at run time.

Initialization of a reference is trivial when the initializer is an lvalue (an object whose address you can take; see §6.4). The initializer for a “plain” T& must be an lvalue of type T.

The initializer for a const T& need not be an lvalue or even of type T. In such cases:

[1] First, implicit type conversion to T is applied if necessary (see §10.5).

[2] Then, the resulting value is placed in a temporary variable of type T.

[3] Finally, this temporary variable is used as the value of the initializer. Consider:

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double& dr = 1;              // error: lvalue needed
const double& cdr {1};       // OK

The interpretation of this last initialization might be:

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double temp = double{1};     // first create a temporary with the right value
const double& cdr {temp};    // then use the temporary as the initializer for cdr

A temporary created to hold a reference initializer persists until the end of its reference’s scope.

References to variables and references to constants are distinguished because introducing a temporary for a variable would have been highly error-prone; an assignment to the variable would become an assignment to the – soon-to-disappear – temporary. No such problem exists for references to constants, and references to constants are often important as function arguments (§18.2.4).

A reference can be used to specify a function argument so that the function can change the value of an object passed to it. For example:

void increment(int& aa)
{
     ++aa;
}

void f()
{
     int x = 1;
     increment(x);      // x = 2
}

The semantics of argument passing are defined to be those of initialization, so when called, increment’s argument aa became another name for x. To keep a program readable, it is often best to avoid functions that modify their arguments. Instead, you can return a value from the function explicitly:

int next(int p) { return p+1; }

void g()
{
     int x = 1;
     increment(x);       // x = 2
     x = next(x);        // x = 3
}

The increment(x) notation doesn’t give a clue to the reader that x’s value is being modified, the way x=next(x) does. Consequently, “plain” reference arguments should be used only where the name of the function gives a strong hint that the reference argument is modified.

References can also be used as return types. This is mostly used to define functions that can be used on both the left-hand and right-hand sides of an assignment. A Map is a good example. For example:

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template<class K, class V>
class Map {         // a simple map class
public:
     V& operator[](const K& v);      // return the value corresponding to the key v

     pair<K,V>* begin() { return &elem[0]; }
     pair<K,V>* end() { return &elem[0]+elem.size(); }
private:
     vector<pair<K,V>> elem;         // {key,value} pairs
};

The standard-library map (§4.4.3, §31.4.3) is typically implemented as a red-black tree, but to avoid distracting implementation details, I’ll just show an implementation based on linear search for a key match:

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template<class K, class V>
V& Map<K,V>::operator[](const K& k)
{
    for (auto& x : elem)
          if (k == x.first)
                return x.second;

    elem.push_back({k,V{}});     // add pair at end (§4.4.2)
    return elem.back().second;   // return the (default) value of the new element
}

I pass the key argument, k, by reference because it might be of a type that is expensive to copy. Similarly, I return the value by reference because it too might be of a type that is expensive to copy. I use a const reference for k because I don’t want to modify it and because I might want to use a literal or a temporary object as an argument. I return the result by non-const reference because the user of a Map might very well want to modify the found value. For example:

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int main() // count the number of occurrences of each word on input
{
     Map<string,int> buf;

     for (string s; cin>>s;) ++buf[s];

     for (const auto& x : buf)
           cout << x.first << ": " << x.second << '\n';
}

Each time around, the input loop reads one word from the standard input stream cin into the string s (§4.3.2) and then updates the counter associated with it. Finally, the resulting table of different words in the input, each with its number of occurrences, is printed. For example, given the input

aa bb bb aa aa bb aa aa

this program will produce

aa: 5
bb: 3

The range-for loop works for this because Map defined begin() and end(), just as is done for the standard-library map.

7.7.2. Rvalue References

The basic idea of having more than one kind of reference is to support different uses of objects:

• A non-const lvalue reference refers to an object, to which the user of the reference can write.

• A const lvalue reference refers to a constant, which is immutable from the point of view of the user of the reference.

• An rvalue reference refers to a temporary object, which the user of the reference can (and typically will) modify, assuming that the object will never be used again.

We want to know if a reference refers to a temporary, because if it does, we can sometimes turn an expensive copy operation into a cheap move operation (§3.3.2, §17.1, §17.5.2). An object (such as a string or a list) that is represented by a small descriptor pointing to a potentially huge amount of information can be simply and cheaply moved if we know that the source isn’t going to be used again. The classic example is a return value where the compiler knows that a local variable returned will never again be used (§3.3.2).

An rvalue reference can bind to an rvalue, but not to an lvalue. In that, an rvalue reference is exactly opposite to an lvalue reference. For example:

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string var {"Cambridge"};
string f();

string& r1 {var};              // lvalue reference, bind r1 to var (an lvalue)
string& r2 {f()};              // lvalue reference, error: f() is an rvalue
string& r3 {"Princeton"};      // lvalue reference, error: cannot bind to temporary
string&& rr1 {f()};            // rvalue reference, fine: bind rr1 to rvalue (a temporary)
string&& rr2 {var};            // rvalue reference, error: var is an lvalue
string&& rr3 {"Oxford"};       // rr3 refers to a temporary holding "Oxford"

const string cr1& {"Harvard"}; // OK: make temporary and bind to cr1

The && declarator operator means “rvalue reference.” We do not use const rvalue references; most of the benefits from using rvalue references involve writing to the object to which it refers. Both a const lvalue reference and an rvalue reference can bind to an rvalue. However, the purposes will be fundamentally different:

• We use rvalue references to implement a “destructive read” for optimization of what would otherwise have required a copy.

• We use a const lvalue reference to prevent modification of an argument.

An object referred to by an rvalue reference is accessed exactly like an object referred to by an lvalue reference or an ordinary variable name. For example:

string f(string&& s)
{
     if (s.size())
            s[0] = toupper(s[0]);
     return s;
}

Sometimes, a programmer knows that an object won’t be used again, even though the compiler does not. Consider:

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template<class T>
swap(T& a, T& b)         // "old-style swap"
{
    T tmp {a};// now we have two copies of a
    a = b;    // now we have two copies of b
    b = tmp;  // now we have two copies of tmp (aka a)
}

If T is a type for which it can be expensive to copy elements, such as string and vector, this swap() becomes an expensive operation. Note something curious: we didn’t want any copies at all; we just wanted to move the values of a, b, and tmp around. We can tell that to the compiler:

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template<class T>
void swap(T& a, T& b)    // "perfect swap" (almost)
{
     T tmp {static_cast<T&&>(a)}; // the initialization may write to a
     a = static_cast<T&&>(b);     // the assignment may write to b
     b = static_cast<T&&>(tmp);   // the assignment may write to tmp
}

The result value of static_cast<T&&>(x) is an rvalue of type T&& for x. An operation that is optimized for rvalues can now use its optimization for x. In particular, if a type T has a move constructor (§3.3.2, §17.5.2) or a move assignment, it will be used. Consider vector:

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template<class T> class vector {
    // ...
    vector(const vector& r); // copy constructor (copy r's representation)
    vector(vector&& r);      // move constructor ("steal" representation from r)
};

vector<string> s;
vector<string> s2 {s};            // s is an lvalue, so use copy constructor
vector<string> s3 {s+"tail");     // s+"tail" is an rvalue so pick move constructor

The use of static_cast in swap() is a bit verbose and slightly prone to mistyping, so the standard library provides a move() function: move(x) means static_cast<X&&>(x) where X is the type of x. Given that, we can clean up the definition of swap() a bit:

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template<class T>
void swap(T& a, T& b)    // "perfect swap" (almost)
{
    T tmp {move(a)};     // move from a
    a = move(b);         // move from b
    b = move(tmp);       // move from tmp
}

In contrast to the original swap(), this latest version need not make any copies; it will use move operations whenever possible.

Since move(x) does not move x (it simply produces an rvalue reference to x), it would have been better if move() had been called rval(), but by now move() has been used for years.

I deemed this swap() “almost perfect” because it will swap only lvalues. Consider:

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void f(vector<int>& v)
{
     swap(v,vector<int>{1,2,3});    // replace v's elements with 1,2,3
     // ...
}

It is not uncommon to want to replace the contents of a container with some sort of default value, but this particular swap() cannot do that. A solution is to augment it by two overloads:

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template<class T> void swap(T&& a, T& b);
template<class T> void swap(T& a, T&& b)

Our example will be handled by that last version of swap(). The standard library takes a different approach by defining shrink_to_fit() and clear() for vector, string, etc. (§31.3.3) to handle the most common cases of rvalue arguments to swap():

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void f(string& s, vector<int>& v)
{
    s.shrink_to_fit();         // make s.capacity()==s.size()
    swap(s,string{s});         // make s.capacity()==s.size()
    v.clear();                 // make v empty
    swap(v.vector<int>{});     // make v empty
    v = {};                    // make v empty
}

Rvalue references can also be used to provide perfect forwarding (§23.5.2.1, §35.5.1).

All standard-library containers provide move constructors and move assignment (§31.3.2). Also, their operations that insert new elements, such as insert() and push_back(), have versions that take rvalue references.

7.7.3. References to References

It you take a reference to a reference to a type, you get a reference to that type, rather than some kind of special reference to reference type. But what kind of reference? Lvalue reference or rvalue reference? Consider:

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using rr_i = int&&;
using lr_i = int&;
using rr_rr_i = rr_i&&;    // "int && &&" is an int&&
using lr_rr_i = rr_i&;     // "int && &" is an int&
using rr_lr_i = lr_i&&;    // "int & &&" is an int&
using lr_lr_i = lr_i&;     // "int & &" is an int&

In other words, lvalue reference always wins. This makes sense: nothing we can do with types can change the fact that an lvalue reference refers to an lvalue. This is sometimes known as reference collapse.

The syntax does not allow

int && & r = i;

Reference to reference can only happen as the result of an alias (§3.4.5, §6.5) or a template type argument (§23.5.2.1).

7.7.4. Pointers and References

Pointers and references are two mechanisms for referring to an object from different places in a program without copying. We can show this similarity graphically:

Each has its strengths and weaknesses.

If you need to change which object to refer to, use a pointer. You can use =, +=, –=, ++, and –– to change the value of a pointer variable (§11.1.4). For example:

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void fp(char* p)
{
     while (*p)
          cout << ++*p;
}

void fr(char& r)
{
     while (r)
          cout << ++r;    // oops: increments the char referred to, not the reference
                          // near-infinite loop!
}

void fr2(char& r)
{
     char* p = &r;        // get a pointer to the object referred to
     while (*p)
          cout << ++*p;
}

Conversely, if you want to be sure that a name always refers to the same object, use a reference. For example:

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template<class T> class Proxy {       // Proxy refers to the object with which it is initialized
    T& m;
public:
    Proxy(T& mm) :m{mm} {}
    // ...
};

template<class T> class Handle { // Handle refers to its current object
    T* m;
public:
    Proxy(T* mm) :m{mm} {}
    void rebind(T* mm) { m = mm; }
   // ...
};

If you want to use a user-defined (overloaded) operator (§18.1) on something that refers to an object, use a reference:

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Matrix operator+(const Matrix&, const Matrix&);   // OK
Matrix operator–(const Matrix*, const Matrix*);   // error: no user-defined type argument

Matrix y, z;
// ...
Matrix x = y+z;     // OK
Matrix x2 = &y–&z;  // error and ugly

It is not possible to (re)define an operator for a pair of built-in types, such as pointers (§18.2.3).

If you want a collection of something that refers to an object, you must use a pointer:

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int x, y;
string& a1[] = {x, y};             // error: array of references
string* a2[] = {&x, &y};           // OK
vector<string&> s1 = {x , y};      // error: vector of references
vector<string*> s2 = {&x, &y};     // OK

Once we leave the cases where C++ leaves no choice for the programmer, we enter the domain of aesthetics. Ideally, we will make our choices so as to minimize the probability of error and in particular to maximize readability of code.

If you need a notion of “no value,” pointers offer nullptr. There is no equivalent “null reference,” so if you need a “no value,” using a pointer may be most appropriate. For example:

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void fp(X* p)
{
     if (p == nullptr) {
           // no value
     }
     else {
           // use *p
     }
}

void fr(X& r)   // common style
{
     // assume that r is valid and use it
}

If you really want to, you can construct and check for a “null reference” for a particular type:

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void fr2(X& r)
{
     if (&r == &nullX) {    // or maybe r==nullX
           // no value
     }
     else {
           // use r
     }
}

Obviously, you need to have suitably defined nullX. The style is not idiomatic and I don’t recommend it. A programmer is allowed to assume that a reference is valid. It is possible to create an invalid reference, but you have to go out of your way to do so. For example:

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char* ident(char* p) { return p; }

char& r {*ident(nullptr)}; // invalid code

This code is not valid C++ code. Don’t write such code even if your current implementation doesn’t catch it.

7.8. Advice

[1] Keep use of pointers simple and straightforward; §7.4.1.

[2] Avoid nontrivial pointer arithmetic; §7.4.

[3] Take care not to write beyond the bounds of an array; §7.4.1.

[4] Avoid multidimensional arrays; define suitable containers instead; §7.4.2.

[5] Use nullptr rather than 0 or NULL; §7.2.2.

[6] Use containers (e.g., vector, array, and valarray) rather than built-in (C-style) arrays; §7.4.1.

[7] Use string rather than zero-terminated arrays of char; §7.4.

[8] Use raw strings for string literals with complicated uses of backslash; §7.3.2.1.

[9] Prefer const reference arguments to plain reference arguments; §7.7.3.

[10] Use rvalue references (only) for forwarding and move semantics; §7.7.2.

[11] Keep pointers that represent ownership inside handle classes; §7.6.

[12] Avoid void* except in low-level code; §7.2.1.

[13] Use const pointers and const references to express immutability in interfaces; §7.5.

[14] Prefer references to pointers as arguments, except where “no object” is a reasonable option; §7.7.4.

8. Structures, Unions, and Enumerations

Form a more perfect Union.

– The people

• Introduction

• Structures

struct Layout; struct Names; Structures and Classes; Structures and Arrays; Type Equivalence; Plain Old Data; Fields

• Unions

Unions and Classes; Anonymous unions

• Enumerations

enum classes; Plain enums; Unnamed enums

• Advice

8.1. Introduction

The key to effective use of C++ is the definition and use of user-defined types. This chapter introduces the three most primitive variants of the notion of a user-defined type:

• A struct (a structure) is a sequence of elements (called members) of arbitrary types.

• A union is a struct that holds the value of just one of its elements at any one time.

• An enum (an enumeration) is a type with a set of named constants (called enumerators).

• enum class (a scoped enumeration) is an enum where the enumerators are within the scope of the enumeration and no implicit conversions to other types are provided.

Variants of these kinds of simple types have existed since the earliest days of C++. They are primarily focused on the representation of data and are the backbone of most C-style programming. The notion of a struct as described here is a simple form of a class (§3.2, Chapter 16).

8.2. Structures

An array is an aggregate of elements of the same type. In its simplest form, a struct is an aggregate of elements of arbitrary types. For example:

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struct Address {
     const char* name;       // "Jim Dandy"
     int number;             // 61
     const char* street;     // "South St"
     const char* town;       // "New Providence"
     char state[2];          // 'N' 'J'
     const char* zip;        // "07974"
};

This defines a type called Address consisting of the items you need in order to send mail to someone within the USA. Note the terminating semicolon.

Variables of type Address can be declared exactly like other variables, and the individual members can be accessed using the . (dot) operator. For example:

void f()
{
     Address jd;
     jd.name = "Jim Dandy";
     jd.number = 61;
}

Variables of struct types can be initialized using the {} notation (§6.3.5). For example:

Address jd = {
    "Jim Dandy",
    61, "South St",
    "New Providence",
    {'N','J'}, "07974"
};

Note that jd.state could not be initialized by the string "NJ". Strings are terminated by a zero character, '\0', so "NJ" has three characters – one more than will fit into jd.state. I deliberately use rather low-level types for the members to illustrate how that can be done and what kinds of problems it can cause.

Structures are often accessed through pointers using the –> (struct pointer dereference) operator. For example:

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void print_addr(Address* p)
{
     cout << p–>name << '\n'
          << p–>number << ' ' << p–>street << '\n'
          << p–>town << '\n'
          << p–>state[0] << p–>state[1] << ' ' << p–>zip << '\n';
}

When p is a pointer, p–>m is equivalent to (*p).m.

Alternatively, a struct can be passed by reference and accessed using the . (struct member access) operator:

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void print_addr2(const Address& r)
{
     cout << r.name << '\n'
          << r.number << ' ' << r.street << '\n'
          << r.town << '\n'
          << r.state[0] << r.state[1] << ' ' << r.zip << '\n';
}

Argument passing is discussed in §12.2.

Objects of structure types can be assigned, passed as function arguments, and returned as the result from a function. For example:

Address current;

Address set_current(Address next)
{
    address prev = current;
    current = next;
    return prev;
}

Other plausible operations, such as comparison (== and !=), are not available by default. However, the user can define such operators (§3.2.1.1, Chapter 18).

8.2.1. struct Layout

An object of a struct holds its members in the order they are declared. For example, we might store primitive equipment readout in a structure like this:

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struct Readout {
     char hour;     // [0:23]
     int value;
     char seq;      // sequence mark ['a':'z']
};

You could imagine the members of a Readout object laid out in memory like this:

Members are allocated in memory in declaration order, so the address of hour must be less than the address of value. See also §8.2.6.

However, the size of an object of a struct is not necessarily the sum of the sizes of its members. This is because many machines require objects of certain types to be allocated on architecture-dependent boundaries or handle such objects much more efficiently if they are. For example, integers are often allocated on word boundaries. On such machines, objects are said to have to be properly aligned (§6.2.9). This leads to “holes” in the structures. A more realistic layout of a Readout on a machine with 4-byte int would be:

In this case, as on many machines, sizeof(Readout) is 12, and not 6 as one would naively expect from simply adding the sizes of the individual members.

You can minimize wasted space by simply ordering members by size (largest member first). For example:

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struct Readout {
     int value;
     char hour;    // [0:23]
     char seq;     // sequence mark ['a':'z']
};

This would give us:

Note that this still leaves a 2-byte “hole” (unused space) in a Readout and sizeof(Readout)==8. The reason is that we need to maintain alignment when we put two objects next to each other, say, in an array of Readouts. The size of an array of 10 Readout objects is 10*sizeof(Readout).

It is usually best to order members for readability and sort them by size only if there is a demonstrated need to optimize.

Use of multiple access specifiers (i.e., public, private, or protected) can affect layout (§20.5).

8.2.2. struct Names

The name of a type becomes available for use immediately after it has been encountered and not just after the complete declaration has been seen. For example:

struct Link {
     Link* previous;
     Link* successor;
};

However, it is not possible to declare new objects of a struct until its complete declaration has been seen. For example:

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struct No_good {
     No_good member;  // error: recursive definition
};

This is an error because the compiler is not able to determine the size of No_good. To allow two (or more) structs to refer to each other, we can declare a name to be the name of a struct. For example:

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struct List;       // struct name declaration: List to be defined later

struct Link {
     Link* pre;
     Link* suc;
     List* member_of;
     int data;
};

struct List {
     Link* head;
};

Without the first declaration of List, use of the pointer type List* in the declaration of Link would have been a syntax error.

The name of a struct can be used before the type is defined as long as that use does not require the name of a member or the size of the structure to be known. However, until the completion of the declaration of a struct, that struct is an incomplete type. For example:

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struct S; // "S" is the name of some type

extern S a;
S f();
void g(S);
S* h(S*);

However, many such declarations cannot be used unless the type S is defined:

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void k(S* p)
{
     S a;           // error: S not defined; size needed to allocate

     f();           // error: S not defined; size needed to return value
     g(a);          // error: S not defined; size needed to pass argument
     p–>m = 7;      // error: S not defined; member name not known

     S* q = h(p);   // ok: pointers can be allocated and passed
     q–>m = 7;      // error: S not defined; member name not known
}

For reasons that reach into the prehistory of C, it is possible to declare a struct and a non-struct with the same name in the same scope. For example:

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struct stat { /* ... */ };
int stat(char* name, struct stat* buf);

In that case, the plain name (stat) is the name of the non-struct, and the struct must be referred to with the prefix struct. Similarly, the keywords class, union (§8.3), and enum (§8.4) can be used as prefixes for disambiguation. However, it is best not to overload names to make such explicit disambiguation necessary.

8.2.3. Structures and Classes

A struct is simply a class where the members are public by default. So, a struct can have member functions (§2.3.2, Chapter 16). In particular, a struct can have constructors. For example:

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struct Points {
     vector<Point> elem;// must contain at least one Point
     Points(Point p0) { elem.push_back(p0);}
     Points(Point p0, Point p1) { elem.push_back(p0); elem.push_back(p1); }
     // ...
};

Points x0;                          // error: no default constructor
Points x1{ {100,200} };             // one Point
Points x1{ {100,200}, {300,400} };  // two Points

You do not need to define a constructor simply to initialize members in order. For example:

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struct Point {
     int x, y;
};

Point p0;        // danger: uninitialized if in local scope (§6.3.5.1)
Point p1 {};     // default construction: {{},{}}; that is {0.0}
Point p2 {1};    // the second member is default constructed: {1,{}}; that is {1,0}
Point p3 {1,2};  // {1,2}

Constructors are needed if you need to reorder arguments, validate arguments, modify arguments, establish invariants (§2.4.3.2, §13.4), etc. For example:

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struct Address {
     string name;       // "Jim Dandy"
     int number;        // 61
     string street;     // "South St"
     string town;       // "New Providence"
     char state[2];     // 'N' 'J'
     char zip[5];       // 07974

     Address(const string n, int nu, const string& s, const string& t, const string& st, int z);
};

Here, I added a constructor to ensure that every member was initialized and to allow me to use a string and an int for the postal code, rather than fiddling with individual characters. For example:

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Address jd = {
    "Jim Dandy",
    61, "South St",
    "New Providence",
    "NJ", 7974            // (07974 would be octal; §6.2.4.1)
};

The Address constructor might be defined like this:

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Address::Address(const string& n, int nu, const string& s, const string& t, const string& st, int z)
                  // validate postal code
    :name{n},
    number{nu},
    street{s},
    town{t}
{
    if (st.size()!=2)
           error("State abbreviation should be two characters")
    state = {st[0],st[1]};     // store postal code as characters
    ostringstream ost;         // an output string stream; see §38.4.2
    ost << z;                  // extract characters from int
    string zi {ost.str()};
    switch (zi.size()) {
    case 5:
         zip = {zi[0], zi[1], zi[2], zi[3], zi[4]};
         break;
    case 4:  // starts with '0'
         zip = {'0', zi[0], zi[1], zi[2], zi[3]};
         break;
    default:
         error("unexpected ZIP code format");
    }
    // ... check that the code makes sense ...
}

8.2.4. Structures and Arrays

Naturally, we can have arrays of structs and structs containing arrays. For example:

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struct Point {
     int x,y
};

Point points[3] {{1,2},{3,4},{5,6}};
int x2 = points[2].x;

struct Array {
     Point elem[3];
};

Array points2 {{1,2},{3,4},{5,6}};
int y2 = points2.elem[2].y;

Placing a built-in array in a struct allows us to treat that array as an object: we can copy the struct containing it in initialization (including argument passing and function return) and assignment. For example:

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Array shift(Array a, Point p)
{
     for (int i=0; i!=3; ++i) {
           a.elem[i].x += p.x;
           a.elem[i].y += p.y;
     }
     return a;
}

Array ax = shift(points2,{10,20});

The notation for Array is a bit primitive: Why i!=3? Why keep repeating .elem[i]? Why just elements of type Point? The standard library provides std::array (§34.2.1) as a more complete and elegant development of the idea of a fixed-size array as a struct:

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template<typename T, size_t N>
struct array { // simplified (see §34.2.1)
     T elem[N];

     T* begin() noexcept { return elem; }
     const T* begin() const noexcept {return elem; }
     T* end() noexcept { return elem+N; } const T* end()
     const noexcept { return elem+N; }

     constexpr size_t size() noexcept;

     T& operator[](size_t n) { return elem[n]; }
     const T& operator[](size_type n) const { return elem[n]; }

     T* data() noexcept { return elem; }
     const T * data() const noexcept { return elem; }

     // ...
};

This array is a template to allow arbitrary numbers of elements of arbitrary types. It also deals directly with the possibility of exceptions (§13.5.1.1) and const objects (§16.2.9.1). Using array, we can now write:

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struct Point {
     int x,y
};

using Array = array<Point,3>; // array of 3 Points

Array points {{1,2},{3,4},{5,6}};
int x2 = points[2].x;
int y2 = points[2].y;

Array shift(Array a, Point p)
{
     for (int i=0; i!=a.size(); ++i) {
           a[i].x += p.x;
           a[i].y += p.y;
     }
     return a;
}

Array ax = shift(points,{10,20});

The main advantages of std::array over a built-in array are that it is a proper object type (has assignment, etc.) and does not implicitly convert to a pointer to an individual element:

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ostream& operator<<(ostream& os, Point p)
{
     cout << '{' << p[i].x << ',' << p[i].y << '}';
}

void print(Point a[],int s) // must specify number of elements
{
     for (int i=0; i!=s; ++i)
           cout << a[i] << '\n';
}

template<typename T, int N>
void print(array<T,N>& a)
{
     for (int i=0; i!=a.size(); ++i)
           cout << a[i] << '\n';
}

Point point1[] = {{1,2},{3,4},{5,6}};          // 3 elements
array<Point,3> point2 = {{1,2},{3,4},{5,6}};   // 3 elements

void f()
{
     print(point1,4);    // 4 is a bad error
     print(point2);
}

The disadvantage of std::array compared to a built-in array is that we can’t deduce the number of elements from the length of the initializer:

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Point point1[] = {{1,2},{3,4},{5,6}};           // 3 elements
array<Point,3> point2 = {{1,2},{3,4},{5,6}};    // 3 elements
array<Point> point3 = {{1,2},{3,4},{5,6}};      // error: number of elements not given

8.2.5. Type Equivalence

Two structs are different types even when they have the same members. For example:

struct S1 { int a; };
struct S2 { int a; };

S1 and S2 are two different types, so:

S1 x;
S2 y = x; // error: type mismatch

A struct is also a different type from a type used as a member. For example:

S1 x;
int i = x;  // error: type mismatch

Every struct must have a unique definition in a program (§15.2.3).

8.2.6. Plain Old Data

Sometimes, we want to treat an object as just “plain old data” (a contiguous sequence of bytes in memory) and not worry about more advanced semantic notions, such as run-time polymorphism (§3.2.3, §20.3.2), user-defined copy semantics (§3.3, §17.5), etc. Often, the reason for doing so is to be able to move objects around in the most efficient way the hardware is capable of. For example, copying a 100-element array using 100 calls of a copy constructor is unlikely to be as fast as calling std::memcpy(), which typically simply uses a block-move machine instruction. Even if the constructor is inlined, it could be hard for an optimizer to discover this optimization. Such “tricks” are not uncommon, and are important, in implementations of containers, such as vector, and in low-level I/O routines. They are unnecessary and should be avoided in higher-level code.

So, a POD (“Plain Old Data”) is an object that can be manipulated as “just data” without worrying about complications of class layouts or user-defined semantics for construction, copy, and move. For example:

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struct S0 { };                                                // a POD
struct S1 { int a; };                                         // a POD
struct S2 { int a; S2(int aa) : a(aa) { } };                  // not a POD (no default constructor)
struct S3 { int a; S3(int aa) : a(aa) { } S3() {} };          // a POD (user-defined default constructor)
struct S4 { int a; S4(int aa) : a(aa) { } S4() = default; };  // a POD
struct S5 { virtual void f(); /* ... */ };                    // not a POD (has a virtual function)

struct S6 : S1 { };              // a POD
struct S7 : S0 { int b; };       // a POD
struct S8 : S1 { int b; };       // not a POD (data in both S1 and S8)
struct S9 : S0, S1 {};           // a POD

For us to manipulate an object as “just data” (as a POD), the object must

• not have a complicated layout (e.g., with a vptr; (§3.2.3, §20.3.2),

• not have nonstandard (user-defined) copy semantics, and

• have a trivial default constructor.

Obviously, we need to be precise about the definition of POD so that we only use such optimizations where they don’t break any language guarantees. Formally (§iso.3.9, §iso.9), a POD object must be of

• a standard layout type, and

• a trivially copyable type,

• a type with a trivial default constructor.

A related concept is a trivial type, which is a type with

• a trivial default constructor and

• trivial copy and move operations

Informally, a default constructor is trivial if it does not need to do any work (use =default if you need to define one §17.6.1).

A type has standard layout unless it

• has a non-static member or a base that is not standard layout,

• has a virtual function (§3.2.3, §20.3.2),

• has a virtual base (§21.3.5),

• has a member that is a reference (§7.7),

• has multiple access specifiers for non-static data members (§20.5), or

• prevents important layout optimizations

• by having non-static data members in more than one base class or in both the derived class and a base, or

• by having a base class of the same type as the first non-static data member.

Basically, a standard layout type is one that has a layout with an obvious equivalent in C and is in the union of what common C++ Application Binary Interfaces (ABIs) can handle.

A type is trivially copyable unless it has a nontrivial copy operation, move operation, or destructor (§3.2.1.2, §17.6). Informally, a copy operation is trivial if it can be implemented as a bitwise copy. So, what makes a copy, move, or destructor nontrivial?

• It is user-defined.

• Its class has a virtual function.

• Its class has a virtual base.

• Its class has a base or a member that is not trivial.

An object of built-in type is trivially copyable, and has standard layout. Also, an array of trivially copyable objects is trivially copyable and an array of standard layout objects has standard layout. Consider an example:

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template<typename T>
    void mycopy(T* to, const T* from, int count);

I’d like to optimize the simple case where T is a POD. I could do that by only calling mycopy() for PODs, but that’s error-prone: if I use mycopy() can I rely on a maintainer of the code to remember never to call mycopy() for non-PODs? Realistically, I cannot. Alternatively, I could call std::copy(), which is most likely implemented with the necessary optimization. Anyway, here is the general and optimized code:

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template<typename T>
void mycopy(T* to, const T* from, int count)
{
     if (is_pod<T>::value)
           memcpy(to,from,count*sizeof(T));
     else
           for (int i=0; i!=count; ++i)
                 to[i]=from[i];
}

The is_pod is a standard-library type property predicate (§35.4.1) defined in <type_traits> allowing us to ask the question “Is T a POD?” in our code. The best thing about is_pod<T> is that it saves us from remembering the exact rules for what a POD is.

Note that adding or subtracting non-default constructors does not affect layout or performance (that was not true in C++98).

If you feel an urge to become a language lawyer, study the layout and triviality concepts in the standard (§iso.3.9, §iso.9) and try to think about their implications to programmers and compiler writers. Doing so might cure you of the urge before it has consumed too much of your time.

8.2.7. Fields

It seems extravagant to use a whole byte (a char or a bool) to represent a binary variable – for example, an on/off switch – but a char is the smallest object that can be independently allocated and addressed in C++ (§7.2). It is possible, however, to bundle several such tiny variables together as fields in a struct. A field is often called a bit-field. A member is defined to be a field by specifying the number of bits it is to occupy. Unnamed fields are allowed. They do not affect the meaning of the named fields, but they can be used to make the layout better in some machine-dependent way:

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struct PPN {      // R6000 Physical Page Number
    unsigned int PFN : 22;  // Page Frame Number
    int : 3;                // unused
    unsigned int CCA : 3;         // Cache Coherency Algorithm
    bool nonreachable : 1;
    bool dirty : 1;
    bool valid : 1;
    bool global : 1;
};

This example also illustrates the other main use of fields: to name parts of an externally imposed layout. A field must be of an integral or enumeration type (§6.2.1). It is not possible to take the address of a field. Apart from that, however, it can be used exactly like other variables. Note that a bool field really can be represented by a single bit. In an operating system kernel or in a debugger, the type PPN might be used like this:

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void part_of_VM_system(PPN* p)
{
     // ...
     if (p–>dirty) { // contents changed
           // copy to disk
           p–>dirty = 0;
     }
}

Surprisingly, using fields to pack several variables into a single byte does not necessarily save space. It saves data space, but the size of the code needed to manipulate these variables increases on most machines. Programs have been known to shrink significantly when binary variables were converted from bit-fields to characters! Furthermore, it is typically much faster to access a char or an int than to access a field. Fields are simply a convenient shorthand for using bitwise logical operators (§11.1.1) to extract information from and insert information into part of a word.

8.3. Unions

A union is a struct in which all members are allocated at the same address so that the union occupies only as much space as its largest member. Naturally, a union can hold a value for only one member at a time. For example, consider a symbol table entry that holds a name and a value:

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enum Type { str, num };

struct Entry {
     char* name;
     Type t;
     char* s;  // use s if t==str
     int i;    // use i if t==num
};

void f(Entry* p)
{
     if (p–>t == str)
           cout << p–>s;
     // ...
}

The members s and i can never be used at the same time, so space is wasted. It can be easily recovered by specifying that both should be members of a union, like this:

union Value {
     char* s;
     int i;
};

The language doesn’t keep track of which kind of value is held by a union, so the programmer must do that:

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struct Entry {
     char* name;
     Type t;
     Value v; // use v.s if t==str; use v.i if t==num
};

void f(Entry* p)
{
     if (p–>t == str)
           cout << p–>v.s;
     // ...
}

To avoid errors, one can encapsulate a union so that the correspondence between a type field and access to the union members can be guaranteed (§8.3.2).

Unions are sometimes misused for “type conversion.” This misuse is practiced mainly by programmers trained in languages that do not have explicit type conversion facilities, so that cheating is necessary. For example, the following “converts” an int to an int* simply by assuming bitwise equivalence:

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union Fudge {
     int i;
     int* p;
};

int* cheat(int i)
{
     Fudge a;
     a.i = i;
     return a.p;     // bad use
}

This is not really a conversion at all. On some machines, an int and an int* do not occupy the same amount of space, while on others, no integer can have an odd address. Such use of a union is dangerous and nonportable. If you need such an inherently ugly conversion, use an explicit type conversion operator (§11.5.2) so that the reader can see what is going on. For example:

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int* cheat2(int i)
{
     return reinterpret_cast<int*>(i);    // obviously ugly and dangerous
}

Here, at least the compiler has a chance to warn you if the sizes of objects are different and such code stands out like the sore thumb it is.

Use of unions can be essential for compactness of data and through that for performance. However, most programs don’t improve much from the use of unions and unions are rather error-prone. Consequently, I consider unions an overused feature; avoid them when you can.

8.3.1. Unions and Classes

Many nontrivial unions have a member that is much larger than the most frequently used members. Because the size of a union is at least as large as its largest member, space is wasted. This waste can often be eliminated by using a set of derived classes (§3.2.2, Chapter 20) instead of a union.

Technically, a union is a kind of a struct (§8.2) which in turn is a kind of a class (Chapter 16). However, many of the facilities provided for classes are not relevant for unions, so some restrictions are imposed on unions:

[1] A union cannot have virtual functions.

[2] A union cannot have members of reference type.

[3] A union cannot have base classes.

[4] If a union has a member with a user-defined constructor, a copy operation, a move operation, or a destructor, then that special function is deleted (§3.3.4, §17.6.4) for that union; that is, it cannot be used for an object of the union type.

[5] At most one member of a union can have an in-class initializer (§17.4.4).

[6] A union cannot be used as a base class.

These restrictions prevent many subtle errors and simplify the implementation of unions. The latter is important because the use of unions is often an optimization and we won’t want “hidden costs” imposed to compromise that.

The rule that deletes constructors (etc.) from a union with a member that has a constructor (etc.) keeps simple unions simple and forces the programmer to provide complicated operations if they are needed. For example, since Entry has no member with constructors, destructors, or assignments, we can create and copy Entrys freely. For example:

void f(Entry a)
{
     Entry b = a;
};

Doing so with a more complicated union would cause implementation difficulties or errors:

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union U {
     int m1;
     complex<double> m2;   // complex has a constructor
     string m3;            // string has a constructor (maintaining a serious invariant)
};

To copy a U we would have to decide which copy operation to use. For example:

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void f2(U x)
{
     U u;                   // error: which default constructor?
     U u2 = x;              // error: which copy constructor?
     u.m1 = 1;              // assign to int member
     string s = u.m3;       // disaster: read from string member
     return;                // error: which destructors are called for x, u, and u2?
}

It’s illegal to write one member and then read another, but people do that nevertheless (usually by mistake). In this case, the string copy constructor would be called with an invalid argument. It is fortunate that U won’t compile. When needed, a user can define a class containing a union that properly handles union members with constructors, destructors, and assignments (§8.3.2). If desired, such a class can also prevent the error of writing one member and then reading another.

It is possible to specify an in-class initializer for at most one member. If so, this initializer will be used for default initialization. For example:

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union U2 {
     int a;
     const char* p {""};
};

U2 x1;         // default initialized to x1.p == ""
U2 x2 {7};     // x2.a == 7

8.3.2. Anonymous unions

To see how we can write a class that overcomes the problems with misuse of a union, consider a variant of Entry (§8.3):

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class Entry2 { // two alternative representations represented as a union
private:
     enum class Tag { number, text };
     Tag type; // discriminant

     union {   // representation
         int i;
         string s; // string has default constructor, copy operations, and destructor
     };
public:
     struct Bad_entry { };     // used for exceptions

     string name;

     ~Entry2();
     Entry2& operator=(const Entry2&);     // necessary because of the string variant
     Entry2(const Entry2&);
     // ...

     int number() const;
     string text() const;

     void set_number(int n);
     void set_text(const string&);
     // ...
};

I’m not a fan of get/set functions, but in this case we really need to perform a nontrivial user-specified action on each access. I chose to name the “get” function after the value and use the set_ prefix for the “set” function. That happens to be my favorite among the many naming conventions.

The read-access functions can be defined like this:

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int Entry2::number() const
{
     if (type!=Tag::number) throw Bad_entry{};
     return i;
};

string Entry2::text() const
{
     if (type!=Tag::text) throw Bad_entry{};
     return s;
};

These access functions check the type tag, and if it is the one that correctly corresponds to the access we want, it returns a reference to the value; otherwise, it throws an exception. Such a union is often called a tagged union or a discriminated union.

The write-access functions basically do the same checking of the type tag, but note how setting a new value must take the previous value into account:

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void Entry2::set_number(int n)
{
     if (type==Tag::text) {
           s.~string();             // explicitly destroy string (§11.2.4)
           type = Tag::number;
     }
     i = n;
}

void Entry2::set_text(const string& ss)
{
     if (type==Tag::text)
           s = ss;
     else {
           new(&s) string{ss};      // placement new: explicitly construct string (§11.2.4)
           type = Tag::text;
     }
}

The use of a union forces us to use otherwise obscure and low-level language facilities (explicit construction and destruction) to manage the lifetime of the union elements. This is another reason to be wary of using unions.

Note that the union in the declaration of Entry2 is not named. That makes it an anonymous union. An anonymous union is an object, not a type, and its members can be accessed without mentioning an object name. That means that we can use members of an anonymous union exactly as we use other members of a class – as long as we remember that union members really can be used only one at a time.

Entry2 has a member of a type with a user-defined assignment operator, string, so Entry2’s assignment operator is deleted (§3.3.4, §17.6.4). If we want to assign Entry2s, we have to define Entry2::operator=(). Assignment combines the complexities of reading and writing but is otherwise logically similar to the access functions:

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Entry2& Entry2::operator=(const Entry2& e) // necessary because of the string variant
{
     if (type==Tag::text && e.type==Tag::text) {
           s = e.s;     // usual string assignment
           return *this;
     }

     if (type==Tag::text) s.~string(); // explicit destroy (§11.2.4)

     switch (e.type) {
     case Tag::number:
          i = e.i;
          break;
     case Tag::text:
          new(&s)(e.s); // placement new: explicit construct (§11.2.4)
          type = e.type;
     }

     return *this;
}

Constructors and a move assignment can be defined similarly as needed. We need at least a constructor or two to establish the correspondence between the type tag and a value. The destructor must handle the string case:

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Entry2::~Entry2()
{
     if (type==Tag::text) s.~string(); // explicit destroy (§11.2.4)
}

8.4. Enumerations

An enumeration is a type that can hold a set of integer values specified by the user (§iso.7.2). Some of an enumeration’s possible values are named and called enumerators. For example:

enum class Color { red, green, blue };

This defines an enumeration called Color with the enumerators red, green, and blue. “An enumeration” is colloquially shortened to “an enum.”

There are two kinds of enumerations:

[1] enum classes, for which the enumerator names (e.g., red) are local to the enum and their values do not implicitly convert to other types

[2] “Plain enums,” for which the enumerator names are in the same scope as the enum and their values implicitly convert to integers

In general, prefer the enum classes because they cause fewer surprises.

8.4.1. enum classes

An enum class is a scoped and strongly typed enumeration. For example:

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enum class Traffic_light { red, yellow, green };
enum class Warning { green, yellow, orange, red };// fire alert levels

Warning a1 = 7;                   // error: no int->Warning conversion
int a2 = green;                   // error: green not in scope
int a3 = Warning::green;          // error: no Warning->int conversion
Warning a4 = Warning::green;      // OK

void f(Traffic_light x)
{
     if (x == 9) { /* ... */ }                      // error: 9 is not a Traffic_light
     if (x == red) { /* ... */ }                    // error: no red in scope
     if (x == Warning::red) { /* ... */ }           // error: x is not a Warning
     if (x == Traffic_light::red) { /* ... */ }     // OK
}

Note that the enumerators present in both enums do not clash because each is in the scope of its own enum class.

An enumeration is represented by some integer type and each enumerator by some integer value. We call the type used to represent an enumeration its underlying type. The underlying type must be one of the signed or unsigned integer types (§6.2.4); the default is int. We could be explicit about that:

enum class Warning : int { green, yellow, orange, red }; // sizeof(Warning)==sizeof(int)

If we considered that too wasteful of space, we could instead use a char:

enum class Warning : char { green, yellow, orange, red }; // sizeof(Warning)==1

By default, enumerator values are assigned increasing from 0. Here, we get:

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static_cast<int>(Warning::green)==0
static_cast<int>(Warning::yellow)==1
static_cast<int>(Warning::orange)==2
static_cast<int>(Warning::red)==3

Declaring a variable Warning instead of plain int can give both the user and the compiler a hint as to the intended use. For example:

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void f(Warning key)
{
     switch (key) {
     case Warning::green:
         // do something
         break;
     case Warning::orange:
         // do something
         break;
    case Warning::red:
         // do something
         break;
     }
}

A human might notice that yellow was missing, and a compiler might issue a warning because only three out of four Warning values are handled.

An enumerator can be initialized by a constant expression (§10.4) of integral type (§6.2.1). For example:

enum class Printer_flags {
    acknowledge=1,
    paper_empty=2,
    busy=4,
    out_of_black=8,
    out_of_color=16,
    //
};

The values for the Printer_flags enumerators are chosen so that they can be combined by bitwise operations. An enum is a user-defined type, so we can define the | and & operators for it (§3.2.1.1, Chapter 18). For example:

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constexpr Printer_flags operator|(Printer_flags a, Printer_flags b)
{
    return static_cast<Printer_flags>(static_cast<int>(a))|static_cast<int>(b));
}

constexpr Printer_flags operator&(Printer_flags a, Printer_flags b)
{
    return static_cast<Printer_flags>(static_cast<int>(a))&static_cast<int>(b));
}

The explicit conversions are necessary because a class enum does not support implicit conversions. Given these definitions of | and & for Printer_flags, we can write:

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void try_to_print(Printer_flags x)
{
     if (x&Printer_flags::acknowledge) {
           // ...
     }
     else if (x&Printer_flags::busy) {
           // ...
     }
     else if (x&(Printer_flags::out_of_black|Printer_flags::out_of_color)) {
           // either we are out of black or we are out of color
           // ...
     }
     // ...
}

I defined operator|() and operator&() to be constexpr functions (§10.4, §12.1.6) because someone might want to use those operators in constant expressions. For example:

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void g(Printer_flags x)
{
     switch (x) {
     case Printer_flags::acknowledge:
          // ...
          break;
     case Printer_flags::busy:
          // ...
          break;
     case Printer_flags::out_of_black:
          // ...
          break;
     case Printer_flags::out_of_color:
          // ...
          break;
     case Printer_flags::out_of_black&Printer_flags::out_of_color:
          // we are out of black *and* out of color
          // ...
          break;
     }

     // ...
}

It is possible to declare an enum class without defining it (§6.3) until later. For example:

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enum class Color_code : char;     // declaration
void foobar(Color_code* p);       // use of declaration
// ...
enum class Color_code : char {    // definition
    red, yellow, green, blue
};

A value of integral type may be explicitly converted to an enumeration type. The result of such a conversion is undefined unless the value is within the range of the enumeration’s underlying type. For example:

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enum class Flag : char{ x=1, y=2, z=4, e=8 };

Flag f0 {};                         // f0 gets the default value 0
Flag f1 = 5;                        // type error: 5 is not of type Flag
Flag f2 = Flag{5};                  // error: no narrowing conversion to an enum class
Flag f3 = static_cast<Flag>(5);     // brute force
Flag f4 = static_cast<Flag>(999);   // error: 999 is not a char value (maybe not caught)

The last assignments show why there is no implicit conversion from an integer to an enumeration; most integer values do not have a representation in a particular enumeration.

Each enumerator has an integer value. We can extract that value explicitly. For example:

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int i = static_cast<int>(Flag::y);      // i becomes 2
char c = static_cast<char>(Flag::e);    // c becomes 8

The notion of a range of values for an enumeration differs from the enumeration notion in the Pascal family of languages. However, bit-manipulation examples that require values outside the set of enumerators to be well defined (e.g., the Printer_flags example) have a long history in C and C++.

The sizeof an enum class is the sizeof of its underlying type. In particular, if the underlying type is not explicitly specified, the size is sizeof(int).

8.4.2. Plain enums

A “plain enum” is roughly what C++ offered before the enum classes were introduced, so you’ll find them in lots of C and C++98-style code. The enumerators of a plain enum are exported into the enum’s scope, and they implicitly convert to values of some integer type. Consider the examples from §8.4.1 with the “class” removed:

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enum Traffic_light { red, yellow, green };
enum Warning { green, yellow, orange, red }; // fire alert levels

// error: two definitions of yellow (to the same value)
// error: two definitions of red (to different values)

Warning a1 = 7;                   // error: no int->Warning conversion
int a2 = green;                   // OK: green is in scope and converts to int
int a3 = Warning::green;          // OK: Warning->int conversion
Warning a4 = Warning::green;      // OK

void f(Traffic_light x)
{
     if (x == 9) { /* ... */ }                  // OK (but Traffic_light doesn't have a 9)
     if (x == red) { /* ... */ }                // error: two reds in scope
     if (x == Warning::red) { /* ... */ }       // OK (Ouch!)
     if (x == Traffic_light::red) { /* ... */ } // OK
}

We were “lucky” that defining red in two plain enumerations in a single scope saved us from hard-to-spot errors. Consider “cleaning up” the plain enums by disambiguating the enumerators (as is easily done in a small program but can be done only with great difficulty in a large one):

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enum Traffic_light { tl_red, tl_yellow, tl_green };
enum Warning { green, yellow, orange, red }; // fire alert levels

void f(Traffic_light x)
{
     if (x == red) { /* ... */ }                    // OK (ouch!)
     if (x == Warning::red) { /* ... */ }           // OK (ouch!)
     if (x == Traffic_light::red) { /* ... */ }     // error: red is not a Traffic_light value
}

The compiler accepts the x==red, which is almost certainly a bug. The injection of names into an enclosing scope (as enums, but not enum classes or classes, do) is namespace pollution and can be a major problem in larger programs (Chapter 14).

You can specify the underlying type of a plain enumeration, just as you can for enum classes. If you do, you can declare the enumerations without defining them until later. For example:

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enum Traffic_light : char { tl_red, tl_yellow, tl_green };  // underlying type is char

enum Color_code : char;       // declaration
void foobar(Color_code *p);   // use of declaration
// ...
enum Color_code : char { red, yellow, green, blue }; // definition

If you don’t specify the underlying type, you can’t declare the enum without defining it, and its underlying type is determined by a relatively complicated algorithm: when all enumerators are nonnegative, the range of the enumeration is [0:2k-1] where 2k is the smallest power of 2 for which all enumerators are within the range. If there are negative enumerators, the range is [-2k:2k-1]. This defines the smallest bit-field capable of holding the enumerator values using the conventional two’s complement representation. For example:

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enum E1 { dark, light };               // range 0:1
enum E2 { a = 3, b = 9 };              // range 0:15
enum E3 { min = –10, max = 1000000 };  // range -1048576:1048575

The rule for explicit conversion of an integer to a plain enum is the same as for the class enum except that when there is no explicit underlying type, the result of such a conversion is undefined unless the value is within the range of the enumeration. For example:

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enum Flag { x=1, y=2, z=4, e=8 };   // range 0:15

Flag f0 {};                         // f0 gets the default value 0
Flag f1 = 5;                        // type error: 5 is not of type Flag
Flag f2 = Flag{5};                  // error: no explicit conversion from int to Flag
Flag f2 = static_cast<Flag>(5);     // OK: 5 is within the range of Flag
Flag f3 = static_cast<Flag>(z|e);   // OK: 12 is within the range of Flag
Flag f4 = static_cast<Flag>(99);    // undefined: 99 is not within the range of Flag

Because there is an implicit conversion from a plain enum to its underlying type, we don’t need to define | to make this example work: z and e are converted to int so that z|e can be evaluated. The sizeof an enumeration is the sizeof its underlying type. If the underlying type isn’t explicitly specified, it is some integral type that can hold its range and not larger than sizeof(int), unless an enumerator cannot be represented as an int or as an unsigned int. For example, sizeof(e1) could be 1 or maybe 4 but not 8 on a machine where sizeof(int)==4.

8.4.3. Unnamed enums

A plain enum can be unnamed. For example:

enum { arrow_up=1, arrow_down, arrow_sideways };

We use that when all we need is a set of integer constants, rather than a type to use for variables.

8.5. Advice

[1] When compactness of data is important, lay out structure data members with larger members before smaller ones; §8.2.1.

[2] Use bit-fields to represent hardware-imposed data layouts; §8.2.7.

[3] Don’t naively try to optimize memory consumption by packing several values into a single byte; §8.2.7.

[4] Use unions to save space (represent alternatives) and never for type conversion; §8.3.

[5] Use enumerations to represent sets of named constants; §8.4.

[6] Prefer class enums over “plain” enums to minimize surprises; §8.4.

[7] Define operations on enumerations for safe and simple use; §8.4.1.

9. Statements

A programmer is a machine for turning caffeine into code.

– A programmer

• Introduction

• Statement Summary

• Declarations as Statements

• Selection Statements

if Statements; switch Statements; Declarations in Conditions

• Iteration Statements

Range-for Statements; for Statements; while Statements; do Statements; Loop exit

• goto Statements

• Comments and Indentation

• Advice

9.1. Introduction

C++ offers a conventional and flexible set of statements. Basically all that is either interesting or complicated is found in expressions and declarations. Note that a declaration is a statement and that an expression becomes a statement when you add a semicolon at its end.

Unlike an expression, a statement does not have a value. Instead, statements are used to specify the order of execution. For example:

Click here to view code image

a = b+c;        // expression statement
if (a==7)       // if-statement
      b = 9;    // execute if and only if a==9

Logically, a=b+c is executed before the if, as everyone would expect. A compiler may reorder code to improve performance as long as the result is identical to that of the simple order of execution.

9.2. Statement Summary

Here is a summary of C++ statements:

statement:
          declaration
          expressionopt ;
          { statement-listopt }
          try { statement-listopt } handler-list

          case constant-expression : statement
          default : statement
          break ;
          continue ;

          return expressionopt ;
          goto identifier ;
          identifier : statement

          selection-statement
          iteration-statement

selection-statement:
          if ( condition ) statement
          if ( condition ) statement else statement
          switch ( condition ) statement

iteration-statement:
          while ( condition ) statement
          do statement while ( expression ) ;
          for ( for-init-statement conditionopt ; expressionopt ) statement
          for ( for-init-declaration : expression ) statement

statement-list:
          statement statement-listopt

condition:
          expression
          type-specifier declarator = expression
          type-specifier declarator { expression }

handler-list:
          handler handler-listopt

handler:
          catch ( exception-declaration ) { statement-listopt}

A semicolon is by itself a statement, the empty statement.

A (possibly empty) sequence of statements within “curly braces” (i.e., { and }) is called a block or a compound statement. A name declared in a block goes out of scope at the end of its block (§6.3.4).

A declaration is a statement and there is no assignment statement or procedure-call statement; assignments and function calls are expressions.

A for-init-statement must be either a declaration or an expression-statement. Note that both end with a semicolon.

A for-init-declaration must be the declaration of a single uninitialized variable. The statements for handling exceptions, try-blocks, are described in §13.5.

9.3. Declarations as Statements

A declaration is a statement. Unless a variable is declared static, its initializer is executed whenever the thread of control passes through the declaration (see also §6.4.2). The reason for allowing declarations wherever a statement can be used (and a few other places; §9.4.3, §9.5.2) is to enable the programmer to minimize the errors caused by uninitialized variables and to allow better locality in code. There is rarely a reason to introduce a variable before there is a value for it to hold. For example:

void f(vector<string>& v, int i, const char* p)
{
     if (p==nullptr) return;
     if (i<0 || v.size()<=i)
           error("bad index");
     string s = v[i];
     if (s == p) {
           // ...
     }
     // ...
}

The ability to place declarations after executable code is essential for many constants and for single-assignment styles of programming where a value of an object is not changed after initialization. For user-defined types, postponing the definition of a variable until a suitable initializer is available can also lead to better performance. For example:

void use()
{
     string s1;
     s1 = "The best is the enemy of the good.";
     // ...
}

This requests a default initialization (to the empty string) followed by an assignment. This can be slower than a simple initialization to the desired value:

string s2 {"Voltaire"};

The most common reason to declare a variable without an initializer is that it requires a statement to give it its desired value. Input variables are among the few reasonable examples of that:

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void input()
{
     int buf[max];
     int count = 0;
     for (int i; cin>>i;) {
           if (i<0) error("unexpected negative value");
           if (count==max) error("buffer overflow");
           buf[count++] = i;
     }
     // ...
}

I assume that error() does not return; if it does, this code may cause a buffer overflow. Often, push_back() (§3.2.1.3, §13.6, §31.3.6) provides a better solution to such examples.

9.4. Selection Statements

A value can be tested by either an if-statement or a switch-statement:

if ( condition ) statement
if ( condition ) statement else statement
switch ( condition ) statement

A condition is either an expression or a declaration (§9.4.3).

9.4.1. if Statements

In an if-statement, the first (or only) statement is executed if the condition is true and the second statement (if it is specified) is executed otherwise. If a condition evaluates to something different from a Boolean, it is – if possible – implicitly converted to a bool. This implies that any arithmetic or pointer expression can be used as a condition. For example, if x is an integer, then

if (x) // ...

means

if (x != 0) // ...

For a pointer p,

if (p) // ...

is a direct statement of the test “Does p point to a valid object (assuming proper initialization)?” and is equivalent to

if (p != nullptr) // ...

Note that a “plain” enum can be implicitly converted to an integer and then to a bool, whereas an enum class cannot (§8.4.1). For example:

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enum E1 { a, b };
enum class E2 { a, b };

void f(E1 x, E2 y)
{
    if (x)         // OK
          // ...
    if (y)         // error: no conversion to bool
          // ...
    if (y==E2::a)  // OK
          // ...
}

The logical operators

&& || !

are most commonly used in conditions. The operators && and || will not evaluate their second argument unless doing so is necessary. For example,

if (p && 1<p–>count) // ...

This tests 1<p–>count only if p is not nullptr.

For choosing between two alternatives each of which produces a value, a conditional expression (§11.1.3) is a more direct expression of intent than an if-statement. For example:

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int max(int a, int b)
{
     return (a>b)?a:b;    // return the larger of a and b
}

A name can only be used within the scope in which it is declared. In particular, it cannot be used on another branch of an if-statement. For example:

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void f2(int i)
{
     if (i) {
            int x = i+2;
            ++x;
            // ...
     }
     else {
           ++x; // error: x is not in scope
     }
     ++x;       // error: x is not in scope
}

A branch of an if-statement cannot be just a declaration. If we need to introduce a name in a branch, it must be enclosed in a block (§9.2). For example:

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void f1(int i)
{
      if (i)
            int x = i+2;      // error: declaration of if-statement branch
}

9.4.2. switch Statements

A switch-statement selects among a set of alternatives (case-labels). The expression in the case labels must be a constant expression of integral or enumeration type. A value may not be used more than once for case-labels in a switch-statement. For example:

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void f(int i)
{
     switch (i) {
     case 2.7: // error: floating point uses for case
          // ...
     case 2:
          // ...
     case 4–2: // error: 2 used twice in case labels
          // ...
};

A switch-statement can alternatively be written as a set of if-statements. For example:

switch (val) {
case 1:
     f();
     break;
case 2:
     g();
     break;
default:
     h();
     break;
}

This could be expressed as:

if (val == 1)
       f();
else if (val == 2)
       g();
else
       h();

The meaning is the same, but the first (switch) version is preferred because the nature of the operation (testing a single value against a set of constants) is explicit. This makes the switch-statement easier to read for nontrivial examples. It typically also leads to the generation of better code because there is no reason to repeatedly check individual values. Instead, a jump table can be used.

Beware that a case of a switch must be terminated somehow unless you want to carry on executing the next case. Consider:

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switch (val) {           // beware
case 1:
     cout << "case 1\n";
case 2:
     cout << "case 2\n";
default:
     cout << "default: case not found\n";
}

Invoked with val==1, the output will greatly surprise the uninitiated:

case 1
case 2
default: case not found

It is a good idea to comment the (rare) cases in which a fall-through is intentional so that an uncommented fall-through can be assumed to be an error. For example:

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switch (action) {           // handle (action,value) pair
case do_and_print:
     act(value);
     // no break: fall through to print
case print:
     print(value);
     break;
// ...
}

A break is the most common way of terminating a case, but a return is often useful (§10.2.1).

When should a switch-statement have a default? There is no single answer that covers all situations. One use is for the default to handle the most common case. Another common use is the exact opposite: the default: action is simply a way to catch errors; every valid alternative is covered by the cases. However, there is one case where a default should not be used: if a switch is intended to have one case for each enumerator of an enumeration. If so, leaving out the default gives the compiler a chance to warn against a set of cases that almost but not quite match the set of enumerators. For example, this is almost certainly an error:

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enum class Vessel { cup, glass, goblet, chalice };

void problematic(Vessel v)
{
     switch (v) {
     case Vessel::cup:       /* ... */    break;
     case Vessel::glass:     /* ... */    break;
     case Vessel::goblet:    /* ... */    break;
     }
}

Such a mistake can easily occur when a new enumerator is added during maintenance.

Testing for an “impossible” enumerator value is best done separately.

9.4.2.1. Declarations in Cases

It is possible, and common, to declare variables within the block of a switch-statement. However, it is not possible to bypass an initialization. For example:

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void f(int i)
{
     switch (i) {
     case 0:
          int x;         // uninitialized
          int y = 3;     // error: declaration can be bypassed (explicitly initialized)
          string s;      // error: declaration can be bypassed (implicitly initialized)
     case 1:
          ++x;           // error: use of uninitialized object
          ++y;
          s = "nasty!";
     }
}

Here, if i==1, the thread of execution would bypass the initializations of y and s, so f() will not compile. Unfortunately, because an int needn’t be initialized, the declaration of x is not an error. However, its use is an error: we read an uninitialized variable. Unfortunately, compilers often give just a warning for the use of an uninitialized variable and cannot reliably catch all such misuses. As usual, avoid uninitialized variables (§6.3.5.1).

If we need a variable within a switch-statement, we can limit its scope by enclosing its declaration and its use in a block. For an example, see prim() in §10.2.1.

9.4.3. Declarations in Conditions

To avoid accidental misuse of a variable, it is usually a good idea to introduce the variable into the smallest scope possible. In particular, it is usually best to delay the definition of a local variable until one can give it an initial value. That way, one cannot get into trouble by using the variable before its initial value is assigned.

One of the most elegant applications of these two principles is to declare a variable in a condition. Consider:

if (double d = prim(true)) {
     left /= d;
     break;
}

Here, d is declared and initialized and the value of d after initialization is tested as the value of the condition. The scope of d extends from its point of declaration to the end of the statement that the condition controls. For example, had there been an else-branch to the if-statement, d would be in scope on both branches.

The obvious and traditional alternative is to declare d before the condition. However, this opens the scope (literally) for the use of d before its initialization or after its intended useful life:

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double d;
// ...
d2 = d; // oops!
// ...
if (d = prim(true)) {
      left /= d;
      break;
}
// ...
d = 2.0; // two unrelated uses of d

In addition to the logical benefits of declaring variables in conditions, doing so also yields the most compact source code.

A declaration in a condition must declare and initialize a single variable or const.

9.5. Iteration Statements

A loop can be expressed as a for-, while-, or do-statement:

while ( condition ) statement
do statement while ( expression ) ;
for ( for-init-statement conditionopt ; expressionopt ) statement
for ( for-declaration : expression ) statement

A for-init-statement must be either a declaration or an expression-statement. Note that both end with a semicolon.

The statement of a for-statement (called the controlled statement or the loop body) is executed repeatedly until the condition becomes false or the programmer breaks out of the loop some other way (such as a break, a return, a throw, or a goto).

More complicated loops can be expressed as an algorithm plus a lambda expression (§11.4.2).

9.5.1. Range-for Statements

The simplest loop is a range-for-statement; it simply gives the programmer access to each element of a range. For example:

int sum(vector<int>& v)
{
     int s = 0;
     for (int x : v)
           s+=x;
     return s;
}

The for (int x : v) can be read as “for each element x in the range v” or just “for each x in v.” The elements of v are visited in order from the first to the last.

The scope of the variable naming the element (here, x) is the for-statement.

The expression after the colon must denote a sequence (a range); that is, it must yield a value for which we can call v.begin() and v.end() or begin(v) and end(v) to obtain an iterators (§4.5):

[1] the compiler first looks for members begin and end and tries to use those. If a begin or an end is found that cannot be used as a range (e.g., because a member begin is a variable rather than a function), the range-for is an error.

[2] Otherwise, the compiler looks for a begin/end member pair in the enclosing scope. If none is found or if what is found cannot be used (e.g., because the begin did not take an argument of the sequence’s type), the range-for is an error.

The compiler uses v and v+N as begin(v) and end(v) for a built-in array T v[N]. The <iterator> header provides begin(c) and end(c) for built-in arrays and for all standard-library containers. For sequences of our own design, we can define begin() and end() in the same way as it is done for standard-library containers (§4.4.5).

The controlled variable, x in the example, that refers to the current element is equivalent to *p when using an equivalent for-statement:

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int sum2(vector<int>& v)
{
     int s = 0;
     for (auto p = begin(v); p!=end(v); ++p)
           s+=*p;
     return s;
}

If you need to modify an element in a range-for loop, the element variable should be a reference. For example, we can increment each element of a vector like this:

void incr(vector<int>& v)
{
     for (int& x : v)
           ++x;
}

References are also appropriate for elements that might be large, so that copying them to the element value could be costly. For example:

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template<class T> T accum(vector<T>& v)
{
     T sum = 0;
     for (const T& x : v)
           sum += x;
     return sum;
}

Note that a range-for loop is a deliberately simple construct. For example, using it you can’t touch two elements at the same time and can’t effectively traverse two ranges simultaneously. For that we need a general for-statement.

9.5.2. for Statements

There is also a more general for-statement allowing greater control of the iteration. The loop variable, the termination condition, and the expression that updates the loop variable are explicitly presented “up front” on a single line. For example:

void f(int v[], int max)
{
     for (int i = 0; i!=max; ++i)
           v[i] = i*i;
}

This is equivalent to

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void f(int v[], int max)
{
     int i = 0;       // introduce loop variable
     while (i!=max) {        // test termination condition
          v[i] = i*i; // execute the loop body
          ++i;        // increment loop variable
     }
}

A variable can be declared in the initializer part of a for-statement. If that initializer is a declaration, the variable (or variables) it introduced is in scope until the end of the for-statement.

It is not always obvious what is the right type to use for a controlled variable in a for loop, so auto often comes in handy:

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for (auto p = begin(c); c!=end(c); ++p) {
      // ... use iterator p for elements in container c ...
}

If the final value of an index needs to be known after exit from a for-loop, the index variable must be declared outside the for-loop (e.g., see §9.6).

If no initialization is needed, the initializing statement can be empty.

If the expression that is supposed to increment the loop variable is omitted, we must update some form of loop variable elsewhere, typically in the body of the loop. If the loop isn’t of the simple “introduce a loop variable, test the condition, update the loop variable” variety, it is often better expressed as a while-statement. However, consider this elegant variant:

for (string s; cin>>s;)
      v.push_back(s);

Here, the reading and testing for termination and combined in cin>>s, so we don’t need an explicit loop variable. On the other hand, the use of for, rather than while, allows us to limit the scope of the “current element,” s, to the loop itself (the for-statement).

A for-statement is also useful for expressing a loop without an explicit termination condition:

for (;;) { // "forever"
      // ...
}

However, many consider this idiom obscure and prefer to use:

while(true) {    // "forever"
     // ...
}

9.5.3. while Statements

A while-statement executes its controlled statement until its condition becomes false. For example:

template<class Iter, class Value>
Iter find(Iter first, Iter last, Value val)
{
      while (first!=last && *first!=val)
           ++first;
      return first;
}

I tend to prefer while-statements over for-statements when there isn’t an obvious loop variable or where the update of a loop variable naturally comes in the middle of the loop body.

A for-statement (§9.5.2) is easily rewritten into an equivalent while-statement and vice versa.

9.5.4. do Statements

A do-statement is similar to a while-statement except that the condition comes after the body. For example:

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void print_backwards(char a[], int i)    // i must be positive
{
     cout << '{';
     do {
          cout << a[––i];
     } while (i);
     cout << '}';
}

This might be called like this: print_backwards(s,strlen(s)); but it is all too easy to make a horrible mistake. For example, what if s was the empty string?

In my experience, the do-statement is a source of errors and confusion. The reason is that its body is always executed once before the condition is evaluated. However, for the body to work correctly, something very much like the condition must hold even the first time through. More often than I would have guessed, I have found that condition not to hold as expected either when the program was first written and tested or later after the code preceding it has been modified. I also prefer the condition “up front where I can see it.” Consequently, I recommend avoiding do-statements.

9.5.5. Loop Exit

If the condition of an iteration statement (a for-, while-, or do-statement) is omitted, the loop will not terminate unless the user explicitly exits it by a break, return (§12.1.4), goto (§9.6), throw (§13.5), or some less obvious way such as a call of exit() (§15.4.3). A break “breaks out of” the nearest enclosing switch-statement (§9.4.2) or iteration-statement. For example:

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void f(vector<string>& v, string terminator)
{
     char c;
     string s;
     while (cin>>c) {
          // ...
          if (c == '\n') break;
          // ...
     }
}

We use a break when we need to leave the loop body “in the middle.” Unless it warps the logic of a loop (e.g., requires the introduction of an extra varible), it is usually better to have the complete exit condition as the condition of a while-statement or a for-statement.

Sometimes, we don’t want to exit the loop completely, we just want to get to the end of the loop body. A continue skips the rest of the body of an iteration-statement. For example:

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void find_prime(vector<string>& v)
{
     for (int i = 0; i!=v.size(); ++i) {
           if (!prime(v[i]) continue;
           return v[i];
     }
}

After a continue, the increment part of the loop (if any) is executed, followed by the loop condition (if any). So find_prime() could equivalently have been written as:

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void find_prime(vector<string>& v)
{
     for (int i = 0; i!=v.size(); ++i) {
           if (!prime(v[i]) {
                 return v[i];
           }
     }
}

9.6. goto Statements

C++ possesses the infamous goto:

goto identifier ;
identifier : statement

The goto has few uses in general high-level programming, but it can be very useful when C++ code is generated by a program rather than written directly by a person; for example, gotos can be used in a parser generated from a grammar by a parser generator.

The scope of a label is the function it is in (§6.3.4). This implies that you can use goto to jump both into and out of blocks. The only restriction is that you cannot jump past an initializer or into an exception handler (§13.5).

One of the few sensible uses of goto in ordinary code is to break out from a nested loop or switch-statement (a break breaks out of only the innermost enclosing loop or switch-statement). For example:

Click here to view code image

void do_something(int i, int j)
     // do something to a two-dimensional matrix called mn
{
     for (i = 0; i!=n; ++i)
          for (j = 0; j!=m; ++j)
                if (nm[i][j] == a)
                      goto found;
     // not found
     // ...
found:
     // nm[i][j] == a
}

Note that this goto just jumps forward to exit its loop. It does not introduce a new loop or enter a new scope. That makes it the least troublesome and least confusing use of a goto.

9.7. Comments and Indentation

Judicious use of comments and consistent use of indentation can make the task of reading and understanding a program much more pleasant. Several different consistent styles of indentation are in use. I see no fundamental reason to prefer one over another (although, like most programmers, I have my preferences, and this book reflects them). The same applies to styles of comments.

Comments can be misused in ways that seriously affect the readability of a program. The compiler does not understand the contents of a comment, so it has no way of ensuring that a comment

• is meaningful,

• describes the program, and

• is up to date.

Most programs contain comments that are incomprehensible, ambiguous, and just plain wrong. Bad comments can be worse than no comments.

If something can be stated in the language itself, it should be, and not just mentioned in a comment. This remark is aimed at comments such as these:

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// variable "v" must be initialized

// variable "v" must be used only by function "f()"

// call function "init()" before calling any other function in this file

// call function "cleanup()" at the end of your program

// don't use function "weird()"

// function "f(int ...)" takes two or three arguments

Such comments can typically be rendered unnecessary by proper use of C++.

Once something has been stated clearly in the language, it should not be mentioned a second time in a comment. For example:

a = b+c; // a becomes b+c
count++; // increment the counter

Such comments are worse than simply redundant. They increase the amount of text the reader has to look at, they often obscure the structure of the program, and they may be wrong. Note, however, that such comments are used extensively for teaching purposes in programming language textbooks such as this. This is one of the many ways a program in a textbook differs from a real program.

A good comment states what a piece of code is supposed to do (the intent of the code), whereas the code (only) states what it does (in terms of how it does it). Preferably, a comment is expressed at a suitably high level of abstraction so that it is easy for a human to understand without delving into minute details.

My preference is for:

• A comment for each source file stating what the declarations in it have in common, references to manuals, the name of the programmer, general hints for maintenance, etc.

• A comment for each class, template, and namespace

• A comment for each nontrivial function stating its purpose, the algorithm used (unless it is obvious), and maybe something about the assumptions it makes about its environment

• A comment for each global and namespace variable and constant

• A few comments where the code is nonobvious and/or nonportable

• Very little else

For example:

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//    tbl.c: Implementation of the symbol table.

/*
      Gaussian elimination with partial pivoting.
      See Ralston: "A first course ..." pg 411.
*/

//    scan(p,n,c) requires that p points to an array of at least n elements

// sort(p,q) sorts the elements of the sequence [p:q) using < for comparison.

// Revised to handle invalid dates. Bjarne Stroustrup, Feb 29 2013

A well-chosen and well-written set of comments is an essential part of a good program. Writing good comments can be as difficult as writing the program itself. It is an art well worth cultivating.

Note that /* */ style comments do not nest. For example:

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/*
     remove expensive check
     if (check(p,q)) error("bad p q") /* should never happen */
*/

This nesting should give an error for an unmatched final */.

9.8. Advice

[1] Don’t declare a variable until you have a value to initialize it with; §9.3, §9.4.3, §9.5.2.

[2] Prefer a switch-statement to an if-statement when there is a choice; §9.4.2.

[3] Prefer a range-for-statement to a for-statement when there is a choice; §9.5.1.

[4] Prefer a for-statement to a while-statement when there is an obvious loop variable; §9.5.2.

[5] Prefer a while-statement to a for-statement when there is no obvious loop variable; §9.5.3.

[6] Avoid do-statements; §9.5.

[7] Avoid goto; §9.6.

[8] Keep comments crisp; §9.7.

[9] Don’t say in comments what can be clearly stated in code; §9.7.

[10] State intent in comments; §9.7.

[11] Maintain a consistent indentation style; §9.7.

10. Expressions

Programming is like sex: It may give some concrete results, but that is not why we do it.

– apologies to Richard Feynman

• Introduction

• A Desk Calculator

The Parser; Input; Low-Level Input; Error Handling; The Driver; Headers; Command-Line Arguments; A Note on Style

• Operator Summary

Results; Order of Evaluation; Operator Precedence; Temporary Objects

• Constant Expressions

Symbolic Constants; consts in Constant Expressions; Literal Types; Reference Arguments; Address Constant Expressions

• Implicit Type Conversion

Promotions; Conversions; Usual Arithmetic Conversions

• Advice

10.1. Introduction

This chapter discusses expressions in some detail. In C++, an assignment is an expression, a function call is an expression, the construction of an object is an expression, and so are many other operations that go beyond conventional arithmetic expression evaluation. To give an impression of how expressions are used and to show them in context, I first present a small complete program, a simple “desk calculator.” Next, the complete set of operators is listed and their meaning for builtin types is briefly outlined. The operators that require more extensive explanation are discussed in Chapter 11.

10.2. A Desk Calculator

Consider a simple desk calculator program that provides the four standard arithmetic operations as infix operators on floating-point numbers. The user can also define variables. For example, given the input

r = 2.5
area = pi * r * r

(pi is predefined) the calculator program will write

2.5
19.635

where 2.5 is the result of the first line of input and 19.635 is the result of the second.

The calculator consists of four main parts: a parser, an input function, a symbol table, and a driver. Actually, it is a miniature compiler in which the parser does the syntactic analysis, the input function handles input and lexical analysis, the symbol table holds permanent information, and the driver handles initialization, output, and errors. We could add many features to this calculator to make it more useful, but the code is long enough as it is, and most features would just add code without providing additional insight into the use of C++.

10.2.1. The Parser

Here is a grammar for the language accepted by the calculator:

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program:
     end                           // end is end-of-input
     expr_list end

expr_list:
     expression print              // print is newline or semicolon
     expression print expr_list

expression:
     expression + term
     expression – term
     term

term:
     term / primary
     term * primary
     primary

primary:
     number                        // number is a floating-point literal
     name                          // name is an identifier
     name = expression
     – primary
     ( expression )

In other words, a program is a sequence of expressions separated by semicolons. The basic units of an expression are numbers, names, and the operators *, /, +, – (both unary and binary), and = (assignment). Names need not be declared before use.

I use a style of syntax analysis called recursive descent; it is a popular and straightforward top-down technique. In a language such as C++, in which function calls are relatively cheap, it is also efficient. For each production in the grammar, there is a function that calls other functions. Terminal symbols (for example, end, number, +, and –) are recognized by a lexical analyzer and nonterminal symbols are recognized by the syntax analyzer functions, expr(), term(), and prim(). As soon as both operands of a (sub)expression are known, the expression is evaluated; in a real compiler, code could be generated at this point.

For input, the parser uses a Token_stream that encapsulates the reading of characters and their composition into Tokens. That is, a Token_stream “tokenizes”: it turns streams of characters, such as 123.45, into Tokens. A Token is a {kind-of-token,value} pair, such as {number,123.45}, where the 123.45 has been turned into a floating point value. The main parts of the parser need only to know the name of the Token_stream, ts, and how to get Tokens from it. To read the next Token, it calls ts.get(). To get the most recently read Token (the “current token”), it calls ts.current(). In addition to providing tokenizing, the Token_stream hides the actual source of the characters. We’ll see that they can come directly from a user typing to cin, from a program command line, or from any other input stream (§10.2.7).

The definition of Token looks like this:

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enum class Kind : char {
     name, number, end,
     plus='+', minus='–', mul='*', div='/', print=';', assign='=', lp='(', rp=')'
};

struct Token {
     Kind kind;
     string string_value;
     double number_value;
};

Representing each token by the integer value of its character is convenient and efficient and can be a help to people using debuggers. This works as long as no character used as input has a value used as an enumerator – and no current character set I know of has a printing character with a single-digit integer value.

The interface to Token_stream looks like this:

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class Token_stream {
public:
     Token get();            // read and return next token
     const Token& current(); // most recently read token
     // ...
};

The implementation is presented in §10.2.2.

Each parser function takes a bool (§6.2.2) argument, called get, indicating whether the function needs to call Token_stream::get() to get the next token. Each parser function evaluates “its” expression and returns the value. The function expr() handles addition and subtraction. It consists of a single loop that looks for terms to add or subtract:

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double expr(bool get)          // add and subtract
{
    double left = term(get);

    for (;;) {                       // "forever"
          switch (ts.current().kind) {
          case Kind::plus:
              left += term(true);
              break;
          case Kind::minus:
              left –= term(true);
              break;
          default:
              return left;
          }
    }
}

This function really does not do much itself. In a manner typical of higher-level functions in a large program, it calls other functions to do the work.

The switch-statement (§2.2.4, §9.4.2) tests the value of its condition, which is supplied in parentheses after the switch keyword, against a set of constants. The break-statements are used to exit the switch-statement. If the value tested does not match any case label, the default is chosen. The programmer need not provide a default.

Note that an expression such as 2–3+4 is evaluated as (2–3)+4, as specified in the grammar.

The curious notation for(;;) is a way to specify an infinite loop; you could pronounce it “forever” (§9.5); while(true) is an alternative. The switch-statement is executed repeatedly until something different from + and – is found, and then the return-statement in the default case is executed.

The operators += and –= are used to handle the addition and subtraction; left=left+term(true) and left=left–term(true) could have been used without changing the meaning of the program. However, left+=term(true) and left–=term(true) are not only shorter but also express the intended operation directly. Each assignment operator is a separate lexical token, so a + = 1; is a syntax error because of the space between the + and the =.

C++ provides assignment operators for the binary operators:

+ – * / % & | ^ << >>

so that the following assignment operators are possible:

= += –= *= /= %= &= |= ^= <<= >>=

The % is the modulo, or remainder, operator; &, |, and ^ are the bitwise logical operators and, or, and exclusive or; << and >> are the left shift and right shift operators; §10.3 summarizes the operators and their meanings. For a binary operator @ applied to operands of built-in types, an expression x@=y means x=x@y, except that x is evaluated once only.

The function term() handles multiplication and division in the same way expr() handles addition and subtraction:

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double term(bool get)         // multiply and divide
{
    double left = prim(get);

    for (;;) {
          switch (ts.current().kind) {
          case Kind::mul:
               left *= prim(true);
               break;
          case Kind::div:
               if (auto d = prim(true)) {
                     left /= d;
                     break;
               }
               return error("divide by 0");
          default:
               return left;
          }
    }
}

The result of dividing by zero is undefined and usually disastrous. We therefore test for 0 before dividing and call error() if we detect a zero divisor. The function error() is described in §10.2.4.

The variable d is introduced into the program exactly where it is needed and initialized immediately. The scope of a name introduced in a condition is the statement controlled by that condition, and the resulting value is the value of the condition (§9.4.3). Consequently, the division and assignment left/=d are done if and only if d is nonzero.

The function prim() handling a primary is much like expr() and term(), except that because we are getting lower in the call hierarchy a bit of real work is being done and no loop is necessary:

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double prim(bool get)             // handle primaries
{
    if (get) ts.get(); // read next token

    switch (ts.current().kind) {
    case Kind::number:         // floating-point constant
    {    double v = ts.current().number_value;
         ts.get();
         return v;
    }
    case Kind::name:
    {    double& v = table[ts.current().string_value];        // find the corresponding
         if (ts.get().kind == Kind::assign) v = expr(true);   // '=' seen: assignment
         return v;
    }
    case Kind::minus:        // unary minus
         return –prim(true);
    case Kind::lp:
    {    auto e = expr(true);
         if (ts.current().kind != Kind::rp) return error("')' expected");
         ts.get();         // eat ')'
         return e;
    }
    default:
         return error("primary expected");
    }
}

When a Token that is a number (that is, an integer or floating-point literal) is seen, its value is placed in its number_value. Similarly, when a Token that is a name (however defined; see §10.2.2 and §10.2.3) is seen, its value is placed in its string_value.

Note that prim() always reads one more Token than it uses to analyze its primary expression. The reason is that it must do that in some cases (e.g., to see if a name is assigned to), so for consistency it must do it in all cases. In the cases where a parser function simply wants to move ahead to the next Token, it doesn’t use the return value from ts.get(). That’s fine because we can get the result from ts.current(). Had ignoring the return value of get() bothered me, I’d have either added a read() function that just updated current() without returning a value or explicitly “thrown away” the result: void(ts.get()).

Before doing anything to a name, the calculator must first look ahead to see if it is being assigned to or simply read. In both cases, the symbol table is consulted. The symbol table is a map (§4.4.3, §31.4.3):

map<string,double> table;

That is, when table is indexed by a string, the resulting value is the double corresponding to the string. For example, if the user enters

radius = 6378.388;

the calculator will reach case Kind::name and execute

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double& v = table["radius"];
// ... expr() calculates the value to be assigned ...
v = 6378.388;

The reference v is used to hold on to the double associated with radius while expr() calculates the value 6378.388 from the input characters.

Chapter 14 and Chapter 15 discuss how to organize a program as a set of modules. However, with one exception, the declarations for this calculator example can be ordered so that everything is declared exactly once and before it is used. The exception is expr(), which calls term(), which calls prim(), which in turn calls expr(). This loop of calls must be broken somehow. A declaration

double expr(bool);

before the definition of prim() will do nicely.

10.2.2. Input

Reading input is often the messiest part of a program. To communicate with a person, the program must cope with that person’s whims, conventions, and seemingly random errors. Trying to force the person to behave in a manner more suitable for the machine is often (rightly) considered offensive. The task of a low-level input routine is to read characters and compose higher-level tokens from them. These tokens are then the units of input for higher-level routines. Here, low-level input is done by ts.get(). Writing a low-level input routine need not be an everyday task. Many systems provide standard functions for this.

First we need to see the complete definition of Token_stream:

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class Token_stream {
public:
     Token_stream(istream& s) : ip{&s}, owns{false} { }
     Token_stream(istream* p) : ip{p}, owns{true} { }

     ∼Token_stream() { close(); }

     Token get();        // read and return next token
     Token& current();   // most recently read token

     void set_input(istream& s) { close(); ip = &s; owns=false; }
     void set_input(istream* p) { close(); ip = p; owns = true; }

private:
     void close() { if (owns) delete ip; }

     istream* ip;                     // pointer to an input stream
     bool owns;                       // does the Token_stream own the istream?
     Token ct {Kind::end} ;           // current token
};

We initialize a Token_stream with an input stream (§4.3.2, Chapter 38) from which it gets its characters. The Token_stream implements the convention that it owns (and eventually deletes; §3.2.1.2, §11.2) an istream passed as a pointer, but not an istream passed as a reference. This may be a bit elaborate for this simple program, but it is a useful and general technique for classes that hold a pointer to a resource requiring destruction.

A Token_stream holds three values: a pointer to its input stream (ip), a Boolean (owns), indicating ownership of the input stream, and the current token (ct).

I gave ct a default value because it seemed sloppy not to. People should not call current() before get(), but if they do, they get a well-defined Token. I chose Kind::end as the initial value for ct so that a program that misuses current() will not get a value that wasn’t on the input stream.

I present Token_stream::get() in two stages. First, I provide a deceptively simple version that imposes a burden on the user. Next, I modify it into a slightly less elegant, but much easier to use, version. The idea for get() is to read a character, use that character to decide what kind of token needs to be composed, read more characters when needed, and then return a Token representing the characters read.

The initial statements read the first non-whitespace character from *ip (the stream pointed to by ip) into ch and check that the read operation succeeded:

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Token Token_stream::get()
{

    char ch = 0;
    *ip>>ch;

    switch (ch) {
    case 0:
         return ct={Kind::end}; // assign and return

By default, operator >> skips whitespace (that is, spaces, tabs, newlines, etc.) and leaves the value of ch unchanged if the input operation failed. Consequently, ch==0 indicates end-of-input.

Assignment is an operator, and the result of the assignment is the value of the variable assigned to. This allows me to assign the value Kind::end to curr_tok and return it in the same statement. Having a single statement rather than two is useful in maintenance. If the assignment and the return became separated in the code, a programmer might update the one and forget to update the other.

Note also how the {}-list notation (§3.2.1.3, §11.3) is used on the right-hand side of an assignment. That is, it is an expression. I could have written that return-statement as:

ct.kind = Kind::end; // assign
return ct;           // return

However, I think that assigning a complete object {Kind::end} is clearer than dealing with individual members of ct. The {Kind::end} is equivalent to {Kind::end,0,0}. That’s good if we care about the last two members of the Token and not so good if we are worried about performance. Neither is the case here, but in general dealing with complete objects is clearer and less error-prone than manipulating data members individually. The cases below give examples of the other strategy.

Consider some of the cases separately before considering the complete function. The expression terminator, ';', the parentheses, and the operators are handled simply by returning their values:

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case ';':  // end of expression; print
case '*':
case '/':
case '+':
case '–':
case '(':
case ')':
case '=':
     return ct={static_cast<Kind>(ch)};

The static_cast (§11.5.2) is needed because there is no implicit conversion from char to Kind (§8.4.1); only some characters correspond to Kind values, so we have to “certify” that in this case ch does.

Numbers are handled like this:

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case '0': case '1': case '2': case '3': case '4': case '5': case '6': case '7': case '8': case '9':
case '.':

ip–>putback(ch);        // put the first digit (or .) back into the input stream
*ip >> ct.number_value; // read the number into ct
ct.kind=Kind::number;
return ct;

Stacking case labels horizontally rather than vertically is generally not a good idea because this arrangement is harder to read. However, having one line for each digit is tedious. Because operator >> is already defined for reading floating-point values into a double, the code is trivial. First the initial character (a digit or a dot) is put back into cin. Then, the floating-point value can be read into ct.number_value.

If the token is not the end of input, an operator, a punctuation character, or a number, it must be a name. A name is handled similarly to a number:

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default:             // name, name =, or error
    if (isalpha(ch)) {
          ip–>putback(ch);                // put the first character back into the input stream
          *ip>>ct.string_value;           // read the string into ct
          ct.kind=Kind::name;
          return ct;
    }

Finally, we may simply have an error. The simple-minded, but reasonably effective way to deal with an error is the write call an error() function and then return a print token if error() returns:

error("bad token");
return ct={Kind::print};

The standard-library function isalpha() (§36.2.1) is used to avoid listing every character as a separate case label. Operator >> applied to a string (in this case, string_value) reads until it hits whitespace. Consequently, a user must terminate a name by a space before an operator using the name as an operand. This is less than ideal, so we will return to this problem in §10.2.3.

Here, finally, is the complete input function:

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Token Token_stream::get()
{
    char ch = 0;
    *ip>>ch;

    switch (ch) {
    case 0:
         return ct={Kind::end};    // assign and return
    case ';': // end of expression; print
    case '*':
    case '/':
    case '+':
    case '–':
    case '(':
    case ')':
    case '=':
         return ct=={static_cast<Kind>(ch)};
    case '0': case '1': case '2': case '3': case '4': case '5': case '6': case '7': case '8': case '9':
    case '.':
         ip–>putback(ch);                // put the first digit (or .) back into the input stream
         *ip >> ct.number_value;         // read number into ct
         ct.kind=Kind::number;
         return ct;
    default:              // name, name =, or error
         if (isalpha(ch)) {
              ip–>putback(ch);           // put the first character back into the input stream
              *ip>>ct.string_value;      // read string into ct
              ct.kind=Kind::name;
              return ct;
          }

          error("bad token");
          return ct={Kind::print};
    }
}

The conversion of an operator to its Token value is trivial because the kind of an operator was defined as the integer value of the operator (§10.2.1).

10.2.3. Low-Level Input

Using the calculator as defined so far reveals a few inconveniences. It is tedious to remember to add a semicolon after an expression in order to get its value printed, and having a name terminated by whitespace only is a real nuisance. For example, x=7 is an identifier – rather than the identifier x followed by the operator = and the number 7. To get what we (usually) want, we would have to add whitespace after x: x =7. Both problems are solved by replacing the type-oriented default input operations in get() with code that reads individual characters.

First, we’ll make a newline equivalent to the semicolon used to mark the end-of-expression:

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Token Token_stream::get()
{

    char ch;

    do { // skip whitespace except '\n'
         if (!ip–>get(ch)) return ct={Kind::end};
    } while (ch!='\n' && isspace(ch));

    switch (ch) {
    case ';':
    case '\n':
         return ct={Kind::print};

Here, I use a do-statement; it is equivalent to a while-statement except that the controlled statement is always executed at least once. The call ip–>get(ch) reads a single character from the input stream *ip into ch. By default, get() does not skip whitespace the way >> does. The test if (!ip–>get(ch)) succeeds if no character can be read from cin; in this case, Kind::end is returned to terminate the calculator session. The operator ! (not) is used because get() returns true in case of success.

The standard-library function isspace() provides the standard test for whitespace (§36.2.1); isspace(c) returns a nonzero value if c is a whitespace character and zero otherwise. The test is implemented as a table lookup, so using isspace() is much faster than testing for the individual whitespace characters. Similar functions test if a character is a digit (isdigit()), a letter (isalpha()), or a digit or letter (isalnum()).

After whitespace has been skipped, the next character is used to determine what kind of lexical token is coming.

The problem caused by >> reading into a string until whitespace is encountered is solved by reading one character at a time until a character that is not a letter or a digit is found:

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default:             // NAME, NAME=, or error
    if (isalpha(ch)) {
           string_value = ch;
           while (ip–>get(ch) && isalnum(ch))
                string_value += ch; // append ch to end of string_value
           ip–>putback(ch);
           return ct={Kind::name};
}

Fortunately, these two improvements could both be implemented by modifying a single local section of code. Constructing programs so that improvements can be implemented through local modifications only is an important design aim.

You might worry that adding characters to the end of a string one by one would be inefficient. It would be for very long strings, but all modern string implementations provide the “small string optimization” (§19.3.3). That means that handling the kind of strings we are likely to use as names in a calculator (or even in a compiler) doesn’t involve any inefficient operations. In particular, using a short string doesn’t require any use of free store. The maximum number of characters for a short string is implementation-dependent, but 14 would be a good guess.

10.2.4. Error Handling

It is always important to detect and report errors. However, for this program, a simple error handling strategy suffices. The error() function simply counts the errors, writes out an error message, and returns:

int no_of_errors;

double error(const string& s)
{
    no_of_errors++;
    cerr << "error: " << s << '\n';
    return 1;
}

The stream cerr is an unbuffered output stream usually used to report errors (§38.1).

The reason for returning a value is that errors typically occur in the middle of the evaluation of an expression, so we should either abort that evaluation entirely or return a value that is unlikely to cause subsequent errors. The latter is adequate for this simple calculator. Had Token_stream::get() kept track of the line numbers, error() could have informed the user approximately where the error occurred. This would be useful when the calculator is used noninteractively.

A more stylized and general error-handling strategy would separate error detection from error recovery. This can be implemented using exceptions (see §2.4.3.1, Chapter 13), but what we have here is quite suitable for a 180-line calculator.

10.2.5. The Driver

With all the pieces of the program in place, we need only a driver to start things. I decided on two functions: main() to do setup and error reporting and calculate() to handle the actual calculation:

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Token_stream ts {cin};  // use input from cin

void calculate()
{
     for (;;) {
           ts.get();
           if (ts.current().kind == Kind::end) break;
           if (ts.current().kind == Kind::print) continue;
           cout << expr(false) << '\n';
     }
}

int main()
{
     table["pi"] = 3.1415926535897932385;  // insert predefined names
     table["e"] = 2.7182818284590452354;

     calculate();

     return no_of_errors;
}

Conventionally, main() returns zero if the program terminates normally and nonzero otherwise (§2.2.1). Returning the number of errors accomplishes this nicely. As it happens, the only initialization needed is to insert the predefined names into the symbol table.

The primary task of the main loop (in calculate()) is to read expressions and write out the answer. This is achieved by the line:

cout << expr(false) << '\n';

The argument false tells expr() that it does not need to call ts.get() to read a token on which to work.

Testing for Kind::end ensures that the loop is correctly exited when ts.get() encounters an input error or an end-of-file. A break-statement exits its nearest enclosing switch-statement or loop (§9.5). Testing for Kind::print (that is, for '\n' and ';') relieves expr() of the responsibility for handling empty expressions. A continue-statement is equivalent to going to the very end of a loop.

10.2.6. Headers

The calculator uses standard-library facilities. Therefore, appropriate headers must be #included to complete the program:

#include<iostream> // I/O
#include<string>   // strings
#include<map>      // map
#include<cctype>   // isalpha(), etc.

All of these headers provide facilities in the std namespace, so to use the names they provide we must either use explicit qualification with std:: or bring the names into the global namespace by

using namespace std;

To avoid confusing the discussion of expressions with modularity issues, I did the latter. Chapter 14 and Chapter 15 discuss ways of organizing this calculator into modules using namespaces and how to organize it into source files.

10.2.7. Command-Line Arguments

After the program was written and tested, I found it a bother to first start the program, then type the expressions, and finally quit. My most common use was to evaluate a single expression. If that expression could be presented as a command-line argument, a few keystrokes could be avoided.

A program starts by calling main() (§2.2.1, §15.4). When this is done, main() is given two arguments specifying the number of arguments, conventionally called argc, and an array of arguments, conventionally called argv. The arguments are C-style character strings (§2.2.5, §7.3), so the type of argv is char*[argc+1]. The name of the program (as it occurs on the command line) is passed as argv[0], so argc is always at least 1. The list of arguments is zero-terminated; that is, argv[argc]==0. For example, for the command

dc 150/1.1934

the arguments have these values:

Because the conventions for calling main() are shared with C, C-style arrays and strings are used.

The idea is to read from the command string in the same way that we read from the input stream. A stream that reads from a string is unsurprisingly called an istringstream (§38.2.2). So to calculate expressions presented on the command line, we simply have to get our Token_stream to read from an appropriate istringstream:

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Token_stream ts {cin};

int main(int argc, char* argv[])
{
    switch (argc) {
    case 1:                                      // read from standard input
         break;
    case 2:                                      // read from argument string
         ts.set_input(new istringstream{argv[1]});
         break;
    default:
         error("too many arguments");
         return 1;
    }

    table["pi"] = 3.1415926535897932385;         // insert predefined names
    table["e"] = 2.7182818284590452354;

    calculate();

    return no_of_errors;
}

To use an istringstream, include <sstream>.

It would be easy to modify main() to accept several command-line arguments, but this does not appear to be necessary, especially as several expressions can be passed as a single argument:

dc "rate=1.1934;150/rate;19.75/rate;217/rate"

I use quotes because ; is the command separator on my UNIX systems. Other systems have different conventions for supplying arguments to a program on startup.

Simple as they are, argc and argv are still a source of minor, yet annoying, bugs. To avoid those and especially to make it easier to pass around the program arguments, I tend to use a simple function to create a vector<string>:

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vector<string> arguments(int argc, char* argv[])
{
    vector<string> res;
    for (int i = 0; i!=argc; ++i)
          res.push_back(argv[i]);
    return res;
}

More elaborate argument parsing functions are not uncommon.

10.2.8. A Note on Style

To programmers unacquainted with associative arrays, the use of the standard-library map as the symbol table seems almost like cheating. It is not. The standard library and other libraries are meant to be used. Often, a library has received more care in its design and implementation than a programmer could afford for a handcrafted piece of code to be used in just one program.

Looking at the code for the calculator, especially at the first version, we can see that there isn’t much traditional C-style, low-level code presented. Many of the traditional tricky details have been replaced by uses of standard-library classes such as ostream, string, and map (§4.3.1, §4.2, §4.4.3, §31.4, Chapter 36, Chapter 38).

Note the relative scarcity of loops, arithmetic, and assignments. This is the way things ought to be in code that doesn’t manipulate hardware directly or implement low-level abstractions.

10.3. Operator Summary

This section presents a summary of expressions and some examples. Each operator is followed by one or more names commonly used for it and an example of its use. In these tables:

• A name is an identifier (e.g., sum and map), an operator name (e.g., operator int, operator+, and operator"" km), or the name of a template specialization (e.g., sort<Record> and array<int,10>), possibly qualified using :: (e.g., std::vector and vector<T>::operator[]).

• A class-name is the name of a class (including decltype(expr) where expr denotes a class).

• A member is a member name (including the name of a destructor or a member template).

• An object is an expression yielding a class object.

• A pointer is an expression yielding a pointer (including this and an object of that type that supports the pointer operation).

• An expr is an expression, including a literal (e.g., 17, "mouse", and true)

• An expr-list is a (possibly empty) list of expressions.

• An lvalue is an expression denoting a modifiable object (§6.4.1).

• A type can be a fully general type name (with *, (), etc.) only when it appears in parentheses; elsewhere, there are restrictions (§iso.A).

• A lambda-declarator is a (possibly empty, comma-separated) list of parameters optionally followed by the mutable specifier, optionally followed by a noexcept specifier, optionally followed by a return type (§11.4).

• A capture-list is a (possibly empty) list specifying context dependencies (§11.4).

• A stmt-list is a (possibly empty) list of statements (§2.2.4, Chapter 9).

The syntax of expressions is independent of operand types. The meanings presented here apply when the operands are of built-in types (§6.2.1). In addition, you can define meanings for operators applied to operands of user-defined types (§2.3, Chapter 18).

A table can only approximate the rules of the grammar. For details, see §iso.5 and §iso.A.

Each box holds operators with the same precedence. Operators in higher boxes have higher precedence. For example, N::x.m means (N::m).m rather than the illegal N::(x.m).

For example, postfix ++ has higher precedence than unary *, so *p++ means *(p++), not (*p)++.

For example: a+b*c means a+(b*c) rather than (a+b)*c because * has higher precedence than +.

Unary operators and assignment operators are right-associative; all others are left-associative. For example, a=b=c means a=(b=c) whereas a+b+c means (a+b)+c.

A few grammar rules cannot be expressed in terms of precedence (also known as binding strength) and associativity. For example, a=b<c?d=e:f=g means a=((b<c)?(d=e):(f=g)), but you need to look at the grammar (§iso.A) to determine that.

Before applying the grammar rules, lexical tokens are composed from characters. The longest possible sequence of characters is chosen to make a token. For example, && is a single operator, rather than two & operators, and a+++1 means (a ++) + 1. This is sometimes called the Max Munch rule.

Whitespace characters (e.g., space, tab, and newline) can be token separators (e.g., int count is a keyword followed by an identifier, rather than intcount) but are otherwise ignored.

Some characters from the basic source character set (§6.1.2), such as |, are not convenient to type on some keywords. Also, some programmers find it odd to use of symbols, such as && and ~, for basic logical operations. Consequently, a set of alternative representation are provided as keywords:

For example

bool b = not (x or y) and z;
int x4 = ~ (x1 bitor x2) bitand x3;

is equivalent to

bool b = !(x || y) && z;
int x4 = ~ (x1 | x2) & x3;

Note that and= is not equivalent to &=; if you prefer keywords, you must write and_eq.

10.3.1. Results

The result types of arithmetic operators are determined by a set of rules known as “the usual arithmetic conversions” (§10.5.3). The overall aim is to produce a result of the “largest” operand type. For example, if a binary operator has a floating-point operand, the computation is done using floating-point arithmetic and the result is a floating-point value. Similarly, if it has a long operand, the computation is done using long integer arithmetic, and the result is a long. Operands that are smaller than an int (such as bool and char) are converted to int before the operator is applied.

The relational operators, ==, <=, etc., produce Boolean results. The meaning and result type of user-defined operators are determined by their declarations (§18.2).

Where logically feasible, the result of an operator that takes an lvalue operand is an lvalue denoting that lvalue operand. For example:

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void f(int x, int y)
{
     int j = x = y;           // the value of x=y is the value of x after the assignment
     int* p = &++x;           // p points to x
     int* q = &(x++);         // error: x++ is not an lvalue (it is not the value stored in x)
     int* p2 = &(x>y?x:y);    // address of the int with the larger value
     int& r = (x<y)?x:1;      // error: 1 is not an lvalue
}

If both the second and third operands of ?: are lvalues and have the same type, the result is of that type and is an lvalue. Preserving lvalues in this way allows greater flexibility in using operators. This is particularly useful when writing code that needs to work uniformly and efficiently with both built-in and user-defined types (e.g., when writing templates or programs that generate C++ code).

The result of sizeof is of an unsigned integral type called size_t defined in <cstddef>. The result of pointer subtraction is of a signed integral type called ptrdiff_t defined in <cstddef>.

Implementations do not have to check for arithmetic overflow and hardly any do. For example:

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void f()
{
     int i = 1;
     while (0 < i) ++i;
     cout << "i has become negative!" << i << '\n';
}

This will (eventually) try to increase i past the largest integer. What happens then is undefined, but typically the value “wraps around” to a negative number (on my machine –2147483648). Similarly, the effect of dividing by zero is undefined, but doing so usually causes abrupt termination of the program. In particular, underflow, overflow, and division by zero do not throw standard exceptions (§30.4.1.1).

10.3.2. Order of Evaluation

The order of evaluation of subexpressions within an expression is undefined. In particular, you cannot assume that the expression is evaluated left-to-right. For example:

int x = f(2)+g(3);       // undefined whether f() or g() is called first

Better code can be generated in the absence of restrictions on expression evaluation order. However, the absence of restrictions on evaluation order can lead to undefined results. For example:

int i = 1;
v[i] = i++; // undefined result

The assignment may be evaluated as either v[1]=1 or v[2]=1 or may cause some even stranger behavior. Compilers can warn about such ambiguities. Unfortunately, most do not, so be careful not to write an expression that reads or writes an object more than once, unless it does so using a single operator that makes it well defined, such as ++ and +=, or explicitly express sequencing using , (comma), &&, or ||.

The operators , (comma), && (logical and), and || (logical or) guarantee that their left-hand operand is evaluated before their right-hand operand. For example, b=(a=2,a+1) assigns 3 to b. Examples of the use of || and && can be found in §10.3.3. For built-in types, the second operand of && is evaluated only if its first operand is true, and the second operand of || is evaluated only if its first operand is false; this is sometimes called short-circuit evaluation. Note that the sequencing operator , (comma) is logically different from the comma used to separate arguments in a function call. For example:

f1(v[i],i++);        // two arguments
f2( (v[i],i++) );    // one argument

The call of f1 has two arguments, v[i] and i++, and the order of evaluation of the argument expressions is undefined. So it should be avoided. Order dependence of argument expressions is very poor style and has undefined behavior. The call of f2 has only one argument, the comma expression (v[i],i++), which is equivalent to i++. That is confusing, so that too should be avoided.

Parentheses can be used to force grouping. For example, a*b/c means (a*b)/c, so parentheses must be used to get a*(b/c); a*(b/c) may be evaluated as (a*b)/c only if the user cannot tell the difference. In particular, for many floating-point computations a*(b/c) and (a*b)/c are significantly different, so a compiler will evaluate such expressions exactly as written.

10.3.3. Operator Precedence

Precedence levels and associativity rules reflect the most common usage. For example:

if (i<=0 || max<i) // ...

means “if i is less than or equal to 0 or if max is less than i.” That is, it is equivalent to

if ( (i<=0) || (max<i) ) // ...

and not the legal but nonsensical

if (i <= (0||max) < i) // ...

However, parentheses should be used whenever a programmer is in doubt about those rules. Use of parentheses becomes more common as the subexpressions become more complicated, but complicated subexpressions are a source of errors. Therefore, if you start feeling the need for parentheses, you might consider breaking up the expression by using an extra variable.

There are cases when the operator precedence does not result in the “obvious” interpretation. For example:

if (i&mask == 0)   // oops! == expression as operand for &

This does not apply a mask to i and then test if the result is zero. Because == has higher precedence than &, the expression is interpreted as i&(mask==0). Fortunately, it is easy enough for a compiler to warn about most such mistakes. In this case, parentheses are important:

if ((i&mask) == 0) // ...

It is worth noting that the following does not work the way a mathematician might expect:

if (0 <= x <= 99) // ...

This is legal, but it is interpreted as (0<=x)<=99, where the result of the first comparison is either true or false. This Boolean value is then implicitly converted to 1 or 0, which is then compared to 99, yielding true. To test whether x is in the range 0..99, we might use

if (0<=x && x<=99) // ...

A common mistake for novices is to use = (assignment) instead of == (equals) in a condition:

if (a = 7) // oops! constant assignment in condition

This is natural because = means “equals” in many languages. Again, it is easy for a compiler to warn about most such mistakes – and many do. I do not recommend warping your style to compensate for compilers with weak warnings. In particular, I don’t consider this style worthwhile:

if (7 == a) // try to protect against misuse of =; not recommended

10.3.4. Temporary Objects

Often, the compiler must introduce an object to hold an intermediate result of an expression. For example, for v=x+y*z the result of y*z has to be put somewhere before it is added to x. For built-in types, this is all handled so that a temporary object (often referred to as just a temporary) is invisible to the user. However, for a user-defined type that holds a resource knowing the lifetime of a temporary can be important. Unless bound to a reference or used to initialize a named object, a temporary object is destroyed at the end of the full expression in which it was created. A full expression is an expression that is not a subexpression of some other expression.

The standard-library string has a member c_str() (§36.3) that returns a C-style pointer to a zero-terminated array of characters (§2.2.5, §43.4). Also, the operator + is defined to mean string concatenation. These are useful facilities for strings. However, in combination they can cause obscure problems. For example:

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void f(string& s1, string& s2, string& s3)
{
     const char* cs = (s1+s2).c_str();
     cout << cs;
     if (strlen(cs=(s2+s3).c_str())<8 && cs[0]=='a') {
            // cs used here
     }
}

Probably, your first reaction is “But don’t do that!” and I agree. However, such code does get written, so it is worth knowing how it is interpreted.

A temporary string object is created to hold s1+s2. Next, a pointer to a C-style string is extracted from that object. Then – at the end of the expression – the temporary object is deleted. However, the C-style string returned by c_str() was allocated as part of the temporary object holding s1+s2, and that storage is not guaranteed to exist after that temporary is destroyed. Consequently, cs points to deallocated storage. The output operation cout<<cs might work as expected, but that would be sheer luck. A compiler can detect and warn against many variants of this problem.

The problem with the if-statement is a bit more subtle. The condition will work as expected because the full expression in which the temporary holding s2+s3 is created is the condition itself. However, that temporary is destroyed before the controlled statement is entered, so any use of cs there is not guaranteed to work.

Please note that in this case, as in many others, the problems with temporaries arose from using a high-level data type in a low-level way. A cleaner programming style yields a more understandable program fragment and avoids the problems with temporaries completely. For example:

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void f(string& s1, string& s2, string& s3)
{
     cout << s1+s2;
     string s = s2+s3;
     if (s.length()<8 && s[0]=='a') {
            // use s here
     }
}

A temporary can be used as an initializer for a const reference or a named object. For example:

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void g(const string&, const string&);

void h(string& s1, string& s2)
{
     const string& s = s1+s2;
     string ss = s1+s2;

     g(s,ss); // we can use s and ss here
}

This is fine. The temporary is destroyed when “its” reference or named object goes out of scope. Remember that returning a reference to a local variable is an error (§12.1.4) and that a temporary object cannot be bound to a non-const lvalue reference (§7.7).

A temporary object can also be created explicitly in an expression by invoking a constructor (§11.5.1). For example:

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void f(Shape& s, int n, char ch)
{
     s.move(string{n,ch}); // construct a string with n copies of ch to pass to Shape::move()
     // ...
}

Such temporaries are destroyed in exactly the same way as the implicitly generated temporaries.

10.4. Constant Expressions

C++ offers two related meanings of “constant”:

• constexpr: Evaluate at compile time (§2.2.3).

• const: Do not modify in this scope (§2.2.3, §7.5).

Basically, constexpr’s role is to enable and ensure compile-time evaluation, whereas const’s primary role is to specify immutability in interfaces. This section is primarily concerned with the first role: compile-time evaluation.

A constant expression is an expression that a compiler can evaluate. It cannot use values that are not known at compile time and it cannot have side effects. Ultimately, a constant expression must start out with an integral value (§6.2.1), a floating-point value (§6.2.5), or an enumerator (§8.4), and we can combine those using operators and constexpr functions that in turn produce values. In addition, some addresses can be used in some forms of constant expressions. For simplicity, I discuss those separately in §10.4.5.

There are a variety of reasons why someone might want a named constant rather than a literal or a value stored in a variable:

[1] Named constants make the code easier to understand and maintain.

[2] A variable might be changed (so we have to be more careful in our reasoning than for a constant).

[3] The language requires constant expressions for array sizes, case labels, and template value arguments.

[4] Embedded systems programmers like to put immutable data into read-only memory because read-only memory is cheaper than dynamic memory (in terms of cost and energy consumption), and often more plentiful. Also, data in read-only memory is immune to most system crashes.

[5] If initialization is done at compile time, there can be no data races on that object in a multi-threaded system.

[6] Sometimes, evaluating something once (at compile time) gives significantly better performance than doing so a million times at run time.

Note that reasons [1], [2], [5], and (partly) [4] are logical. We don’t just use constant expressions because of an obsession with performance. Often, the reason is that a constant expression is a more direct representation of our system requirements.

As part of the definition of a data item (here, I deliberately avoid the word “variable”), constexpr expresses the need for compile-time evaluation. If the initializer for a constexpr can’t be evaluated at compile time, the compiler will give an error. For example:

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int x1 = 7;
constexpr int x2 = 7;

constexpr int x3 = x1;           // error: initializer is not a constant expression
constexpr int x4 = x2;           // OK

void f()
{
     constexpr int y3 = x1;      // error: initializer is not a constant expression
     constexpr int y4 = x2;      // OK
     // ...
}

A clever compiler could deduce that the value of x1 in the initializer for x3 was 7. However, we prefer not to rely on degrees of cleverness in compilers. In a large program, determining the values of variables at compile time is typically either very difficult or impossible.

The expressive power of constant expressions is great. We can use integer, floating-point, and enumeration values. We can use any operator that doesn’t modify state (e.g., +, ?:, and [], but not = or ++). We can use constexpr functions (§12.1.6) and literal types (§10.4.3) to provide a significant level of type safety and expressive power. It is almost unfair to compare this to what is commonly done with macros (§12.6).

The conditional-expression operator ?: is the means of selection in a constant expression. For example, we can compute an integer square root at compile time:

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constexpr int isqrt_helper(int sq, int d, int a)
{
    return sq <= a ? isqrt_helper(sq+d,d+2,a) : d;
}

constexpr int isqrt(int x)
{
    return isqrt_helper(1,3,x)/2 – 1;
}

constexpr int s1 = isqrt(9);    // s1 becomes 3
constexpr int s2 = isqrt(1234);

The condition of a ?: is evaluated and then the selected alternative is evaluated. The alternative not selected is not evaluated and might even not be a constant expression. Similarly, operands of && and || that are not evaluated need not be constant expressions. This feature is primarily useful in constexpr functions that are sometimes used as constant expressions and sometimes not.

10.4.1. Symbolic Constants

The most important single use of constants (constexpr or const values) is simply to provide symbolic names for values. Symbolic names should be used systematically to avoid “magic numbers” in code. Literal values scattered freely around in code is one of the nastiest maintenance hazards. If a numeric constant, such as an array bound, is repeated in code, it becomes hard to revise that code because every occurrence of that constant must be changed to update the code correctly. Using a symbolic name instead localizes information. Usually, a numeric constant represents an assumption about the program. For example, 4 may represent the number of bytes in an integer, 128 the number of characters needed to buffer input, and 6.24 the exchange factor between Danish kroner and U.S. dollars. Left as numeric constants in the code, these values are hard for a maintainer to spot and understand. Also, many such values need to change over time. Often, such numeric values go unnoticed and become errors when a program is ported or when some other change violates the assumptions they represent. Representing assumptions as well-commented named (symbolic) constants minimizes such maintenance problems.

10.4.2. consts in Constant Expressions

A const is primarily used to express interfaces (§7.5). However, const can also be used to express constant values. For example:

const int x = 7;
const string s = "asdf";
const int y = sqrt(x);

A const initialized with a constant expression can be used in a constant expression. A const differs from a constexpr in that it can be initialized by something that is not a constant expression; in that case, the const cannot be used as a constant expression. For example:

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constexpr int xx = x;       // OK
constexpr string ss = s;    // error: s is not a constant expression
constexpr int yy = y;       // error: sqrt(x) is not a constant expression

The reasons for the errors are that string is not a literal type (§10.4.3) and sqrt() is not a constexpr function (§12.1.6).

Usually, constexpr is a better choice than const for defining simple constants, but constexpr is new in C++11, so older code tends to use const. In many cases, enumerators (§8.4) are another alternative to consts.

10.4.3. Literal Types

A sufficiently simple user-defined type can be used in a constant expression. For example:

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struct Point {
     int x,y,z;
     constexpr Point up(int d) { return {x,y,z+d}; }
     constexpr Point move(int dx, int dy) { return {x+dx,y+dy}; }
     // ...
};

A class with a constexpr constructor is called a literal type. To be simple enough to be constexpr, a constructor must have an empty body and all members must be initialized by potentially constant expressions. For example:

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constexpr Point origo {0,0};
constexpr int z = origo.x;

constexpr Point a[] = {
    origo, Point{1,1}, Point{2,2}, origo.move(3,3)
};
constexpr int x = a[1].x;      // x becomes 1

constexpr Point xy{0,sqrt(2)}; // error: sqrt(2) is not a constant expression

Note that we can have constexpr arrays and also access array elements and object members.

Naturally, we can define constexpr functions to take arguments of literal types. For example:

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constexpr int square(int x)
{
    return x*x;
}

constexpr int radial_distance(Point p)
{
    return isqrt(square(p.x)+square(p.y)+square(p.z));
}

constexpr Point p1 {10,20,30};           // the default constructor is constexpr
constexpr p2 {p1.up(20)};                // Point::up() is constexpr
constexpr int dist = radial_distance(p2);

I used int rather than double just because I didn’t have a constexpr floating-point square root function handy.

For a member function constexpr implies const, so I did not have to write:

constexpr Point move(int dx, int dy) const { return {x+dx,y+dy}; }

10.4.4. Reference Arguments

When working with constexpr, the key thing to remember is that constexpr is all about values. There are no objects that can change values or side effects here: constexpr provides a miniature compile-time functional programming language. That said, you might guess that constexpr cannot deal with references, but that’s only partially true because const references refer to values and can therefore be used. Consider the specialization of the general complex<T> to a complex<double> from the standard library:

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template<> class complex<double> {
public:
     constexpr complex(double re = 0.0, double im = 0.0);
     constexpr complex(const complex<float>&);
     explicit constexpr complex(const complex<long double>&);

     constexpr double real();     // read the real part
     void real(double);           // set the real part
     constexpr double imag();     // read the imaginary part
     void imag(double);           // set the imaginary part

     complex<double>& operator= (double);
     complex<double>& operator+=(double);
     // ...
};

Obviously, operations, such as = and +=, that modify an object cannot be constexpr. Conversely, operations that simply read an object, such as real() and imag(), can be constexpr and be evaluated at compile time given a constant expression. The interesting member is the template constructor from another complex type. Consider:

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constexpr complex<float> z1 {1,2};        // note: <float> not <double>
constexpr double re = z1.real();
constexpr double im = z1.imag();
constexpr complex<double> z2 {re,im};     // z2 becomes a copy of z1
constexpr complex<double> z3 {z1};        // z3 becomes a copy of z1

The copy constructor works because the compiler recognizes that the reference (the const complex<float>&) refers to a constant value and we just use that value (rather than trying anything advanced or silly with references or pointers).

Literal types allow for type-rich compile-time programming. Traditionally, C++ compile-time evaluation has been restricted to using integer values (and without functions). This has resulted in code that was unnecessarily complicated and error-prone, as people encoded every kind of information as integers. Some uses of template metaprogramming (Chapter 28) are examples of that. Other programmers have simply preferred run-time evaluation to avoid the difficulties of writing in an impoverished language.

10.4.5. Address Constant Expressions

The address of a statically allocated object (§6.4.2), such as a global variable, is a constant. However, its value is assigned by the linker, rather than the compiler, so the compiler cannot know the value of such an address constant. That limits the range of constant expressions of pointer and reference type. For example:

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constexpr const char* p1 = "asdf";
constexpr const char* p2 = p1;       // OK
constexpr const char* p2 = p1+2;     // error: the compiler does not know the value of p1
constexpr char c = p1[2];            // OK, c=='d'; the compiler knows the value pointed to by p1

10.5. Implicit Type Conversion

Integral and floating-point types (§6.2.1) can be mixed freely in assignments and expressions. Wherever possible, values are converted so as not to lose information. Unfortunately, some value-destroying (“narrowing”) conversions are also performed implicitly. A conversion is value-preserving if you can convert a value and then convert the result back to its original type and get the original value. If a conversion cannot do that, it is a narrowing conversion (§10.5.2.6). This section provides a description of conversion rules, conversion problems, and their resolution.

10.5.1. Promotions

The implicit conversions that preserve values are commonly referred to as promotions. Before an arithmetic operation is performed, integral promotion is used to create ints out of shorter integer types. Similarly, floating-point promotion is used to create doubles out of floats. Note that these promotions will not promote to long (unless the operand is a char16_t, char32_t, wchar_t, or a plain enumeration that is already larger than an int) or long double. This reflects the original purpose of these promotions in C: to bring operands to the “natural” size for arithmetic operations.

The integral promotions are:

• A char, signed char, unsigned char, short int, or unsigned short int is converted to an int if int can represent all the values of the source type; otherwise, it is converted to an unsigned int.

• A char16_t, char32_t, wchar_t (§6.2.3), or a plain enumeration type (§8.4.2) is converted to the first of the following types that can represent all the values of its underlying type: int, unsigned int, long, unsigned long, or unsigned long long.

• A bit-field (§8.2.7) is converted to an int if int can represent all the values of the bit-field; otherwise, it is converted to unsigned int if unsigned int can represent all the values of the bit-field. Otherwise, no integral promotion applies to it.

• A bool is converted to an int; false becomes 0 and true becomes 1.

Promotions are used as part of the usual arithmetic conversions (§10.5.3).

10.5.2. Conversions

The fundamental types can be implicitly converted into each other in a bewildering number of ways (§iso.4). In my opinion, too many conversions are allowed. For example:

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void f(double d)
{
     char c = d;       // beware: double-precision floating-point to char conversion
}

When writing code, you should always aim to avoid undefined behavior and conversions that quietly throw away information (“narrowing conversions”).

A compiler can warn about many questionable conversions. Fortunately, many compilers do.

The {}-initializer syntax prevents narrowing (§6.3.5). For example:

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void f(double d)
{
     char c {d};       // error: double-precision floating-point to char conversion
}

If potentially narrowing conversions are unavoidable, consider using some form of run-time checked conversion function, such as narrow_cast<>() (§11.5).

10.5.2.1. Integral Conversions

An integer can be converted to another integer type. A plain enumeration value can be converted to an integer type (§8.4.2) .

If the destination type is unsigned, the resulting value is simply as many bits from the source as will fit in the destination (high-order bits are thrown away if necessary). More precisely, the result is the least unsigned integer congruent to the source integer modulo 2 to the nth, where n is the number of bits used to represent the unsigned type. For example:

unsigned char uc = 1023;// binary 1111111111: uc becomes binary 11111111, that is, 255

If the destination type is signed, the value is unchanged if it can be represented in the destination type; otherwise, the value is implementation-defined:

signed char sc = 1023;    // implementation-defined

Plausible results are 127 and –1 (§6.2.3).

A Boolean or plain enumeration value can be implicitly converted to its integer equivalent (§6.2.2, §8.4).

10.5.2.2. Floating-Point Conversions

A floating-point value can be converted to another floating-point type. If the source value can be exactly represented in the destination type, the result is the original numeric value. If the source value is between two adjacent destination values, the result is one of those values. Otherwise, the behavior is undefined. For example:

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float f = FLT_MAX;      // largest float value
double d = f;           // OK: d == f

double d2 = DBL_MAX;    // largest double value
float f2 = d2;          // undefined if FLT_MAX<DBL_MAX

long double ld = d2;    // OK: ld = d3
long double ld2 = numeric_limits<long double>::max();
double d3 = ld2;        // undefined if sizeof(long double)>sizeof(double)

DBL_MAX and FLT_MAX are defined in <climits>; numeric_limits is defined in <limits> (§40.2).

10.5.2.3. Pointer and Reference Conversions

Any pointer to an object type can be implicitly converted to a void* (§7.2.1). A pointer (reference) to a derived class can be implicitly converted to a pointer (reference) to an accessible and unambiguous base (§20.2). Note that a pointer to function or a pointer to member cannot be implicitly converted to a void*.

A constant expression (§10.4) that evaluates to 0 can be implicitly converted to a null pointer of any pointer type. Similarly, a constant expression that evaluates to 0 can be implicitly converted to a pointer-to-member type (§20.6). For example:

int* p = (1+2)*(2*(1–1)); // OK, but weird

Prefer nullptr (§7.2.2).

A T* can be implicitly converted to a const T* (§7.5). Similarly, a T& can be implicitly converted to a const T&.

10.5.2.4. Pointer-to-Member Conversions

Pointers and references to members can be implicitly converted as described in §20.6.3.

10.5.2.5. Boolean Conversions

Pointer, integral, and floating-point values can be implicitly converted to bool (§6.2.2). A nonzero value converts to true; a zero value converts to false. For example:

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void f(int* p, int i)
{
     bool is_not_zero = p;        // true if p!=0
     bool b2 = i;                 // true if i!=0
     // ...
}

The pointer-to-bool conversion is useful in conditions, but confusing elsewhere:

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void fi(int);
void fb(bool);

void ff(int* p, int* q)
{
     if (p) do_something(*p);          // OK
     if (q!=nullptr) do_something(*q); // OK, but verbose
     // ...
     fi(p);                        // error: no pointer to int conversion
     fb(p);                        // OK: pointer to bool conversion (surprise!?)
}

Hope for a compiler warning for fb(p).

10.5.2.6. Floating-Integral Conversions

When a floating-point value is converted to an integer value, the fractional part is discarded. In other words, conversion from a floating-point type to an integer type truncates. For example, the value of int(1.6) is 1. The behavior is undefined if the truncated value cannot be represented in the destination type. For example:

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int i = 2.7;        // i becomes 2
char b = 2000.7;    // undefined for 8-bit chars: 2000 cannot be represented as an 8-bit char

Conversions from integer to floating types are as mathematically correct as the hardware allows. Loss of precision occurs if an integral value cannot be represented exactly as a value of the floating type. For example:

int i = float(1234567890);

On a machine where both ints and floats are represented using 32 bits, the value of i is 1234567936.

Clearly, it is best to avoid potentially value-destroying implicit conversions. In fact, compilers can detect and warn against some obviously dangerous conversions, such as floating to integral and long int to char. However, general compile-time detection is impractical, so the programmer must be careful. When “being careful” isn’t enough, the programmer can insert explicit checks. For example:

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char checked_cast(int i)
{
     char c = i;   // warning: not portable (§10.5.2.1)
     if (i != c) throw std::runtime_error{"int–to–char check failed"};
     return c;
}

void my_code(int i)
{
     char c = checked_cast(i);
     // ...
}

A more general technique for expressing checked conversions is presented in §25.2.5.1.

To truncate in a way that is guaranteed to be portable requires the use of numeric_limits (§40.2). In initializations, truncation can be avoided by using the {}-initializer notation (§6.3.5).

10.5.3. Usual Arithmetic Conversions

These conversions are performed on the operands of a binary operator to bring them to a common type, which is then used as the type of the result:

[1] If either operand is of type long double, the other is converted to long double.

• Otherwise, if either operand is double, the other is converted to double.

• Otherwise, if either operand is float, the other is converted to float.

• Otherwise, integral promotions (§10.5.1) are performed on both operands.

[2] Otherwise, if either operand is unsigned long long, the other is converted to unsigned long long.

• Otherwise, if one operand is a long long int and the other is an unsigned long int, then if a long long int can represent all the values of an unsigned long int, the unsigned long int is converted to a long long int; otherwise, both operands are converted to unsigned long long int. Otherwise, if either operand is unsigned long long, the other is converted to unsigned long long.

• Otherwise, if one operand is a long int and the other is an unsigned int, then if a long int can represent all the values of an unsigned int, the unsigned int is converted to a long int; otherwise, both operands are converted to unsigned long int.

• Otherwise, if either operand is long, the other is converted to long.

• Otherwise, if either operand is unsigned, the other is converted to unsigned.

• Otherwise, both operands are int.

These rules make the result of converting an unsigned integer to a signed one of possibly larger size implementation-defined. That is yet another reason to avoid mixing unsigned and signed integers.

10.6. Advice

[1] Prefer the standard library to other libraries and to “handcrafted code”; §10.2.8.

[2] Use character-level input only when you have to; §10.2.3.

[3] When reading, always consider ill-formed input; §10.2.3.

[4] Prefer suitable abstractions (classes, algorithms, etc.) to direct use of language features (e.g., ints, statements); §10.2.8.

[5] Avoid complicated expressions; §10.3.3.

[6] If in doubt about operator precedence, parenthesize; §10.3.3.

[7] Avoid expressions with undefined order of evaluation; §10.3.2.

[8] Avoid narrowing conversions; §10.5.2.

[9] Define symbolic constants to avoid “magic constants”; §10.4.1.

[10] Avoid narrowing conversions; §10.5.2.

11. Select Operations

When someone says “I want a programming language in which I need only say what I wish done,” give him a lollipop.

– Alan Perlis

• Etc. Operators

Logical Operators; Bitwise Logical Operators; Conditional Expressions; Increment and Decrement

• Free Store

Memory Management; Arrays; Getting Memory Space; Overloading new

• Lists

Implementation Model; Qualified Lists; Unqualified Lists

• Lambda Expressions

Implementation Model; Alternatives to Lambdas; Capture; Call and Return; The Type of a Lambda

• Explicit Type Conversion

Construction; Named Casts; C-Style Cast; Function-Style Cast

• Advice

11.1. Etc. Operators

This section examines a mixed bag of simple operators: logical operators (&&, ||, and !), bitwise logical operators (&, |, ~, <<, and >>), conditional expressions (?:), and increment and decrement operators (++ and ––). They have little in common beyond their details not fitting elsewhere in the discussions of operators.

11.1.1. Logical Operators

The logical operators && (and), || (or), and ! (not) take operands of arithmetic and pointer types, convert them to bool, and return a bool result. The && and || operators evaluate their second argument only if necessary, so they can be used to control evaluation order (§10.3.2). For example:

while (p && !whitespace(p)) ++p;

Here, p is not dereferenced if it is the nullptr.

11.1.2. Bitwise Logical Operators

The bitwise logical operators & (and), | (or), ^ (exclusive or, xor), ~ (complement), >> (right shift), and << (left shift) are applied to objects of integral types – that is, char, short, int, long, long long and their unsigned counterparts, and bool, wchar_t, char16_t, and char32_t. A plain enum (but not an enum class) can be implicitly converted to an integer type and used as an operand to bitwise logical operations. The usual arithmetic conversions (§10.5.3) determine the type of the result.

A typical use of bitwise logical operators is to implement the notion of a small set (a bit vector). In this case, each bit of an unsigned integer represents one member of the set, and the number of bits limits the number of members. The binary operator & is interpreted as intersection, | as union, ^ as symmetric difference, and ~ as complement. An enumeration can be used to name the members of such a set. Here is a small example borrowed from an implementation of ostream:

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enum ios_base::iostate {
    goodbit=0, eofbit=1, failbit=2, badbit=4
};

The implementation of a stream can set and test its state like this:

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state = goodbit;
// ...
if (state&(badbit|failbit)) // stream not good

The extra parentheses are necessary because & has higher precedence than | (§10.3).

A function that reaches the end-of-input might report it like this:

state |= eofbit;

The |= operator is used to add to the state. A simple assignment, state=eofbit, would have cleared all other bits.

These stream state flags are observable from outside the stream implementation. For example, we could see how the states of two streams differ like this:

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int old = cin.rdstate();   // rdstate() returns the state
// ... use cin ...
if (cin.rdstate()^old) {   // has anything changed?
       // ...
}

Computing differences of stream states is not common. For other similar types, computing differences is essential. For example, consider comparing a bit vector that represents the set of interrupts being handled with another that represents the set of interrupts waiting to be handled.

Please note that this bit fiddling is taken from the implementation of iostreams rather than from the user interface. Convenient bit manipulation can be very important, but for reliability, maintainability, portability, etc., it should be kept at low levels of a system. For more general notions of a set, see the standard-library set (§31.4.3) and bitset (§34.2.2).

Bitwise logical operations can be used to extract bit-fields from a word. For example, one could extract the middle 16 bits of a 32-bit int like this:

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constexpr unsigned short middle(int a)
{
    static_assert(sizeof(int)==4,"unexpected int size");
    static_assert(sizeof(short)==2,"unexpected short size");
    return (a>>8)&0xFFFF;
}

int x = 0xFF00FF00; // assume sizeof(int)==4
short y = middle(x); // y = 0x00FF

Using fields (§8.2.7) is a convenient shorthand for such shifting and masking.

Do not confuse the bitwise logical operators with the logical operators: &&, ||, and !. The latter return true or false, and they are primarily useful for writing the test in an if-, while-, or for-statement (§9.4, §9.5). For example, !0 (not zero) is the value true, which converts to 1, whereas ~0 (complement of zero) is the bit pattern all-ones, which in two’s complement representation is the value –1 .

11.1.3. Conditional Expressions

Some if-statements can conveniently be replaced by conditional-expressions. For example:

if (a <= b)
      max = b;
else
      max = a;

This is more directly expressed like this:

max = (a<=b) ? b : a;

The parentheses around the condition are not necessary, but I find the code easier to read when they are used.

Conditional expressions are important in that they can be used in constant expressions (§10.4).

A pair of expressions e1 and e2 can be used as alternatives in a conditional expression, c?e1:e2, if they are of the same type or if there is a common type T, to which they can both be implicitly converted. For arithmetic types, the usual arithmetic conversions (§10.5.3) are used to find that common type. For other types, either e1 must be implicitly convertible to e2’s type or vice versa. In addition, one branch may be a throw-expression (§13.5.1). For example:

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void fct(int *p)
{
     int i = (p) ? *p : std::runtime_error{"unexpected nullptr};
     // ...
}

11.1.4. Increment and Decrement

The ++ operator is used to express incrementing directly, rather than expressing it indirectly using a combination of an addition and an assignment. Provided lvalue has no side effects, ++lvalue means lvalue+=1, which again means lvalue=lvalue+1. The expression denoting the object to be incremented is evaluated once (only). Decrementing is similarly expressed by the –– operator.

The operators ++ and –– can be used as both prefix and postfix operators. The value of ++x is the new (that is, incremented) value of x. For example, y=++x is equivalent to y=(x=x+1). The value of x++, however, is the old value of x. For example, y=x++ is equivalent to y=(t=x,x=x+1,t), where t is a variable of the same type as x.

Like adding an int to a pointer, or subtracting it, ++ and –– on a pointer operate in terms of elements of the array into which the pointer points; p++ makes p point to the next element (§7.4.1).

The ++ and –– operators are particularly useful for incrementing and decrementing variables in loops. For example, one can copy a zero-terminated C-style string like this:

void cpy(char* p, const char* q)
{
     while (*p++ = *q++);
}

Like C, C++ is both loved and hated for enabling such terse, expression-oriented coding. Consider:

while (*p++ = *q++) ;

This is more than a little obscure to non-C programmers, but because the style of coding is not uncommon, it is worth examining more closely. Consider first a more traditional way of copying an array of characters:

int length = strlen(q);
for (int i = 0; i<=length; i++)
      p[i] = q[i];

This is wasteful. The length of a zero-terminated string is found by reading the string looking for the terminating zero. Thus, we read the string twice: once to find its length and once to copy it. So we try this instead:

int i;
for (i = 0; q[i]!=0 ; i++)
      p[i] = q[i];
p[i] = 0;         // terminating zero

The variable i used for indexing can be eliminated because p and q are pointers:

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while (*q !=0){
      *p= *q;
      p++;     // point to next character
      q++;     // point to next character
}
*p = 0;        // terminating zero

Because the post-increment operation allows us first to use the value and then to increment it, we can rewrite the loop like this:

while (*q!=0) {
      *p++ = *q++;
}
*p = 0; // terminating zero

The value of *p++ = *q++ is *q. We can therefore rewrite the example like this:

while ((*p++ = *q++) != 0) { }

In this case, we don’t notice that *q is zero until we already have copied it into *p and incremented p. Consequently, we can eliminate the final assignment of the terminating zero. Finally, we can reduce the example further by observing that we don’t need the empty block and that the !=0 is redundant because the result of an integral condition is always compared to zero anyway. Thus, we get the version we set out to discover:

while (*p++ = *q++) ;

Is this version less readable than the previous versions? Not to an experienced C or C++ programmer. Is this version more efficient in time or space than the previous versions? Except for the first version that called strlen(), not really; the performance will be equivalent and often identical code will be generated.

The most efficient way of copying a zero-terminated character string is typically the standard C-style string copy function:

char* strcpy(char*, const char*);  // from <string.h>

For more general copying, the standard copy algorithm (§4.5, §32.5) can be used. Whenever possible, use standard-library facilities in preference to fiddling with pointers and bytes. Standard-library functions may be inlined (§12.1.3) or even implemented using specialized machine instructions. Therefore, you should measure carefully before believing that some piece of handcrafted code outperforms library functions. Even if it does, the advantage may not exist on some other handware+compiler combination, and your alternative may give a maintainer a headache.

11.2. Free Store

A named object has its lifetime determined by its scope (§6.3.4). However, it is often useful to create an object that exists independently of the scope in which it was created. For example, it is common to create objects that can be used after returning from the function in which they were created. The operator new creates such objects, and the operator delete can be used to destroy them. Objects allocated by new are said to be “on the free store” (also, “on the heap” or “in dynamic memory”).

Consider how we might write a compiler in the style used for the desk calculator (§10.2). The syntax analysis functions might build a tree of the expressions for use by the code generator:

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struct Enode {
     Token_value oper;
     Enode* left;
     Enode* right;
     // ...
};
Enode* expr(bool get)
{
     Enode* left = term(get);

     for (;;) {
            switch (ts.current().kind) {
            case Kind::plus:
            case Kind::minus:
                 left = new Enode {ts.current().kind,left,term(true)};
                 break;
            default:
                 return left;            // return node
            }
     }
}

In cases Kind::plus and Kind::minus, a new Enode is created on the free store and initialized by the value {ts.current().kind,left,term(true)}. The resulting pointer is assigned to left and eventually returned from expr().

I used the {}-list notation for specifying arguments. Alternatively, I could have used the old-style ()-list notation to specify an initializer. However, trying the = notation for initializing an object created using new results in an error:

int* p = new int = 7; // error

If a type has a default constructor, we can leave out the initializer, but built-in types are by default uninitialized. For example:

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auto pc = new complex<double>;  // the complex is initialized to {0,0}
auto pi = new int;              // the int is uninitialized

This can be confusing. To be sure to get default initialization, use {}. For example:

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auto pc = new complex<double>{}; // the complex is initialized to {0,0}
auto pi = new int{};             // the int is initialized to 0

A code generator could use the Enodes created by expr() and delete them:

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void generate(Enode* n)
{
     switch (n–>oper) {
     case Kind::plus:
          // use n
          delete n; // delete an Enode from the free store
     }
}

An object created by new exists until it is explicitly destroyed by delete. Then, the space it occupied can be reused by new. A C++ implementation does not guarantee the presence of a “garbage collector” that looks out for unreferenced objects and makes them available to new for reuse. Consequently, I will assume that objects created by new are manually freed using delete.

The delete operator may be applied only to a pointer returned by new or to the nullptr. Applying delete to the nullptr has no effect.

If the deleted object is of a class with a destructor (§3.2.1.2, §17.2), that destructor is called by delete before the object’s memory is released for reuse.

11.2.1. Memory Management

The main problems with free store are:

• Leaked objects: People use new and then forget to delete the allocated object.

• Premature deletion: People delete an object that they have some other pointer to and later use that other pointer.

• Double deletion: An object is deleted twice, invoking its destructor (if any) twice.

Leaked objects are potentially a bad problem because they can cause a program to run out of space. Premature deletion is almost always a nasty problem because the pointer to the “deleted object” no longer points to a valid object (so reading it may give bad results) and may indeed point to memory that has been reused for another object (so writing to it may corrupt an unrelated object). Consider this example of very bad code:

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int* p1 = new int{99};
int* p2 = p1;                 // potential trouble
delete p1;                    // now p2 doesn't point to a valid object
p1 = nullptr;                 // gives a false sense of safety
char* p3 = new char{'x'};     // p3 may now point to the memory pointed to by p2
*p2 = 999;                    // this may cause trouble
cout << *p3 << '\n';          // may not print x

Double deletion is a problem because resource managers typically cannot track what code owns a resource. Consider:

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void sloppy() // very bad code
{
     int* p = new int[1000];   // acquire memory
     // ... use *p ...
     delete[] p;               // release memory

     // ... wait a while ...

     delete[] p;               // but sloppy() does not own *p
}

By the second delete[], the memory pointed to by* p may have been reallocated for some other use and the allocator may get corrupted. Replace int with string in that example, and we’ll see string’s destructor trying to read memory that has been reallocated and maybe overwritten by other code, and using what it read to try to delete memory. In general, a double deletion is undefined behavior and the results are unpredictable and usually disastrous.

The reason people make these mistakes is typically not maliciousness and often not even simple sloppiness; it is genuinely hard to consistently deallocate every allocated object in a large program (once and at exactly the right point in a computation). For starters, analysis of a localized part of a program will not detect these problems because an error usually involves several separate parts.

As alternatives to using “naked” news and deletes, I can recommend two general approaches to resource management that avoid such problems:

[1] Don’t put objects on the free store if you don’t have to; prefer scoped variables.

[2] When you construct an object on the free store, place its pointer into a manager object (sometimes called a handle) with a destructor that will destroy it. Examples are string, vector and all the other standard-library containers, unique_ptr (§5.2.1, §34.3.1), and shared_ptr (§5.2.1, §34.3.2). Wherever possible, have that manager object be a scoped variable. Many classical uses of free store can be eliminated by using move semantics (§3.3, §17.5.2) to return large objects represented as manager objects from functions.

This rule [2] is often referred to as RAII (“Resource Acquisition Is Initialization”; §5.2, §13.3) and is the basic technique for avoiding resource leaks and making error handling using exceptions simple and safe.

The standard-library vector is an example of these techniques:

void f(const string& s)
{
      vector<char> v;
      for (auto c : s)
           v.push_back(c);
      // ...
}

The vector keeps its elements on the free store, but it handles all allocations and deallocations itself. In this example, push_back() does news to acquire space for its elements and deletes to free space that it no longer needs. However, the users of vector need not know about those implementation details and will just rely on vector not leaking.

The Token_stream from the calculator example is an even simpler example (§10.2.2). There, a user can use new and hand the resulting pointer to a Token_stream to manage:

Token_stream ts{new istringstream{some_string}};

We do not need to use the free store just to get a large object out of a function. For example:

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string reverse(const string& s)
{
     string ss;
     for (int i=s.size()–1; 0<=i; ––i)
           ss.push_back(s[i]);
     return ss;
}

Like vector, a string is really a handle to its elements. So, we simply move the ss out of reverse() rather than copying any elements (§3.3.2).

The resource management “smart pointers” (e.g., unique_ptr and smart_ptr) are a further example of these ideas (§5.2.1, §34.3.1). For example:

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void f(int n)
{
     int* p1 = new int[n];                   // potential trouble
     unique_ptr<int[]> p2 {new int[n]};
// ...
     if (n%2) throw runtime_error("odd");
     delete[] p1;                       // we may never get here
}

For f(3) the memory pointed to by p1 is leaked, but the memory pointed to by p2 is correctly and implicitly deallocated.

My rule of thumb for the use of new and delete is “no naked news”; that is, new belongs in constructors and similar operations, delete belongs in destructors, and together they provide a coherent memory management strategy. In addition, new is often used in arguments to resource handles.

If everything else fails (e.g., if someone has a lot of old code with lots of undisciplined use of new), C++ offers a standard interface to a garbage collector (§34.5).

11.2.2. Arrays

Arrays of objects can also be created using new. For example:

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char* save_string(const char* p)
{
    char* s = new char[strlen(p)+1];
    strcpy(s,p);        // copy from p to s
    return s;
}

int main(int argc, char* argv[])
{
    if (argc < 2) exit(1);
    char* p = save_string(argv[1]);
    // ...
    delete[] p;
}

The “plain” operator delete is used to delete individual objects; delete[] is used to delete arrays.

Unless you really must use a char* directly, the standard-library string can be used to simplify the save_string():

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string save_string(const char* p)
{
     return string{p};
}
int main(int argc, char* argv[])
{
     if (argc < 2) exit(1);
     string s = save_string(argv[1]);
     // ...
}

In particular, the new[] and the delete[] vanished.

To deallocate space allocated by new, delete and delete[] must be able to determine the size of the object allocated. This implies that an object allocated using the standard implementation of new will occupy slightly more space than a static object. At a minimum, space is needed to hold the object’s size. Usually two or more words per allocation are used for free-store management. Most modern machines use 8-byte words. This overhead is not significant when we allocate many objects or large objects, but it can matter if we allocate lots of small objects (e.g., ints or Points) on the free store.

Note that a vector (§4.4.1, §31.4) is a proper object and can therefore be allocated and deallocated using plain new and delete. For example:

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void f(int n)
{
     vector<int>* p = new vector<int>(n);   // individual object
     int* q = new int[n];               // array
     // ...
     delete p;
     delete[] q;
}

The delete[] operator may be applied only to a pointer to an array returned by new of an array or to the null pointer (§7.2.2). Applying delete[] to the null pointer has no effect.

However, do not use new to create local objects. For example:

void f1()
{
     X* p =new X;
     // ... use *p ...
     delete p;
}

That’s verbose, inefficient, and error-prone (§13.3). In particular, a return or an exception thrown before the delete will cause a memory leak (unless even more code is added). Instead, use a local variable:

void f2()
{
     X x;
     // ... use x ...
}

The local variable x is implicitly destroyed upon exit from f2.

11.2.3. Getting Memory Space

The free-store operators new, delete, new[], and delete[] are implemented using functions presented in the <new> header:

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void* operator new(size_t);       // allocate space for individual object
void operator delete(void* p);    // if (p) deallocate space allocated using operator new()
void* operator new[](size_t);     // allocate space for array
void operator delete[](void* p);  // if (p) deallocate space allocated using operator new[]()

When operator new needs to allocate space for an object, it calls operator new() to allocate a suitable number of bytes. Similarly, when operator new needs to allocate space for an array, it calls operator new[]().

The standard implementations of operator new() and operator new[]() do not initialize the memory returned.

The allocation and deallocation functions deal in untyped and uninitialized memory (often called “raw memory”), as opposed to typed objects. Consequently, they take arguments or return values of type void*. The operators new and delete handle the mapping between this untyped-memory layer and the typed-object layer.

What happens when new can find no store to allocate? By default, the allocator throws a standard-library bad_alloc exception (for an alternative, see §11.2.4.1). For example:

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void f()
{
     vector<char* >v;
     try {
          for (;;) {
                 char* p = new char[10000];  // acquire some memory
                 v.push_back(p);             // make sure the new memory is referenced
                 p[0] = 'x';                 // use the new memory
          }
     }
     catch(bad_alloc) {
          cerr << "Memory exhausted!\n";
     }
}

However much memory we have available, this will eventually invoke the bad_alloc handler. Please be careful: the new operator is not guaranteed to throw when you run out of physical main memory. So, on a system with virtual memory, this program can consume a lot of disk space and take a long time doing so before the exception is thrown.

We can specify what new should do upon memory exhaustion; see §30.4.1.3.

In addition to the functions defined in <new>, a user can define operator new(), etc., for a specific class (§19.2.5). Class members operator new(), etc., are found and used in preference to the ones from <new> according to the usual scope rules.

11.2.4. Overloading new

By default, operator new creates its object on the free store. What if we wanted the object allocated elsewhere? Consider a simple class:

class X {
public:
     X(int);
     // ...
};

We can place objects anywhere by providing an allocator function (§11.2.3) with extra arguments and then supplying such extra arguments when using new:

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void* operator new(size_t, void *p) { return p; }   // explicit placement operator

void* buf = reinterpret_cast<void* =>(0xF00F);      // significant address
X* p2 = new(buf) X;                                 // construct an X at buf;
                                                    // invokes: operator new(sizeof(X),buf)

Because of this usage, the new(buf) X syntax for supplying extra arguments to operator new() is known as the placement syntax. Note that every operator new() takes a size as its first argument and that the size of the object allocated is implicitly supplied (§19.2.5). The operator new() used by the new operator is chosen by the usual argument matching rules (§12.3); every operator new() has a size_t as its first argument.

The “placement” operator new() is the simplest such allocator. It is defined in the standard header <new>:

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void* operator new (size_t sz, void* p) noexcept;       // place object of size sz at p
void* operator new[](size_t sz, void* p) noexcept;      // place object of size sz at p

void operator delete (void* p, void*) noexcept;         // if (p) make *p invalid
void operator delete[](void* p, void*) noexcept;        // if (p) make *p invalid

The “placement delete” operators do nothing except possibly inform a garbage collector that the deleted pointer is no longer safely derived (§34.5).

The placement new construct can also be used to allocate memory from a specific arena:

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class Arena {
public:
     virtual void* alloc(size_t) =0;
     virtual void free(void*) =0;
     // ...
};

void* operator new(size_t sz, Arena* a)
{
     return a–>alloc(sz);
}

Now objects of arbitrary types can be allocated from different Arenas as needed. For example:

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extern Arena* Persistent;
extern Arena* Shared;

void g(int i)
{
     X* p = new(Persistent) X(i);   // X in persistent storage
     X* q = new(Shared) X(i);       // X in shared memory
     // ...
}

Placing an object in an area that is not (directly) controlled by the standard free-store manager implies that some care is required when destroying the object. The basic mechanism for that is an explicit call of a destructor:

void destroy(X* p, Arena* a)
{
     p–>~X();       // call destructor
     a–>free(p);    // free memory
}

Note that explicit calls of destructors should be avoided except in the implementation of resource management classes. Even most resource handles can be written using new and delete. However, it would be hard to implement an efficient general container along the lines of the standard-library vector (§4.4.1, §31.3.3) without using explicit destructor calls. A novice should think thrice before calling a destructor explicitly and also should ask a more experienced colleague before doing so.

See §13.6.1 for an example of how placement new can interact with exception handling.

There is no special syntax for placement of arrays. Nor need there be, since arbitrary types can be allocated by placement new. However, an operator delete() can be defined for arrays (§11.2.3).

11.2.4.1. nothrow new

In programs where exceptions must be avoided (§13.1.5), we can use nothrow versions of new and delete. For example:

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void f(int n)
{
     int* p = new(nothrow) int[n];        // allocate n ints on the free store
     if (p==nullptr) {// no memory available
           // ... handle allocation error ...
     }
     // ...
     operator delete(nothrow,p);         // deallocate *p
}

That nothrow is the name of an object of the standard-library type nothrow_t that is used for disambiguation; nothrow and nothrow_t are declared in <new>.

The functions implementing this are found in <new>:

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void* operator new(size_t sz, const nothrow_t&) noexcept;   // allocate sz bytes;
                                                            // return nullptr if allocation failed
void operator delete(void* p, const nothrow_t&) noexcept;   // deallocate space allocated by new

void* operator new[](size_t sz, const nothrow_t&) noexcept; // allocate sz bytes;
                                                            // return nullptr if allocation failed
void operator delete[](void* p, const nothrow_t&) noexcept; // deallocate space allocated by new

These operator new functions return nullptr, rather than throwing bad_alloc, if there is not sufficient memory to allocate.

11.3. Lists

In addition to their use for initializing named variables (§6.3.5.2), {}-lists can be used as expressions in many (but not all) places. They can appear in two forms:

[1] Qualified by a type, T{...}, meaning “create an object of type T initialized by T{...}”; §11.3.2

[2] Unqualified {...}, for which the the type must be determined from the context of use; §11.3.3

For example:

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struct S { int a, b; };
struct SS { double a, b; };

void f(S);     // f() takes an S

void g(S);
void g(SS);    // g() is overloaded

void h()
{
     f({1,2});          // OK: call f(S{1,2})

     g({1,2});          // error: ambiguous
     g(S{1,2});         // OK: call g(S)
     g(SS{1,2});        // OK: call g(SS)
}

As in their use for initializing named variables (§6.3.5), lists can have zero, one, or more elements. A {}-list is used to construct an object of some type, so the number of elements and their types must be what is required to construct an object of that type.

11.3.1. Implementation Model

The implementation model for {}-lists comes in three parts:

• If the {}-list is used as constructor arguments, the implementation is just as if you had used a ()-list. List elements are not copied except as by-value constructor arguments.

• If the {}-list is used to initialize the elements of an aggregate (an array or a class without a constructor), each list element initializes an element of the aggregate. List elements are not copied except as by-value arguments to aggregate element constructors.

• If the {}-list is used to construct an initializer_list object each list element is used to initialize an element of the underlying array of the initializer_list. Elements are typically copied from the initializer_list to wherever we use them.

Note that this is the general model that we can use to understand the semantics of a {}-list; a compiler may apply clever optimizations as long as the meaning is preserved.

Consider:

vector<double> v = {1, 2, 3.14};

The standard-library vector has an initializer-list constructor (§17.3.4), so the initializer list {1,2,3.14} is interpreted as a temporary constructed and used like this:

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const double temp[] = {double{1}, double{2}, 3.14 } ;
const initializer_list<double> tmp(temp,sizeof(temp)/sizeof(double));
vector<double> v(tmp);

That is, the compiler constructs an array containing the initializers converted to the desired type (here, double). This array is passed to vectors initializer-list constructor as an initializer_list. The initializer-list constructor then copies the values from the array into its own data structure for elements. Note that an initializer_list is a small object (probably two words), so passing it by value makes sense.

The underlying array is immutable, so there is no way (within the standard’s rules) that the meaning of a {}-list can change between two uses. Consider:

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void f()
{
     initializer_list<int> lst {1,2,3};
     cout << *lst.begin() << '\n';
     *lst.begin() = 2;                 // error: lst is immutable
     cout << *lst.begin() << '\n';
}

In particular, having a {}-list be immutable implies that a container taking elements from it must use a copy operation, rather than a move operation.

The lifetime of a {}-list (and its underlying array) is determined by the scope in which it is used (§6.4.2). When used to initialize a variable of type initializer_list<T>, the list lives as long as the variable. When used in an expression (including as an initializer to a variable of some other type, such as vector<T>), the list is destroyed at the end of its full expression.

11.3.2. Qualified Lists

The basic idea of initializer lists as expressions is that if you can initialize a variable x using the notation

T x {v};

then you can create an object with the same value as an expression using T{v} or new T{v}. Using new places the object on the free store and returns a pointer to it, whereas “plain T{v}” makes a temporary object in the local scope (§6.4.2). For example:

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struct S { int a, b; };

void f()
{
      S v {7,8};          // direct initialization of a variable
      v = S{7,8};         // assign using qualified list
      S* p = new S{7,8};  // construct on free store using qualified list
}

The rules constructing an object using a qualified list are those of direct initialization (§16.2.6).

One way of looking at a qualified initializer list with one element is as a conversion from one type to another. For example:

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template<class T>
T square(T x)
{
    return x*x;
}
void f(int i)
{
    double d = square(double{i});
    complex<double> z = square(complex<double>{i});
}

That idea is explored further in §11.5.1.

11.3.3. Unqualified Lists

A unqualified list is used where an expected type is unambiguously known. It can be used as an expression only as:

• A function argument

• A return value

• The right-hand operand of an assignment operator (=, +=*, =, etc.)

• A subscript

For example:

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int f(double d, Matrix& m)
{
      int v {7};          // initializer (direct initialization)
      int v2 = {7};       // initializer (copy initialization)
      int v3 = m[{2,3}];  // assume m takes value pairs as subscripts

      v = {8};            // right-hand operand of assignment
      v += {88};          // right-hand operand of assignment
      {v} = 9;            // error: not left-hand operand of assignment
      v = 7+{10};         // error: not an operand of a non-assignment operator
      f({10.0});          // function argument
      return {11};        // return value
}

The reason that an unqualified list is not allowed on the left-hand side of assignments is primarily that the C++ grammar allows { in that position for compound statements (blocks), so that readability would be a problem for humans and ambiguity resolution would be tricky for compilers. This is not an insurmountable problem, but it was decided not to extend C++ in that direction.

When used as the initializer for a named object without the use of a = (as for v above), an unqualified {}-list performs direct initialization (§16.2.6). In all other cases, it performs copy initialization (§16.2.6). In particular, the otherwise redundant = in an initializer restricts the set of initializations that can be performed with a given {}-list.

The standard-library type initializer_list<T> is used to handle variable-length {}-lists (§12.2.3). Its most obvious use is to allow initializer lists for user-defined containers (§3.2.1.3), but it can also be used directly; for example:

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int high_value(initializer_list<int> val)
{
      int high = numeric_traits<int>lowest();
      if (val.size()==0) return high;
      for (auto x : val)
            if (x>high) high = x;
      return high;
}

int v1 = high_value({1,2,3,4,5,6,7});
int v2 = high_value({–1,2,v1,4,–9,20,v1});

A {}-list is the simplest way of dealing with homogeneous lists of varying lengths. However, beware that zero elements can be a special case. If so, that case should be handled by a default constructor (§17.3.3).

The type of a {}-list can be deduced (only) if all elements are of the same type. For example:

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auto x0 = {};       // error (no element type)
auto x1 = {1};      // initializer_list<int>
auto x2 = {1,2};    // initializer_list<int>
auto x3 = {1,2,3};  // initializer_list<int>
auto x4 = {1,2.0};  // error: nonhomogeneous list

Unfortunately, we do not deduce the type of an unqualified list for a plain template argument. For example:

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template<typename T>
void f(T);

f({});        // error: type of initializer is unknown
f({1});       // error: an unqualified list does not match "plain T"
f({1,2});     // error: an unqualified list does not match "plain T"
f({1,2,3});   // error: an unqualified list does not match "plain T"

I say “unfortunately” because this is a language restriction, rather than a fundamental rule. It would be technically possible to deduce the type of those {}-lists as initializer_list<int>, just like we do for auto initializers.

Similarly, we do not deduce the element type of a container represented as a template. For example:

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template<class T>
void f2(const vector<T>&);

f2({1,2,3});                // error: cannot deduce T
f2({"Kona","Sidney"});      // error: cannot deduce T

This too is unfortunate, but it is a bit more understandable from a language-technical point of view: nowhere in those calls does it say vector. To deduce T the compiler would first have to decide that the user really wanted a vector and then look into the definition of vector to see if it has a constructor that accepts {1,2,3}. In general, that would require an instantiation of vector (§26.2). It would be possible to handle that, but it could be costly in compile time, and the opportunities for ambiguities and confusion if there were many overloaded versions of f2() are reasons for caution. To call f2(), be more specific:

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f2(vector<int>{1,2,3});               // OK
f2(vector<string>{"Kona","Sidney"});  // OK

11.4. Lambda Expressions

A lambda expression, sometimes also referred to as a lambda function or (strictly speaking incorrectly, but colloquially) as a lambda, is a simplified notation for defining and using an anonymous function object. Instead of defining a named class with an operator(), later making an object of that class, and finally invoking it, we can use a shorthand. This is particularly useful when we want to pass an operation as an argument to an algorithm. In the context of graphical user interfaces (and elsewhere), such operations are often referred to as callbacks. This section focuses on technical aspects of lambdas; examples and techniques for the use of lambdas can be found elsewhere (§3.4.3, §32.4, §33.5.2).

A lambda expression consists of a sequence of parts:

• A possibly empty capture list, specifying what names from the definition environment can be used in the lambda expression’s body, and whether those are copied or accessed by reference. The capture list is delimited by [] (§11.4.3).

• An optional parameter list, specifying what arguments the lambda expression requires. The parameter list is delimited by () (§11.4.4).

• An optional mutable specifier, indicating that the lambda expression’s body may modify the state of the lambda (i.e., change the lambda’s copies of variables captured by value) (§11.4.3.4).

• An optional noexcept specifier.

• An optional return type declaration of the form –> type (§11.4.4).

• A body, specifying the code to be executed. The body is delimited by {} (§11.4.3).

The details of passing arguments, returning results, and specifying the body are those of functions and are presented in Chapter 12. The notion of “capture” of local variables is not provided for functions. This implies that a lambda can act as a local function even though a function cannot.

11.4.1. Implementation Model

Lambda expressions can be implemented in a variety of ways, and there are some rather effective ways of optimizing them. However, I find it useful to understand the semantics of a lambda by considering it a shorthand for defining and using a function object. Consider a relatively simple example:

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void print_modulo(const vector<int>& v, ostream& os, int m)
     // output v[i] to os if v[i]%m==0
{
     for_each(begin(v),end(v),
          [&os,m](int x) { if (x%m==0) os << x << '\n'; }
     );
}

To see what this means, we can define the equivalent function object:

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class Modulo_print {
     ostream& os; // members to hold the capture list
     int m;
public:
      Modulo_print(ostream& s, int mm) :os(s), m(mm) {} // capture
      void operator()(int x) const
           { if (x%m==0) os << x << '\n'; }
};

The capture list, [&os,m], becomes two member variables and a constructor to initialize them. The & before os means that we should store a reference, and the absence of a & for m means that we should store a copy. This use of & mirrors its use in function argument declarations.

The body of the lambda simply becomes the body of the operator()(). Since the lambda doesn’t return a value, the operator()() is void. By default, operator()() is const, so that the lambda body doesn’t modify the captured variables. That’s by far the most common case. Should you want to modify the state of a lambda from its body, the lambda can be declared mutable (§11.4.3.4). This corresponds to an operator()() not being declared const.

An object of a class generated from a lambda is called a closure object (or simply a closure). We can now write the original function like this:

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void print_modulo(const vector<int>& v, ostream& os, int m)
     // output v[i] to os if v[i]%m==0
{
     for_each(begin(v),end(v),Modulo_print{os,m});
}

If a lambda potentially captures every local variable by reference (using the capture list [&]), the closure may be optimized to simply contain a pointer to the enclosing stack frame.

11.4.2. Alternatives to Lambdas

That final version of print_modulo() is actually quite attractive, and naming nontrivial operations is generally a good idea. A separately defined class also leaves more room for comments than does a lambda embedded in some argument list.

However, many lambdas are small and used only once. For such uses, the realistic equivalent involves a local class defined immediately before its (only) use. For example:

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void print_modulo(const vector<int>& v, ostream& os, int m)
     // output v[i] to os if v[i]%m==0
{
     class Modulo_print
{
          ostream& os; // members to hold the capture list
          int m;
     public:
          Modulo_print (ostream& s, int mm) :os(s), m(mm) {} // capture
          void operator()(int x) const
               { if (x%m==0) os << x << '\n'; }
     };

     for_each(begin(v),end(v),Modulo_print{os,m});
}

Compared to that, the version using the lambda is a clear winner. If we really want a name, we can just name the lambda:

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void print_modulo(const vector<int>& v, ostream& os, int m)
     // output v[i] to os if v[i]%m==0
{
     auto Modulo_print = [&os,m] (int x) { if (x%m==0) os << x << '\n'; };

     for_each(begin(v),end(v),Modulo_print);
}

Naming the lambda is often a good idea. Doing so forces us to consider the design of the operation a bit more carefully. It also simplifies code layout and allows for recursion (§11.4.5).

Writing a for-loop is an alternative to using a lambda with a for_each(). Consider:

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void print_modulo(const vector<int>& v, ostream& os, int m)
     // output v[i] to os if v[i]%m==0
{
     for (auto x : v)
          if (x%m==0) os << x << '\n';
}

Many would find this version much clearer than any of the lambda versions. However, for_each is a rather special algorithm, and vector<int> is a very specific container. Consider generalizing print_modulo() to handle arbitrary containers:

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template<class C>
void print_modulo(const C& v, ostream& os, int m)
     // output v[i] to os if v[i]%m==0
{
     for (auto x : v)
          if (x%m==0) os << x << '\n';
}

This version works nicely for a map. The C++ range-for-statement specifically caters to the special case of traversing a sequence from its beginning to its end. The STL containers make such traversals easy and general. For example, using a for-statement to traverse a map gives a depth-first traversal. How would we do a breadth-first traversal? The for-loop version of print_modulo() is not amenable to change, so we have to rewrite it to an algorithm. For example:

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template<class C>
void print_modulo(const C& v, ostream& os, int m)
     // output v[i] to os if v[i]%m==0
{
     breadth_first(begin(v),end(v),
         [&os,m](int x) { if (x%m==0) os << x << '\n'; }
     );
}

Thus, a lambda can be used as “the body” for a generalized loop/traversal construct represented as an algorithm. Using for_each rather than breadth_first would give depth-first traversal.

The performance of a lambda as an argument to a traversal algorithm is equivalent (typically identical) to that of the equivalent loop. I have found that to be quite consistent across implementations and platforms. The implication is that we have to base our choice between “algorithm plus lambda” and “for-statement with body” on stylistic grounds and on estimates of extensibility and maintainability.

11.4.3. Capture

The main use of lambdas is for specifying code to be passed as arguments. Lambdas allow that to be done “inline” without having to name a function (or function object) and use it elsewhere. Some lambdas require no access to their local environment. Such lambdas are defined with the empty lambda introducer []. For example:

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void algo(vector<int>& v)
{
     sort(v.begin(),v.end());  // sort values
     // ...
     sort(v.begin(),v.end(),[](int x, int y) { return abs(x)<abs(y); });    // sort absolute values
     // ...
}

If we want to access local names, we have to say so or get an error:

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void f(vector<int>& v)
{
     bool sensitive = true;
     // ...
     sort(v.begin(),v.end(),
          [](int x, int y) { return sensitive ? x<y : abs(x)<abs(y); }  // error: can't access sensitive
     );
}

I used the lambda introducer []. This is the simplest lambda introducer and does not allow the lambda to refer to names in the calling environment. The first character of a lambda expression is always [. A lambda introducer can take various forms:

• []: an empty capture list. This implies that no local names from the surrounding context can be used in the lambda body. For such lambda expressions, data is obtained from arguments or from nonlocal variables.

• [&]: implicitly capture by reference. All local names can be used. All local variables are accessed by reference.

• [=]: implicitly capture by value. All local names can be used. All names refer to copies of the local variables taken at the point of call of the lambda expression.

• [capture-list]: explicit capture; the capture-list is the list of names of local variables to be captured (i.e., stored in the object) by reference or by value. Variables with names preceded by & are captured by reference. Other variables are captured by value. A capture list can also contain this and names followed by ... as elements.

• [&, capture-list]: implicitly capture by reference all local variables with names not mentioned in the list. The capture list can contain this. Listed names cannot be preceded by &. Variables named in the capture list are captured by value.

• [=, capture-list]: implicitly capture by value all local variables with names not mentioned in the list. The capture list cannot contain this. The listed names must be preceded by &. Variables named in the capture list are captured by reference.

Note that a local name preceded by & is always captured by reference and a local name not preceded by & is always captured by value. Only capture by reference allows modification of variables in the calling environment.

The capture-list cases are used for fine-grained control over what names from the call environment are used and how. For example:

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void f(vector<int>& v)
{
     bool sensitive = true;
     // ...
     sort(v.begin(),v.end()
          [sensitive](int x, int y) { return sensitive ? x<y : abs(x)<abs(y); }
     );
}

By mentioning sensitive in the capture list, we make it accessible from within the lambda. By not specifying otherwise, we ensure that the capture of sensitive is done “by value”; just as for argument passing, passing a copy is the default. Had we wanted to capture sensitive “by reference,” we could have said so by adding a & before sensitive in the capture list: [&sensitive].

The choice between capturing by value and by reference is basically the same as the choice for function arguments (§12.2). We use a reference if we need to write to the captured object or if it is large. However, for lambdas, there is the added concern that a lambda might outlive its caller (§11.4.3.1). When passing a lambda to another thread, capturing by value ([=]) is typically best: accessing another thread’s stack through a reference or a pointer can be most disruptive (to performance or correctness), and trying to access the stack of a terminated thread can lead to extremely difficult-to-find errors.

If you need to capture a variadic template (§28.6) argument, use .... For example:

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template<typename ... Var>
void algo(int s, Var... v)
{
     auto helper = [&s,&v...] { return s*(h1(v...)+h2(v...)); }
     // ...
}

Beware that is it easy to get too clever about capture. Often, there is a choice between capture and argument passing. When that’s the case, capture is usually the least typing but has the greatest potential for confusion.

11.4.3.1. Lambda and Lifetime

A lambda might outlive its caller. This can happen if we pass a lambda to a different thread or if the callee stores away the lambda for later use. For example:

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void setup(Menu& m)
{
     // ...
     Point p1, p2, p3;
     // compute positions of p1, p2, and p3
     m.add("draw triangle",[&]{ m.draw(p1,p2,p3); });  // probable disaster
     // ...
}

Assuming that add() is an operation that adds a (name,action) pair to a menu and that the draw() operation makes sense, we are left with a time bomb: the setup() completes and later – maybe minutes later – a user presses the draw triangle button and the lambda tries to access the long-gone local variables. A lambda that wrote to a variable caught by reference would be even worse in that situation.

If a lambda might outlive its caller, we must make sure that all local information (if any) is copied into the closure object and that values are returned through the return mechanism (§12.1.4) or through suitable arguments. For the setup() example, that is easily done:

m.add("draw triangle",[=]{m.draw(p1,p2,p3);});

Think of the capture list as the initializer list for the closure object and [=] and [&] as short-hand notation (§11.4.1).

11.4.3.2. Namespace Names

We don’t need to “capture” namespace variables (including global variables) because they are always accessible (provided they are in scope). For example:

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template<typename U, typename V>
ostream& operator<<(ostream& os, const pair<U,V>& p)
{
     return os << '{' << p.first << ',' << p.second << '}';
}

void print_all(const map<string,int>& m, const string& label)
{
     cout << label << ":\n{\n";
     for_each(m.begin(),m.end(),
          [](const pair<string,int>& p) { cout << p << '\n'; }
     );
     cout << "}\n";
}

Here, we don’t need to capture cout or the output operator for pair.

11.4.3.3. Lambda and this

How do we access members of a class object from a lambda used in a member function? We can include class members in the set of names potentially captured by adding this to the capture list. This is used when we want to use a lambda in the implementation of a member function. For example, we might have a class for building up requests and retrieving results:

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class Request {
     function<map<string,string>(const map<string,string>&)> oper;         // operation
     map<string,string> values;           // arguments
     map<string,string> results;          // targets
public:
     Request(const string& s);            // parse and store request
     void execute()
     {
          [this](){results=oper(values);}  // do oper to values yielding results
     }
};

Members are always captured by reference. That is, [this] implies that members are accessed through this rather than copied into the lambda. Unfortunately, [this] and [=] are incompatible. This implies that incautious use can lead to race conditions in multi-threaded programs (§42.4.6).

11.4.3.4. mutable Lambdas

Usually, we don’t want to modify the state of the function object (the closure), so by default we can’t. That is, the operator()() for the generated function object (§11.4.1) is a const member function. In the unlikely event that we want to modify the state (as opposed to modifying the state of some variable captured by reference; §11.4.3), we can declare the lambda mutable. For example:

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void algo(vector<int>& v)
{
     int count = v.size();
     std::generate(v.begin(),v.end(),
          [count]()mutable{ return ––count; }
     );
}

The ––count decrements the copy of v’s size stored in the closure.

11.4.4. Call and Return

The rules for passing arguments to a lambda are the same as for a function (§12.2), and so are the rules for returning results (§12.1.4). In fact, with the exception of the rules for capture (§11.4.3) most rules for lambdas are borrowed from the rules for functions and classes. However, two irregularities should be noted:

[1] If a lambda expression does not take any arguments, the argument list can be omitted. Thus, the minimal lambda expression is []{}.

[2] A lambda expression’s return type can be deduced from its body. Unfortunately, that is not also done for a function.

If a lambda body does not have a return-statement, the lambda’s return type is void. If a lambda body consists of just a single return-statement, the lambda’s return type is the type of the return’s expression. If neither is the case, we have to explicitly supply a return type. For example:

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void g(double y)
{

     [&]{ f(y);}                                                   // return type is void
     auto z1 = [=](int x){ return x+y; }                           // return type is double
     auto z2 = [=,y]{ if (y) return 1; else return 2; }            // error: body too complicated
                                                                   // for return type deduction
     auto z3 =[y]() { return 1 : 2; }                              // return type is int
     auto z4 = [=,y]()–>int { if (y) return 1; else return 2; }    // OK: explicit return type
}

When the suffix return type notation is used, we cannot omit the argument list.

11.4.5. The Type of a Lambda

To allow for optimized versions of lambda expressions, the type of a lambda expression is not defined. However, it is defined to be the type of a function object in the style presented in §11.4.1. This type, called the closure type, is unique to the lambda, so no two lambdas have the same type. Had two lambdas had the same type, the template instantiation mechanism might have gotten confused. A lambda is of a local class type with a constructor and a const member function operator()(). In addition to using a lambda as an argument, we can use it to initialize a variable declared auto or std::function<R(AL)> where R is the lambda’s return type and AL is its argument list of types (§33.5.3).

For example, I might try to write a lambda to reverse the characters in a C-style string:

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auto rev = [&rev](char* b, char* e)
               { if (1<e–b) { swap(*b,*––e); rev(++b,e); } };      // error

However, that’s not possible because I cannot use an auto variable before its type has been deduced. Instead, I can introduce a name and then use it:

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void f(string& s1, string& s2)
{
     function<void(char* b, char* e)> rev =
          [&](char* b, char* e) { if (1<e–b) { swap( *b, *––e); rev(++b,e); } };

          rev(&s1[0],&s1[0]+s1.size());
          rev(&s2[0],&s2[0]+s2.size());
}

Now, the type of rev is specified before it is used.

If we just want to name a lambda, rather than using it recursively, auto can simplify things:

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void g(vector<string>& vs1, vector<string>& vs2)
{
     auto rev = [&](char* b, char* e) { while (1<e–b) swap( *b++,* ––e); };

     rev(&s1[0],&s1[0]+s1.size());
     rev(&s2[0],&s2[0]+s2.size());
}

A lambda that captures nothing can be assigned to a pointer to function of an appropriate type. For example:

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double (*p1)(double) = [](double a) { return sqrt(a); };
double (*p2)(double) = [&](double a) { return sqrt(a); };      // error: the lambda captures
double (*p3)(int) = [](int a) { return sqrt(a); };             // error: argument types do not match

11.5. Explicit Type Conversion

Sometimes, we have to convert a value of one type into a value of another. Many (arguably too many) such conversions are done implicitly according to the language rules (§2.2.2, §10.5). For example:

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double d = 1234567890;  // integer to floating-point
int i = d;              // floating-point to integer

In other cases, we have to be explicit.

For logical and historical reasons, C++ offers explicit type conversion operations of varying convenience and safety:

• Construction, using the {} notation, providing type-safe construction of new values (§11.5.1)

• Named conversions, providing conversions of various degrees of nastiness:

• const_cast for getting write access to something declared const (§7.5)

• static_cast for reversing a well-defined implicit conversion (§11.5.2)

• reinterpret_cast for changing the meaning of bit patterns (§11.5.2)

• dynamic_cast for dynamically checked class hierarchy navigation (§22.2.1)

• C-style casts, providing any of the named conversions and some combinations of those (§11.5.3)

• Functional notation, providing a different notation for C-style casts (§11.5.4)

I have ordered these conversions in my order of preference and safety of use.

Except for the {} construction notation, I can’t say I like any of those, but at least dynamic_cast is run-time checked. For conversion between two scalar numeric types, I tend to use a homemade explicit conversion function, narrow_cast, where a value might be narrowed:

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template<class Target, class Source>
Target narrow_cast(Source v)
{
    auto r = static_cast<Target>(v);       // convert the value to the target type
    if (static_cast<Source>(r)!=v)
          throw runtime_error("narrow_cast<>() failed");
    return r;
}

That is, if I can convert a value to the target type, convert the result back to the source type, and get back the original value, I’m happy with the result. That is a generalization of the rule the language applies to values in {} initialization (§6.3.5.2). For example:

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void test(double d, int i, char* p)
{
     auto c1 = narrow_cast<char>(64);
     auto c2 = narrow_cast<char>(–64);          // will throw if chars are unsigned
     auto c3 = narrow_cast<char>(264);          // will throw if chars are 8-bit and signed

     auto d1 = narrow_cast<double>(1/3.0F);     // OK
     auto f1 = narrow_cast<float>(1/3.0);       // will probably throw

     auto c4 = narrow_cast<char>(i);            // may throw
     auto f2 = narrow_cast<float>(d);           // may throw

     auto p1 = narrow_cast<char* >(i);          // compile-time error
     auto i1 = narrow_cast<int>(p);             // compile-time error

     auto d2 = narrow_cast<double>(i);          // may throw (but probably will not)
     auto i2 = narrow_cast<int>(d);             // may throw
}

Depending on your use of floating-point numbers, it may be worthwhile to use a range test for floating-point conversions, rather than !=. That is easily done using specializations (§25.3.4.1) or type traits (§35.4.1).

11.5.1. Construction

The construction of a value of type T from a value e can be expressed by the notation T{e} (§iso.8.5.4). For example:

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auto d1 = double{2};       // d1==2.0
double d2 {double{2}/4};   // d1==0.5

Part of the attraction of the T{v} notation is that it will perform only “well-behaved” conversions. For example:

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void f(int);
void f(double);
void g(int i, double d)
{
     f(i);                            // call f(int)
     f(double{i});                    // error: {} doesn't do int to floating conversion

     f(d);                            // call f(double)
     f(int{d});                       // error: {} doesn't truncate
     f(static_cast<int>(d));          // call f(int) with a truncated value

     f(round(d));                     // call f(double) with a rounded value
     f(static_cast<int>(lround(d)));  // call f(int) with a rounded value
                                      // if the d is overflows the int, this still truncates
}

I don’t consider truncation of floating-point numbers (e.g., 7.9 to 7) “well behaved,” so having to be explicit when you want it is a good thing. If rounding is desirable, we can use the standard-library function round(); it performs “conventional 4/5 rounding,” such as 7.9 to 8 and 7.4 to 7.

It sometimes comes as a surprise that {}-construction doesn’t allow int to double conversion, but if (as is not uncommon) the size of an int is the same as the size of a double, then some such conversions must lose information. Consider:

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static_assert(sizeof(int)==sizeof(double),"unexpected sizes");

int x = numeric_limits<int>::max(); // largest possible integer
double d = x;
int y = x;

We will not get x==y. However, we can still initialize a double with an integer literal that can be represented exactly. For example:

double d { 1234 }; // fine

Explicit qualification with the desired type does not enable ill-behaved conversions. For example:

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void g2(char* p)
{
     int x = int{p};           // error: no char* to int conversion
     using Pint = int*;
     int* p2 = Pint{p};        // error: no char* to int* conversion
     // ...
}

For T{v}, “reasonably well behaved” is defined as having a “non-narrowing” (§10.5) conversion from v to T or having an appropriate constructor for T (§17.3).

The constructor notation T{} is used to express the default value of type T. For example:

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template<class T> void f(const T&);

void g3()
{
     f(int{});              // default int value
     f(complex<double>{});  // default complex value
     // ...
}

The value of an explicit use of the constructor for a built-in type is 0 converted to that type (§6.3.5). Thus, int{} is another way of writing 0. For a user-defined type T, T{} is defined by the default constructor (§3.2.1.1, §17.6), if any, otherwise by default construction, MT{}, of each member.

Explicitly constructed unnamed objects are temporary objects, and (unless bound to a reference) their lifetime is limited to the full expression in which they are used (§6.4.2). In this, they differ from unnamed objects created using new (§11.2).

11.5.2. Named Casts

Some type conversions are not well behaved or easy to type check; they are not simple constructions of values from a well-defined set of argument values. For example:

IO_device* d1 = reinterpret_cast<IO_device* >(0Xff00); // device at 0Xff00

There is no way a compiler can know whether the integer 0Xff00 is a valid address (of an I/O device register). Consequently, the correctness of the conversions is completely in the hands of the programmer. Explicit type conversion, often called casting, is occasionally essential. However, traditionally it is seriously overused and a major source of errors.

Another classical example of the need for explicit type conversion is dealing with “raw memory,” that is, memory that holds or will hold objects of a type not known to the compiler. For example, a memory allocator (such as operator new(); §11.2.3) may return a void* pointing to newly allocated memory:

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void* my_allocator(size_t);

void f()
{
     int* p = static_cast<int* >(my_allocator(100));   // new allocation used as ints
     // ...
}

A compiler does not know the type of the object pointed to by the void*.

The fundamental idea behind the named casts is to make type conversion more visible and to allow the programmer to express the intent of a cast:

• static_cast converts between related types such as one pointer type to another in the same class hierarchy, an integral type to an enumeration, or a floating-point type to an integral type. It also does conversions defined by constructors (§16.2.6, §18.3.3, §iso.5.2.9) and conversion operators (§18.4).

• reinterpret_cast handles conversions between unrelated types such as an integer to a pointer or a pointer to an unrelated pointer type (§iso.5.2.10).

• const_cast converts between types that differ only in const and volatile qualifiers (§iso.5.2.11).

• dynamic_cast does run-time checked conversion of pointers and references into a class hierarchy (§22.2.1, §iso.5.2.7).

These distinctions among the named casts allow the compiler to apply some minimal type checking and make it easier for a programmer to find the more dangerous conversions represented as reinterpret_casts. Some static_casts are portable, but few reinterpret_casts are. Hardly any guarantees are made for reinterpret_cast, but generally it produces a value of a new type that has the same bit pattern as its argument. If the target has at least as many bits as the original value, we can reinterpret_cast the result back to its original type and use it. The result of a reinterpret_cast is guaranteed to be usable only if its result is converted back to the exact original type. Note that reinterpret_cast is the kind of conversion that must be used for pointers to functions (§12.5). Consider:

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char x = 'a';
int* p1 = &x;                               // error: no implicit char* to int* conversion
int* p2 = static_cast<int* >(&x);           // error: no implicit char* to int* conversion
int* p3 = reinterpret_cast<int* >(&x);      // OK: on your head be it

struct B { /* ... */ };
struct D : B { /* ... */ };                 // see §3.2.2 and §20.5.2

B* pb = new D;                              // OK: implicit conversion from D* to B*
D* pd = pb;                                 // error: no implicit conversion from B* to D*
D* pd = static_cast<D >(pb);                // OK

Conversions among class pointers and among class reference types are discussed in §22.2.

If you feel tempted to use an explicit type conversion, take the time to consider if it is really necessary. In C++, explicit type conversion is unnecessary in most cases when C needs it (§1.3.3) and also in many cases in which earlier versions of C++ needed it (§1.3.2, §44.2.3). In many programs, explicit type conversion can be completely avoided; in others, its use can be localized to a few routines.

11.5.3. C-Style Cast

From C, C++ inherited the notation (T)e, which performs any conversion that can be expressed as a combination of static_casts, reinterpret_casts, const_casts to make a value of type T from the expression e (§44.2.3). Unfortunately, the C-style cast can also cast from a pointer to a class to a pointer to a private base of that class. Never do that, and hope for a warning from the compiler if you do it by mistake. This C-style cast is far more dangerous than the named conversion operators because the notation is harder to spot in a large program and the kind of conversion intended by the programmer is not explicit. That is, (T)e might be doing a portable conversion between related types, a nonportable conversion between unrelated types, or removing the const modifier from a pointer type. Without knowing the exact types of T and e, you cannot tell.

11.5.4. Function-Style Cast

The construction of a value of type T from a value e can be expressed by the functional notation T(e). For example:

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void f(double d)
{
     int i = int(d);         // truncate d
     complex z = complex(d); // make a complex from d
     // ...
}

The T(e) construct is sometimes referred to as a function-style cast. Unfortunately, for a built-in type T, T(e) is equivalent to (T)e (§11.5.3). This implies that for many built-in types T(e) is not safe.

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void f(double d, char* p)
{
     int a = int(d);  // truncates
     int b = int(p);  // not portable
     // ...
}

Even explicit conversion of a longer integer type to a shorter (such as long to char) can result in nonportable implementation-defined behavior.

Prefer T{v} conversions for well-behaved construction and the named casts (e.g., static_cast) for other conversions.

11.6. Advice

[1] Prefer prefix ++ over suffix ++; §11.1.4.

[2] Use resource handles to avoid leaks, premature deletion, and double deletion; §11.2.1.

[3] Don’t put objects on the free store if you don’t have to; prefer scoped variables; §11.2.1.

[4] Avoid “naked new” and “naked delete”; §11.2.1.

[5] Use RAII; §11.2.1.

[6] Prefer a named function object to a lambda if the operation requires comments; §11.4.2.

[7] Prefer a named function object to a lambda if the operation is generally useful; §11.4.2.

[8] Keep lambdas short; §11.4.2.

[9] For maintainability and correctness, be careful about capture by reference; §11.4.3.1.

[10] Let the compiler deduce the return type of a lambda; §11.4.4.

[11] Use the T{e} notation for construction; §11.5.1.

[12] Avoid explicit type conversion (casts); §11.5.

[13] When explicit type conversion is necessary, prefer a named cast; §11.5.

[14] Consider using a run-time checked cast, such as narrow_cast<>(), for conversion between numeric types; §11.5.

12. Functions

Death to all fanatics!

– Paradox

• Function Declarations

Why Functions?; Parts of a Function Declaration; Function Definitions; Returning Values; inline Functions; constexpr Functions; [[noreturn]] Functions; Local Variables

• Argument Passing

Reference Arguments; Array Arguments; List Arguments; Unspecified Number of Arguments; Default Arguments

• Overloaded Functions

Automatic Overload Resolution; Overloading and Return Type; Overloading and Scope; Resolution for Multiple Arguments; Manual Overload Resolution

• Pre- and Postconditions

• Pointer to Function

• Macros

Conditional Compilation; Predefined Macros; Pragmas

• Advice

12.1. Function Declarations

The main way of getting something done in a C++ program is to call a function to do it. Defining a function is the way you specify how an operation is to be done. A function cannot be called unless it has been previously declared.

A function declaration gives the name of the function, the type of the value returned (if any), and the number and types of the arguments that must be supplied in a call. For example:

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Elem* next_elem();      // no argument; return an Elem*
void exit(int);         // int argument; return nothing
double sqrt(double);    // double argument; return a double

The semantics of argument passing are identical to the semantics of copy initialization (§16.2.6). Argument types are checked and implicit argument type conversion takes place when necessary. For example:

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double s2 = sqrt(2);          // call sqrt() with the argument double{2}
double s3 = sqrt("three");    // error: sqrt() requires an argument of type double

The value of such checking and type conversion should not be underestimated.

A function declaration may contain argument names. This can be a help to the reader of a program, but unless the declaration is also a function definition, the compiler simply ignores such names. As a return type, void means that the function does not return a value (§6.2.7).

The type of a function consists of the return type and the argument types. For class member functions (§2.3.2, §16.2), the name of the class is also part of the function type. For example:

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double f(int i, const Info&);      // type: double(int,const Info&)
char& String::operator[](int);     // type: char& String::(int)

12.1.1. Why Functions?

There is a long and disreputable tradition of writing very long functions – hundreds of lines long. I once encountered a single (handwritten) function with more than 32,768 lines of code. Writers of such functions seem to fail to appreciate one of the primary purposes of functions: to break up complicated computations into meaningful chunks and name them. We want our code to be comprehensible, because that is the first step on the way to maintainability. The first step to comprehensibility is to break computational tasks into comprehensible chunks (represented as functions and classes) and name those. Such functions then provide the basic vocabulary of computation, just as the types (built-in and user-defined) provide the basic vocabulary of data. The C++ standard algorithms (e.g., find, sort, and iota) provide a good start (Chapter 32). Next, we can compose functions representing common or specialized tasks into larger computations.

The number of errors in code correlates strongly with the amount of code and the complexity of the code. Both problems can be addressed by using more and shorter functions. Using a function to do a specific task often saves us from writing a specific piece of code in the middle of other code; making it a function forces us to name the activity and document its dependencies. Also, function call and return saves us from using error-prone control structures, such as gotos (§9.6) and continues (§9.5.5). Unless they are very regular in structure, nested loops are an avoidable source of errors (e.g., use a dot product to express a matrix algorithm rather than nesting loops; §40.6).

The most basic advice is to keep a function of a size so that you can look at it in total on a screen. Bugs tend to creep in when we can view only part of an algorithm at a time. For many programmers that puts a limit of about 40 lines on a function. My ideal is a much smaller size still, maybe an average of 7 lines.

In essentially all cases, the cost of a function call is not a significant factor. Where that cost could be significant (e.g., for frequently used access functions, such as vector subscripting) inlining can eliminate it (§12.1.5). Use functions as a structuring mechanism.

12.1.2. Parts of a Function Declaration

In addition to specifying a name, a set of arguments, and a return type, a function declaration can contain a variety of specifiers and modifiers. In all we can have:

• The name of the function; required

• The argument list, which may be empty (); required

• The return type, which may be void and which may be prefix or suffix (using auto); required

• inline, indicating a desire to have function calls implemented by inlining the function body (§12.1.5)

• constexpr, indicating that it should be possible to evaluate the function at compile time if given constant expressions as arguments (§12.1.6)

• noexcept, indicating that the function may not throw an exception (§13.5.1.1)

• A linkage specification, for example, static (§15.2)

• [[noreturn]], indicating that the function will not return using the normal call/return mechanism (§12.1.4)

In addition, a member function may be specified as:

• virtual, indicating that it can be overridden in a derived class (§20.3.2)

• override, indicating that it must be overriding a virtual function from a base class (§20.3.4.1)

• final, indicating that it cannot be overriden in a derived class (§20.3.4.2)

• static, indicating that it is not associated with a particular object (§16.2.12)

• const, indicating that it may not modify its object (§3.2.1.1, §16.2.9.1)

If you feel inclined to give readers a headache, you may write something like:

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struct S {
     [[noreturn]] virtual inline auto f(const unsigned long int *const) –> void const noexcept;
};

12.1.3. Function Definitions

Every function that is called must be defined somewhere (once only; §15.2.3). A function definition is a function declaration in which the body of the function is presented. For example:

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void swap(int*, int*);        // a declaration

void swap(int* p, int* q)     // a definition
{
     int t = *p;
     *p = *q;
     *q = t;
}

The definition and all declarations for a function must specify the same type. Unfortunately, to preserve C compatibility, a const is ignored at the highest level of an argument type. For example, this is two declarations of the same function:

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void f(int);          // type is void(int)
void f(const int);    // type is void(int)

That function, f(), could be defined as:

void f(int x) { /*we can modify x here */ }

Alternatively, we could define f() as:

void f(const int x) { /*we cannot modify x here */ }

In either case, the argument that f() can or cannot modify is a copy of what a caller provided, so there is no danger of an obscure modification of the calling context.

Function argument names are not part of the function type and need not be identical in different declarations. For example:

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int& max(int& a, int& b, int& c); // return a reference to the larger of a, b, and c

int& max(int& x1, int& x2, int& x3)
{
     return (x1>x2)? ((x1>x3)?x1:x3) : ((x2>x3)?x2:x3);
}

Naming arguments in declarations that are not definitions is optional and commonly used to simplify documentation. Conversely, we can indicate that an argument is unused in a function definition by not naming it. For example:

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void search(table* t, const char* key, const char*)
{
     // no use of the third argument
}

Typically, unnamed arguments arise from the simplification of code or from planning ahead for extensions. In both cases, leaving the argument in place, although unused, ensures that callers are not affected by the change.

In addition to functions, there are a few other things that we can call; these follow most rules defined for functions, such as the rules for argument passing (§12.2):

• Constructors (§2.3.2, §16.2.5) are technicallly not functions; in particular, they don’t return a value, can initialize bases and members (§17.4), and can’t have their address taken.

• Destructors (§3.2.1.2, §17.2) can’t be overloaded and can’t have their address taken.

• Function objects (§3.4.3, §19.2.2) are not functions (they are objects) and can’t be overloaded, but their operator()s are functions.

• Lambda expressions (§3.4.3, §11.4) are basically a shorthand for defining function objects.

12.1.4. Returning Values

Every function declaration contains a specification of the function’s return type (except for constructors and type conversion functions). Traditionally, in C and C++, the return type comes first in a function declaration (before the name of the function). However, a function declaration can also be written using a syntax that places the return type after the argument list. For example, the following two declarations are equivalent:

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string to_string(int a);             // prefix return type
auto to_string(int a) –> string;     // suffix return type

That is, a prefix auto indicates that the return type is placed after the argument list. The suffix return type is preceded by –>.

The essential use for a suffix return type comes in function template declarations in which the return type depends on the arguments. For example:

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template<class T, class U>
auto product(const vector<T>& x, const vector<U>& y) –> decltype(x*y);

However, the suffix return syntax can be used for any function. There is an obvious similarity between the suffix return syntax for a function and the lambda expression syntax (§3.4.3, §11.4); it is a pity those two constructs are not identical.

A function that does not return a value has a “return type” of void.

A value must be returned from a function that is not declared void (however, main() is special; see §2.2.1). Conversely, a value cannot be returned from a void function. For example:

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int f1() { }                // error: no value returned
void f2() { }               // OK

int f3() { return 1; }      // OK
void f4() { return 1; }     // error: return value in void function

int f5() { return; }        // error: return value missing
void f6() { return; }       // OK

A return value is specified by a return-statement. For example:

int fac(int n)
{
      return (n>1) ? n*fac(n–1) : 1;
}

A function that calls itself is said to be recursive.

There can be more than one return-statement in a function:

int fac2(int n)
{
      if (n > 1)
            return n*fac2(n–1);
      return 1;
}

Like the semantics of argument passing, the semantics of function value return are identical to the semantics of copy initialization (§16.2.6). A return-statement initializes a variable of the returned type. The type of a return expression is checked against the type of the returned type, and all standard and user-defined type conversions are performed. For example:

double f() { return 1; }        // 1 is implicitly converted to double{1}

Each time a function is called, a new copy of its arguments and local (automatic) variables is created. The store is reused after the function returns, so a pointer to a local non-static variable should never be returned. The contents of the location pointed to will change unpredictably:

int* fp()
{
      int local = 1;
      // ...
      return &local; // bad
}

An equivalent error can occur when using references:

int& fr()
{
     int local = 1;
     // ...
     return local;   // bad
}

Fortunately, a compiler can easily warn about returning references to local variables (and most do).

There are no void values. However, a call of a void function may be used as the return value of a void function. For example:

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void g(int* p);

void h(int* p)
{
     // ...
     return g(p);    // OK: equivalent to "g(p); return;"
}

This form of return is useful to avoid special cases when writing template functions where the return type is a template parameter.

A return-statement is one of five ways of exiting a function:

• Executing a return-statement.

• “Falling off the end” of a function; that is, simply reaching the end of the function body. This is allowed only in functions that are not declared to return a value (i.e., void functions) and in main(), where falling off the end indicates successful completion (§12.1.4).

• Throwing an exception that isn’t caught locally (§13.5).

• Terminating because an exception was thrown and not caught locally in a noexcept function (§13.5.1.1).

• Directly or indirectly invoking a system function that doesn’t return (e.g., exit(); §15.4).

A function that does not return normally (i.e., through a return or “falling off the end”) can be marked [[noreturn]] (§12.1.7).

12.1.5. inline Functions

A function can be defined to be inline. For example:

inline int fac(int n)
{
     return (n<2) ? 1 : n*fac(n–1);
}

The inline specifier is a hint to the compiler that it should attempt to generate code for a call of fac() inline rather than laying down the code for the function once and then calling through the usual function call mechanism. A clever compiler can generate the constant 720 for a call fac(6). The possibility of mutually recursive inline functions, inline functions that recurse or not depending on input, etc., makes it impossible to guarantee that every call of an inline function is actually inlined. The degree of cleverness of a compiler cannot be legislated, so one compiler might generate 720, another 6*fac(5), and yet another an un-inlined call fac(6). If you want a guarantee that a value is computed at compile time, declare it constexpr and make sure that all functions used in its evaluation are constexpr (§12.1.6).

To make inlining possible in the absence of unusually clever compilation and linking facilities, the definition – and not just the declaration – of an inline function must be in scope (§15.2). An inline specifier does not affect the semantics of a function. In particular, an inline function still has a unique address, and so do static variables (§12.1.8) of an inline function.

If an inline function is defined in more than one translation unit (e.g., typically because it was defined in a header; §15.2.2), its definition in the different translation units must be identical (§15.2.3).

12.1.6. constexpr Functions

In general, a function cannot be evaluated at compile time and therefore cannot be called in a constant expression (§2.2.3, §10.4). By specifying a function constexpr, we indicate that we want it to be usable in constant expressions if given constant expressions as arguments. For example:

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constexpr int fac(int n)
{
    return (n>1) ? n*fac(n–1) : 1;
}

constexpr int f9 = fac(9);          // must be evaluated at compile time

When constexpr is used in a function definition, it means “should be usable in a constant expression when given constant expressions as arguments.” When used in an object definition, it means “evaluate the initializer at compile time.” For example:

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void f(int n)
{
     int f5 = fac(5);               // may be evaluated at compile time
     int fn = fac(n);               // evaluated at run time (n is a variable)

     constexpr int f6 = fac(6);     // must be evaluated at compile time
     constexpr int fnn = fac(n);    // error: can't guarantee compile-time evaluation (n is a variable)

     char a[fac(4)];                // OK: array bounds must be constants and fac() is constexpr
     char a2[fac(n)];               // error: array bounds must be constants and n is a variable

     // ...
}

To be evaluated at compile time, a function must be suitably simple: a constexpr function must consist of a single return-statement; no loops and no local variables are allowed. Also, a constexpr function may not have side effects. That is, a constexpr function is a pure function. For example:

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int glob;

constexpr void bad1(int a)     // error: constexpr function cannot be void
{
     glob = a;           // error: side effect in constexpr function
}

constexpr int bad2(int a)
{
     if (a>=0) return a; else return –a;    // error: if-statement in constexpr function
}

constexpr int bad3(int a)
{
     sum = 0;                               // error: local variable in constexpr function
     for (int i=0; i<a; +=i) sum +=fac(i);  // error: loop in constexpr function
     return sum;
}

The rules for a constexpr constructor are suitably different (§10.4.3); there, only simple initialization of members is allowed.

A constexpr function allows recursion and conditional expressions. This implies that you can express just about anything as a constexpr function if you really want to. However, you’ll find the debugging gets unnecessarily difficult and compile times longer than you would like unless you restrict the use of constexpr functions to the relatively simple tasks for which they are intended.

By using literal types (§10.4.3), constexpr functions can be defined to use user-defined types.

Like inline functions, constexpr functions obey the ODR (“one-definition rule”), so that definitions in the different translation units must be identical (§15.2.3). You can think of constexpr functions as a restricted form of inline functions (§12.1.5).

12.1.6.1. constexpr and References

A constexpr function cannot have side effects, so writing to nonlocal objects is not possible. However, a constexpr function can refer to nonlocal objects as long as it does not write to them.

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constexpr int ftbl[] { 1, 2, 3, 5, 8, 13 };

constexpr int fib(int n)
{
    return (n<sizeof(ftbl)/sizeof(*ftbl)) ? ftbl[n] : fib(n);
}

A constexpr function can take reference arguments. Of course, it cannot write through such references, but const reference parameters are as useful as ever. For example, in the standard library (§40.4) we find:

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template<> class complex<float> {
public:
// ...
     explicit constexpr complex(const complex<double>&);
     // ...
};

This allows us to write:

constexpr complex<float> z {2.0};

The temporary variable that is logically constructed to hold the const reference argument simply becomes a value internal to the compiler.

It is possible for a constexpr function to return a reference or a pointer. For example:

constexpr const int* addr(const int& r) { return &r; }   // OK

However, doing so brings us away from the fundamental role of constexpr functions as parts of constant expression evaluation. In particular, it can be quite tricky to determine whether the result of such a function is a constant expression. Consider:

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static const int x = 5;
constexpr const int* p1 = addr(x);      // OK
constexpr int xx = *p1;                 // OK

static int y;
constexpr const int* p2 = addr(y);      // OK
constexpr int yy = *y;                  // error: attempt to read a variable

constexpr const int* tp = addr(5);      // error: address of temporary

12.1.6.2. Conditional Evaluation

A branch of a conditional expression that is not taken in a constexpr function is not evaluated. This implies that a branch not taken can require run-time evaluation. For example:

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constexpr int check(int i)
{
    return (low<=i && i<high) ? i : throw out_of_range();
}

constexpr int low = 0;
constexpr int high = 99;

// ...
constexpr int val = check(f(x,y,z));

You might imagine low and high to be configuration parameters that are known at compile time, but not at design time, and that f(x,y,z) computes some implementation-dependent value.

12.1.7. [[noreturn]] Functions

A construct [[...]] is called an attribute and can be placed just about anywhere in the C++ syntax. In general, an attribute specifies some implementation-dependent property about the syntactic entity that precedes it. In addition, an attribute can be placed in front of a declaration. There are only two standard attributes (§iso.7.6), and [[noreturn]] is one of them. The other is [[carries_dependency]] (§41.3).

Placing [[noreturn]] at the start of a function declaration indicates that the function is not expected to return. For example:

[[noreturn]] void exit(int);     // exit will never return

Knowing that a function does not return is useful for both comprehension and code generation. What happens if the function returns despite a [[noreturn]] attribute is undefined.

12.1.8. Local Variables

A name defined in a function is commonly referred to as a local name. A local variable or constant is initialized when a thread of execution reaches its definition. Unless declared static, each invocation of the function has its own copy of the variable. If a local variable is declared static, a single, statically allocated object (§6.4.2) will be used to represent that variable in all calls of the function. It will be initialized only the first time a thread of execution reaches its definition. For example:

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void f(int a)
{
     while (a––) {
          static int n = 0;     // initialized once
          int x = 0;            // initialized 'a' times in each call of f()

          cout << "n == " << n++ << ", x == " << x++ << '\n';
     }
}

int main()
{
     f(3);
}

This prints:

n == 0, x == 0
n == 1, x == 0
n == 2, x == 0

A static local variable allows the function to preserve information between calls without introducing a global variable that might be accessed and corrupted by other functions (see also §16.2.12).

Initialization of a static local variable does not lead to a data race (§5.3.1) unless you enter the function containing it recursively or a deadlock occurs (§iso.6.7). That is, the C++ implementation must guard the initialization of a local static variable with some kind of lock-free construct (e.g., a call_once; §42.3.3). The effect of initializing a local static recursively is undefined. For example:

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int fn(int n)
{
      static int n1 = n;             // OK
      static int n2 = fn(n–1)+1;     // undefined
      return n;
}

A static local variable is useful for avoiding order dependencies among nonlocal variables (§15.4.1).

There are no local functions; if you feel you need one, use a function object or a lambda expression (§3.4.3, §11.4).

The scope of a label (§9.6), should you be foolhardy enough to use one, is the complete function, independent of which nested scope it may be in.

12.2. Argument Passing

When a function is called (using the suffix (), known as the call operator or application operator), store is set aside for its formal arguments (also known as its parameters), and each formal argument is initialized by its corresponding actual argument. The semantics of argument passing are identical to the semantics of initialization (copy initialization, to be precise; §16.2.6). In particular, the type of an actual argument is checked against the type of the corresponding formal argument, and all standard and user-defined type conversions are performed. Unless a formal argument (parameter) is a reference, a copy of the actual argument is passed to the function. For example:

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int* find(int* first, int* last, int v)   // find x in [first:last)
{
     while (first!=last && *first!=v)
          ++first;
     return first;
}

void g(int* p, int* q)
{
     int* pp = find(p,q,'x');
     // ...
}

Here, the caller’s copy of the argument, p, is not modified by the operations on find()’s copy, called first. The pointer is passed by value.

There are special rules for passing arrays (§12.2.2), a facility for passing unchecked arguments (§12.2.4), and a facility for specifying default arguments (§12.2.5). The use of initializer lists is described in §12.2.3 and the ways of passing arguments to template functions in §23.5.2 and §28.6.2.

12.2.1. Reference Arguments

Consider:

void f(int val, int& ref)
{
     ++val;
     ++ref;
}

When f() is called, ++val increments a local copy of the first actual argument, whereas ++ref increments the second actual argument. Consider:

void g()
{
     int i = 1;
     int j = 1;
     f(i,j);
}

The call f(i,j) will increment j but not i. The first argument, i, is passed by value; the second argument, j, is passed by reference. As mentioned in §7.7, functions that modify call-by-reference arguments can make programs hard to read and should most often be avoided (but see §18.2.5). It can, however, be noticeably more efficient to pass a large object by reference than to pass it by value. In that case, the argument might be declared a const reference to indicate that the reference is used for efficiency reasons only and not to enable the called function to change the value of the object:

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void f(const Large& arg)
{
     // the value of "arg" cannot be changed
     // (except by using explicit type conversion; §11.5)
}

The absence of const in the declaration of a reference argument is taken as a statement of intent to modify the variable:

void g(Large& arg);     // assume that g() modifies arg

Similarly, declaring a pointer argument const tells readers that the value of an object pointed to by that argument is not changed by the function. For example:

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int strlen(const char*);                     // number of characters in a C-style string
char* strcpy(char* to, const char* from);    // copy a C-style string
int strcmp(const char*, const char*);        // compare C-style strings

The importance of using const arguments increases with the size of a program.

Note that the semantics of argument passing are different from the semantics of assignment. This is important for const arguments, reference arguments, and arguments of some user-defined types.

Following the rules for reference initialization, a literal, a constant, and an argument that requires conversion can be passed as a const T& argument, but not as a plain (non-const)T& argument. Allowing conversions for a const T& argument ensures that such an argument can be given exactly the same set of values as a T argument by passing the value in a temporary, if necessary. For example:

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float fsqrt(const float&); // Fortran-style sqrt taking a reference argument

void g(double d)
{
     float r = fsqrt(2.0f);      // pass reference to temp holding 2.0f
     r = fsqrt(r);               // pass reference to r
     r = fsqrt(d);               // pass reference to temp holding static_cast<float>(d)
}

Disallowing conversions for non-const reference arguments (§7.7) avoids the possibility of silly mistakes arising from the introduction of temporaries. For example:

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void update(float& i);

void g(double d, float r)
{
     update(2.0f);          // error: const argument
     update(r);             // pass reference to r
     update(d);             // error: type conversion required
}

Had these calls been allowed, update() would quietly have updated temporaries that immediately were deleted. Usually, that would come as an unpleasant surprise to the programmer.

If we wanted to be precise, pass-by-reference would be pass-by-lvalue-reference because a function can also take rvalue references. As described in §7.7, an rvalue can be bound to an rvalue reference (but not to an lvalue reference) and an lvalue can be bound to an lvalue reference (but not to an rvalue reference). For example:

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void f(vector<int>&);              // (non-const) lvalue reference argument
void f(const vector<int>&);        // const lvalue reference argument
void f(vector<int>&&);             // rvalue reference argument

void g(vector<int>& vi, const vector<int>& cvi)
{
     f(vi);                    // call f(vector<int>&)
     f(vci);                   // call f(const vector<int>&)
     f(vector<int>{1,2,3,4});  // call f(vector<int>&&);
}

We must assume that a function will modify an rvalue argument, leaving it good only for destruction or reassignment (§17.5). The most obvious use of rvalue references is to define move constructors and move assignments (§3.3.2, §17.5.2). I’m sure someone will find a clever use for const-rvalue-reference arguments, but so far, I have not seen a genuine use case.

Please note that for a template argument T, the template argument type deduction rules give T&& a significantly different meaning from X&& for a type X (§23.5.2.1). For template arguments, an rvalue reference is most often used to implement “perfect forwarding” (§23.5.2.1, §28.6.3).

How do we choose among the ways of passing arguments? My rules of thumb are:

[1] Use pass-by-value for small objects.

[2] Use pass-by-const-reference to pass large values that you don’t need to modify.

[3] Return a result as a return value rather than modifying an object through an argument.

[4] Use rvalue references to implement move (§3.3.2, §17.5.2) and forwarding (§23.5.2.1).

[5] Pass a pointer if “no object” is a valid alternative (and represent “no object” by nullptr).

[6] Use pass-by-reference only if you have to.

The “when you have to” in the last rule of thumb refers to the observation that passing pointers is often a less obscure mechanism for dealing with objects that need modification (§7.7.1, §7.7.4) than using references.

12.2.2. Array Arguments

If an array is used as a function argument, a pointer to its initial element is passed. For example:

int strlen(const char*);

void f()
{
     char v[] = "Annemarie";
     int i = strlen(v);
     int j = strlen("Nicholas");
}

That is, an argument of type T[] will be converted to a T* when passed as an argument. This implies that an assignment to an element of an array argument changes the value of an element of the argument array. In other words, arrays differ from other types in that an array is not passed by value. Instead, a pointer is passed (by value).

A parameter of array type is equivalent to a parameter of pointer type. For example:

void odd(int* p);
void odd(int a[]);
void odd(int buf[1020]);

These three declarations are equivalent and declare the same function. As usual, the argument names do not affect the type of the function (§12.1.3). The rules and techniques for passing multidimensional arrays can be found in §7.4.3.

The size of an array is not available to the called function. This is a major source of errors, but there are several ways of circumventing this problem. C-style strings are zero-terminated, so their size can be computed (e.g., by a potentially expensive call of strlen(); §43.4). For other arrays, a second argument specifying the size can be passed. For example:

void compute1(int* vec_ptr, int vec_size);    // one way

At best, this is a workaround. It is usually preferable to pass a reference to some container, such as vector (§4.4.1, §31.4), array (§34.2.1), or map (§4.4.3, §31.4.3).

If you really want to pass an array, rather than a container or a pointer to the first element of an array, you can declare a parameter of type reference to array. For example:

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void f(int(&r)[4]);

void g()
{
     int a1[] = {1,2,3,4};
     int a2[] = {1,2};

     f(a1);      // OK
     f(a2);      // error : wrong number of elements
}

Note that the number of elements is part of a reference-to-array type. That makes such references far less flexible than pointers and containers (such as vector). The main use of references to arrays is in templates, where the number of elements is then deduced. For example:

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template<class T, int N> void f(T(&r)[N])
{
     // ...
}

int a1[10];
double a2[100];

void g()
{
     f(a1);         // T is int; N is 10
     f(a2);         // T is double; N is 100
}

This typically gives rise to as many function definitions as there are calls to f() with distinct array types.

Multidimensional arrays are tricky (see §7.3), but often arrays of pointers can be used instead, and they need no special treatment. For example:

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const char* day[] = {
    "mon", "tue", "wed", "thu", "fri", "sat", "sun"
};

As ever, vector and similar types are alternatives to the built-in, low-level arrays and pointers.

12.2.3. List Arguments

A {}-delimited list can be used as an argument to a parameter of:

[1] Type std::initializer_list<T>, where the values of the list can be implicitly converted to T

[2] A type that can be initialized with the values provided in the list

[3] A reference to an array of T, where the values of the list can be implicitly converted to T

Technically, case [2] covers all examples, but I find it easier to think of the three cases separately. Consider:

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template<class T>
void f1(initializer_list<T>);

struct S {
     int a;
     string s;
};
void f2(S);

template<class T, int N>
void f3(T (&r)[N]);

void f4(int);

void g()
{
     f1({1,2,3,4});  // T is int and the initializer_list has size() 4
     f2({1,"MKS"});  // f2(S{1,"MKS"})
     f3({1,2,3,4});  // T is int and N is 4
     f4({1});        // f4(int{1});
}

If there is a possible ambiguity, an initializer_list parameter takes priority. For example:

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template<class T>
void f(initializer_list<T>);

struct S {
     int a;
     string s;

};
void f(S);

template<class T, int N>
void f(T (&r)[N]);

void f(int);

void g()
{
     f({1,2,3,4});   // T is int and the initializer_list has size() 4
     f({1,"MKS"});   // calls f(S)
     f({1});         // T is int and the initializer_list has size() 1
}

The reason that a function with an initializer_list argument take priority is that it could be very confusing if different functions were chosen based on the number of elements of a list. It is not possible to eliminate every form of confusion in overload resolution (for example, see §4.4, §17.3.4.1), but giving initializer_list parameters priority for {}-list arguments seems to minimize confusion.

If there is a function with an initializer-list argument in scope, but the argument list isn’t a match for that, another function can be chosen. The call f({1,"MKS"}) was an example of that.

Note that these rules apply to std::initializer_list<T> arguments only. There are no special rules for std::initializer_list<T>& or for other types that just happen to be called initializer_list (in some other scope).

12.2.4. Unspecified Number of Arguments

For some functions, it is not possible to specify the number and type of all arguments expected in a call. To implement such interfaces, we have three choices:

[1] Use a variadic template (§28.6): this allows us to handle an arbitrary number of arbitrary types in a type-safe manner by writing a small template metaprogram that interprets the argument list to determine its meaning and take appropriate actions.

[2] Use an initializer_list as the argument type (§12.2.3). This allows us to handle an arbitrary number of arguments of a single type in a type-safe manner. In many contexts, such homogeneous lists are the most common and important case.

[3] Terminate the argument list with the ellipsis (...), which means “and maybe some more arguments.” This allows us to handle an arbitrary number of (almost) arbitrary types by using some macros from <cstdarg>. This solution is not inherently type-safe and can be hard to use with sophisticated user-defined types. However, this mechanism has been used from the earliest days of C.

The first two mechanisms are described elsewhere, so I describe only the third mechanism (even though I consider it inferior to the others for most uses). For example:

int printf(const char* ...);

This specifies that a call of the standard-library function printf() (§43.3) must have at least one argument, a C-style string, but may or may not have others. For example:

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printf("Hello, world!\n");
printf("My name is %s %s\n", first_name, second_name);
printf("%d + %d = %d\n",2,3,5);

Such a function must rely on information not available to the compiler when interpreting its argument list. In the case of printf(), the first argument is a format string containing special character sequences that allow printf() to handle other arguments correctly; %s means “expect a char* argument” and %d means “expect an int argument.” However, the compiler cannot in general ensure that the expected arguments are really provided in a call or that an argument is of the expected type. For example:

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#include <cstdio>

int main()
{
     std::printf("My name is %s %s\n",2);
}

This is not valid code, but most compilers will not catch this error. At best, it will produce some strange-looking output (try it!).

Clearly, if an argument has not been declared, the compiler does not have the information needed to perform the standard type checking and type conversion for it. In that case, a char or a short is passed as an int and a float is passed as a double. This is not necessarily what the programmer expects.

A well-designed program needs at most a few functions for which the argument types are not completely specified. Overloaded functions, functions using default arguments, functions taking initializer_list arguments, and variadic templates can be used to take care of type checking in most cases when one would otherwise consider leaving argument types unspecified. Only when both the number of arguments and the types of arguments vary and a variadic template solution is deemed undesirable is the ellipsis necessary.

The most common use of the ellipsis is to specify an interface to C library functions that were defined before C++ provided alternatives:

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int fprintf(FILE*, const char* ...);       // from <cstdio>
int execl(const char* ...);                // from UNIX header

A standard set of macros for accessing the unspecified arguments in such functions can be found in <cstdarg>. Consider writing an error function that takes one integer argument indicating the severity of the error followed by an arbitrary number of strings. The idea is to compose the error message by passing each word as a separate C-style string argument. The list of string arguments should be terminated by the null pointer:

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extern void error(int ...);
extern char* itoa(int, char[]);  // int to alpha

int main(int argc, char* argv[])
{
     switch (argc) {
     case 1:
          error(0,argv[0],nullptr);
          break;
     case 2:
          error(0,argv[0],argv[1],nullptr);
          break;
     default:
          char buffer[8];
          error(1,argv[0],"with",itoa(argc–1,buffer),"arguments",nullptr);
     }
     // ...
}

The function itoa() returns a C-style string representing its int argument. It is popular in C, but not part of the C standard.

I always pass argv[0] because that, conventionally, is the name of the program.

Note that using the integer 0 as the terminator would not have been portable: on some implementations, the integer 0 and the null pointer do not have the same representation (§6.2.8). This illustrates the subtleties and extra work that face the programmer once type checking has been suppressed using the ellipsis.

The error() function could be defined like this:

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#include <cstdarg>

void error(int severity ...) // "severity" followed by a zero-terminated list of char*s
{
     va_list ap;
     va_start(ap,severity);    // arg startup

     for (;;) {
            char* p = va_arg(ap,char*);
            if (p == nullptr) break;
            cerr << p << ' ';
     }

     va_end(ap);               // arg cleanup

     cerr << '\n';
     if (severity) exit(severity);
}

First, a va_list is defined and initialized by a call of va_start(). The macro va_start takes the name of the va_list and the name of the last formal argument as arguments. The macro va_arg() is used to pick the unnamed arguments in order. In each call, the programmer must supply a type; va_arg() assumes that an actual argument of that type has been passed, but it typically has no way of ensuring that. Before returning from a function in which va_start() has been used, va_end() must be called. The reason is that va_start() may modify the stack in such a way that a return cannot successfully be done; va_end() undoes any such modifications.

Alternatively, error() could have been defined using a standard-library initializer_list:

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void error(int severity, initializer_list<string> err)
{
     for (auto& s : err)
           cerr << s << ' ';
     cerr << '\n';
     if (severity) exit(severity);
}

It would then have to be called using the list notation. For example:

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switch (argc) {
case 1:
     error(0,{argv[0]});
     break;
case 2:
     error(0,{argv[0],argv[1]});
     break;
default:
     error(1,{argv[0],"with",to_string(argc–1),"arguments"});
}

The int-to-string conversion function to_string() is provided by the standard library (§36.3.5).

If I didn’t have to mimic C style, I would further simplify the code by passing a container as a single argument:

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void error(int severity, const vector<string>& err) // almost as before
{
     for (auto& s : err)
           cerr << s << ' ';
     cerr << '\n';
     if (severity) exit(severity);
}

vector<string> arguments(int argc, char* argv[]) // package arguments
{
     vector<string> res;
     for (int i = 0; i!=argc; ++i)
           res.push_back(argv[i]);
     return res
}

int main(int argc, char* argv[])
{
     auto args = arguments(argc,argv);
     error((args.size()<2)?0:1,args);
     // ...
}

The helper function, arguments(), is trivial, and main() and error() are simple. The interface between main() and error() is more general in that it now passes all arguments. That would allow later improvements of error(). The use of the vector<string> is far less error-prone than any use of an unspecified number of arguments.

12.2.5. Default Arguments

A general function often needs more arguments than are necessary to handle simple cases. In particular, functions that construct objects (§16.2.5) often provide several options for flexibility. Consider class complex from §3.2.1.1:

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class complex {
     double re, im;
public:
     complex(double r, double i) :re{r}, im{i} {}     // construct complex from two scalars
     complex(double r) :re{r}, im{0} {}               // construct complex from one scalar
     complex() :re{0}, im{0} {}
// default complex: {0,0}
     // ...
};

The actions of complex’s constructors are quite trivial, but logically there is something odd about having three functions (here, constructors) doing essentially the same task. Also, for many classes, constructors do more work and the repetitiveness is common. We could deal with the repetitiveness by considering one of the constructors “the real one” and forward to that (§17.4.3):

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complex(double r, double i) :re{r}, im{i} {}    // construct complex from two scalars
complex(double r) :complex{2,0} {}              // construct complex from one scalar
complex() :complex{0,0} {}                      // default complex: {0,0}

Say we wanted to add some debugging, tracing, or statistics-gathering code to complex; we now have a single place to do so. However, this can be abbreviated further:

complex(double r ={}, double i ={}) :re{r}, im{i} {}  // construct complex from two scalars

This makes it clear that if a user supplies fewer than the two arguments needed, the default is used. The intent of having a single constructor plus some shorthand notation is now explicit.

A default argument is type checked at the time of the function declaration and evaluated at the time of the call. For example:

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class X {
public:
     static int def_arg;
     void f(int =def_arg);
     // ...
};

int X::def_arg = 7;

void g(X& a)
{
     a.f();         // maybe f(7)
     a.def_arg = 9;
     a.f();         // f(9)
}

Default arguments that can change value are most often best avoided because they introduce subtle context dependencies.

Default arguments may be provided for trailing arguments only. For example:

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int f(int, int =0, char* =nullptr);// OK
int g(int =0, int =0, char*);           // error
int h(int =0, int, char* =nullptr);     // error

Note that the space between the * and the = is significant (*= is an assignment operator; §10.3):

int nasty(char*=nullptr);               // syntax error

A default argument cannot be repeated or changed in a subsequent declaration in the same scope. For example:

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void f(int x = 7);
void f(int = 7);          // error: cannot repeat default argument
void f(int = 8);          // error: different default arguments

void g()
{
     void f(int x = 9);   // OK: this declaration hides the outer one
     // ...
}

Declaring a name in a nested scope so that the name hides a declaration of the same name in an outer scope is error-prone.

12.3. Overloaded Functions

Most often, it is a good idea to give different functions different names, but when different functions conceptually perform the same task on objects of different types, it can be more convenient to give them the same name. Using the same name for operations on different types is called overloading. The technique is already used for the basic operations in C++. That is, there is only one name for addition, +, yet it can be used to add values of integer and floating-point types and combinations of such types. This idea is easily extended to functions defined by the programmer. For example:

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void print(int);           // print an int
void print(const char*);   // print a C-style string

As far as the compiler is concerned, the only thing functions of the same name have in common is that name. Presumably, the functions are in some sense similar, but the language does not constrain or aid the programmer. Thus, overloaded function names are primarily a notational convenience. This convenience is significant for functions with conventional names such as sqrt, print, and open. When a name is semantically significant, this convenience becomes essential. This happens, for example, with operators such as +, *, and <<, in the case of constructors (§16.2.5, §17.1), and in generic programming (§4.5, Chapter 32).

Templates provide a systematic way of defining sets of overloaded functions (§23.5).

12.3.1. Automatic Overload Resolution

When a function fct is called, the compiler must determine which of the functions named fct to invoke. This is done by comparing the types of the actual arguments with the types of the parameters of all functions in scope called fct. The idea is to invoke the function that is the best match to the arguments and give a compile-time error if no function is the best match. For example:

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void print(double);
void print(long);

void f()
{
     print(1L);      // print(long)
     print(1.0);     // print(double)
     print(1);       // error, ambiguous: print(long(1)) or print(double(1))?
}

To approximate our notions of what is reasonable, a series of criteria are tried in order:

[1] Exact match; that is, match using no or only trivial conversions (for example, array name to pointer, function name to pointer to function, and T to const T)

[2] Match using promotions; that is, integral promotions (bool to int, char to int, short to int, and their unsigned counterparts; §10.5.1) and float to double

[3] Match using standard conversions (e.g., int to double, double to int, double to long double, Derived* to Base* (§20.2), T* to void* (§7.2.1), int to unsigned int (§10.5))

[4] Match using user-defined conversions (e.g., double to complex<double>; §18.4)

[5] Match using the ellipsis ... in a function declaration (§12.2.4)

If two matches are found at the highest level where a match is found, the call is rejected as ambiguous. The resolution rules are this elaborate primarily to take into account the elaborate C and C++ rules for built-in numeric types (§10.5). For example:

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void print(int);
void print(const char*);
void print(double);
void print(long);
void print(char);

void h(char c, int i, short s, float f)
{
     print(c);         // exact match: invoke print(char)
     print(i);         // exact match: invoke print(int)
     print(s);         // integral promotion: invoke print(int)
     print(f);         // float to double promotion: print(double)

     print('a');       // exact match: invoke print(char)
     print(49);        // exact match: invoke print(int)
     print(0);         // exact match: invoke print(int)
     print("a");       // exact match: invoke print(const char*)
     print(nullptr);   // nullptr_t to const char* promotion: invoke print(cost char*)
}

The call print(0) invokes print(int) because 0 is an int. The call print('a') invokes print(char) because 'a' is a char (§6.2.3.2). The reason to distinguish between conversions and promotions is that we want to prefer safe promotions, such as char to int, over unsafe conversions, such as int to char. See also §12.3.5.

Overload resolution is independent of the order of declaration of the functions considered.

Function templates are handled by applying the overload resolution rules to the result of specialization based on a set of arguments (§23.5.3). There are separate rules for overloading when a {}-list is used (initializer lists take priority; §12.2.3, §17.3.4.1) and for rvalue reference template arguments (§23.5.2.1).

Overloading relies on a relatively complicated set of rules, and occasionally a programmer will be surprised which function is called. So, why bother? Consider the alternative to overloading. Often, we need similar operations performed on objects of several types. Without overloading, we must define several functions with different names:

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void print_int(int);
void print_char(char);
void print_string(const char*);       // C-style string

void g(int i, char c, const char* p, double d)
{
     print_int(i);         // OK
     print_char(c);        // OK
     print_string(p);      // OK

     print_int(c);         // OK? calls print_int(int(c)), prints a number
     print_char(i);        // OK? calls print_char(char(i)), narrowing
     print_string(i);      // error
     print_int(d);         // OK? calls print_int(int(d)), narrowing
}

Compared to the overloaded print(), we have to remember several names and remember to use those correctly. This can be tedious, defeats attempts to do generic programming (§4.5), and generally encourages the programmer to focus on relatively low-level type issues. Because there is no overloading, all standard conversions apply to arguments to these functions. It can also lead to errors. In the previous example, this implies that only one of the four calls with doubtful semantics is caught by the compiler. In particular, two calls rely on error-prone narrowing (§2.2.2, §10.5). Thus, overloading can increase the chances that an unsuitable argument will be rejected by the compiler.

12.3.2. Overloading and Return Type

Return types are not considered in overload resolution. The reason is to keep resolution for an individual operator (§18.2.1, §18.2.5) or function call context-independent. Consider:

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float sqrt(float);
double sqrt(double);

void f(double da, float fla)
{
     float fl = sqrt(da); // call sqrt(double)
     double d = sqrt(da); // call sqrt(double)
     fl = sqrt(fla);      // call sqrt(float)
     d = sqrt(fla);       // call sqrt(float)
}

If the return type were taken into account, it would no longer be possible to look at a call of sqrt() in isolation and determine which function was called.

12.3.3. Overloading and Scope

Overloading takes place among the members of an overload set. By default, that means the functions of a single scope; functions declared in different non-namespace scopes do not overload. For example:

void f(int);

void g()
{
     void f(double);
     f(1);          // call f(double)
}

Clearly, f(int) would have been the best match for f(1), but only f(double) is in scope. In such cases, local declarations can be added or subtracted to get the desired behavior. As always, intentional hiding can be a useful technique, but unintentional hiding is a source of surprises.

A base class and a derived class provide different scopes so that overloading between a base class function and a derived class function doesn’t happen by default. For example:

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struct Base {
     void f(int);
};

struct Derived : Base {
     void f(double);
};

void g(Derived& d)
{
     d.f(1);  // call Derived::f(double);
}

When overloading across class scopes (§20.3.5) or namespace scopes (§14.4.5) is wanted, using-declarations or using-directives can be used (§14.2.2). Argument-dependent lookup (§14.2.4) can also lead to overloading across namespaces.

12.3.4. Resolution for Multiple Arguments

We can use the overload resolution rules to select the most appropriate function when the efficiency or precision of computations differs significantly among types. For example:

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int pow(int, int);
double pow(double, double);
complex pow(double, complex);
complex pow(complex, int);
complex pow(complex, complex);

void k(complex z)
{
     int i = pow(2,2);            // invoke pow(int,int)
     double d = pow(2.0,2.0);     // invoke pow(double,double)
     complex z2 = pow(2,z);       // invoke pow(double,complex)
     complex z3 = pow(z,2);       // invoke pow(complex,int)
     complex z4 = pow(z,z);       // invoke pow(complex,complex)
}

In the process of choosing among overloaded functions with two or more arguments, a best match is found for each argument using the rules from §12.3. A function that is the best match for one argument and a better or equal match for all other arguments is called. If no such function exists, the call is rejected as ambiguous. For example:

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void g()
{
     double d = pow(2.0,2);    // error: pow(int(2.0),2) or pow(2.0,double(2))?
}

The call is ambiguous because 2.0 is the best match for the first argument of pow(double,double) and 2 is the best match for the second argument of pow(int,int).

12.3.5. Manual Overload Resolution

Declaring too few (or too many) overloaded versions of a function can lead to ambiguities. For example:

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void f1(char);
void f1(long);

void f2(char*);
void f2(int*);

void k(int i)
{
     f1(i);     // ambiguous: f1(char) or f1(long)?
     f2(0);     // ambiguous: f2(char*) or f2(int*)?
}

Where possible, consider the set of overloaded versions of a function as a whole and see if it makes sense according to the semantics of the function. Often the problem can be solved by adding a version that resolves ambiguities. For example, adding

inline void f1(int n) { f1(long(n)); }

would resolve all ambiguities similar to f1(i) in favor of the larger type long int.

One can also add an explicit type conversion to resolve a specific call. For example:

f2(static_cast<int*>(0));

However, this is most often simply an ugly stopgap. Soon another similar call will be made and have to be dealt with.

Some C++ novices get irritated by the ambiguity errors reported by the compiler. More experienced programmers appreciate these error messages as useful indicators of design errors.

12.4. Pre- and Postconditions

Every function has some expectations on its arguments. Some of these expectations are expressed in the argument types, but others depend on the actual values passed and on relationships among argument values. The compiler and linker can ensure that arguments are of the right types, but it is up to the programmer to decide what to do about “bad” argument values. We call logical criteria that are supposed to hold when a function is called preconditions, and logical criteria that are supposed to hold when a function returns its postconditions. For example:

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int area(int len, int wid)
/*
      calculate the area of a rectangle

      precondition: len and wid are positive

      postcondition: the return value is positive

      postcondition: the return value is the area of a rectange with sides len and wid
*/
{
      return len*wid;
}

Here, the statements of the pre- and postconditions are longer than the function body. This may seem excessive, but the information provided is useful to the implementer, to the users of area(), and to testers. For example, we learn that 0 and –12 are not considered valid arguments. Furthermore, we note that we could pass a couple of huge values without violating the precondition, but if len*wid overflows either or both of the postconditions are not met.

What should we do about a call area(numeric_limits<int>::max(),2)?

[1] Is it the caller’s task to avoid it? Yes, but what if the caller doesn’t?

[2] Is it the implementer’s task to avoid it? If so, how is an error to be handled?

There are several possible answers to these questions. It is easy for a caller to make a mistake and fail to establish a precondition. It is also difficult for an implementer to cheaply, efficiently, and completely check preconditions. We would like to rely on the caller to get the preconditions right, but we need a way to test for correctness. For now, just note that some pre- and postconditions are easy to check (e.g., len is positive and len*wid is positive). Others are semantic in nature and hard to test directly. For example, how do we test “the return value is the area of a rectangle with sides len and wid”? This is a semantic constraint because we have to know the meaning of “area of a rectangle,” and just trying to multiply len and wid again with a precision that precluded overflow could be costly.

It seems that writing out the pre- and postconditions for area() uncovered a subtle problem with this very simple function. This is not uncommon. Writing out pre- and postconditions is a great design tool and provides good documentation. Mechanisms for documenting and enforcing conditions are discussed in §13.4.

If a function depends only on its arguments, its preconditions are on its arguments only. However, we have to be careful about functions that depend on non-local values (e.g., a member function that depends on the state of its object). In essence, we have to consider every nonlocal value read as an implicit argument to a function. Similarly, the postcondition of a function without side effects simply states that a value is correctly computed, but if a function writes to nonlocal objects, its effect must be considered and documented.

The writer of a function has several alternatives, including:

[1] Make sure that every input has a valid result (so that we don’t have a precondition).

[2] Assume that the precondition holds (rely on the caller not to make mistakes).

[3] Check that the precondition holds and throw an exception if it does not.

[4] Check that the precondition holds and terminate the program if it does not.

If a postconditon fails, there was either an unchecked precondition or a programming error. §13.4 discusses ways to represent alternative strategies for checking.

12.5. Pointer to Function

Like a (data) object, the code generated for a function body is placed in memory somewhere, so it has an address. We can have a pointer to a function just as we can have a pointer to an object. However, for a variety of reasons – some related to machine architecture and others to system design – a pointer to function does not allow the code to be modified. There are only two things one can do to a function: call it and take its address. The pointer obtained by taking the address of a function can then be used to call the function. For example:

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void error(string s) { /* ... */ }

void (*efct)(string);        // pointer to function taking a string argument and returning nothing

void f()
{
     efct = &error;          // efct points to error
     efct("error");          // call error through efct
}

The compiler will discover that efct is a pointer and call the function pointed to. That is, dereferencing a pointer to function using * is optional. Similarly, using & to get the address of a function is optional:

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void (*f1)(string) = &error;    // OK: same as = error
void (*f2)(string) = error;     // OK: same as = &error

void g()
{
     f1("Vasa");                // OK: same as (*f1)("Vasa")
     (*f1)("Mary Rose");        // OK: as f1("Mary Rose")
}

Pointers to functions have argument types declared just like the functions themselves. In pointer assignments, the complete function type must match exactly. For example:

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void (*pf)(string);   // pointer to void(string)
void f1(string);      // void(string)
int f2(string);       // int(string)
void f3(int*);        // void(int*)
void f()
{
     pf = &f1;             // OK
     pf = &f2;             // error: bad return type
     pf = &f3;             // error: bad argument type

     pf("Hera");           // OK
     pf(1);                // error: bad argument type

     int i = pf("Zeus");   // error: void assigned to int
}

The rules for argument passing are the same for calls directly to a function and for calls to a function through a pointer.

You can convert a pointer to function to a different pointer-to-function type, but you must cast the resulting pointer back to its original type or strange things may happen:

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using P1 = int(*)(int*);
using P2 = void(*)(void);

void f(P1 pf)
{
     P2 pf2 = reinterpret_cast<P2>(pf)
     pf2();                                  // likely serious problem
     P1 pf1 = reinterpret_cast<P1>(pf2);     // convert pf2 "back again"
     int x = 7;
     int y = pf1(&x);                        // OK
     // ...
}

We need the nastiest of casts, reinterpret_cast, to do conversion of pointer-to-function types. The reason is that the result of using a pointer to function of the wrong type is so unpredictable and system-dependent. For example, in the example above, the called function may write to the object pointed to by its argument, but the call pf2() didn’t supply any argument!

Pointers to functions provide a way of parameterizing algorithms. Because C does not have function objects (§3.4.3) or lambda expressions (§11.4), pointers to functions are widely used as function arguments in C-style code. For example, we can provide the comparison operation needed by a sorting function as a pointer to function:

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using CFT = int(const void*, const void*);

void ssort(void* base, size_t n, size_t sz, CFT cmp)
/*
     Sort the "n" elements of vector "base" into increasing order
     using the comparison function pointed to by "cmp".
     The elements are of size "sz".

     Shell sort (Knuth, Vol3, pg84)
*/

{
     for (int gap=n/2; 0<gap; gap/=2)
           for (int i=gap; i!=n; i++)
                 for (int j=i-gap; 0<=j; j-=gap) {
                       char* b = static_cast<char*>(base);     // necessary cast
                       char* pj = b+j*sz;                 // &base[j]
                       char* pjg = b+(j+gap)*sz;          // &base[j+gap]
                       if (cmp(pjg,pj)<0) {          // swap base[j] and base[j+gap]:
                            for (int k=0; k!=sz; k++) {
                                  char temp = pj[k];
                                  pj[k] = pjg[k];
                                  pjg[k] = temp;
                            }
                       }
                 }
}

The ssort() routine does not know the type of the objects it sorts, only the number of elements (the array size), the size of each element, and the function to call to perform a comparison. The type of ssort() was chosen to be the same as the type of the standard C library sort routine, qsort(). Real programs use qsort(), the C++ standard-library algorithm sort (§32.6), or a specialized sort routine. This style of code is common in C, but it is not the most elegant way of expressing this algorithm in C++ (see §23.5, §25.3.4.1).

Such a sort function could be used to sort a table such as this:

Click here to view code image

struct User {
     const char* name;
     const char* id;
     int dept;
};

vector<User> heads = {
     "Ritchie D.M.",    "dmr",   11271,
     "Sethi R.",        "ravi",  11272,
     "Szymanski T.G.",  "tgs",   11273,
     "Schryer N.L.",    "nls",   11274,
     "Schryer N.L.",    "nls",   11275,
     "Kernighan B.W.",  "bwk",   11276
};

void print_id(vector<User>& v)
{
     for (auto& x : v)
           cout << x.name << '\t' << x.id << '\t' << x.dept << '\n';
}

To be able to sort, we must first define appropriate comparison functions. A comparison function must return a negative value if its first argument is less than the second, zero if the arguments are equal, and a positive number otherwise:

Click here to view code image

int cmp1(const void* p, const void* q)  // Compare name strings
{
     return strcmp(static_cast<const User*>(p)–>name,static_cast<const User*>(q)–>name);
}

int cmp2(const void* p, const void* q)  // Compare dept numbers
{
     return static_cast<const User*>(p)–>dept – static_cast<const User*>(q)–>dept;
}

There is no implicit conversion of argument or return types when pointers to functions are assigned or initialized. This means that you cannot avoid the ugly and error-prone casts by writing:

Click here to view code image

int cmp3(const User* p, const User* q) // Compare ids
{
     return strcmp(p–>id,q–>id);
}

The reason is that accepting cmp3 as an argument to ssort() would violate the guarantee that cmp3 will be called with arguments of type const User* (see also §15.2.6).

This program sorts and prints:

Click here to view code image

int main()
{
     cout << "Heads in alphabetical order:\n";
     ssort(heads,6,sizeof(User),cmp1);
     print_id(heads);
     cout << '\n';

     cout << "Heads in order of department number:\n";
     ssort(heads,6,sizeof(User),cmp2);
     print_id(heads);
}

To compare, we can equivalently write:

Click here to view code image

int main()
{
     cout << "Heads in alphabetical order:\n";
     sort(heads.begin(), head.end(),
          [](const User& x, const User& y) { return x.name<y.name; }
     );
     print_id(heads);
     cout << '\n';

     cout << "Heads in order of department number:\n";
     sort(heads.begin(), head.end(),
          [](const User& x, const User& y) { return x.dept<y.dept; }
     );
     print_id(heads);
}

No mention of sizes is needed nor any helper functions. If the explicit use of begin() and end() is annoying, it can be eliminated by using a version of sort() that takes a container (§14.4.5):

sort(heads,[](const User& x, const User& y) { return x.name<y.name; });

You can take the address of an overloaded function by assigning to or initializing a pointer to function. In that case, the type of the target is used to select from the set of overloaded functions. For example:

Click here to view code image

void f(int);
int f(char);

void (*pf1)(int) = &f;     // void f(int)
int (*pf2)(char) = &f;     // int f(char)
void (*pf3)(char) = &f;    // error: no void f(char)

It is also possible to take the address of member functions (§20.6), but a pointer to member function is quite different from a pointer to (nonmember) function.

A pointer to a noexcept function can be declared noexcept. For example:

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void f(int) noexcept;
void g(int);

void (*p1)(int) = f;            // OK: but we throw away useful information
void (*p2)(int) noexcept = f;   // OK: we preserve the noexcept information
void (*p3)(int) noexcept = g;   // error: we don't know that g doesn't throw

A pointer to function must reflect the linkage of a function (§15.2.6). Neither linkage specification nor noexcept may appear in type aliases:

Click here to view code image

using Pc = extern "C" void(int);   // error: linkage specification in alias
using Pn = void(int) noexcept;     // error: noexcept in alias

12.6. Macros

Macros are very important in C but have far fewer uses in C++. The first rule about macros is: don’t use them unless you have to. Almost every macro demonstrates a flaw in the programming language, in the program, or in the programmer. Because they rearrange the program text before the compiler proper sees it, macros are also a major problem for many programming support tools. So when you use macros, you should expect inferior service from tools such as debuggers, cross-reference tools, and profilers. If you must use macros, please read the reference manual for your own implementation of the C++ preprocessor carefully and try not to be too clever. Also, to warn readers, follow the convention to name macros using lots of capital letters. The syntax of macros is presented in §iso.16.3.

I recommend using macros only for conditional compilation (§12.6.1) and in particular for include guards (§15.3.3).

A simple macro is defined like this:

#define NAME rest of line

Where NAME is encountered as a token, it is replaced by rest of line. For example:

named = NAME

will expand into

named = rest of line

A macro can also be defined to take arguments. For example:

#define MAC(x,y) argument1: x argument2: y

When MAC is used, two argument strings must be presented. They will replace x and y when MAC() is expanded. For example:

expanded = MAC(foo bar, yuk yuk)

will be expanded into

expanded = argument1: foo bar argument2: yuk yuk

Macro names cannot be overloaded, and the macro preprocessor cannot handle recursive calls:

Click here to view code image

#define PRINT(a,b) cout<<(a)<<(b)
#define PRINT(a,b,c) cout<<(a)<<(b)<<(c)     /* trouble?: redefines, does not overload */

#define FAC(n) (n>1)?n*FAC(n–1):1            /* trouble: recursive macro */

Macros manipulate character strings and know little about C++ syntax and nothing about C++ types or scope rules. Only the expanded form of a macro is seen by the compiler, so an error in a macro will be reported when the macro is expanded, not when it is defined. This leads to very obscure error messages.

Here are some plausible macros:

#define CASE break;case
#define FOREVER for(;;)

Here are some completely unnecessary macros:

#define PI 3.141593
#define BEGIN {
#define END }

Here are some dangerous macros:

#define SQUARE(a) a*a
#define INCR_xx (xx)++

To see why they are dangerous, try expanding this:

Click here to view code image

int xx = 0;     // global counter

void f(int xx)
{
     int y = SQUARE(xx+2);    // y=xx+2*xx+2; that is, y=xx+(2*xx)+2
     INCR_xx;                 // increments argument xx (not the global xx)
}

If you must use a macro, use the scope resolution operator, ::, when referring to global names (§6.3.4) and enclose occurrences of a macro argument name in parentheses whenever possible. For example:

#define MIN(a,b) (((a)<(b))?(a):(b))

This handles the simpler syntax problems (which are often caught by compilers), but not the problems with side effects. For example:

Click here to view code image

int x = 1;
int y = 10;
int z = MIN(x++,y++);        // x becomes 3; y becomes 11

If you must write macros complicated enough to require comments, it is wise to use / ** / comments because old C preprocessors that do not know about // comments are sometimes used as part of C++ tools. For example:

#define M2(a) something(a)   /* thoughtful comment */

Using macros, you can design your own private language. Even if you prefer this “enhanced language” to plain C++, it will be incomprehensible to most C++ programmers. Furthermore, the preprocessor is a very simple-minded macro processor. When you try to do something nontrivial, you are likely to find it either impossible or unnecessarily hard to do. The auto, constexpr, const, decltype, enum, inline, lambda expressions, namespace, and template mechanisms can be used as better-behaved alternatives to many traditional uses of preprocessor constructs. For example:

Click here to view code image

const int answer = 42;

template<class T>
inline const T& min(const T& a, const T& b)
{
     return (a<b)?a:b;
}

When writing a macro, it is not unusual to need a new name for something. A string can be created by concatenating two strings using the ## macro operator. For example:

#define NAME2(a,b) a##b

int NAME2(hack,cah)();

will produce

int hackcah();

A single # before a parameter name in a replacement string means a string containing the macro argument. For example:

Click here to view code image

#define printx(x) cout << #x " = " << x << '\n';

int a = 7;
string str = "asdf";
void f()
{
     printx(a);      // cout << "a" << " = " << a << '\n';
     printx(str);    // cout << "str" << " = " << str << '\n';
}

Writing #x " = " rather than #x << " = " is obscure “clever code” rather than an error. Adjacent string literals are concatenated (§7.3.2).

The directive

#undef X

ensures that no macro called X is defined – whether or not one was before the directive. This affords some protection against undesired macros. However, it is not always easy to know what the effects of X on a piece of code were supposed to be.

The argument list (“replacement list”) of a macro can be empty:

Click here to view code image

#define EMPTY() std::cout<<"empty\n"
EMPTY();     // print "empty\n"
EMPTY;       // error: macro replacement list missing

I have a hard time thinking of uses of an empty macro argument list that are not error-prone or malicious.

Macros can even be variadic. For example:

Click here to view code image

#define err_print(...) fprintf(stderr,"error: %s %d\n", __VA_ARGS__)
err_print("The answer",54);

The ellipsis (...) means that __VA_ARGS__ represents the arguments actually passed as a string, so the output is:

error: The answer 54

12.6.1. Conditional Compilation

One use of macros is almost impossible to avoid. The directive

#ifdef IDENTIFIER

does nothing if IDENTIFIER is defined, but if it is not, the directive causes all input to be ignored until a #endif directive is seen. For example:

int f(int a
#ifdef arg_two
,int b
#endif
);

Unless a macro called arg_two has been #defined, this produces:

int f(int a
);

This example confuses tools that assume sane behavior from the programmer.

Most uses of #ifdef are less bizarre, and when used with restraint, #ifdef and its complement #ifndef do little harm. See also §15.3.3.

Names of the macros used to control #ifdef should be chosen carefully so that they don’t clash with ordinary identifiers. For example:

struct Call_info {
     Node* arg_one;
     Node* arg_two;
     // ...
};

This innocent-looking source text will cause some confusion should someone write:

#define arg_two x

Unfortunately, common and unavoidable headers contain many dangerous and unnecessary macros.

12.6.2. Predefined Macros

A few macros are predefined by the compiler (§iso.16.8, §iso.8.4.1):

• __cplusplus: defined in a C++ compilation (and not in a C compilation). Its value is 201103L in a C++11 program; previous C++ standards have lower values.

• __DATE__: date in “yyyy:mm:dd” format.

• __TIME__: time in “hh:mm:ss” format.

• __FILE__: name of current source file.

• __LINE__: source line number within the current source file.

• __FUNC__: an implementation-defined C-style string naming the current function.

• __STDC_HOSTED__: 1 if the implementation is hosted (§6.1.1); otherwise 0.

In addition, a few macros are conditionally defined by the implementation:

• __STDC__: defined in a C compilation (and not in a C++ compilation)

• __STDC_MB_MIGHT_NEQ_WC__: 1 if, in the encoding for wchar_t, a member of the basic character set (§6.1) might have a code value that differs from its value as an ordinary character literal

• __STDCPP_STRICT_POINTER_SAFETY__: 1 if the implementation has strict pointer safety (§34.5); otherwise undefined.

• __STDCPP_THREADS__: 1 if a program can have more than one thread of execution; otherwise undefined.

For example:

cout << __FUNC__ << "() in file " << __FILE__ << " on line " << __LINE__ << "\n";

In addition, most C++ implementations allow a user to define arbitrary macros on the command line or in some other form of compile-time environment. For example, NDEBUG is defined unless the compilation is done in (some implementation-specific) “debug mode” and is used by the assert() macro (§13.4). This can be useful, but it does imply that you can’t be sure of the meaning of a program just by reading its source text.

12.6.3. Pragmas

Implementations often provide facilities that differ from or go beyond what the standard offers. Obviously, the standard cannot specify how such facilities are provided, but one standard syntax is a line of tokens prefixed with the preprocessor directive #pragma. For example:

#pragma foo bar 666 foobar

If possible, #pragmas are best avoided.

12.7. Advice

[1] “Package” meaningful operations as carefully named functions; §12.1.

[2] A function should perform a single logical operation; §12.1.

[3] Keep functions short; §12.1.

[4] Don’t return pointers or references to local variables; §12.1.4.

[5] If a function may have to be evaluated at compile time, declare it constexpr; §12.1.6.

[6] If a function cannot return, mark it [[noreturn]]; §12.1.7.

[7] Use pass-by-value for small objects; §12.2.1.

[8] Use pass-by-const-reference to pass large values that you don’t need to modify; §12.2.1.

[9] Return a result as a return value rather than modifying an object through an argument; §12.2.1.

[10] Use rvalue references to implement move and forwarding; §12.2.1.

[11] Pass a pointer if “no object” is a valid alternative (and represent “no object” by nullptr); §12.2.1.

[12] Use pass-by-non-const-reference only if you have to; §12.2.1.

[13] Use const extensively and consistently; §12.2.1.

[14] Assume that a char* or a const char* argument points to a C-style string; §12.2.2.

[15] Avoid passing arrays as pointers; §12.2.2.

[16] Pass a homogeneous list of unknown length as an initializer_list<T> (or as some other container); §12.2.3.

[17] Avoid unspecified numbers of arguments (...); §12.2.4.

[18] Use overloading when functions perform conceptually the same task on different types; §12.3.

[19] When overloading on integers, provide functions to eliminate common ambiguities; §12.3.5.

[20] Specify preconditions and postconditions for your functions; §12.4.

[21] Prefer function objects (including lambdas) and virtual functions to pointers to functions; §12.5.

[22] Avoid macros; §12.6.

[23] If you must use macros, use ugly names with lots of capital letters; §12.6.

13. Exception Handling

Don’t interrupt me while I’m interrupting.

– Winston S. Churchill

• Error Handling

Exceptions; Traditional Error Handling; Muddling Through; Alternative Views of Exceptions; When You Can’t Use Exceptions; Hierarchical Error Handling; Exceptions and Efficiency

• Exception Guarantees

• Resource Management

Finally

• Enforcing Invariants

• Throwing and Catching Exceptions

Throwing Exceptions; Catching Exceptions; Exceptions and Threads

• A vector Implementation

A Simple vector; Representing Memory Explicitly; Assignment; Changing Size

• Advice

13.1. Error Handling

This chapter presents error handling using exceptions. For effective error handling, the language mechanisms must be used based on a strategy. Consequently, this chapter presents the exception-safety guarantees that are central to recovery from run-time errors and the Resource Acquisition Is Initialization (RAII) technique for resource management using constructors and destructors. Both the exception-safety guarantees and RAII depend on the specification of invariants, so mechanisms for enforcement of assertions are presented.

The language facilities and techniques presented here address problems related to the handling of errors in software; the handling of asynchronous events is a different topic.

The discussion of errors focuses on errors that cannot be handled locally (within a single small function), so that they require separation of error-handling activities into different parts of a program. Such parts of a program are often separately developed. Consequently, I often refer to a part of a program that is invoked to perform a task as “a library.” A library is just ordinary code, but in the context of a discussion of error handling it is worth remembering that a library designer often cannot even know what kind of programs the library will become part of:

• The author of a library can detect a run-time error but does not in general have any idea what to do about it.

• The user of a library may know how to cope with a run-time error but cannot easily detect it (or else it would have been handled in the user’s code and not left for the library to find).

The discussion of exceptions focuses on problems that need to be handled in long-running systems, systems with stringent reliability requirements, and libraries. Different kinds of programs have different requirements, and the amount of care and effort we expend should reflect that. For example, I would not apply every technique recommended here to a two-page program written just for myself. However, many of the techniques presented here simplify code, so I would use those.

13.1.1. Exceptions

The notion of an exception is provided to help get information from the point where an error is detected to a point where it can be handled. A function that cannot cope with a problem throws an exception, hoping that its (direct or indirect) caller can handle the problem. A function that wants to handle a kind of problem indicates that by catching the corresponding exception (§2.4.3.1):

• A calling component indicates the kinds of failures that it is willing to handle by specifying those exceptions in a catch-clause of a try-block.

• A called component that cannot complete its assigned task reports its failure to do so by throwing an exception using a throw-expression.

Consider a simplified and stylized example:

Click here to view code image

void taskmaster()
{
     try {
          auto result = do_task();
          // use result
     }
     catch (Some_error) {
         // failure to do_task: handle problem
     }
}

int do_task()
{
     // ...
     if (/* could perform the task */)
            return result;
     else
           throw Some_error{};
}

The taskmaster() asks do_task() to do a job. If do_task() can do that job and return a correct result, all is fine. Otherwise, do_task() must report a failure by throwing some exception. The taskmaster() is prepared to handle a Some_error, but some other kind of exception may be thrown. For example, do_task() may call other functions to do a lot of subtasks, and one of those may throw because it can’t do its assigned subtask. An exception different from Some_error indicates a failure of taskmaster() to do its job and must be handled by whatever code invoked taskmaster().

A called function cannot just return with an indication that an error happened. If the program is to continue working (and not just print an error message and terminate), the returning function must leave the program in a good state and not leak any resources. The exception-handling mechanism is integrated with the constructor/destructor mechanisms and the concurrency mechanisms to help ensure that (§5.2). The exception-handling mechanism:

• Is an alternative to the traditional techniques when they are insufficient, inelegant, or error-prone

• Is complete; it can be used to handle all errors detected by ordinary code

• Allows the programmer to explicitly separate error-handling code from “ordinary code,” thus making the program more readable and more amenable to tools

• Supports a more regular style of error handling, thus simplifying cooperation between separately written program fragments

An exception is an object thrown to represent the occurrence of an error. It can be of any type that can be copied, but it is strongly recommended to use only user-defined types specifically defined for that purpose. That way, we minimize the chances of two unrelated libraries using the same value, say 17, to represent different errors, thereby throwing our recovery code into chaos.

An exception is caught by code that has expressed interest in handling a particular type of exception (a catch-clause). Thus, the simplest way of defining an exception is to define a class specifically for a kind of error and throw that. For example:

Click here to view code image

struct Range_error {};

void f(int n)
{
     if (n<0 || max<n) throw Range_error {};
     // ...
}

If that gets tedious, the standard library defines a small hierarchy of exception classes (§13.5.2).

An exception can carry information about the error it represents. Its type represents the kind of error, and whatever data it holds represents the particular occurrence of that error. For example, the standard-library exceptions contain a string value, which can be used to transmit information such as the location of the throw (§13.5.2).

13.1.2. Traditional Error Handling

Consider the alternatives to exceptions for a function detecting a problem that cannot be handled locally (e.g., an out-of-range access) so that an error must be reported to a caller. Each conventional approach has problems, and none are general:

• Terminate the program. This is a pretty drastic approach. For example:

if (something_wrong) exit(1);

For most errors, we can and must do better. For example, in most situations we should at least write out a decent error message or log the error before terminating. In particular, a library that doesn’t know about the purpose and general strategy of the program in which it is embedded cannot simply exit() or abort(). A library that unconditionally terminates cannot be used in a program that cannot afford to crash.

• Return an error value. This is not always feasible because there is often no acceptable “error value.” For example:

int get_int();   // get next integer from input

For this input function, every int is a possible result, so there can be no integer value representing an input failure. At a minimum, we would have to modify get_int() to return a pair of values. Even where this approach is feasible, it is often inconvenient because every call must be checked for the error value. This can easily double the size of a program (§13.1.7). Also, callers often ignore the possibility of errors or simply forget to test a return value. Consequently, this approach is rarely used systematically enough to detect all errors. For example, printf() (§43.3) returns a negative value if an output or encoding error occurred, but programmers essentially never test for that. Finally, some operations simply do not have return values; a constructor is the obvious example.

• Return a legal value and leave the program in an “error state.” This has the problem that the calling function may not notice that the program has been put in an error state. For example, many standard C library functions set the nonlocal variable errno to indicate an error (§43.4, §40.3):

double d = sqrt(–1.0);

Here, the value of d is meaningless and errno is set to indicate that –1.0 isn’t an acceptable argument for a floating-point square root function. However, programs typically fail to set and test errno and similar nonlocal state consistently enough to avoid consequential errors caused by values returned from failed calls. Furthermore, the use of nonlocal variables for recording error conditions doesn’t work well in the presence of concurrency.

• Call an error-handler function. For example:

if (something_wrong) something_handler();  // and possibly continue here

This must be some other approach in disguise because the problem immediately becomes “What does the error-handling function do?” Unless the error-handling function can completely resolve the problem, the error-handling function must in turn either terminate the program, return with some indication that an error had occurred, set an error state, or throw an exception. Also, if the error-handling function can handle the problem without bothering the ultimate caller, why do we consider it an error?

Traditionally, an unsystematic combination of these approached co-exists in a program.

13.1.3. Muddling Through

One aspect of the exception-handling scheme that will appear novel to some programmers is that the ultimate response to an unhandled error (an uncaught exception) is to terminate the program. The traditional response has been to muddle through and hope for the best. Thus, exception handling makes programs more “brittle” in the sense that more care and effort must be taken to get a program to run acceptably. This is preferable, though, to getting wrong results later in the development process – or after the development process is considered complete and the program is handed over to innocent users. Where termination is unacceptable, we can catch all exceptions (§13.5.2.2). Thus, an exception terminates a program only if a programmer allows it to terminate. Typically, this is preferable to the unconditional termination that happens when a traditional incomplete recovery leads to a catastrophic error. Where termination is an acceptable response, an uncaught exception will achieve that because it turns into a call of terminate() (§13.5.2.5). Also, a noexcept specifier (§13.5.1.1) can make that desire explicit.

Sometimes, people try to alleviate the unattractive aspects of “muddling through” by writing out error messages, putting up dialog boxes asking the user for help, etc. Such approaches are primarily useful in debugging situations in which the user is a programmer familiar with the structure of the program. In the hands of nondevelopers, a library that asks the (possibly absent) user/operator for help is unacceptable. A good library doesn’t “blabber” in this way. If a user has to be informed, an exception handler can compose a suitable message (e.g., in Finnish for Finnish users or in XML for an error-logging system). Exceptions provide a way for code that detects a problem from which it cannot recover to pass the problem on to a part of the system that might be able to recover. Only a part of the system that has some idea of the context in which the program runs has any chance of composing a meaningful error message.

Please recognize that error handling will remain a difficult task and that the exception-handling mechanism – although more formalized than the techniques it replaces – is still relatively unstructured compared with language features involving only local control flow. The C++ exception-handling mechanism provides the programmer with a way of handling errors where they are most naturally handled, given the structure of a system. Exceptions make the complexity of error handling visible. However, exceptions are not the cause of that complexity. Be careful not to blame the messenger for bad news.

13.1.4. Alternative Views of Exceptions

“Exception” is one of those words that means different things to different people. The C++ exception-handling mechanism is designed to support handling of errors that cannot be handled locally (“exceptional conditions”). In particular, it is intended to support error handling in programs composed of independently developed components. Given that there is nothing particularly exceptional about a part of a program being unable to perform its given task, the word “exception” may be considered a bit misleading. Can an event that happens most times a program is run be considered exceptional? Can an event that is planned for and handled be considered an error? The answer to both questions is “yes.” “Exceptional” does not mean “almost never happens” or “disastrous.”

13.1.4.1. Asynchronous Events

The mechanism is designed to handle only synchronous exceptions, such as array range checks and I/O errors. Asynchronous events, such as keyboard interrupts and power failures, are not necessarily exceptional and are not handled directly by this mechanism. Asynchronous events require mechanisms fundamentally different from exceptions (as defined here) to handle them cleanly and efficiently. Many systems offer mechanisms, such as signals, to deal with asynchrony, but because these tend to be system-dependent, they are not described here.

13.1.4.2. Exceptions That Are Not Errors

Think of an exception as meaning “some part of the system couldn’t do what it was asked to do” (§13.1.1, §13.2).

Exception throws should be infrequent compared to function calls or the structure of the system has been obscured. However, we should expect most large programs to throw and catch at least some exceptions in the course of a normal and successful run.

If an exception is expected and caught so that it has no bad effects on the behavior of the program, then how can it be an error? Only because the programmer thinks of it as an error and of the exception-handling mechanisms as tools for handling errors. Alternatively, one might think of the exception-handling mechanisms as simply another control structure, an alternative way of returning a value to a caller. Consider a binary tree search function:

Click here to view code image

void fnd(Tree* p, const string& s)
{
     if (s == p–>str) throw p;       // found s
     if (p–>left) fnd(p–>left,s);
     if (p–>right) fnd(p–>right,s);
}

Tree* find(Tree* p, const string& s)
{
     try {
          fnd(p,s);
     }
     catch (Tree* q) {    // q->str==s
          return q;
     }
     return 0;
}

This actually has some charm, but it should be avoided because it is likely to cause confusion and inefficiencies. When at all possible, stick to the “exception handling is error handling” view. When this is done, code is clearly separated into two categories: ordinary code and error-handling code. This makes code more comprehensible. Furthermore, the implementations of the exception mechanisms are optimized based on the assumption that this simple model underlies the use of exceptions.

Error handling is inherently difficult. Anything that helps preserve a clear model of what is an error and how it is handled should be treasured.

13.1.5. When You Can’t Use Exceptions

Use of exceptions is the only fully general and systematic way of dealing with errors in a C++ program. However, we must reluctantly conclude that there are programs that for practical and historical reasons cannot use exceptions. For example:

• A time-critical component of an embedded system where an operation must be guaranteed to complete in a specific maximum time. In the absence of tools that can accurately estimate the maximum time for an exception to propagate from a throw to a catch, alternative error-handling methods must be used.

• A large old program in which resource management is an ad hoc mess (e.g., free store is unsystematically “managed” using “naked” pointers, news, and deletes), rather than relying on some systematic scheme, such as resource handles (e.g., string and vector; §4.2, §4.4).

In such cases, we are thrown back onto “traditional” (pre-exception) techniques. Because such programs arise in a great variety of historical contexts and in response to a variety of constraints, I cannot give a general recommendation for how to handle them. However, I can point to two popular techniques:

• To mimic RAII, give every class with a constructor an invalid() operation that returns some error_code. A useful convention is for error_code==0 to represent success. If the constructor fails to establish the class invariant, it ensures that no resource is leaked and invalid() returns a nonzero error_code. This solves the problem of how to get an error condition out of a constructor. A user can then systematically test invalid() after each construction of an object and engage in suitable error handling in case of failure. For example:

void f(int n)
{
     my_vector<int> x(n);
     if (x.invalid()) {
           // ... deal with error ...
     }
     // ...
}

• To mimic a function either returning a value or throwing an exception, a function can return a pair<Value,Error_code> (§5.4.3). A user can then systematically test the error_code after each function call and engage in suitable error handling in case of failure. For example:

Click here to view code image

void g(int n)
{
     auto v = make_vector(n); // return a pair
     if (v.second) {
            // ... deal with error ...
     }
     auto val = v.first;
     // ...
}

Variations of this scheme have been reasonably successful, but they are clumsy compared to using exceptions in a systematic manner.

13.1.6. Hierarchical Error Handling

The purpose of the exception-handling mechanisms is to provide a means for one part of a program to inform another part that a requested task could not be performed (that an “exceptional circumstance” has been detected). The assumption is that the two parts of the program are written independently and that the part of the program that handles the exception often can do something sensible about the error.

To use handlers effectively in a program, we need an overall strategy. That is, the various parts of the program must agree on how exceptions are used and where errors are dealt with. The exception-handling mechanisms are inherently nonlocal, so adherence to an overall strategy is essential. This implies that the error-handling strategy is best considered in the earliest phases of a design. It also implies that the strategy must be simple (relative to the complexity of the total program) and explicit. Something complicated would not be consistently adhered to in an area as inherently tricky as error recovery.

Successful fault-tolerant systems are multilevel. Each level copes with as many errors as it can without getting too contorted and leaves the rest to higher levels. Exceptions support that view. Furthermore, terminate() supports this view by providing an escape if the exception-handling mechanism itself is corrupted or if it has been incompletely used, thus leaving exceptions uncaught. Similarly, noexcept provides a simple escape for errors where trying to recover seems infeasible.

Not every function should be a firewall. That is, not every function can test its preconditions well enough to ensure that no errors could possibly stop it from meeting its postcondition. The reasons that this will not work vary from program to program and from programmer to programmer. However, for larger programs:

[1] The amount of work needed to ensure this notion of “reliability” is too great to be done consistently.

[2] The overhead in time and space is too great for the system to run acceptably (there will be a tendency to check for the same errors, such as invalid arguments, over and over again).

[3] Functions written in other languages won’t obey the rules.

[4] This purely local notion of “reliability” leads to complexities that actually become a burden to overall system reliability.

However, separating the program into distinct subsystems that either complete successfully or fail in well-defined ways is essential, feasible, and economical. Thus, major libraries, subsystems, and key interface functions should be designed in this way. Furthermore, in most systems, it is feasible to design every function to ensure that it always either completes successfully or fails in a well-defined manner.

Usually, we don’t have the luxury of designing all of the code of a system from scratch. Therefore, to impose a general error-handling strategy on all parts of a program, we must take into account program fragments implemented using strategies different from ours. To do this we must address a variety of concerns relating to the way a program fragment manages resources and the state in which it leaves the system after an error. The aim is to have the program fragment appear to follow the general error-handling strategy even if it internally follows a different strategy.

Occasionally, it is necessary to convert from one style of error reporting to another. For example, we might check errno and possibly throw an exception after a call to a C library or, conversely, catch an exception and set errno before returning to a C program from a C++ library:

Click here to view code image

void callC()    // Call a C function from C++; convert errno to a throw
{
     errno = 0;
     c_function();
     if (errno) {
           // ... local cleanup, if possible and necessary ...
           throw C_blewit(errno);
     }
}

extern "C" void call_from_C() noexcept       // Call a C++ function from C; convert a throw to errno
{
     try {
          c_plus_plus_function();
     }
     catch (...) {
          // ... local cleanup, if possible and necessary ...
          errno = E_CPLPLFCTBLEWIT;
     }
}

In such cases, it is important to be systematic enough to ensure that the conversion of error-reporting styles is complete. Unfortunately, such conversions are often most desirable in “messy code” without a clear error-handling strategy and therefore difficult to be systematic about.

Error handling should be – as far as possible – hierarchical. If a function detects a run-time error, it should not ask its caller for help with recovery or resource acquisition. Such requests set up cycles in the system dependencies. That in turn makes the program hard to understand and introduces the possibility of infinite loops in the error-handling and recovery code.

13.1.7. Exceptions and Efficiency

In principle, exception handling can be implemented so that there is no run-time overhead when no exception is thrown. In addition, this can be done so that throwing an exception isn’t all that expensive compared to calling a function. Doing so without adding significant memory overhead while maintaining compatibility with C calling sequences, debugger conventions, etc., is possible, but hard. However, please remember that the alternatives to exceptions are not free either. It is not unusual to find traditional systems in which half of the code is devoted to error handling.

Consider a simple function f() that appears to have nothing to do with exception handling:

void f()
{
     string buf;
     cin>>buf;
     // ...
     g(1);
     h(buf);
}

However, g() or h() may throw an exception, so f() must contain code ensuring that buf is destroyed correctly in case of an exception.

Had g() not thrown an exception, it would have had to report its error some other way. Consequently, the comparable code using ordinary code to handle errors instead of exceptions isn’t the plain code above, but something like:

bool g(int);
bool h(const char*);
char* read_long_string();

bool f()
{
     char* s = read_long_string();
     // ...
     if (g(1)) {
           if (h(s)) {
                 free(s);
                 return true;
           }
           else {
                 free(s);
                 return false;
           }
     }
     else {
           free(s);
           return false;
     }
}

Using a local buffer for s would simplify the code by eliminating the calls to free(), but then we’d have range-checking code instead. Complexity tends to move around rather than just disappear.

People don’t usually handle errors this systematically, though, and it is not always critical to do so. However, when careful and systematic handling of errors is necessary, such housekeeping is best left to a computer, that is, to the exception-handling mechanisms.

The noexcept specifier (§13.5.1.1) can be most helpful in improving generated code. Consider:

void g(int) noexcept;
void h(const string&) noexcept;

Now, the code generated for f() can possibly be improved.

No traditional C function throws an exception, so most C functions can be declared noexcept. In particular, a standard-library implementer knows that only a few standard C library functions (such as atexit() and qsort()) can throw, and can take advantage of that fact to generate better code.

Before declaring a “C function” noexcept, take a minute to consider if it could possibly throw an exception. For example, it might have been converted to use the C++ operator new, which can throw bad_alloc, or it might call a C++ library that throws an exception.

As ever, discussions about efficiency are meaningless in the absence of measurements.

13.2. Exception Guarantees

To recover from an error – that is, to catch an exception and continue executing a program – we need to know what can be assumed about the state of the program before and after the attempted recovery action. Only then can recovery be meaningful. Therefore, we call an operation exception-safe if that operation leaves the program in a valid state when the operation is terminated by throwing an exception. However, for that to be meaningful and useful, we have to be precise about what we mean by “valid state.” For practical design using exceptions, we must also break down the overly general “exception-safe” notion into a few specific guarantees.

When reasoning about objects, we assume that a class has a class invariant (§2.4.3.2, §17.2.1). We assume that this invariant is established by its constructor and maintained by all functions with access to the object’s representation until the object is destroyed. So, by valid state we mean that a constructor has completed and the destructor has not yet been entered. For data that isn’t easily viewed as an object, we must reason similarly. That is, if two pieces of nonlocal data are assumed to have a specific relationship, we must consider that an invariant and our recovery action must preserve it. For example:

Click here to view code image

namespace Points {     // (vx[i],vy[i]) is a point for all i
   vector<int> vx;
   vector<int> vy;
};

Here it is assumed that vx.size()==vy.size() is (always) true. However, that was only stated in a comment, and compilers do not read comments. Such implicit invariants can be very hard to discover and maintain.

Before a throw, a function must place all constructed objects in valid states. However, such a valid state may be one that doesn’t suit the caller. For example, a string may be left as the empty string or a container may be left unsorted. Thus, for complete recovery, an error handler may have to produce values that are more appropriate/desirable for the application than the (valid) ones existing at the entry to a catch-clause.

The C++ standard library provides a generally useful conceptual framework for design for exception-safe program components. The library provides one of the following guarantees for every library operation:

• The basic guarantee for all operations: The basic invariants of all objects are maintained, and no resources, such as memory, are leaked. In particular, the basic invariants of every built-in and standard-library type guarantee that you can destroy an object or assign to it after every standard-library operation (§iso.17.6.3.1).

• The strong guarantee for key operations: in addition to providing the basic guarantee, either the operation succeeds, or it has no effect. This guarantee is provided for key operations, such as push_back(), single-element insert() on a list, and uninitialized_copy().

• The nothrow guarantee for some operations: in addition to providing the basic guarantee, some operations are guaranteed not to throw an exception. This guarantee is provided for a few simple operations, such as swap() of two containers and pop_back().

Both the basic guarantee and the strong guarantee are provided on the condition that

• user-supplied operations (such as assignments and swap() functions) do not leave container elements in invalid states,

• user-supplied operations do not leak resources, and

• destructors do not throw exceptions (§iso.17.6.5.12).

Violating a standard-library requirement, such as having a destructor exit by throwing an exception, is logically equivalent to violating a fundamental language rule, such as dereferencing a null pointer. The practical effects are also equivalent and often disastrous.

Both the basic guarantee and the strong guarantee require the absence of resource leaks. This is necessary for every system that cannot afford resource leaks. In particular, an operation that throws an exception must not only leave its operands in well-defined states but must also ensure that every resource that it acquired is (eventually) released. For example, at the point where an exception is thrown, all memory allocated must be either deallocated or owned by some object, which in turn must ensure that the memory is properly deallocated. For example:

Click here to view code image

void f(int i)
{
     int* p = new int[10];
     // ...
     if (i<0) {
            delete[] p;    // delete before the throw or leak
            throw Bad();
     }
     // ...
}

Remember that memory isn’t the only kind of resource that can leak. I consider anything that has to be acquired from another part of the system and (explicitly or implicitly) given back to be a resource. Files, locks, network connections, and threads are examples of system resources. A function may have to release those or hand them over to some resource handler before throwing an exception.

The C++ language rules for partial construction and destruction ensure that exceptions thrown while constructing subobjects and members will be handled correctly without special attention from standard-library code (§17.2.3). This rule is an essential underpinning for all techniques dealing with exceptions.

In general, we must assume that every function that can throw an exception will throw one. This implies that we must structure our code so that we don’t get lost in a rat’s nest of complicated control structures and brittle data structures. When analyzing code for potential errors, simple, highly structured, “stylized” code is the ideal; §13.6 includes a realistic example of such code.

13.3. Resource Management

When a function acquires a resource – that is, it opens a file, allocates some memory from the free store, acquires a mutex, etc. – it is often essential for the future running of the system that the resource be properly released. Often that “proper release” is achieved by having the function that acquired it release it before returning to its caller. For example:

void use_file(const char* fn) // naive code
{
     FILE* f = fopen(fn,"r");

     // ... use f ...

     fclose(f);
}

This looks plausible until you realize that if something goes wrong after the call of fopen() and before the call of fclose(), an exception may cause use_file() to be exited without fclose() being called. Exactly the same problem can occur in languages that do not support exception handling. For example, the standard C library function longjmp() can cause the same problem. Even an ordinary return-statement could exit use_file without closing f.

A first attempt to make use_file() fault-tolerant looks like this:

Click here to view code image

void use_file(const char* fn)  // clumsy code
{
     FILE* f = fopen(fn,"r");
     try {
          // ... use f ...
     }
     catch (...) {        // catch every possible exception
          fclose(f);
          throw;
     }
     fclose(f);
}

The code using the file is enclosed in a try-block that catches every exception, closes the file, and rethrows the exception.

The problem with this solution is that it is verbose, tedious, and potentially expensive. Worse still, such code becomes significantly more complex when several resources must be acquired and released. Fortunately, there is a more elegant solution. The general form of the problem looks like this:

void acquire()
{
     // acquire resource 1
     // ...
     // acquire resource n

     // ... use resources ...

     // release resource n
     // ...
     // release resource 1
}

It is typically important that resources are released in the reverse order of their acquisition. This strongly resembles the behavior of local objects created by constructors and destroyed by destructors. Thus, we can handle such resource acquisition and release problems using objects of classes with constructors and destructors. For example, we can define a class File_ptr that acts like a FILE*:

Click here to view code image

class File_ptr {
     FILE* p;
public:
     File_ptr(const char* n, const char* a)   // open file n
          : p{fopen(n,a)}
     {
          if (p==nullptr) throw runtime_error{"File_ptr: Can't open file"};
     }

     File_ptr(const string& n, const char* a) // open file n
          :File_ptr{n.c_str(),a}
     { }

     explicit File_ptr(FILE* pp)              // assume ownership of pp
          :p{pp}
     {
          if (p==nullptr) throw runtime_error("File_ptr: nullptr"};
     }

     // ... suitable move and copy operations ...

     ~File_ptr() { fclose(p); }

     operator FILE*() { return p; }
};

We can construct a File_ptr given either a FILE* or the arguments required for fopen(). In either case, a File_ptr will be destroyed at the end of its scope and its destructor will close the file. File_ptr throws an exception if it cannot open a file because otherwise every operation on the file handle would have to test for nullptr. Our function now shrinks to this minimum:

void use_file(const char* fn)
{
     File_ptr f(fn,"r");
     // ... use f ...
}

The destructor will be called independently of whether the function is exited normally or exited because an exception is thrown. That is, the exception-handling mechanisms enable us to remove the error-handling code from the main algorithm. The resulting code is simpler and less error-prone than its traditional counterpart.

This technique for managing resources using local objects is usually referred to as “Resource Acquisition Is Initialization” (RAII; §5.2). This is a general technique that relies on the properties of constructors and destructors and their interaction with exception handling.

It is often suggested that writing a “handle class” (a RAII class) is tedious so that providing a nicer syntax for the catch(...) action would provide a better solution. The problem with that approach is that you need to remember to “catch and correct” the problem wherever a resource is acquired in an undisciplined way (typically dozens or hundreds of places in a large program), whereas the handler class need be written only once.

An object is not considered constructed until its constructor has completed. Then and only then will stack unwinding (§13.5.1) call the destructor for the object. An object composed of subobjects is constructed to the extent that its subobjects have been constructed. An array is constructed to the extent that its elements have been constructed (and only fully constructed elements are destroyed during unwinding).

A constructor tries to ensure that its object is completely and correctly constructed. When that cannot be achieved, a well-written constructor restores – as far as possible – the state of the system to what it was before creation. Ideally, a well-designed constructor always achieves one of these alternatives and doesn’t leave its object in some “half-constructed” state. This can be simply achieved by applying the RAII technique to the members.

Consider a class X for which a constructor needs to acquire two resources: a file x and a mutex y (§5.3.4). This acquisition might fail and throw an exception. Class X’s constructor must never complete having acquired the file but not the mutex (or the mutex and not the file, or neither). Furthermore, this should be achieved without imposing a burden of complexity on the programmer. We use objects of two classes, File_ptr and std::unique_lock (§5.3.4), to represent the acquired resources. The acquisition of a resource is represented by the initialization of the local object that represents the resource:

Click here to view code image

class Locked_file_handle {
     File_ptr p;
     unique_lock<mutex> lck;
public:
     X(const char* file, mutex& m)
         : p{file,"rw"},     // acquire "file"
           lck{m}            // acquire "m"
     {}
     // ...
};

Now, as in the local object case, the implementation takes care of all of the bookkeeping. The user doesn’t have to keep track at all. For example, if an exception occurs after p has been constructed but before lck has been, then the destructor for p but not for lck will be invoked.

This implies that where this simple model for acquisition of resources is adhered to, the author of the constructor need not write explicit exception-handling code.

The most common resource is memory, and string, vector, and the other standard containers use RAII to implicitly manage acquisition and release. Compared to ad hoc memory management using new (and possibly also delete), this saves lots of work and avoids lots of errors.

When a pointer to an object, rather than a local object, is needed, consider using the standard-library types unique_ptr and shared_ptr (§5.2.1, §34.3) to avoid leaks.

13.3.1. Finally

The discipline required to represent a resource as an object of a class with a destructor have bothered some. Again and again, people have invented “finally” language constructs for writing arbitrary code to clean up after an exception. Such techniques are generally inferior to RAII because they are ad hoc, but if you really want ad hoc, RAII can supply that also. First, we define a class that will execute an arbitrary action from its destructor.

template<typename F>
struct Final_action {
      Final_action(F f): clean{f} {}
      ~Final_action() { clean(); }
      F clean;
};

The “finally action” is provided as an argument to the constructor.

Next, we define a function that conveniently deduces the type of an action:

template<class F>
Final_action<F> finally(F f)
{
     return Final_action<F>(f);
}

Finally, we can test finally():

Click here to view code image

void test()
     // handle undiciplined resource acquisition
     // demonstrate that arbitrary actions are possible
{
     int* p = new int{7};                              // probably should use a unique_ptr (§5.2)
     int* buf = (int*)malloc(100*sizeof(int));         // C-style allocation

     auto act1 = finally([&]{   delete p;
                                free(buf);             // C-style deallocation
                                cout<< "Goodby, Cruel world!\n";
                           }
                     );

     int var = 0;
     cout << "var = " << var << '\n';

     // nested block:
     {
           var = 1;
           auto act2 = finally([&]{ cout<< "finally!\n"; var=7; });
           cout << "var = " << var << '\n';
     } // act2 is invoked here

     cout << "var = " << var << '\n';
}// act1 is invoked here

This produced:

var = 0
var = 1
finally!
var = 7
Goodby, Cruel world!

In addition, the memory allocated and pointed to by p and buf is appropriately deleted and free()d.

It is generally a good idea to place a guard close to the definition of whatever it is guarding. That way, we can at a glance see what is considered a resource (even if ad hoc) and what is to be done at the end of its scope. The connection between finally() actions and the resources they manipulate is still ad hoc and implicit compared to the use of RAII for resource handles, but using finally() is far better than scattering cleanup code around in a block.

Basically, finally() does for a block what the increment part of a for-statement does for the for-statement (§9.5.2): it specifies the final action at the top of a block where it is easy to be seen and where it logically belongs from a specification point of view. It says what is to be done upon exit from a scope, saving the programmer from trying to write code at each of the potentially many places from which the thread of control might exit the scope.

13.4. Enforcing Invariants

When a precondition for a function (§12.4) isn’t met, the function cannot correctly perform its task. Similarly, when a constructor cannot establish its class invariant (§2.4.3.2, §17.2.1), the object is not usable. In those cases, I typically throw exceptions. However, there are programs for which throwing an exception is not an option (§13.1.5), and there are people with different views of how to deal with the failure of a precondition (and similar conditions):

• Just don’t do that: It is the caller’s job to meet preconditions, and if the caller doesn’t do that, let bad results occur – eventually those errors will be eliminated from the system through improved design, debugging, and testing.

• Terminate the program: Violating a precondition is a serious design error, and the program must not proceed in the presence of such errors. Hopefully, the total system can recover from the failure of one component (that program) – eventually such failures may be eliminated from the system through improved design, debugging, and testing.

Why would anyone choose one of these alternatives? The first approach often relates to the need for performance: systematically checking preconditions can lead to repeated tests of logically unnecessary conditions (for example, if a caller has correctly validated data, millions of tests in thousands of called functions may be logically redundant). The cost in performance can be significant. It may be worthwhile to suffer repeated crashes during testing to gain that performance. Obviously, this assumes that you eventually get all critical precondition violations out of the system. For some systems, typically systems completely under the control of a single organization, that can be a realistic aim.

The second approach tends to be used in systems where complete and timely recovery from a precondition failure is considered infeasible. That is, making sure that recovery is complete imposes unacceptable complexity on the system design and implementation. On the other hand, termination of a program is considered acceptable. For example, it is not unreasonable to consider program termination acceptable if it is easy to rerun the program with inputs and parameters that make repeated failure unlikely. Some distributed systems are like this (as long as the program that terminates is only a part of the complete system), and so are many of the small programs we write for our own consumption.

Realistically, many systems use a mix of exceptions and these two alternative approaches. All three share a common view that preconditions should be defined and obeyed; what differs is how enforcement is done and whether recovery is considered feasible. Program structure can be radically different depending on whether (localized) recovery is an aim. In most systems, some exceptions are thrown without real expectation of recovery. For example, I often throw an exception to ensure some error logging or to produce a decent error message before terminating or re-initializing a process (e.g., from a catch(...) in main()).

A variety of techniques are used to express checks of desired conditions and invariants. When we want to be neutral about the logical reason for the check, we typically use the word assertion, often abbreviated to an assert. An assertion is simply a logical expression that is assumed to be true. However, for an assertion to be more than a comment, we need a way of expressing what happens if it is false. Looking at a variety of systems, I see a variety of needs when it comes to expressing assertions:

• We need to choose between compile-time asserts (evaluated by the compiler) and run-time asserts (evaluated at run time).

• For run-time asserts we need a choice of throw, terminate, or ignore.

• No code should be generated unless some logical condition is true. For example, some runtime asserts should not be evaluated unless the logical condition is true. Usually, the logical condition is something like a debug flag, a level of checking, or a mask to select among asserts to enforce.

• Asserts should not be verbose or complicated to write (because they can be very common).

Not every system has a need for or supports every alternative.

The standard offers two simple mechanisms:

• In <cassert>, the standard library provides the assert(A) macro, which checks its assertion, A, at run time if and only if the macro NDEBUG (“not debugging”) is not defined (§12.6.2). If the assertion fails, the compiler writes out an error message containing the (failed) assertion, the source file name, and the source file line number and terminates the program.

• The language provides static_assert(A,message), which unconditionally checks its assertion, A, at compile time (§2.4.3.3). If the assertion fails, the compiler writes out the message and the compilation fails.

Where assert() and static_assert() are insufficient, we could use ordinary code for checking. For example:

Click here to view code image

void f(int n)
     // n should be in [1:max)
{
     if (2<debug_level && (n<=0 || max<n)
           throw Assert_error("range problem");
     // ...
}

However, using such “ordinary code” tends to obscure what is being tested. Are we:

• Evaluating the conditions under which we test? (Yes, the 2<debug_level part.)

• Evaluating a condition that is expected to be true for some calls and not for others? (No, because we are throwing an exception – unless someone is trying to use exceptions as simply another return mechanism; §13.1.4.2.)

• Checking a precondition which should never fail? (Yes, the exception is simply our chosen response.)

Worse, the precondition testing (or invariant testing) can easily get dispersed in other code and thus be harder to spot and easier to get wrong. What we would like is a recognizable mechanism for checking assertions. What follows here is a (possibly slightly overelaborate) mechanism for expressing a variety of assertions and a variety of responses to failures. First, I define mechanisms for deciding when to test and deciding what to do if an assertion fails:

Click here to view code image

namespace Assert {
    enum class Mode { throw_, terminate_, ignore_ };
    constexpr Mode current_mode = CURRENT_MODE;
    constexpr int current_level = CURRENT_LEVEL;
    constexpr int default_level = 1;

    constexpr bool level(int n)
        { return n<=current_level; }

    struct Error : runtime_error {
         Error(const string& p) :runtime_error(p) {}
    };

    // ...
}

The idea is to test whenever an assertion has a “level” lower than or equal to current_level. If an assertion fails, current_mode is used to choose among three alternatives. The current_level and current_mode are constants because the idea is to generate no code whatsoever for an assertion unless we have made a decision to do so. Imagine CURRENT_MODE and CURRENT_LEVEL to be set in the build environment for a program, possibly as compiler options.

The programmer will use Assert::dynamic() to make assertions:

Click here to view code image

namespace Assert {
   // ...

   string compose(const char* file, int line, const string& message)
        // compose message including file name and line number
   {
        ostringstream os ("(");
        os << file << "," << line << "):" << message;
        return os.str();
   }

   template<bool condition =level(default_level), class Except = Error>
   void dynamic(bool assertion, const string& message ="Assert::dynamic failed")
   {
        if (assertion)
              return;
        if (current_mode == Assert_mode::throw_)
              throw Except{message};
        if (current_mode == Assert_mode::terminate_)
              std::terminate();
   }

   template<>
   void dynamic<false,Error>(bool, const string&)    // do nothing
   {
   }

   void dynamic(bool b, const string& s)       // default action
   {
        dynamic<true,Error>(b,s);
   }

   void dynamic(bool b)                        // default message
   {
        dynamic<true,Error>(b);
   }
}

I chose the name Assert::dynamic (meaning “evaluate at run time”) to contrast with static_assert (meaning “evaluate at compile time”; §2.4.3.3).

Further implementation trickery could be used to minimize the amount of code generated. Alternatively, we could do more of the testing at run time if more flexibility is needed. This Assert is not part of the standard and is presented primarily as an illustration of the problems and the implementation techniques. I suspect that the demands on an assertion mechanism vary too much for a single one to be used everywhere.

We can use Assert::dynamic like this:

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void f(int n)
     // n should be in [1:max)
{
     Assert::dynamic<Assert::level(2),Assert::Error>(
         (n<=0 || max<n), Assert::compose(__FILE__,__LINE__,"range problem");
     // ...
}

The __FILE__ and __LINE__ are macros that expand at their point of appearance in the source code (§12.6.2). I can’t hide them from the user’s view by placing them inside the implementation of Assert where they belong.

Assert::Error is the default exception, so we need not mention it explicitly. Similarly, if we are willing to use the default assertion level, we don’t need to mention the level explicitly:

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void f(int n)
     // n should be in [1:max)
{
     Assert::dynamic((n<=0 || max<n),Assert::compose(__FILE__,__LINE__,"range problem");
     // ...
}

I do not recommend obsessing about the amount of text needed to express an assertion, but by using a namespace directive (§14.2.3) and the default message, we can get to a minimum:

void f(int n)
     // n should be in [1:max)
{
     dynamic(n<=0||max<n);
     // ...
}

It is possible to control the testing done and the response to testing through build options (e.g., controlling conditional compilation) and/or through options in the program code. That way, you can have a debug version of a system that tests extensively and enters the debugger and a production version that does hardly any testing.

I personally favor leaving at least some tests in the final (shipping) version of a program. For example, with Assert the obvious convention is that assertions marked as level zero will always be checked. We never find the last bug in a large program under continuous development and maintenance. Also, even if all else works perfectly, having a few “sanity checks” left to deal with hardware failures can be wise.

Only the builder of the final complete system can decide whether a failure is acceptable or not. The writer of a library or reusable component usually does not have the luxury of terminating unconditionally. I interpret that to mean that for general library code, reporting an error – preferably by throwing an exception – is essential.

As usual, destructors should not throw, so don’t use a throwing Assert() in a destructor.

13.5. Throwing and Catching Exceptions

This section presents exceptions from a language-technical point of view.

13.5.1. Throwing Exceptions

We can throw an exception of any type that can be copied or moved. For example:

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class No_copy {
     No_copy(const No_copy&) = delete;    // prohibit copying (§17.6.4)
};

class My_error {
     // ...
};

void f(int n)
{
     switch (n) {
     case 0:   throw My_error{};      // OK
     case 1:   throw No_copy{};       // error: can't copy a No_copy
     case 2:   throw My_error;        // error: My_error is a type, rather than an object
     }
}

The exception object caught (§13.5.2) is in principle a copy of the one thrown (though an optimizer is allowed to minimize copying); that is, a throw x; initializes a temporary variable of x’s type with x. This temporary may be further copied several times before it is caught: the exception is passed (back) from called function to calling function until a suitable handler is found. The type of the exception is used to select a handler in the catch-clause of some try-block. The data in the exception object – if any – is typically used to produce error messages or to help recovery. The process of passing the exception “up the stack” from the point of throw to a handler is called stack unwinding . In each scope exited, the destructors are invoked so that every fully constructed object is properly destroyed. For example:

void f()
{
     string name {"Byron"};
     try {
          string s = "in";
          g();
     }
     catch (My_error) {
          // ...
     }
}

void g()
{
     string s = "excess";
     {
          string s = "or";
          h();
     }
}

void h()
{
     string s = "not";
     throw My_error{};
     string s2 = "at all";
}

After the throw in h(), all the strings that were constructed are destroyed in the reverse order of their construction: "not", "or", "excess", "in", but not "at all", which the thread of control never reached, and not "Byron", which was unaffected.

Because an exception is potentially copied several times before it is caught, we don’t usually put huge amounts of data in it. Exceptions containing a few words are very common. The semantics of exception propagation are those of initialization, so objects of types with move semantics (e.g., strings) are not expensive to throw. Some of the most common exceptions carry no information; the name of the type is sufficient to report the error. For example:

struct Some_error { };

void fct()
{
     // ...
     if (something_wrong)
           throw Some_error{};
}

There is a small standard-library hierarchy of exception types (§13.5.2) that can be used either directly or as base classes. For example:

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struct My_error2 : std::runtime_error {
     const char* what() const noexcept { return "My_error2"; }
};

The standard-library exception classes, such as runtime_error and out_of_range, take a string argument as a constructor argument and have a virtual function what() that will regurgitate that string. For example:

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void g(int n)   // throw some exception
{
     if (n)
           throw std::runtime_error{"I give up!"};
     else
           throw My_error2{};
}

void f(int n)   // see what exception g() throws
{
     try {
            void g(n);
     }
     catch (std::exception& e) {
          cerr << e.what() << '\n';
     }
}

13.5.1.1. noexcept Functions

Some functions don’t throw exceptions and some really shouldn’t. To indicate that, we can declare such a function noexcept. For example:

double compute(double) noexcept; // may not throw an exception

Now no exception will come out of compute().

Declaring a function noexcept can be most valuable for a programmer reasoning about a program and for a compiler optimizing a program. The programmer need not worry about providing try-clauses (for dealing with failures in a noexcept function) and an optimizer need not worry about control paths from exception handling.

However, noexcept is not completely checked by the compiler and linker. What happens if the programmer “lied” so that a noexcept function deliberately or accidentally threw an exception that wasn’t caught before leaving the noexcept function? Consider:

double compute(double x) noexcept;
{
     string s = "Courtney and Anya";
     vector<double> tmp(10);
     // ...
}

The vector constructor may fail to acquire memory for its ten doubles and throw a std::bad_alloc. In that case, the program terminates. It terminates unconditionally by invoking std::terminate() (§30.4.1.3). It does not invoke destructors from calling functions. It is implementation-defined whether destructors from scopes between the throw and the noexcept (e.g., for s in compute()) are invoked. The program is just about to terminate, so we should not depend on any object anyway. By adding a noexcept specifier, we indicate that our code was not written to cope with a throw.

13.5.1.2. The noexcept Operator

It is possible to declare a function to be conditionally noexcept. For example:

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template<typename T>
void my_fct(T& x) noexcept(Is_pod<T>());

The noexcept(Is_pod<T>()) means that My_fct may not throw if the predicate Is_pod<T>() is true but may throw if it is false. I may want to write this if my_fct() copies its argument. I know that copying a POD does not throw, whereas other types (e.g., a string or a vector) may.

The predicate in a noexcept() specification must be a constant expression. Plain noexcept means noexcept(true).

The standard library provides many type predicates that can be useful for expressing the conditions under which a function may throw an exception (§35.4).

What if the predicate we want to use isn’t easily expressed using type predicates only? For example, what if the critical operation that may or may not throw is a function call f(x)? The noexcept() operator takes an expression as its argument and returns true if the compiler “knows” that it cannot throw and false otherwise. For example:

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template<typename T>
void call_f(vector<T>& v) noexcept(noexcept(f(v[0]))
{
     for (auto x : v)
           f(x);
}

The double mention of noexcept looks a bit odd, but noexcept is not a common operator.

The operand of noexcept() is not evaluated, so in the example we do not get a run-time error if we pass call_f() with an empty vector.

A noexcept(expr) operator does not go to heroic lengths to determine whether expr can throw; it simply looks at every operation in expr and if they all have noexcept specifications that evaluate to true, it returns true. A noexcept(expr) does not look inside definitions of operations used in expr.

Conditional noexcept specifications and the noexcept() operator are common and important in standard-library operations that apply to containers. For example (§iso.20.2.2):

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template<class T, size_t N>
void swap(T (&a)[N], T (&b)[N]) noexcept(noexcept(swap(*a, *b)));

13.5.1.3. Exception Specifications

In older C++ code, you may find exception specifications. For example:

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void f(int) throw(Bad,Worse);  // may only throw Bad or Worse exceptions
void g(int) throw();           // may not throw

An empty exception specification throw() is defined to be equivalent to noexcept (§13.5.1.1). That is, if an exception is thrown, the program terminates.

The meaning of a nonempty exception specification, such as throw(Bad,Worse), is that if the function (here f()) throws any exception that is not mentioned in the list or publicly derived from an exception mentioned there, an unexpected handler is called. The default effect of an unexpected exception is to terminate the program (§30.4.1.3). A nonempty throw specification is hard to use well and implies potentially expensive run-time checks to determine if the right exception is thrown. This feature has not been a success and is deprecated. Don’t use it.

If you want to dynamically check which exceptions are thrown, use a try-block.

13.5.2. Catching Exceptions

Consider:

void f()
{
     try {
          throw E{};
     }
     catch(H) {
         // when do we get here?
     }
}

The handler is invoked:

[1] If H is the same type as E

[2] If H is an unambiguous public base of E

[3] If H and E are pointer types and [1] or [2] holds for the types to which they refer

[4] If H is a reference and [1] or [2] holds for the type to which H refers

In addition, we can add const to the type used to catch an exception in the same way that we can add it to a function parameter. This doesn’t change the set of exceptions we can catch; it only restricts us from modifying the exception caught.

In principle, an exception is copied when it is thrown (§13.5). The implementation may apply a wide variety of strategies for storing and transmitting exceptions. It is guaranteed, however, that there is sufficient memory to allow new to throw the standard out-of-memory exception, bad_alloc (§11.2.3).

Note the possibility of catching an exception by reference. Exception types are often defined as part of class hierarchies to reflect relationships among the kinds of errors they represent. For examples, see §13.5.2.3 and §30.4.1.1. The technique of organizing exception classes into hierarchies is common enough for some programmers to prefer to catch every exception by reference.

The {} in both the try-part and a catch-clause of a try-block are real scopes. Consequently, if a name is to be used in both parts of a try-block or outside it, that name must be declared outside the try-block. For example:

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void g()
{
     int x1;
     try {
          int x2 = x1;
          // ...
     }
     catch (Error) {
          ++x1;     // OK
          ++x2;     // error: x2 not in scope
          int x3 = 7;
          // ...
     }
     catch(...) {
          ++x3;     // error: x3 not in scope
          // ...
     }

     ++x1;          // OK
     ++x2;          // error: x2 not in scope
     ++x3;          // error: x3 not in scope
}

The “catch everything” clause, catch(...), is explained in §13.5.2.2.

13.5.2.1. Rethrow

Having caught an exception, it is common for a handler to decide that it can’t completely handle the error. In that case, the handler typically does what can be done locally and then throws the exception again. Thus, an error can be handled where it is most appropriate. This is the case even when the information needed to best handle the error is not available in a single place, so that the recovery action is best distributed over several handlers. For example:

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void h()
{
     try {
          // ... code that might throw an exception ...
     }
     catch (std::exception& err) {
          if (can_handle_it_completely) {
                // ... handle it ...
                return;
          }
          else {
                // ... do what can be done here ...
                throw;      // rethrow the exception
          }
     }
}

A rethrow is indicated by a throw without an operand. A rethrow may occur in a catch-clause or in a function called from a catch-clause. If a rethrow is attempted when there is no exception to rethrow, std::terminate() (§13.5.2.5) will be called. A compiler can detect and warn about some, but not all, such cases.

The exception rethrown is the original exception caught and not just the part of it that was accessible as an exception. For example, had an out_of_range been thrown, h() would catch it as a plain exception, but throw; would still rethrow it as an out_of_range. Had I written throw err; instead of the simpler throw;, the exception would have been sliced (§17.5.1.4) and h()’s caller could not have caught it as an out_of_range.

13.5.2.2. Catch Every Exception

In <stdexcept>, the standard library provides a small hierarchy of exception classes with a common base exception (§30.4.1.1). For example:

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void m()
{
     try {
          // ... do something ...
     }
     catch (std::exception& err) {      // handle every standard-library exception
          // ... cleanup ...
          throw;
     }
}

This catches every standard-library exception. However, the standard-library exceptions are just one set of exception types. Consequently, you cannot catch every exception by catching std::exception. If someone (unwisely) threw an int or an exception from some application-specific hierarchy, it would not be caught by the handler for std::exception&.

However, we often need to deal with every kind of exception. For example, if m() is supposed to leave some pointers in the state in which it found them, then we can write code in the handler to give them acceptable values. As for functions, the ellipsis, ..., indicates “any argument” (§12.2.4), so catch(...) means “catch any exception.” For example:

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void m()
{
     try {
          // ... something ...
     }
     catch(...) {          // handle every exception
          // ... cleanup ...
          throw;
     }
}

13.5.2.3. Multiple Handlers

A try-block may have multiple catch-clauses (handlers). Because a derived exception can be caught by handlers for more than one exception type, the order in which the handlers are written in a try-statement is significant. The handlers are tried in order. For example:

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void f()
{
     try {
          // ...
     }
     catch (std::ios_base::failure) {
          // ... handle any iostream error (§30.4.1.1) ...
     }
     catch (std::exception& e) {
          // ... handle any standard-library exception (§30.4.1.1) ...
     }
     catch (...) {
          // ... handle any other exception (§13.5.2.2) ...
     }
}

The compiler knows the class hierarchy, so it can warn about many logical mistakes. For example:

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void g()
{
     try {
          // ...
     }
     catch (...) {
          // ... handle every exception (§13.5.2.2) ...
     }
     catch (std::exception& e) {
          // ... handle any standard library exception (§30.4.1.1) ...
     }

     catch (std::bad_cast) {
          // ... handle dynamic_cast failure (§22.2.1) ...
     }
}

Here, the exception is never considered. Even if we removed the “catch-all” handler, bad_cast wouldn’t be considered because it is derived from exception. Matching exception types to catch-clauses is a (fast) run-time operation and is not as general as (compile-time) overload resolution.

13.5.2.4. Function try-Blocks

The body of a function can be a try-block. For example:

int main()
try
{
     // ... do something ...
}
catch (...} {
     // ... handle exception ...
}

For most functions, all we gain from using a function try-block is a bit of notational convenience. However, a try-block allows us to deal with exceptions thrown by base-or-member initializers in constructors (§17.4). By default, if an exception is thrown in a base-or-member initializer, the exception is passed on to whatever invoked the constructor for the member’s class. However, the constructor itself can catch such exceptions by enclosing the complete function body – including the member initializer list – in a try-block. For example:

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class X {
     vector<int> vi;
     vector<string> vs;

     // ...
public:
     X(int,int);
     // ...
};

X::X(int sz1, int sz2)
try
     :vi(sz1), // construct vi with sz1 ints
     vs(sz2),  // construct vs with sz2 strings
{
     // ...
}
catch (std::exception& err) { // exceptions thrown for vi and vs are caught here
     // ...
}

So, we can catch exceptions thrown by member constructors. Similarly, we can catch exceptions thrown by member destructors in a destructor (though a destructor should never throw). However, we cannot “repair” the object and return normally as if the exception had not happened: an exception from a member constructor means that the member may not be in a valid state. Also, other member objects will either not be constructed or already have had their destructors invoked as part of the stack unwinding.

The best we can do in a catch-clause of a function try-block for a constructor or destructor is to throw an exception. The default action is to rethrow the original exception when we “fall off the end” of the catch-clause (§iso.15.3).

There are no such restrictions for the try-block of an ordinary function.

13.5.2.5. Termination

There are cases where exception handling must be abandoned for less subtle error-handling techniques. The guiding principles are:

• Don’t throw an exception while handling an exception.

• Don’t throw an exception that can’t be caught.

If the exception-handling implementation catches you doing either, it will terminate your program.

If you managed to have two exceptions active at one time (in the same thread, which you can’t), the system would have no idea which of the exceptions to try to handle: your new one or the one it was already trying to handle. Note that an exception is considered handled immediately upon entry into a catch-clause. Rethrowing an exception (§13.5.2.1) or throwing a new exception from within a catch-clause is considered a new throw done after the original exception has been handled. You can throw an exception from within a destructor (even during stack unwinding) as long as you catch it before it leaves the destructor.

The specific rules for calling terminate() are (§iso.15.5.1)

• When no suitable handler was found for a thrown exception

• When a noexcept function tries to exit with a throw

• When a destructor invoked during stack unwinding tries to exit with a throw

• When code invoked to propagate an exception (e.g., a copy constructor) tries to exit with a throw

• When someone tries to rethrow (throw;) when there is no current exception being handled

• When a destructor for a statically allocated or thread-local object tries to exit with a throw

• When an initializer for a statically allocated or thread-local object tries to exit with a throw

• When a function invoked as an atexit() function tries to exit with a throw

In such cases, the function std::terminate() is called. In addition, a user can call terminate() if less drastic approaches are infeasible.

By “tries to exit with a throw,” I mean that an exception is thrown somewhere and not caught so that the run-time system tries to propagate it from a function to its caller.

By default, terminate() will call abort() (§15.4.3). This default is the correct choice for most users – especially during debugging. If that is not acceptable, the user can provide a terminate handler function by a call std::set_terminate() from <exception>:

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using terminate_handler = void(*)();  // from <exception>

[[noreturn]] void my_handler()        // a terminate handler cannot return
{
     // handle termination my way
}

void dangerous()  // very!
{
     terminate_handler old = set_terminate(my_handler);
     // ...
     set_terminate(old); // restore the old terminate handler
}

The return value is the previous function given to set_terminate().

For example, a terminate handler could be used to abort a process or maybe to re-initialize a system. The intent is for terminate() to be a drastic measure to be applied when the error recovery strategy implemented by the exception-handling mechanism has failed and it is time to go to another level of a fault tolerance strategy. If a terminate handler is entered, essentially nothing can be assumed about a program’s data structures; they must be assumed to be corrupted. Even writing an error message using cerr must be assumed to be hazardous. Also, note that as dangerous() is written, it is not exception-safe. A throw or even a return before set_terminate(old) will leave my_handler in place when it wasn’t meant to be. If you must mess with terminate(), at least use RAII (§13.3).

A terminate handler cannot return to its caller. If it tries to, terminate() will call abort().

Note that abort() indicates abnormal exit from the program. The function exit() can be used to exit a program with a return value that indicates to the surrounding system whether the exit is normal or abnormal (§15.4.3).

It is implementation-defined whether destructors are invoked when a program is terminated because of an uncaught exception. On some systems, it is essential that the destructors are not called so that the program can be resumed from the debugger. On other systems, it is architecturally close to impossible not to invoke the destructors while searching for a handler.

If you want to ensure cleanup when an otherwise uncaught exception happens, you can add a catch-all handler (§13.5.2.2) to main() in addition to handlers for exceptions you really care about. For example:

int main()
try {
     // ...
}
catch (const My_error& err) {
     // ... handle my error ...
}
catch (const std::range_error&)
{
     cerr << "range error: Not again!\n";
}
catch (const std::bad_alloc&)
{
     cerr << "new ran out of memory\n";
}
catch (...) {
     // ...
}

This will catch every exception, except those thrown by construction and destruction of namespace and thread-local variables (§13.5.3). There is no way of catching exceptions thrown during initialization or destruction of namespace and thread-local variables. This is another reason to avoid global variables whenever possible.

When an exception is caught, the exact point where it was thrown is generally not known. This represents a loss of information compared to what a debugger might know about the state of a program. In some C++ development environments, for some programs, and for some people, it might therefore be preferable not to catch exceptions from which the program isn’t designed to recover.

See Assert (§13.4) for an example of how one might encode the location of a throw into the thrown exception.

13.5.3. Exceptions and Threads

If an exception is not caught on a thread (§5.3.1, §42.2), std::terminate() (§13.5.2.5) is called. So, if we don’t want an error in a thread to stop the whole program, we must catch all errors from which we would like to recover and somehow report them to a part of the program that is interested in the results of the thread. The “catch-all” construct catch(...) (§13.5.2.2) comes in handy for that.

We can transfer an exception thrown on one thread to a handler on another thread using the standard-library function current_exception() (§30.4.1.2). For example:

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try {
     // ... do the work ...
}
catch(...) {
     prom.set_exception(current_exception());
}

This is the basic technique used by packaged_task to handle exceptions from user code (§5.3.5.2).

13.6. A vector Implementation

The standard vector provides splendid examples of techniques for writing exception-safe code: its implementation illustrates problems that occur in many contexts and solutions that apply widely.

Obviously, a vector implementation relies on many language facilities provided to support the implementation and use of classes. If you are not (yet) comfortable with C++’s classes and templates, you may prefer to delay studying this example until you have read Chapter 16, Chapter 25, and Chapter 26. However, a good understanding of the use of exceptions in C++ requires a more extensive example than the code fragments so far in this chapter.

The basic tools available for writing exception-safe code are:

• The try-block (§13.5).

• The support for the “Resource Acquisition Is Initialization” technique (§13.3).

The general principles to follow are to

• Never let go of a piece of information before its replacement is ready for use.

• Always leave objects in valid states when throwing or rethrowing an exception.

That way, we can always back out of an error situation. The practical difficulty in following these principles is that innocent-looking operations (such as <, =, and sort()) might throw exceptions. Knowing what to look for in an application takes experience.

When you are writing a library, the ideal is to aim at the strong exception-safety guarantee (§13.2) and always to provide the basic guarantee. When writing a specific program, there may be less concern for exception safety. For example, if I write a simple data analysis program for my own use, I’m usually quite willing to have the program terminate in the unlikely event of memory exhaustion.

Correctness and basic exception safety are closely related. In particular, the techniques for providing basic exception safety, such as defining and checking invariants (§13.4), are similar to the techniques that are useful to get a program small and correct. It follows that the overhead of providing the basic exception-safety guarantee (§13.2) – or even the strong guarantee – can be minimal or even insignificant.

13.6.1. A Simple vector

A typical implementation of vector (§4.4.1, §31.4) will consist of a handle holding pointers to the first element, one-past-the-last element, and one-past-the-last allocated space (§31.2.1) (or the equivalent information represented as a pointer plus offsets):

In addition, it holds an allocator (here, alloc), from which the vector can acquire memory for its elements. The default allocator (§34.4.1) uses new and delete to acquire and release memory.

Here is a declaration of vector simplified to present only what is needed to discuss exception safety and avoidance of resource leaks:

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template<class T, class A = allocator<T>>
class vector {
private:
     T* elem;       // start of allocation
     T* space;      // end of element sequence, start of space allocated for possible expansion
     T* last;       // end of allocated space
     A alloc;       // allocator

public:
     using size_type = unsigned int;                // type used for vector sizes

     explicit vector(size_type n, const T& val = T(), const A& = A());

     vector(const vector& a);                       // copy constructor
     vector& operator=(const vector& a);            // copy assignment

     vector(vector&& a);                            // move constructor
     vector& operator=(vector&& a);                 // move assignment

     ~vector();

     size_type size() const { return space–elem; }
     size_type capacity() const { return last–elem; }
     void reserve(size_type n);                     // increase capacity to n

     void resize(size_type n, const T& = {});       // increase size to n
     void push_back(const T&);                      // add an element at the end

     // ...
};

Consider first a naive implementation of the constructor that initializes a vector to n elements initialized to val:

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template<class T, class A>
vector<T,A>::vector(size_type n, const T& val, const A& a) // warning: naive implementation
    :alloc{a}                      // copy the allocator
{
    elem = alloc.allocate(n);      // get memory for elements (§34.4)
    space = last = elem+n;
    for (T* p = elem; p!=last; ++p)
          a.construct(p,val);      // construct copy of val in *p (§34.4)
}

There are two potential sources of exceptions here:

[1] allocate() may throw an exception if no memory is available.

[2] T’s copy constructor may throw an exception if it can’t copy val.

What about the copy of the allocator? We can imagine that it throws, but the standard specifically requires that it does not do that (§iso.17.6.3.5). Anyway, I have written the code so that it wouldn’t matter if it did.

In both cases of a throw, no vector object is created, so vector’s destructor is not called (§13.3).

When allocate() fails, the throw will exit before any resources are acquired, so all is well.

When T’s copy constructor fails, we have acquired some memory that must be freed to avoid memory leaks. Worse still, the copy constructor for T might throw an exception after correctly constructing a few elements but before constructing them all. These T objects may own resources that then would be leaked.

To handle this problem, we could keep track of which elements have been constructed and destroy those (and only those) in case of an error:

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template<class T, class A>
vector<T,A>::vector(size_type n, const T& val, const A& a)       // elaborate implementation
    :alloc{a}                           // copy the allocator
{
    elem = alloc.allocate(n);           // get memory for elements

    iterator p;

    try {
         iterator end = elem+n;
         for (p=elem; p!=end; ++p)
               alloc.construct(p,val);        // construct element (§34.4)
         last = space = p;
    }
    catch (...) {
         for (iterator q = elem; q!=p; ++q)
               alloc.destroy(q);              // destroy constructed elements
         alloc.deallocate(elem,n);            // free memory
         throw;                               // rethrow
    }
}

Note that the declaration of p is outside the try-block; otherwise, we would not be able to access it in both the try-part and the catch-clause.

The overhead here is the overhead of the try-block. In a good C++ implementation, this overhead is negligible compared to the cost of allocating memory and initializing elements. For implementations where entering a try-block incurs a cost, it may be worthwhile to add a test if (n) before the try to explicitly handle the (very common) empty vector case.

The main part of this constructor is a repeat of the implementation of std::uninitialized_fill():

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template<class For, class T>
void uninitialized_fill(For beg, For end, const T& x)
{
     For p;
     try {
          for (p=beg; p!=end; ++p)
                ::new(static_cast<void* >(&*p)) T(x);    // construct copy of x in *p (§11.2.4)
     }
     catch (...) {
          for (For q = beg; q!=p; ++q)
               (&*q)–>~T();                             // destroy element (§11.2.4)
          throw;                                        // rethrow (§13.5.2.1)
     }
}

The curious construct &p takes care of iterators that are not pointers. In that case, we need to take the address of the element obtained by dereference to get a pointer. Together with the explicitly global ::new, the explicit cast to void* ensures that the standard-library placement function (§17.2.4) is used to invoke the constructor, and not some user-defined operator new() for T*s. The calls to alloc.construct() in the vector constructors are simply syntactic sugar for this placement new. Similarly, the alloc.destroy() call simply hides explicit destruction (like (&*xq)–>~T()). This code is operating at a rather low level where writing truly general code can be difficult.

Fortunately, we don’t have to invent or implement uninitialized_fill(), because the standard library provides it (§32.5.6). It is often essential to have initialization operations that either complete successfully, having initialized every element, or fail, leaving no constructed elements behind. Consequently, the standard library provides uninitialized_fill(), uninitialized_fill_n(), and uninitialized_copy() (§32.5.6), which offer the strong guarantee (§13.2).

The uninitialized_fill() algorithm does not protect against exceptions thrown by element destructors or iterator operations (§32.5.6). Doing so would be prohibitively expensive and probably impossible.

The uninitialized_fill() algorithm can be applied to many kinds of sequences. Consequently, it takes a forward iterator (§33.1.2) and cannot guarantee to destroy elements in the reverse order of their construction.

Using uninitialized_fill(), we can simplify our constructor:

Click here to view code image

template<class T, class A>
vector<T,A>::vector(size_type n, const T& val, const A& a)    // still a bit messy
     :alloc(a)                                 // copy the allocator
{
     elem = alloc.allocate(n);                 // get memory for elements
     try {
          uninitialized_fill(elem,elem+n,val); // copy elements
          space = last = elem+n;
     }
     catch (...) {
          alloc.deallocate(elem,n);            // free memory
          throw;                               // rethrow
     }
}

This is a significant improvement on the first version of this constructor, but the next section demonstrates how to further simplify it.

The constructor rethrows a caught exception. The intent is to make vector transparent to exceptions so that the user can determine the exact cause of a problem. All standard-library containers have this property. Exception transparency is often the best policy for templates and other “thin” layers of software. This is in contrast to major parts of a system (“modules”) that generally need to take responsibility for all exceptions thrown. That is, the implementer of such a module must be able to list every exception that the module can throw. Achieving this may involve grouping exceptions into hierarchies (§13.5.2) and using catch(...) (§13.5.2.2).

13.6.2. Representing Memory Explicitly

Experience shows that writing correct exception-safe code using explicit try-blocks is more difficult than most people expect. In fact, it is unnecessarily difficult because there is an alternative: The “Resource Acquisition Is Initialization” technique (§13.3) can be used to reduce the amount of code that must be written and to make the code more stylized. In this case, the key resource required by the vector is memory to hold its elements. By providing an auxiliary class to represent the notion of memory used by a vector, we can simplify the code and decrease the chances of accidentally forgetting to release it:

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template<class T, class A = allocator<T> >
struct vector_base {                    // memory structure for vector
     A alloc;       // allocator
     T* elem;       // start of allocation
     T* space;      // end of element sequence, start of space allocated for possible expansion
     T* last;       // end of allocated space

     vector_base(const A& a, typename A::size_type n)
         : alloc{a}, elem{alloc.allocate(n)}, space{elem+n}, last{elem+n} { }
     ~vector_base() { alloc.deallocate(elem,last–elem); }

     vector_base(const vector_base&) = delete;             // no copy operations
     vector_base& operator=(const vector_base&) = delete;

     vector_base(vector_base&&);                           // move operations
     vector_base& operator=(vector_base&&);
};

As long as elem and last are correct, vector_base can be destroyed. Class vector_base deals with memory for a type T, not objects of type T. Consequently, a user of vector_base must construct all objects explicitly in the allocated space and later destroy all constructed objects in a vector_base before the vector_base itself is destroyed.

The vector_base is designed exclusively to be part of the implementation of vector. It is always hard to predict where and how a class will be used, so I made sure that a vector_base can’t be copied and also that a move of a vector_base properly transfers ownership of the memory allocated for elements:

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template<class T, class A>
vector_base<T,A>::vector_base(vector_base&& a)
     : alloc{a.alloc},
     elem{a.elem},
     space{a.space},
     last{a.space}
{
     a.elem = a.space = a.last = nullptr; // no longer owns any memory
}

template<class T, class A>
vector_base<T,A>::& vector_base<T,A>::operator=(vector_base&& a)
{
     swap(*this,a);
     return *this;
}

This definition of the move assignment uses swap() to transfer ownership of any memory allocated for elements. There are no objects of type T to destroy: vector_base deals with memory and leaves concerns about objects of type T to vector.

Given vector_base, vector can be defined like this:

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template<class T, class A = allocator<T> >
class vector {
     vector_base<T,A> vb;                     // the data is here
     void destroy_elements();
public:
     using size_type = unsigned int;

     explicit vector(size_type n, const T& val = T(), const A& = A());

     vector(const vector& a);                 // copy constructor
     vector& operator=(const vector& a);      // copy assignment

     vector(vector&& a);                      // move constructor
     vector& operator=(vector&& a);           // move assignment

     ~vector() { destroy_elements(); }

     size_type size() const { return vb.space–vb.elem; }
     size_type capacity() const { return vb.last–vb.elem; }

     void reserve(size_type);                 // increase capacity

     void resize(size_type, T = {});          // change the number of elements
     void clear() { resize(0); }              // make the vector empty
     void push_back(const T&);                // add an element at the end

     // ...
};

template<class T, class A>
void vector<T,A>::destroy_elements()
{
     for (T* p = vb.elem; p!=vb.space; ++p)
           p–>~T();                // destroy element (§17.2.4)
     vb.space=vb.elem;
}

The vector destructor explicitly invokes the T destructor for every element. This implies that if an element destructor throws an exception, the vector destruction fails. This can be a disaster if it happens during stack unwinding caused by an exception and terminate() is called (§13.5.2.5). In the case of normal destruction, throwing an exception from a destructor typically leads to resource leaks and unpredictable behavior of code relying on reasonable behavior of objects. There is no really good way to protect against exceptions thrown from destructors, so the library makes no guarantees if an element destructor throws (§13.2).

Now the constructor can be simply defined:

Click here to view code image

template<class T, class A>
vector<T,A>::vector(size_type n, const T& val, const A& a)
     :vb{a,n}      // allocate space for n elements
{
     uninitialized_fill(vb.elem,vb.elem+n,val);// make n copies of val
}

The simplification achieved for this constructor carries over to every vector operation that deals with initialization or allocation. For example, the copy constructor differs mostly by using uninitialized_copy() instead of uninitialized_fill():

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template<class T, class A>
vector<T,A>::vector(const vector<T,A>& a)
     :vb{a.alloc,a.size()}
{
     uninitialized_copy(a.begin(),a.end(),vb.elem);
}

This style of constructor relies on the fundamental language rule that when an exception is thrown from a constructor, subobjects (including bases) that have already been completely constructed will be properly destroyed (§13.3). The uninitialized_fill() algorithm and its cousins (§13.6.1) provide the equivalent guarantee for partially constructed sequences.

The move operations are even simpler:

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template<class T, class A>
vector<T,A>::vector(vector&& a)                       // move constructor
     :vb{move(a.vb)}        // transfer ownership
{
}

The vector_base move constructor will set the argument’s representation to “empty.”

For the move assignment, we must take care of the old value of the target:

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template<class T, class A>
vector<T,A>::& vector<T,A>::operator=(vector&& a)          // move assignment
{
     clear();           // destroy elements
     swap(*this,a);     // transfer ownership
}

The clear() is strictly speaking redundant because I could assume that the rvalue a would be destroyed immediately after the assignment. However, I don’t know if some programmer has been playing games with std::move().

13.6.3. Assignment

As usual, assignment differs from construction in that an old value must be taken care of. First consider a straightforward implementation:

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template<class T, class A>
vector<T,A>& vector<T,A>::operator=(const vector& a)        // offers the strong guarantee (§13.2)
{
     vector_base<T,A> b(alloc,a.size());           // get memory
     uninitialized_copy(a.begin(),a.end(),b.elem); // copy elements
     destroy_elements();                           // destroy old elements
     swap(vb,b);                                   // transfer ownership
     return *this;                                 // implicitly destroy the old value
}

This vector assignment provides the strong guarantee, but it repeats a lot of code from constructors and destructors. We can avoid repetition:

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template<class T, class A>
vector<T,A>& vector<T,A>::operator=(const vector& a)        // offers the strong guarantee (§13.2)
{
     vector temp {a};            // copy allocator
     std::swap(*this,temp);      // swap representations
     return *this;
}

The old elements are destroyed by temp’s destructor, and the memory used to hold them is deallocated by temp’s vector_base’s destructor.

The reason that the standard-library swap() (§35.5.2) works for vector_bases is that we defined vector_base move operations for swap() to use.

The performance of the two versions ought to be equivalent. Essentially, they are just two different ways of specifying the same set of operations. However, the second implementation is shorter and doesn’t replicate code from related vector functions, so writing the assignment that way ought to be less error-prone and lead to simpler maintenance.

Note that I did not test for self-assignment, such as v=v. This implementation of = works by first constructing a copy and then swapping representations. This obviously handles self-assignment correctly. I decided that the efficiency gained from the test in the rare case of self-assignment was more than offset by its cost in the common case where a different vector is assigned.

In either case, two potentially significant optimizations are missing:

[1] If the capacity of the vector assigned to is large enough to hold the assigned vector, we don’t need to allocate new memory.

[2] An element assignment may be more efficient than an element destruction followed by an element construction.

Implementing these optimizations, we get:

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template<class T, class A>
vector<T,A>& vector<T,A>::operator=(const vector& a)          // optimized, basic guarantee (§13.2) only
{
     if (capacity() < a.size()) { // allocate new vector representation:
           vector temp {a};              // copy allocator
           swap(*this,temp);             // swap representations
           return *this;                 // implicitly destroy the old value
     }
     if (this == &a) return *this;                            // optimize self assignment

     size_type sz = size();
     size_type asz = a.size();
     vb.alloc = a.vb.alloc;                                   // copy the allocator
     if (asz<=sz) {
           copy(a.begin(),a.begin()+asz,vb.elem);
           for (T* p = vb.elem+asz; p!=vb.space; ++p)         // destroy surplus elements (§16.2.6)
                 p–>~T();
     }
     else {
           copy(a.begin(),a.begin()+sz,vb.elem);
           uninitialized_copy(a.begin()+sz,a.end(),vb.space); // construct extra elements
     }
     vb.space = vb.elem+asz;
     return *this;
}

These optimizations are not free. Obviously, the complexity of the code is far higher. Here, I also test for self-assignment. However, I do so mostly to show how it is done because here it is only an optimization.

The copy() algorithm (§32.5.1) does not offer the strong exception-safety guarantee. Thus, if T::operator=() throws an exception during copy(), the vector being assigned to need not be a copy of the vector being assigned, and it need not be unchanged. For example, the first five elements might be copies of elements of the assigned vector and the rest unchanged. It is also plausible that an element – the element that was being copied when T::operator=() threw an exception – ends up with a value that is neither the old value nor a copy of the corresponding element in the vector being assigned. However, if T::operator=() leaves its operands in valid states before it throws (as it should), the vector is still in a valid state – even if it wasn’t the state we would have preferred.

The standard-library vector assignment offers the (weaker) basic exception-safety guarantee of this last implementation – and its potential performance advantages. If you need an assignment that leaves the vector unchanged if an exception is thrown, you must either use a library implementation that provides the strong guarantee or provide your own assignment operation. For example:

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template<class T, class A>
void safe_assign(vector<T,A>& a, const vector<T,A>& b)      // simple a = b
{
     vector<T,A> temp{b};         // copy the elements of b into a temporary
     swap(a,temp);
}

Alternatively, we could simply use call-by-value (§12.2):

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template<class T, class A>
void safe_assign(vector<T,A>& a, vector<T,A> b)       // simple a = b (note: b is passed by value)
{
     swap(a,b);
}

I never can decide if this last version is simply beautiful or too clever for real (maintainable) code.

13.6.4. Changing Size

One of the most useful aspects of vector is that we can change its size to suit our needs. The most popular functions for changing size are v.push_back(x), which adds an x at the end of v, and v.resize(s), which makes s the number of elements in v.

13.6.4.1. reserve()

The key to a simple implementation of such functions is reserve(), which adds free space at the end for the vector to grow into. In other words, reserve() increases the capacity() of a vector. If the new allocation is larger than the old, reserve() needs to allocate new memory and move the elements into it. We could try the trick from the unoptimized assignment (§13.6.3):

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template<class T, class A>
void vector<T,A>::reser ve(size_type newalloc)    // flawed first attempt
{
     if (newalloc<=capacity()) return;       // never decrease allocation
     vector<T,A> v(capacity());              // make a vector with the new capacity
     copy(elem,elem+size(),v.begin())        // copy elements
     swap(*this,v);                          // install new value
} // implicitly release old value

This has the nice property of providing the strong guarantee. However, not all types have a default value, so this implementation is flawed. Furthermore, looping over the elements twice, first to default construct and then to copy, is a bit odd. So let us optimize:

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template<class T, class A>
void vector<T,A>::reserve(size_type newalloc)
{
     if (newalloc<=capacity()) return;                // never decrease allocation
     vector_base<T,A> b {vb.alloc,newalloc};          // get new space
     uninitialized_move(elem,elem+size(),b.elem);     // move elements
     swap(vb,b);                                      // install new base
} // implicitly release old space

The problem is that the standard library doesn’t offer uninitialized_move(), so we have to write it:

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template<typename In, typename Out>
Out uninitialized_move(In b, In e, Out oo)
{
     for (; b!=e; ++b,++oo) {
            new(static_cast<void*>(&*oo)) T{move(*b)}; // move construct
            b–>~T();                                   // destroy
     }
     return b;
}

In general, there is no way of recovering the original state from a failed move, so I don’t try to. This uninitialized_move() offers only the basic guarantee. However, it is simple and for the vast majority of cases it is fast. Also, the standard-library reserve() only offers the basic guarantee.

Whenever reserve() may have moved the elements, any iterators into the vector may have been invalidated (§31.3.3).

Remember that a move operation should not throw. In the rare cases where the obvious implementation of a move might throw, we typically go out of our way to avoid that. A throw from a move operation is rare, unexpected, and damaging to normal reasoning about code. If at all possible avoid it. The standard-library move_if_noexcept() operations may be of help here (§35.5.1).

The explicit use of move() is needed because the compiler doesn’t know that elem[i] is just about to be destroyed.

13.6.4.2. resize()

The vector member function resize() changes the number of elements. Given reserve(), the implementation resize() is fairly simple. If the number of elements increases, we must construct the new elements. Conversely, if the number of elements decrease, we must destroy the surplus elements:

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template<class T, class A>
void vector<T,A>::resize(size_type newsize, const T& val)
{
     reserve(newsize);
     if (size()<newsize)
           uninitialized_fill(elem+size(),elem+newsize,val);   // construct new elements: [size():newsize)
     else
           destroy(elem.size(),elem+newsize);                  // destroy surplus elements: [newsize:size())
     vb.space = vb.last = vb.elem+newsize;
}

There is no standard destroy(), but that easily written:

template<typename In>
void destroy(In b, In e)
{
     for (; b!=e; ++b)    // destroy [b:e)
            b–>~T();
}

13.6.4.3. push_back()

From an exception-safety point of view, push_back() is similar to assignment in that we must take care that the vector remains unchanged if we fail to add a new element:

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template< class T, class A>
void vector<T,A>::push_back(const T& x)
{
     if (capacity()==size())                        // no more free space; relocate:
           reserve(sz?2*sz:8);                      // grow or start with 8
     vb.alloc.construct(&vb.elem[size()],val);      // add val at end
     ++vb.space;                                    // increment size
}

Naturally, the copy constructor used to initialize *space might throw an exception. If that happens, the value of the vector remains unchanged, with space left unincremented. However, reserve() may already have reallocated the existing elements.

This definition of push_back() contains two “magic numbers” (2 and 8). An industrial-strength implementation would not do that, but it would still have values determining the size of the initial allocation (here, 8) and the rate of growth (here, 2, indicating a doubling in size each time the vector would otherwise overflow). As it happens, these are not unreasonable or uncommon values. The assumption is that once we have seen one push_back() for a vector, we will almost certainly see many more. The factor two is larger than the mathematically optimal factor to minimize average memory use (1.618), so as to give better run-time performance for systems where memories are not tiny.

13.6.4.4. Final Thoughts

Note the absence of try-blocks in the vector implementation (except for the one hidden inside uninitialized_copy()). The changes in state were done by carefully ordering the operations so that if an exception is thrown, the vector remains unchanged or at least valid.

The approach of gaining exception safety through ordering and the RAII technique (§13.3) tends to be more elegant and more efficient than explicitly handling errors using try-blocks. More problems with exception safety arise from a programmer ordering code in unfortunate ways than from lack of specific exception-handling code. The basic rule of ordering is not to destroy information before its replacement has been constructed and can be assigned without the possibility of an exception.

Exceptions introduce possibilities for surprises in the form of unexpected control flows. For a piece of code with a simple local control flow, such as the reserve(), safe_assign(), and push_back() examples, the opportunities for surprises are limited. It is relatively simple to look at such code and ask, “Can this line of code throw an exception, and what happens if it does?” For large functions with complicated control structures, such as complicated conditional statements and nested loops, this can be hard. Adding try-blocks increases this local control structure complexity and can therefore be a source of confusion and errors (§13.3). I conjecture that the effectiveness of the ordering approach and the RAII approach compared to more extensive use of try-blocks stems from the simplification of the local control flow. Simple, stylized code is easier to understand, easier to get right, and easier to generate good code for.

This vector implementation is presented as an example of the problems that exceptions can pose and of techniques for addressing those problems. The standard does not require an implementation to be exactly like the one presented here. However, the standard does require the exception-safety guarantees as provided by the example.

13.7. Advice

[1] Develop an error-handling strategy early in a design; §13.1.

[2] Throw an exception to indicate that you cannot perform an assigned task; §13.1.1.

[3] Use exceptions for error handling; §13.1.4.2.

[4] Use purpose-designed user-defined types as exceptions (not built-in types); §13.1.1.

[5] If you for some reason cannot use exceptions, mimic them; §13.1.5.

[6] Use hierarchical error handling; §13.1.6.

[7] Keep the individual parts of error handling simple; §13.1.6.

[8] Don’t try to catch every exception in every function; §13.1.6.

[9] Always provide the basic guarantee; §13.2, §13.6.

[10] Provide the strong guarantee unless there is a reason not to; §13.2, §13.6.

[11] Let a constructor establish an invariant, and throw if it cannot; §13.2.

[12] Release locally owned resources before throwing an exception; §13.2.

[13] Be sure that every resource acquired in a constructor is released when throwing an exception in that constructor; §13.3.

[14] Don’t use exceptions where more local control structures will suffice; §13.1.4.

[15] Use the “Resource Acquisition Is Initialization” technique to manage resources; §13.3.

[16] Minimize the use of try-blocks; §13.3.

[17] Not every program needs to be exception-safe; §13.1.

[18] Use “Resource Acquisition Is Initialization” and exception handlers to maintain invariants; §13.5.2.2.

[19] Prefer proper resource handles to the less structured finally; §13.3.1.

[20] Design your error-handling strategy around invariants; §13.4.

[21] What can be checked at compile time is usually best checked at compile time (using static_assert); §13.4.

[22] Design your error-handling strategy to allow for different levels of checking/enforcement; §13.4.

[23] If your function may not throw, declare it noexcept; §13.5.1.1

[24] Don’t use exception specification; §13.5.1.3.

[25] Catch exceptions that may be part of a hierarchy by reference; §13.5.2.

[26] Don’t assume that every exception is derived from class exception; §13.5.2.2.

[27] Have main() catch and report all exceptions; §13.5.2.2, §13.5.2.4.

[28] Don’t destroy information before you have its replacement ready; §13.6.

[29] Leave operands in valid states before throwing an exception from an assignment; §13.2.

[30] Never let an exception escape from a destructor; §13.2.

[31] Keep ordinary code and error-handling code separate; §13.1.1, §13.1.4.2.

[32] Beware of memory leaks caused by memory allocated by new not being released in case of an exception; §13.3.

[33] Assume that every exception that can be thrown by a function will be thrown; §13.2.

[34] A library shouldn’t unilaterally terminate a program. Instead, throw an exception and let a caller decide; §13.4.

[35] A library shouldn’t produce diagnostic output aimed at an end user. Instead, throw an exception and let a caller decide; §13.1.3.

14. Namespaces

The year is 787!

A.D.?

– Monty Python

• Composition Problems

• Namespaces

Explicit Qualification; using-Declarations; using-Directives; Argument-Dependent Lookup; Namespaces Are Open

• Modularization and Interfaces

Namespaces as Modules; Implementations; Interfaces and Implementations

• Composition Using Namespaces

Convenience vs. Safety; Namespace Aliases; Namespace Composition; Composition and Selection; Namespaces and Overloading; Versioning; Nested Namespaces; Unnamed Namespaces; C Headers

• Advice

14.1. Composition Problems

Any realistic program consists of a number of separate parts. Functions (§2.2.1, Chapter 12) and classes (§3.2, Chapter 16) provide relatively fine-grained separation of concerns, whereas “libraries,” source files, and translation units (§2.4, Chapter 15) provide coarser grain. The logical ideal is modularity, that is, to keep separate things separate and to allow access to a “module” only through a well-specified interface. C++ does not provide a single language feature supporting the notion of a module; there is no module construct. Instead, modularity is expressed through combinations of other language facilities, such as functions, classes, and namespaces, and source code organization.

This chapter and the next deal with the coarse structure of a program and its physical representation as source files. That is, these two chapters are more concerned with programming in the large than with the elegant expression of individual types, algorithms, and data structures.

Consider some of the problems that can arise when people fail to design for modularity. For example, a graphics library may provide different kinds of graphical Shapes and functions to help use them:

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// Graph_lib:

class Shape { /* ... */ };
class Line : public Shape { /* ... */ };
class Poly_line: public Shape { /* ... */ };   // connected sequence of lines
class Text : public Shape { /* ... */ };       // text label

Shape operator+(const Shape&, const Shape&);   // compose

Graph_reader open(const char*);                // open file of Shapes

Now someone comes along with another library, providing facilities for text manipulation:

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// Text_lib:

class Glyph { /* ... */ };
class Word { /* ... */ };        // sequence of Glyphs
class Line { /* ... */ };        // sequence of Words
class Text { /* ... */ };        // sequence of Lines

File* open(const char*);                    // open text file

Word operator+(const Line&, const Line&);   // concatenate

For the moment, let us ignore the specific design issues for graphics and text manipulation and just consider the problems of using Graph_lib and Text_lib together in a program.

Assume (realistically enough) that the facilities of Graph_lib are defined in a header (§2.4.1), Graph_lib.h, and the facilities of Text_lib are defined in another header, Text_lib.h. Now, I can “innocently” #include both and try to use facilities from the two libraries:

#include "Graph_lib.h"
#include "Text_lib.h"
// ...

Just #includeing those headers causes a slurry of error messages: Line, Text, and open() are defined twice in ways that a compiler cannot disambiguate. Trying to use the libraries would give further error messages.

There are many techniques for dealing with such name clashes. For example, some such problems can be addressed by placing all the facilities of a library inside a few classes, by using supposedly uncommon names (e.g., Text_box rather than Text), or by systematically using a prefix for names from a library (e.g., gl_shape and gl_line). Each of these techniques (also known as “workarounds” and “hacks”) works in some cases, but they are not general and can be inconvenient to use. For example, names tend to become long, and the use of many different names inhibits generic programming (§3.4).

14.2. Namespaces

The notion of a namespace is provided to directly represent the notion of a set of facilities that directly belong together, for example, the code of a library. The members of a namespace are in the same scope and can refer to each other without special notation, whereas access from outside the namespace requires explicit notation. In particular, we can avoid name clashes by separating sets of declarations (e.g., library interfaces) into namespaces. For example, we might call the graph library Graph_lib:

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namespace Graph_lib {
    class Shape { /* ... */ };
    class Line : public Shape { /* ... */ };
    class Poly_line: public Shape { /* ... */ };    // connected sequence of lines
    class Text : public Shape { /* ... */ };        // text label

    Shape operator+(const Shape&, const Shape&);    // compose

    Graph_reader open(const char*);                 // open file of Shapes
}

Similarly, the obvious name for our text library is Text_lib:

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namespace Text_lib {
    class Glyph { /* ... */ };
    class Word { /* ... */ };        // sequence of Glyphs
    class Line { /* ... */ };        // sequence of Words
    class Text { /* ... */ };        // sequence of Lines

    File* open(const char*);                    // open text file

    Word operator+(const Line&, const Line&);   // concatenate
}

As long as we manage to pick distinct namespace names, such as Graph_lib and Text_lib (§14.4.2), we can now compile the two sets of declarations together without name clashes.

A namespace should express some logical structure: the declarations within a namespace should together provide facilities that unite them in the eyes of their users and reflect a common set of design decisions. They should be seen as a logical unit, for example, “the graphics library” or “the text manipulation library,” similar to the way we consider the members of a class. In fact, the entities declared in a namespace are referred to as the members of the namespace.

A namespace is a (named) scope. You can access members defined earlier in a namespace from later declarations, but you cannot (without special effort) refer to members from outside the namespace. For example:

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class Glyph { /* ... */ };
class Line { /* ... */ };

namespace Text_lib {
    class Glyph { /* ... */ };
    class Word { /* ... */ };    // sequence of Glyphs

    class Line { /* ... */ };// sequence of Words
    class Text { /* ... */ };// sequence of Lines

    File* open(const char*);              // open text file

    Word operator+(const Line&, const Line&);   // concatenate
}

Glyph glyph(Line& ln, int i);   // ln[i]

Here, the Word and Line in the declaration of Text_lib::operator+() refer to Text_lib::Word and Text_lib::Line. That local name lookup is not affected by the global Line. Conversely, the Glyph and Line in the declaration of the global glyph() refer to the global ::Glyph and ::Line. That (nonlocal) lookup is not affected by Text_lib’s Glyph and Line.

To refer to members of a namespace, we can use its fully qualified name. For example, if we want a glyph() that uses definitions from Text_lib, we can write:

Text_lib::Glyph glyph(Text_lib::Line& ln, int i);    // ln[i]

Other ways of referring to members from outside their namespace are using-declarations (§14.2.2), using-directives (§14.2.3), and argument-dependent lookup (§14.2.4).

14.2.1. Explicit Qualification

A member can be declared within a namespace definition and defined later using the namespace-name :: member-name notation.

Members of a namespace must be introduced using this notation:

namespace namespace–name {
    // declaration and definitions
}

For example:

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namespace Parser {
    double expr(bool);         // declaration
    double term(bool);
    double prim(bool);
}

double val = Parser::expr();   // use

double Parser::expr(bool b)    // definition
{
    // ...
}

We cannot declare a new member of a namespace outside a namespace definition using the qualifier syntax (§iso.7.3.1.2). The idea is to catch errors such as misspellings and type mismatches, and also to make it reasonably easy to find all names in a namespace declaration. For example:

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void Parser::logical(bool);   // error: no logical() in Parser
double Parser::trem(bool);    // error: no trem() in Parser (misspelling)
double Parser::prim(int);     // error: Parser::prim() takes a bool argument (wrong type)

A namespace is a scope. The usual scope rules hold for namespaces. Thus, “namespace” is a very fundamental and relatively simple concept. The larger a program is, the more useful namespaces are to express logical separations of its parts. The global scope is a namespace and can be explicitly referred to using ::. For example:

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int f();       // global function

int g()
{
     int f;    // local variable; hides the global function
     f();      // error: we can't call an int
     ::f();    // OK: call the global function
}

Classes are namespaces (§16.2).

14.2.2. using-Declarations

When a name is frequently used outside its namespace, it can be a bother to repeatedly qualify it with its namespace name. Consider:

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#include<string>
#include<vector>
#include<sstream>

std::vector<std::string> split(const std::string& s)
    // split s into its whitespace-separated substrings
{
    std::vector<std::string> res;
    std::istringstream iss(s);
    for (std::string buf; iss>>buf;)
          res.push_back(buf);
    return res;
}

The repeated qualification std is tedious and distracting. In particular, we repeat std::string four times in this small example. To alleviate that we can use a using-declaration to say that in this code string means std::string:

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using std::string;   // use "string" to mean "std::string"

std::vector<string> split(const string& s)
     // split s into its whitespace-separated substrings
{
    std::vector<string> res;
    std::istringstream iss(s);
    for (string buf; iss>>buf;)
          res.push_back(buf);
    return res;
}

A using-declaration introduces a synonym into a scope. It is usually a good idea to keep local synonyms as local as possible to avoid confusion.

When used for an overloaded name, a using-declaration applies to all the overloaded versions. For example:

namespace N {
    void f(int);
    void f(string);
};

void g()
{
     using N::f;
     f(789);           // N::f(int)
     f("Bruce");       // N::f(string)
}

For the use of using-declarations within class hierarchies, see §20.3.5.

14.2.3. using-Directives

In the split() example (§14.2.2), we still had three uses of std:: left after introducing a synonym for std::string. Often, we like to use every name from a namespace without qualification. That can be achieved by providing a using-declaration for each name from the namespace, but that’s tedious and requires extra work each time a new name is added to or removed from the namespace. Alternatively, we can use a using-directive to request that every name from a namespace be accessible in our scope without qualification. For example:

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using namespace std;   // make every name from std accessible

vector<string> split(const string& s)
    // split s into its whitespace-separated substrings
{
    vector<string> res;
    istringstream iss(s);
    for (string buf; iss>>buf;)
          res.push_back(buf);
    return res;
}

A using-directive makes names from a namespace available almost as if they had been declared outside their namespace (see also §14.4). Using a using-directive to make names from a frequently used and well-known library available without qualification is a popular technique for simplifying code. This is the technique used to access standard-library facilities throughout this book. The standard-library facilities are defined in namespace std.

Within a function, a using-directive can be safely used as a notational convenience, but care should be taken with global using-directives because overuse can lead to exactly the name clashes that namespaces were introduced to avoid. For example:

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namespace Graph_lib {
    class Shape { /* ... */ };
    class Line : Shape { /* ... */ };
    class Poly_line: Shape { /* ... */ };   // connected sequence of lines
    class Text : Shape { /* ... */ };       // text label

    Shape operator+(const Shape&, const Shape&);   // compose

    Graph_reader open(const char*);   // open file of Shapes

}

namespace Text_lib {
    class Glyph { /* ... */ };
    class Word { /* ... */ };  // sequence of Glyphs
    class Line { /* ... */ };  // sequence of Words
    class Text { /* ... */ };  // sequence of Lines

    File* open(const char*);   // open text file

    Word operator+(const Line&, const Line&);  // concatenate

}

using namespace Graph_lib;
using namespace Text_lib;

Glyph gl;              // Text_lib::Glyph
vector<Shape*>vs;      // Graph_lib::Shape

So far, so good. In particular, we can use names that do not clash, such as Glyph and Shape. However, name clashes now occur as soon as we use one of the names that clash – exactly as if we had not used namespaces. For example:

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Text txt;                                  // error: ambiguous
File* fp = open("my_precious_data");       // error: ambiguous

Consequently, we must be careful with using-directives in the global scope. In particular, don’t place a using-directive in the global scope in a header file except in very specialized circumstances (e.g., to aid transition) because you never know where a header might be #included.

14.2.4. Argument-Dependent Lookup

A function taking an argument of user-defined type X is more often than not defined in the same namespace as X. Consequently, if a function isn’t found in the context of its use, we look in the namespaces of its arguments. For example:

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namespace Chrono {
    class Date { /* ... */ };

    bool operator==(const Date&, const std::string&);

    std::string format(const Date&);   // make string representation
    // ...
}

void f(Chrono::Date d, int i)
{
    std::string s = format(d);     // Chrono::format()
    std::string t = format(i);     // error: no format() in scope
}

This lookup rule (called argument-dependent lookup or simply ADL) saves the programmer a lot of typing compared to using explicit qualification, yet it doesn’t pollute the namespace the way a using-directive (§14.2.3) can. It is especially useful for operator operands (§18.2.5) and template arguments (§26.3.5), where explicit qualification can be quite cumbersome.

Note that the namespace itself needs to be in scope and the function must be declared before it can be found and used.

Naturally, a function can take arguments from more than one namespace. For example:

void f(Chrono::Date d, std::string s)
{
     if (d == s) {
           // ...
     }
     else if (d == "August 4, 1914") {
           // ...
     }
}

In such cases, we look for the function in the scope of the call (as ever) and in the namespaces of every argument (including each argument’s class and base classes) and do the usual overload resolution (§12.3) of all functions we find. In particular, for the call d==s, we look for operator== in the scope surrounding f(), in the std namespace (where == is defined for string), and in the Chrono namespace. There is a std::operator==(), but it doesn’t take a Date argument, so we use Chrono::operator==(), which does. See also §18.2.5.

When a class member invokes a named function, other members of the same class and its base classes are preferred over functions potentially found based on the argument types (operators follow a different rule; §18.2.1, §18.2.5). For example:

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namespace N {
    struct S { int i };
    void f(S);
    void g(S);
    void h(int);
}

struct Base {
    void f(N::S);
};

struct D : Base {
    void mf();

    void g(N::S x)
    {
         f(x);      // call Base::f()
         mf(x);     // call D::mf()
         h(1);      // error: no h(int) available
    }
};

In the standard, the rules for argument-dependent lookup are phrased in terms of associated namespaces (§iso.3.4.2). Basically:

• If an argument is a class member, the associated namespaces are the class itself (including its base classes) and the class’s enclosing namespaces.

• If an argument is a member of a namespace, the associated namespaces are the enclosing namespaces.

• If an argument is a built-in type, there are no associated namespaces.

Argument-dependent lookup can save a lot of tedious and distracting typing, but occasionally it can give surprising results. For example, the search for a declaration of a function f() does not have a preference for functions in a namespace in which f() is called (the way it does for functions in a class in which f() is called):

namespace N {
    template<class T>
        void f(T, int);  // N::f()
    class X { };
}

namespace N2 {
    N::X x;

    void f(N::X, unsigned);

    void g()
    {
         f(x,1);    // calls N::f(X,int)
    }
}

It may seem obvious to choose N2::f(), but that is not done. Overload resolution is applied and the best match is found: N::f() is the best match for f(x,1) because 1 is an int rather than an unsigned. Conversely, examples have been seen where a function in the caller’s namespace is chosen but the programmer expected a better function from a known namespace to be used (e.g., a standard-library function from std). This can be most confusing. See also §26.3.6.

14.2.5. Namespaces Are Open

A namespace is open; that is, you can add names to it from several separate namespace declarations. For example:

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namespace A {
    int f();    // now A has member f()
}
namespace A {
    int g();    // now A has two members, f() and g()
}

That way, the members of a namespace need not be placed contiguously in a single file. This can be important when converting older programs to use namespaces. For example, consider a header file written without the use of namespaces:

// my header:

      void mf();     // my function
      void yf();     // your function
      int mg();      // my function
      // ...

Here, we have (unwisely) just added the declarations needed without concerns of modularity. This can be rewritten without reordering the declarations:

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// my header:

      namespace Mine {
          void mf();   // my function
          // ...
      }

      void yf();       // your function (not yet put into a namespace)

      namespace Mine {
          int mg();    // my function
          // ...
      }

When writing new code, I prefer to use many smaller namespaces (see §14.4) rather than putting really major pieces of code into a single namespace. However, that is often impractical when converting major pieces of software to use namespaces.

Another reason to define the members of a namespace in several separate namespace declarations is that sometimes we want to distinguish parts of a namespace used as an interface from parts used to support easy implementation; §14.3 provides an example.

A namespace alias (§14.4.2) cannot be used to re-open a namespace.

14.3. Modularization and Interfaces

Any realistic program consists of a number of separate parts. For example, even the simple “Hello, world!” program involves at least two parts: the user code requests Hello, world! to be printed, and the I/O system does the printing.

Consider the desk calculator example from §10.2. It can be viewed as composed of five parts:

[1] The parser, doing syntax analysis: expr(), term(), and prim()

[2] The lexer, composing tokens out of characters: Kind, Token, Token_stream, and ts

[3] The symbol table, holding (string,value) pairs: table

[4] The driver: main() and calculate()

[5] The error handler: error() and number_of_errors

This can be represented graphically:

where an arrow means “using.” To simplify the picture, I have not represented the fact that every part relies on error handling. In fact, the calculator was conceived as three parts, with the driver and error handler added for completeness.

When one module uses another, it doesn’t need to know everything about the module used. Ideally, most of the details of a module are unknown to its users. Consequently, we make a distinction between a module and its interface. For example, the parser directly relies on the lexer’s interface (only), rather than on the complete lexer. The lexer simply implements the services advertised in its interface. This can be presented graphically like this:

A dashed line means “implements.” I consider this to be the real structure of the program, and our job as programmers is to represent this faithfully in code. That done, the code will be simple, efficient, comprehensible, maintainable, etc., because it will directly reflect our fundamental design.

The following subsections show how the logical structure of the desk calculator program can be made clear, and §15.3 shows how the program source text can be physically organized to take advantage of it. The calculator is a tiny program, so in “real life” I wouldn’t bother using namespaces and separate compilation (§2.4.1, §15.1) to the extent done here. Making the structure of the calculator explicit is simply an illustration of techniques useful for larger programs without drowning in code. In real programs, each “module” represented by a separate namespace will often have hundreds of functions, classes, templates, etc.

Error handling permeates the structure of a program. When breaking up a program into modules or (conversely) when composing a program out of modules, we must take care to minimize dependencies between modules caused by error handling. C++ provides exceptions to decouple the detection and reporting of errors from the handling of errors (§2.4.3.1, Chapter 13).

There are many more notions of modularity than the ones discussed in this chapter and the next. For example, we might use concurrently executing and communicating tasks (§5.3, Chapter 41) or processes to represent important aspects of modularity. Similarly, the use of separate address spaces and the communication of information between address spaces are important topics not discussed here. I consider these notions of modularity largely independent and orthogonal. Interestingly, in each case, separating a system into modules is easy. The hard problem is to provide safe, convenient, and efficient communication across module boundaries.

14.3.1. Namespaces as Modules

A namespace is a mechanism for expressing logical grouping. That is, if some declarations logically belong together according to some criteria, they can be put in a common namespace to express that fact. So we can use namespaces to express the logical structure of our calculator. For example, the declarations of the parser from the desk calculator (§10.2.1) may be placed in a namespace Parser:

namespace Parser {
    double expr(bool);
    double prim(bool get) { /* ... */ }
    double term(bool get) { /* ... */ }
    double expr(bool get) { /* ... */ }
}

The function expr() must be declared first and then later defined to break the dependency loop described in §10.2.1.

The input part of the desk calculator could also be placed in its own namespace:

namespace Lexer {
    enum class Kind : char { /* ... */ };
    class Token { /* ... */ };
    class Token_stream { /* ... */ };

    Token_stream ts;
}

The symbol table is extremely simple:

namespace Table {
    map<string,double> table;
}

The driver cannot be completely put into a namespace because the language rules require main() to be a global function:

namespace Driver {
    void calculate() { /* ... */ }
}

int main() { /* ... */ }

The error handler is also trivial:

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namespace Error {
    int no_of_errors;
    double error(const string& s) { /* ... */ }
}

This use of namespaces makes explicit what the lexer and the parser provide to a user. Had I included the source code for the functions, this structure would have been obscured. If function bodies are included in the declaration of a realistically sized namespace, you typically have to wade through screenfuls of information to find what services are offered, that is, to find the interface.

An alternative to relying on separately specified interfaces is to provide a tool that extracts an interface from a module that includes implementation details. I don’t consider that a good solution. Specifying interfaces is a fundamental design activity, a module can provide different interfaces to different users, and often an interface is designed long before the implementation details are made concrete.

Here is a version of the Parser with the interface separated from the implementation:

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namespace Parser {
    double prim(bool);
    double term(bool);
    double expr(bool);
}

double Parser::prim(bool get) { /* ... */ }
double Parser::term(bool get) { /* ... */ }
double Parser::expr(bool get) { /* ... */ }

Note that as a result of separating the implementation from the interface, each function now has exactly one declaration and one definition. Users will see only the interface containing declarations. The implementation – in this case, the function bodies – will be placed “somewhere else” where a user need not look.

Ideally, every entity in a program belongs to some recognizable logical unit (“module”). Therefore, every declaration in a nontrivial program should ideally be in some namespace named to indicate its logical role in the program. The exception is main(), which must be global in order for the compiler to recognize it as special (§2.2.1, §15.4).

14.3.2. Implementations

What will the code look like once it has been modularized? That depends on how we decide to access code in other namespaces. We can always access names from “our own” namespace exactly as we did before we introduced namespaces. However, for names in other namespaces, we have to choose among explicit qualification, using-declarations, and using-directives.

Parser::prim() provides a good test case for the use of namespaces in an implementation because it uses each of the other namespaces (except Driver). If we use explicit qualification, we get:

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double Parser::prim(bool get)      // handle primaries
{
    if (get) Lexer::ts.get();

    switch (Lexer::ts.current().kind) {
    case Lexer::Kind::number:            // floating-point constant
    {    double v = Lexer::ts.current().number_value;
         Lexer::ts.get();
         return v;
    }
    case Lexer::Kind::name:
    {    double& v = Table::table[Lexer::ts.current().string_value];
         if (Lexer::ts.get().kind == Lexer::Kind::assign) v = expr(true); // '=' seen: assignment
         return v;
    }
    case Lexer::Kind::minus:      // unary minus
         return -prim(true);
    case Lexer::Kind::lp:
    {    double e = expr(true);
         if (Lexer::ts.current().kind != Lexer::Kind::rp) return Error::error(" ')' expected");
         Lexer::ts.get();     // eat ')'
         return e;
    }
    default:
        return Error::error("primary expected");
    }
}

I count 14 occurrences of Lexer::, and (despite theories to the contrary) I don’t think the more explicit use of modularity has improved readability. I didn’t use Parser:: because that would be redundant within namespace Parser.

If we use using-declarations, we get:

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using Lexer::ts;         // saves eight occurrences of "Lexer::"
using Lexer::Kind;       // saves six occurrences of "Lexer::"
using Error::error;      // saves two occurrences of "Error::"
using Table::table;      // saves one occurrence of "Table::"

double prim(bool get)    // handle primaries
{
    if (get) ts.get();

    switch (ts.current().kind) {
    case Kind::number:        // floating-point constant
    {    double v = ts.current().number_value;
         ts.get();
         return v;
    }
    case Kind::name:
    {    double& v = table[ts.current().string_value];
         if (ts.get().kind == Kind::assign) v = expr(true);    // '=' seen: assignment
         return v;
    }
    case Kind::minus:        // unary minus
         return -prim(true);
    case Kind::lp:
    {    double e = expr(true);
         if (ts.current().kind != Kind::rp) return error("')' expected");
         ts.get();         // eat ')'
         return e;
    }
    default:
        return error("primary expected");
    }
}

My guess is that the using-declarations for Lexer:: were worth it, but that the value of the others was marginal.

If we use using-directives, we get:

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using namespace Lexer;     // saves fourteen occurrences of "Lexer::"
using namespace Error;     // saves two occurrences of "Error::"
using namespace Table;     // saves one occurrence of "Table::"

double prim(bool get)            // handle primaries
{
    // as before
}

The using-declarations for Error and Table don’t buy much notationally, and it can be argued that they obscure the origins of the formerly qualified names.

So, the tradeoff among explicit qualification, using-declarations, and using-directives must be made on a case-by-case basis. The rules of thumb are:

[1] If some qualification is really common for several names, use a using-directive for that namespace.

[2] If some qualification is common for a particular name from a namespace, use a using-declaration for that name.

[3] If a qualification for a name is uncommon, use explicit qualification to make it clear from where the name comes.

[4] Don’t use explicit qualification for names in the same namespace as the user.

14.3.3. Interfaces and Implementations

It should be clear that the namespace definition we used for Parser is not the ideal interface for Parser to present to its users. Instead, that Parser declares the set of declarations that is needed to write the individual parser functions conveniently. The Parser’s interface to its users should be far simpler:

namespace Parser {// user interface
    double expr(bool);
}

We see the namespace Parser used to provide two things:

[1] The common environment for the functions implementing the parser

[2] The external interface offered by the parser to its users

Thus, the driver code, main(), should see only the user interface.

The functions implementing the parser should see whichever interface we decided on as the best for expressing those functions’ shared environment. That is:

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namespace Parser {         // implementer interface
    double prim(bool);
    double term(bool);
    double expr(bool);

    using namespace Lexer;       // use all facilities offered by lexer
    using Error::error;
    using Table::table;
}

or graphically:

The arrows represent “relies on the interface provided by” relations.

We could give the user’s interface and the implementer’s interface different names, but (because namespaces are open; §14.2.5) we don’t have to. The lack of separate names need not lead to confusion because the physical layout of the program (see §15.3.2) naturally provides separate (file) names. Had we decided to use a separate implementation namespace, the design would not have looked different to users:

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namespace Parser {// user interface
    double expr(bool);
}

namespace Parser_impl {               // implementer interface
    using namespace Parser;

    double prim(bool);
    double term(bool);
    double expr(bool);

    using namespace Lexer; // use all facilities offered by Lexer
    using Error::error;
    using Table::table;
}

or graphically:

For larger programs, I lean toward introducing _impl interfaces.

The interface offered to implementers is larger than the interface offered to users. Had this interface been for a realistically sized module in a real system, it would change more often than the interface seen by users. It is important that the users of a module (in this case, Driver using Parser) be insulated from such changes.

14.4. Composition Using Namespaces

In larger programs, we tend to use many namespaces. This section examines technical aspects of composing code out of namespaces.

14.4.1. Convenience vs. Safety

A using-declaration adds a name to a local scope. A using-directive does not; it simply renders names accessible in the scope in which they were declared. For example:

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namespace X {
    int i, j, k;
}

int k;

void f1()
{
     int i = 0;
     using namespace X;     // make names from X accessible
     i++;                   // local i
     j++;                   // X::j
     k++;                   // error: X's k or the global k?
     ::k++;                 // the global k
     X::k++;                // X's k
}

void f2()
{
     int i = 0;
     using X::i;    // error: i declared twice in f2()
     using X::j;
     using X::k;    // hides global k

     i++;
     j++;           // X::j
     k++;           // X::k
}

A locally declared name (declared either by an ordinary declaration or by a using-declaration) hides nonlocal declarations of the same name, and any illegal overloading of the name is detected at the point of declaration.

Note the ambiguity error for k++ in f1(). Global names are not given preference over names from namespaces made accessible in the global scope. This provides significant protection against accidental name clashes, and – importantly – ensures that there are no advantages to be gained from polluting the global namespace.

When libraries declaring many names are made accessible through using-directives, it is a significant advantage that clashes of unused names are not considered errors.

14.4.2. Namespace Aliases

If users give their namespaces short names, the names of different namespaces will clash:

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namespace A {// short name, will clash (eventually)
     // ...
}

A::String s1 = "Grieg";
A::String s2 = "Nielsen";

However, long namespace names can be impractical in real code:

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namespace American_Telephone_and_Telegraph {     // too long
    // ...
}

American_Telephone_and_Telegraph::String s3 = "Grieg";
American_Telephone_and_Telegraph::String s4 = "Nielsen";

This dilemma can be resolved by providing a short alias for a longer namespace name:

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// use namespace alias to shorten names:

namespace ATT = American_Telephone_and_Telegraph;

ATT::String s3 = "Grieg";
ATT::String s4 = "Nielsen";

Namespace aliases also allow a user to refer to “the library” and have a single declaration defining what library that really is. For example:

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namespace Lib = Foundation_library_v2r11;

// ...

Lib::set s;
Lib::String s5 = "Sibelius";

This can immensely simplify the task of replacing one version of a library with another. By using Lib rather than Foundation_library_v2r11 directly, you can update to version “v3r02” by changing the initialization of the alias Lib and recompiling. The recompile will catch source-level incompatibilities. On the other hand, overuse of aliases (of any kind) can lead to confusion.

14.4.3. Namespace Composition

Often, we want to compose an interface out of existing interfaces. For example:

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namespace His_string {
    class String { /* ... */ };
    String operator+(const String&, const String&);
    String operator+(const String&, const char*);
    void fill(char);
    // ...
}

namespace Her_vector {
    template<class T>
        class Vector { /* ... */ };
    // ...
}

namespace My_lib {
    using namespace His_string;
    using namespace Her_vector;
    void my_fct(String&);
}

Given this, we can now write the program in terms of My_lib:

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void f()
{
     My_lib::String s = "Byron";    // finds My_lib::His_string::String
     // ...
}

using namespace My_lib;

void g(Vector<String>& vs)
{
     // ...
     my_fct(vs[5]);
     // ...
}

If an explicitly qualified name (such as My_lib::String) isn’t declared in the namespace mentioned, the compiler looks in namespaces mentioned in using-directives (such as His_string).

Only if we need to define something do we need to know the real namespace of an entity:

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void My_lib::fill(char c)      // error: no fill() declared in My_lib
{
     // ...
}

void His_string::fill(char c)  // OK: fill() declared in His_string
{
     // ...
}

void My_lib::my_fct(String& v)// OK: String is My_lib::String, meaning His_string::String
{
     // ...
}

Ideally, a namespace should

[1] express a logically coherent set of features,

[2] not give users access to unrelated features, and

[3] not impose a significant notational burden on users.

Together with the #include mechanism (§15.2.2), the composition techniques presented here and in the following subsections provide strong support for this.

14.4.4. Composition and Selection

Combining composition (by using-directives) with selection (by using-declarations) yields the flexibility needed for most real-world examples. With these mechanisms, we can provide access to a variety of facilities in such a way that we resolve name clashes and ambiguities arising from their composition. For example:

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namespace His_lib {
    class String { /* ... */ };
    template<class T>
        class Vector { /* ... */ };
    // ...
}

namespace Her_lib {
    template<class T>
        class Vector { /* ... */ };
    class String { /* ... */ };
    // ...
}

namespace My_lib {
    using namespace His_lib;        // everything from His_lib
    using namespace Her_lib;        // everything from Her_lib

    using His_lib::String;          // resolve potential clash in favor of His_lib
    using Her_lib::Vector;          // resolve potential clash in favor of Her_lib

    template<class T>
         class List { /* ... */ };  // additional stuff
    // ...
}

When looking into a namespace, names explicitly declared there (including names declared by using-declarations) take priority over names made accessible in another scope by a using-directive (see also §14.4.1). Consequently, a user of My_lib will see the name clashes for String and Vector resolved in favor of His_lib::String and Her_lib::Vector. Also, My_lib::List will be used by default independently of whether His_lib or Her_lib is providing a List.

Usually, I prefer to leave a name unchanged when including it into a new namespace. Then, I don’t have to remember two different names for the same entity. However, sometimes a new name is needed or simply nice to have. For example:

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namespace Lib2 {
    using namespace His_lib;    // everything from His_lib
    using namespace Her_lib;    // everything from Her_lib

    using His_lib::String;      // resolve potential clash in favor of His_lib
    using Her_lib::Vector;      // resolve potential clash in favor of Her_lib

    using Her_string = Her_lib::String;                // rename
    template<class T>
        using His_vec = His_lib::Vector<T>;      // rename

    template<class T>
         class List { /* ... */ };     // additional stuff
    // ...
}

There is no general language mechanism for renaming, but for types and templates, we can introduce aliases with using (§3.4.5, §6.5).

14.4.5. Namespaces and Overloading

Function overloading (§12.3) works across namespaces. This is essential to allow us to migrate existing libraries to use namespaces with minimal source code changes. For example:

// old A.h:
       void f(int);
       // ...

// old B.h:
       void f(char);
       // ...

// old user.c:
       #include "A.h"
       #include "B.h"

       void g()
       {
            f('a'); // calls the f() from B.h
       }

This program can be upgraded to a version using namespaces without changing the actual code:

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// new A.h:

      namespace A {
          void f(int);
          // ...
      }

// new B.h:

      namespace B {
          void f(char);
          // ...
      }

// new user.c:

      #include "A.h"
      #include "B.h"

      using namespace A;
      using namespace B;

      void g()
      {
           f('a');     // calls the f() from B.h
      }

Had we wanted to keep user.c completely unchanged, we would have placed the using-directives in the header files. However, it is usually best to avoid using-directives in header files, because putting them there greatly increases the chances of name clashes.

This overloading rule also provides a mechanism for extending libraries. For example, people often wonder why they have to explicitly mention a sequence to manipulate a container using a standard-library algorithm. For example:

sort(v.begin(),v.end());

Why not write:

sort(v);

The reason is the need for generality (§32.2), but manipulating a container is by far the most common case. We can accommodate that case like this:

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#include<algorithm>

namespace Estd {
    using namespace std;
    template<class C>
        void sort(C& c) { std::sort(c.begin(),c.end()); }
    template<class C, class P>
        void sort(C& c, P p) { std::sort(c.begin(),c.end(),p); }
}

Estd (my “extended std”) provides the frequently wanted container versions of sort(). Those are of course implemented using std::sort() from <algorithm>. We can use it like this:

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using namespace Estd;

template<class T>
void print(const vector<T>& v)
{
     for (auto& x : v)
           cout << v << ' ';
     cout << '\n';
}

void f()
{
     std::vector<int> v {7, 3, 9, 4, 0, 1};

     sort(v);
     print(v);
     sort(v,[](int x, int y) { return x>y; });
     print(v);
     sort(v.begin(),v.end());
     print(v);
     sort(v.begin(),v.end(),[](int x, int y) { return x>y; });
     print(v);
}

The namespace lookup rules and the overloading rules for templates ensure that we find and invoke the correct variants of sort() and get the expected output:

0 1 3 4 7 9
9 7 4 3 1 0
0 1 3 4 7 9
9 7 4 3 1 0

If we removed the using namespace std; from Estd, this example would still work because std’s sort()s would be found by argument-dependent lookup (§14.2.4). However, we would then not find the standard sort()s for our own containers defined outside std.

14.4.6. Versioning

The toughest test for many kinds of interfaces is to cope with a sequence of new releases (versions). Consider a widely used interface, say, an ISO C++ standard header. After some time, a new version is defined, say, the C++11 version of the C++98 header. Functions may have been added, classes renamed, proprietary extensions (that should never have been there) removed, types changed, templates modified. To make life “interesting” for the implementer, hundreds of millions of lines of code are “out there” using the old header, and the implementer of the new version cannot ever see or modify them. Needless to say, breaking such code will cause howls of outrage, as will the absence of a new and better version. The namespace facilities described so far can be used to handle this problem with very minor exceptions, but when large amounts of code are involved, “very minor” still means a lot of code. Consequently, there is a way of selecting between two versions that simply and obviously guarantees that a user sees exactly one particular version. This is called an inline namespace:

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namespace Popular {

    inline namespace V3_2 { // V3_2 provides the default meaning of Popular
          double f(double);
          int f(int);
          template<class T>
              class C { /* ... */ };
    }
    namespace V3_0 {
        // ...
    }
    namespace V2_4_2 {
        double f(double);
        template<class T>
             class C { /* ... */ };
    }
}

Here, Popular contains three subnamespaces, each defining a version. The inline specifies that V3_2 is the default meaning of Popular. So we can write:

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using namespace Popular;

void f()
{
     f(1);           // Popular::V3_2::f(int)
     V3_0::f(1);           // Popular::V3_0::f(double)
     V2_4_2::f(1);   // Popular::V2_4_2::f(double)
}

template<class T>
Popular::C<T*> { /* ... */ };

This inline namespace solution is intrusive; that is, to change which version (subnamespace) is the default requires modification of the header source code. Also, naively using this way of handling versioning would involve a lot of replication (of common code in the different versions). However, that replication can be minimized using #include tricks. For example:

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// file V3_common:
        // ... lots of declarations ...

// file V3_2:

        namespace V3_2 { // V3_2 provides the default meaning of Popular
            double f(double);
            int f(int);
            template<class T>
                class C { /* ... */ };
            #include "V3_common"
        }

// file V3_0.h:

        namespace V3_0 {
            #include "V3_common"
        }

// file Popular.h:

        namespace Popular {
            inline
            #include "V3_2.h"
            #include "V3_0.h"
            #include "V2_4_2.h"
        }

I do not recommend such intricate use of header files unless it is really necessary. The example above repeatedly violates the rules against including into a nonlocal scope and against having a syntactic construct span file boundaries (the use of inline); see §15.2.2. Sadly, I have seen worse.

In most cases, we can achieve versioning by less intrusive means. The only example I can think of that is completely impossible to do by other means is the specialization of a template explicitly using the namespace name (e.g., Popular::C<T*>). However, in many important cases “in most cases” isn’t good enough. Also, a solution based on a combination of other techniques is less obviously completely right.

14.4.7. Nested Namespaces

One obvious use of namespaces is to wrap a complete set of declarations and definitions in a separate namespace:

namespace X {
    // ... all my declarations ...
}

The list of declarations will, in general, contain namespaces. Thus, nested namespaces are allowed. This is allowed for practical reasons, as well as for the simple reason that constructs ought to nest unless there is a strong reason for them not to. For example:

void h();

namespace X {
    void g();
    // ...
    namespace Y {
        void f();
        void ff();
        // ...
    }
}

The usual scope and qualification rules apply:

void X::Y::ff()
{
     f(); g(); h();
}

void X::g()
{
     f();      // error: no f() in X
     Y::f();   // OK
}

void h()
{
     f();           // error: no global f()
     Y::f();        // error: no global Y
     X::f();        // error: no f() in X
     X::Y::f();     // OK
}

For examples of nested namespaces in the standard library, see chrono (§35.2) and rel_ops (§35.5.3).

14.4.8. Unnamed Namespaces

It is sometimes useful to wrap a set of declarations in a namespace simply to protect against the possibility of name clashes. That is, the aim is to preserve locality of code rather than to present an interface to users. For example:

#include "header.h"
namespace Mine {
    int a;
    void f() { /* ... */ }
    int g() { /* ... */ }
}

Since we don’t want the name Mine to be known outside a local context, it simply becomes a bother to invent a redundant global name that might accidentally clash with someone else’s names. In that case, we can simply leave the namespace without a name:

#include "header.h"
namespace {
    int a;
    void f() { /* ... */ }
    int g() { /* ... */ }
}

Clearly, there has to be some way of accessing members of an unnamed namespace from outside the unnamed namespace. Consequently, an unnamed namespace has an implied using-directive. The previous declaration is equivalent to

namespace $$$ {
    int a;
    void f() { /* ... */ }
    int g() { /* ... */ }
}
using namespace $$$;

where $$$ is some name unique to the scope in which the namespace is defined. In particular, unnamed namespaces in different translation units are different. As desired, there is no way of naming a member of an unnamed namespace from another translation unit.

14.4.9. C Headers

Consider the canonical first C program:

#include <stdio.h>

int main()
{
     printf("Hello, world!\n");
}

Breaking this program wouldn’t be a good idea. Making standard libraries special cases isn’t a good idea either. Consequently, the language rules for namespaces are designed to make it relatively easy to take a program written without namespaces and turn it into a more explicitly structured one using namespaces. In fact, the calculator program (§10.2) is an example of this.

One way to provide the standard C I/O facilities in a namespace would be to place the declarations from the C header stdio.h in a namespace std:

// cstdio:

       namespace std {
           int printf(const char* ... );
           // ...
       }

Given this <cstdio>, we could provide backward compatibility by adding a using-directive:

// stdio.h:

      #include<cstdio>
      using namespace std;

This <stdio.h> makes the Hello, world! program compile. Unfortunately, the using-directive makes every name from namespace std accessible in the global namespace. For example:

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#include<vector>    // carefully avoids polluting the global namespace
vector v1;          // error: no "vector" in global scope
#include<stdio.h>   // contains a "using namespace std;"
vector v2;          // oops: this now works

So the standard requires that <stdio.h> place only names from <cstdio> in the global scope. This can be done by providing a using-declaration for each declaration in <cstdio>:

// stdio.h:

       #include<cstdio>
       using std::printf;
       // ...

Another advantage is that the using-declaration for printf() prevents a user from (accidentally or deliberately) defining a nonstandard printf() in the global scope. I consider nonlocal using-directives primarily a transition tool. I also use them for essential foundation libraries, such as the ISO C++ standard library (std). Most code referring to names from other namespaces can be expressed more clearly with explicit qualification and using-declarations.

The relationship between namespaces and linkage is described in §15.2.5.

14.5. Advice

[1] Use namespaces to express logical structure; §14.3.1.

[2] Place every nonlocal name, except main(), in some namespace; §14.3.1.

[3] Design a namespace so that you can conveniently use it without accidentally gaining access to unrelated namespaces; §14.3.3.

[4] Avoid very short names for namespaces; §14.4.2.

[5] If necessary, use namespace aliases to abbreviate long namespace names; §14.4.2.

[6] Avoid placing heavy notational burdens on users of your namespaces; §14.2.2, §14.2.3.

[7] Use separate namespaces for interfaces and implementations; §14.3.3.

[8] Use the Namespace::member notation when defining namespace members; §14.4.

[9] Use inline namespaces to support versioning; §14.4.6.

[10] Use using-directives for transition, for foundational libraries (such as std), or within a local scope; §14.4.9.

[11] Don’t put a using-directive in a header file; §14.2.3.

15. Source Files and Programs

Form must follow function.

– Le Corbusier

• Separate Compilation

• Linkage

File-Local Names; Header Files; The One-Definition Rule; Standard-Library Headers; Linkage to Non-C++ Code; Linkage and Pointers to Functions

• Using Header Files

Single-Header Organization; Multiple-Header Organization; Include Guards

• Programs

Initialization of Nonlocal Variables; Initialization and Concurrency; Program Termination

• Advice

15.1. Separate Compilation

Any realistic program consists of many logically separate components (e.g., namespaces; Chapter 14). To better manage these components, we can represent the program as a set of (source code) files where each file contains one or more logical components. Our task is to devise a physical structure (set of files) for the program that represents the logical components in a consistent, comprehensible, and flexible manner. In particular, we aim for a clean separation of interfaces (e.g., function declarations) and implementations (e.g., function definitions). A file is the traditional unit of storage (in a file system) and the traditional unit of compilation. There are systems that do not store, compile, and present C++ programs to the programmer as sets of files. However, the discussion here will concentrate on systems that employ the traditional use of files.

Having a complete program in one file is usually impossible. In particular, the code for the standard libraries and the operating system is typically not supplied in source form as part of a user’s program. For realistically sized applications, even having all of the user’s own code in a single file is both impractical and inconvenient. The way a program is organized into files can help emphasize its logical structure, help a human reader understand the program, and help the compiler enforce that logical structure. Where the unit of compilation is a file, all of the file must be recompiled whenever a change (however small) has been made to it or to something on which it depends. For even a moderately sized program, the amount of time spent recompiling can be significantly reduced by partitioning the program into files of suitable size.

A user presents a source file to the compiler. The file is then preprocessed; that is, macro processing (§12.6) is done and #include directives bring in headers (§2.4.1, §15.2.2). The result of preprocessing is called a translation unit. This unit is what the compiler proper works on and what the C++ language rules describe. In this book, I differentiate between source file and translation unit only where necessary to distinguish what the programmer sees from what the compiler considers.

To enable separate compilation, the programmer must supply declarations providing the type information needed to analyze a translation unit in isolation from the rest of the program. The declarations in a program consisting of many separately compiled parts must be consistent in exactly the same way the declarations in a program consisting of a single source file must be. Your system has tools to help ensure this. In particular, the linker can detect many kinds of inconsistencies. The linker is the program that binds together the separately compiled parts. A linker is sometimes (confusingly) called a loader. Linking can be done completely before a program starts to run. Alternatively, new code can be added to the running program (“dynamically linked”) later.

The organization of a program into source files is commonly called the physical structure of a program. The physical separation of a program into separate files should be guided by the logical structure of the program. The same dependency concerns that guide the composition of programs out of namespaces guide its composition into source files. However, the logical and physical structures of a program need not be identical. For example, it can be helpful to use several source files to store the functions from a single namespace, to store a collection of namespace definitions in a single file, or to scatter the definition of a namespace over several files (§14.3.3).

Here, we will first consider some technicalities relating to linking and then discuss two ways of breaking the desk calculator (§10.2, §14.3.1) into files.

15.2. Linkage

Names of functions, classes, templates, variables, namespaces, enumerations, and enumerators must be used consistently across all translation units unless they are explicitly specified to be local.

It is the programmer’s task to ensure that every namespace, class, function, etc., is properly declared in every translation unit in which it appears and that all declarations referring to the same entity are consistent. For example, consider two files:

// file1.cpp:
       int x = 1;
       int f() { /* do something */ }

// file2.cpp:
       extern int x;
       int f();
       void g() { x = f(); }

The x and f() used by g() in file2.cpp are the ones defined in file1.cpp. The keyword extern indicates that the declaration of x in file2.cpp is (just) a declaration and not a definition (§6.3). Had x been initialized, extern would simply be ignored because a declaration with an initializer is always a definition. An object must be defined exactly once in a program. It may be declared many times, but the types must agree exactly. For example:

// file1.cpp:
       int x = 1;
       int b = 1;
       extern int c;

// file2.cpp:
       int x;             // means "int x = 0;"
       extern double b;
       extern int c;

There are three errors here: x is defined twice, b is declared twice with different types, and c is declared twice but not defined. These kinds of errors (linkage errors) cannot be detected by a compiler that looks at only one file at a time. Many, however, are detectable by the linker. For example, all implementations I know of correctly diagnose the double definition of x. However, the inconsistent declarations of b are uncaught on popular implementations, and the missing definition of c is typically only caught if c is used.

Note that a variable defined without an initializer in the global or a namespace scope is initialized by default (§6.3.5.1). This is not the case for non-static local variables or objects created on the free store (§11.2).

Outside a class body, an entity must be declared before it is used (§6.3.4). For example:

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// file1.cpp:
       int g() { return f()+7; } // error: f() not (yet) declared
       int f() { return x; }     // error: x not (yet) declared
       int x;

A name that can be used in translation units different from the one in which it was defined is said to have external linkage. All the names in the previous examples have external linkage. A name that can be referred to only in the translation unit in which it is defined is said to have internal linkage. For example:

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static int x1 = 1;       // internal linkage: not accessible from other translation units
const char x2 = 'a';     // internal linkage: not accessible from other translation units

When used in namespace scope (including the global scope; §14.2.1), the keyword static (some-what illogically) means “not accessible from other source files” (i.e., internal linkage). If you wanted x1 to be accessible from other source files (“have external linkage”), you should remove the static. The keyword const implies default internal linkage, so if you wanted x2 to have external linkage, you need to precede its definitions with extern:

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int x1 = 1;                 // external linkage: accessible from other translation units
extern const char x2 = 'a'; // external linkage: accessible from other translation units

Names that a linker does not see, such as the names of local variables, are said to have no linkage.

An inline function (§12.1.3, §16.2.8) must be defined identically in every translation unit in which it is used (§15.2.3). Consequently, the following example isn’t just bad taste; it is illegal:

// file1.cpp:
       inline int f(int i) { return i; }

// file2.cpp:
       inline int f(int i) { return i+1; }

Unfortunately, this error is hard for an implementation to catch, and the following – otherwise perfectly logical – combination of external linkage and inlining is banned to make life simpler for compiler writers:

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// file1.cpp:
       extern inline int g(int i);
       int h(int i) { return g(i); } // error: g() undefined in this translation unit

// file2.cpp:
       extern inline int g(int i) { return i+1; }
       // ...

We keep inline function definitions consistent by using header files(§15.2.2). For example:

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// h.h:
    inline int next(int i) { return i+1; }

// file1.cpp:
    #include "h.h"
    int h(int i) { return next(i); }   // fine

// file2.cpp:
    #include "h.h"
    // ...

By default, const objects (§7.5), constexpr objects (§10.4), type aliases (§6.5), and anything declared static (§6.3.4) in a namespace scope have internal linkage. Consequently, this example is legal (although potentially confusing):

// file1.cpp:
       using T = int;
       const int x = 7;
       constexpr T c2 = x+1;

// file2.cpp:
       using T = double;
       const int x = 8;
       constexpr T c2 = x+9;

To ensure consistency, place aliases, consts, constexprs, and inlines in header files (§15.2.2).

A const can be given external linkage by an explicit declaration:

// file1.cpp:
       extern const int a = 77;

// file2.cpp:
       extern const int a;

       void g()
       {
           cout << a << '\n';
       }

Here, g() will print 77.

The techniques for managing template definitions are described in §23.7.

15.2.1. File-Local Names

Global variables are in general best avoided because they cause maintenance problems. In particular, it is hard to know where in a program they are used, and they can be a source of data races in multi-threaded programs (§41.2.4), leading to very obscure bugs.

Placing variables in a namespace helps a bit, but such variables are still subject to data races.

If you must use global variables, at least restrict their use to a single source file. This restriction can be achieved in one of two ways:

[1] Place declarations in an unnamed namespace.

[2] Declare an entity static.

An unnamed namespace (§14.4.8) can be used to make names local to a compilation unit. The effect of an unnamed namespace is very similar to that of internal linkage. For example:

// file 1.cpp:
       namespace {
           class X { /* ... */ };
           void f();
           int i;
           // ...
       }

// file2.cpp:
       class X { /* ... */ };
       void f();
       int i;
       // ...

The function f() in file1.cpp is not the same function as the f() in file2.cpp. Having a name local to a translation unit and also using that same name elsewhere for an entity with external linkage is asking for trouble.

The keyword static (confusingly) means “use internal linkage” (§44.2.3). That’s an unfortunate leftover from the earliest days of C.

15.2.2. Header Files

The types in all declarations of the same object, function, class, etc., must be consistent. Consequently, the source code submitted to the compiler and later linked together must be consistent. One imperfect but simple method of achieving consistency for declarations in different translation units is to #include header files containing interface information in source files containing executable code and/or data definitions.

The #include mechanism is a text manipulation facility for gathering source program fragments together into a single unit (file) for compilation. Consider:

#include "to_be_included"

The #include-directive replaces the line in which the #include appears with the contents of the file to_be_included. The content of to_be_included should be C++ source text because the compiler will proceed to read it.

To include standard-library headers, use the angle brackets, < and >, around the name instead of quotes. For example:

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#include <iostream>     // from standard include directory
#include "myheader.h"   // from current directory

Unfortunately, spaces are significant within the < > or " " of an include directive:

#include < iostream >       // will not find <iostream>

It seems extravagant to recompile a source file each time it is included somewhere, but the text can be a reasonably dense encoding for program interface information, and the compiler need only analyze details actually used (e.g., template bodies are often not completely analyzed until instantiation time; §26.3). Furthermore, most modern C++ implementations provide some form of (implicit or explicit) precompiling of header files to minimize the work needed to handle repeated compilation of the same header.

As a rule of thumb, a header may contain:

This rule of thumb for what may be placed in a header is not a language requirement. It is simply a reasonable way of using the #include mechanism to express the physical structure of a program. Conversely, a header should never contain:

Including a header containing such definitions will lead to errors or (in the case of the using-directive) to confusion. Header files are conventionally suffixed by .h, and files containing function or data definitions are suffixed by .cpp. They are therefore often referred to as “.h files” and “.cpp files,” respectively. Other conventions, such as .c, .C, .cxx, .cc, .hh, and hpp are also found. The manual for your compiler will be quite specific about this issue.

The reason for recommending that the definition of simple constants, but not the definition of aggregates, be placed in header files is that it is hard for implementations to avoid replication of aggregates presented in several translation units. Furthermore, the simple cases are far more common and therefore more important for generating good code.

It is wise not to be too clever about the use of #include. My recommendations are:

• #include only as headers (don’t #include “ordinary source code containing variable definitions and non-inline functions”).

• #include only complete declarations and definitions.

• #include only in the global scope, in linkage specification blocks, and in namespace definitions when converting old code (§15.2.4).

• Place all #includes before other code to minimize unintended dependencies.

• Avoid macro magic.

• Minimize the use of names (especially aliases) not local to a header in a header.

One of my least favorite activities is tracking down an error caused by a name being macro-substituted into something completely different by a macro defined in an indirectly #included header that I have never even heard of.

15.2.3. The One-Definition Rule

A given class, enumeration, and template, etc., must be defined exactly once in a program.

From a practical point of view, this means that there must be exactly one definition of, say, a class residing in a single file somewhere. Unfortunately, the language rule cannot be that simple. For example, the definition of a class may be composed through macro expansion (ugh!), and a definition of a class may be textually included in two source files by #include directives (§15.2.2). Worse, a “file” isn’t a concept that is part of the C++ language definition; there exist implementations that do not store programs in source files.

Consequently, the rule in the standard that says that there must be a unique definition of a class, template, etc., is phrased in a somewhat more complicated and subtle manner. This rule is commonly referred to as the one-definition rule (“the ODR”). That is, two definitions of a class, template, or inline function are accepted as examples of the same unique definition if and only if

[1] they appear in different translation units, and

[2] they are token-for-token identical, and

[3] the meanings of those tokens are the same in both translation units.

For example:

// file1.cpp:
       struct S { int a; char b; };
       void f(S*);

// file2.cpp:
       struct S { int a; char b; };
       void f(S* p) { /* ... */ }

The ODR says that this example is valid and that S refers to the same class in both source files. However, it is unwise to write out a definition twice like that. Someone maintaining file2.cpp will naturally assume that the definition of S in file2.cpp is the only definition of S and so feel free to change it. This could introduce a hard-to-detect error.

The intent of the ODR is to allow inclusion of a class definition in different translation units from a common source file. For example:

// s.h:
       struct S { int a; char b; };
       void f(S*);

// file1.cpp:
       #include "s.h"
       // use f() here

// file2.cpp:
       #include "s.h"
       void f(S* p) { /* ... */ }

or graphically:

Here are examples of the three ways of violating the ODR:

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// file1.cpp:
       struct S1 { int a; char b; };

       struct S1 { int a; char b; };    // error: double definition

This is an error because a struct may not be defined twice in a single translation unit.

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// file1.cpp:
       struct S2 { int a; char b; };

// file2.cpp:
       struct S2 { int a; char bb; };   // error

This is an error because S2 is used to name classes that differ in a member name.

// file1.cpp:
       typedef int X;
       struct S3 { X a; char b; };

// file2.cpp:
       typedef char X;
       struct S3 { X a; char b; }; // error

Here the two definitions of S3 are token-for-token identical, but the example is an error because the meaning of the name X has sneakily been made to differ in the two files.

Checking against inconsistent class definitions in separate translation units is beyond the ability of most C++ implementations. Consequently, declarations that violate the ODR can be a source of subtle errors. Unfortunately, the technique of placing shared definitions in headers and #includeing them doesn’t protect against this last form of ODR violation. Local type aliases and macros can change the meaning of #included declarations:

// s.h:
       struct S { Point a; char b; };

// file1.cpp:
       #define Point int
       #include "s.h"
       // ...

// file2.cpp:
       class Point { /* ... */ };
       #include "s.h"
       // ...

The best defense against this kind of hackery is to make headers as self-contained as possible. For example, if class Point had been declared in the s.h header, the error would have been detected.

A template definition can be #included in several translation units as long as the ODR is adhered to. This applies even to function template definitions and to class templates containing member function definitions.

15.2.4. Standard-Library Headers

The facilities of the standard library are presented through a set of standard headers (§4.1.2, §30.2). No suffix is needed for standard-library headers; they are known to be headers because they are included using the #include<...> syntax rather than #include"...". The absence of a .h suffix does not imply anything about how the header is stored. A header such as <map> is usually stored as a text file called map.h in some standard directory. On the other hand, standard headers are not required to be stored in a conventional manner. An implementation is allowed to take advantage of knowledge of the standard-library definition to optimize the standard-library implementation and the way standard headers are handled. For example, an implementation might have knowledge of the standard math library (§40.3) built in and treat #include<cmath> as a switch that makes the standard math functions available without actually reading any file.

For each C standard-library header <X.h>, there is a corresponding standard C++ header <cX>. For example, #include<cstdio> provides what #include<stdio.h> does. A typical stdio.h will look something like this:

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#ifdef __cplusplus      // for C++ compilers only (§15.2.5)
namespace std {         // the standard library is defined in namespace std (§4.1.2)
extern "C" {            // stdio functions have C linkage (§15.2.5)
#endif
     /* ... */
     int printf(const char*, ...);
     /* ... */
#ifdef __cplusplus
}
}
// ...
using std::printf; // make printf available in global namespace
// ...
#endif

That is, the actual declarations are (most likely) shared, but linkage and namespace issues must be addressed to allow C and C++ to share a header. The macro __cplusplus is defined by the C++ compiler (§12.6.2) and can be used to distinguish C++ code from code intended for a C compiler.

15.2.5. Linkage to Non-C++ Code

Typically, a C++ program contains parts written in other languages (e.g., C or Fortran). Similarly, it is common for C++ code fragments to be used as parts of programs written mainly in some other language (e.g., Python or Matlab). Cooperation can be difficult between program fragments written in different languages and even between fragments written in the same language but compiled with different compilers. For example, different languages and different implementations of the same language may differ in their use of machine registers to hold arguments, the layout of arguments put on a stack, the layout of built-in types such as strings and integers, the form of names passed by the compiler to the linker, and the amount of type checking required from the linker. To help, one can specify a linkage convention to be used in an extern declaration. For example, this declares the C and C++ standard-library function strcpy() and specifies that it should be linked according to the (system-specific) C linkage conventions:

extern "C" char* strcpy(char*, const char*);

The effect of this declaration differs from the effect of the “plain” declaration

extern char* strcpy(char*, const char*);

only in the linkage convention used for calling strcpy().

The extern "C" directive is particularly useful because of the close relationship between C and C++. Note that the C in extern "C" names a linkage convention and not a language. Often, extern "C" is used to link to Fortran and assembler routines that happen to conform to the conventions of a C implementation.

An extern "C" directive specifies the linkage convention (only) and does not affect the semantics of calls to the function. In particular, a function declared extern "C" still obeys the C++ type-checking and argument conversion rules and not the weaker C rules. For example:

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extern "C" int f();

int g()
{
    return f(1);      // error: no argument expected
}

Adding extern "C" to a lot of declarations can be a nuisance. Consequently, there is a mechanism to specify linkage to a group of declarations. For example:

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extern "C" {
    char* strcpy(char*, const char*);
    int strcmp(const char*, const char*);
    int strlen(const char*);
    // ...
}

This construct, commonly called a linkage block, can be used to enclose a complete C header to make a header suitable for C++ use. For example:

extern "C" {
#include <string.h>
}

This technique is commonly used to produce a C++ header from a C header. Alternatively, conditional compilation (§12.6.1) can be used to create a common C and C++ header:

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#ifdef __cplusplus
extern "C" {
#endif
    char* strcpy(char*, const char*);
    int strcmp(const char*, const char*);
    int strlen(const char*);
    // ...
#ifdef __cplusplus
}
#endif

The predefined macro name __cplusplus (§12.6.2) is used to ensure that the C++ constructs are edited out when the file is used as a C header.

Any declaration can appear within a linkage block:

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extern "C" {        // any declaration here, for example:
    int g1;         // definition
    extern int g2;  // declaration, not definition
}

In particular, the scope and storage class (§6.3.4, §6.4.2) of variables are not affected, so g1 is still a global variable – and is still defined rather than just declared. To declare but not define a variable, you must apply the keyword extern directly in the declaration. For example:

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extern "C" int g3;        // declaration, not definition
extern "C" { int g4; }    // definition

This looks odd at first glance. However, it is a simple consequence of keeping the meaning unchanged when adding "C" to an extern-declaration and the meaning of a file unchanged when enclosing it in a linkage block.

A name with C linkage can be declared in a namespace. The namespace will affect the way the name is accessed in the C++ program, but not the way a linker sees it. The printf() from std is a typical example:

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#include<cstdio>

void f()
{
    std::printf("Hello, ");     // OK
    printf("world!\n");         // error: no global printf()
}

Even when called std::printf, it is still the same old C printf() (§43.3).

Note that this allows us to include libraries with C linkage into a namespace of our choice rather than polluting the global namespace. Unfortunately, the same flexibility is not available to us for headers defining functions with C++ linkage in the global namespace. The reason is that linkage of C++ entities must take namespaces into account so that the object files generated will reflect the use or lack of use of namespaces.

15.2.6. Linkage and Pointers to Functions

When mixing C and C++ code fragments in one program, we sometimes want to pass pointers to functions defined in one language to functions defined in the other. If the two implementations of the two languages share linkage conventions and function call mechanisms, such passing of pointers to functions is trivial. However, such commonality cannot in general be assumed, so care must be taken to ensure that a function is called the way it expects to be called.

When linkage is specified for a declaration, the specified linkage applies to all function types, function names, and variable names introduced by the declaration(s). This makes all kinds of strange – and occasionally essential – combinations of linkage possible. For example:

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typedef int (*FT)(const void*, const void*);                  // FT has C++ linkage

extern "C" {
    typedef int (*CFT)(const void*, const void*);             // CFT has C linkage
    void qsort(void* p, size_t n, size_t sz, CFT cmp);        // cmp has C linkage
}

void isort(void* p, size_t n, size_t sz, FT cmp);             // cmp has C++ linkage
void xsort(void* p, size_t n, size_t sz, CFT cmp);            // cmp has C linkage
extern "C" void ysort(void* p, size_t n, size_t sz, FT cmp);  // cmp has C++ linkage

int compare(const void*, const void*);                        // compare() has C++ linkage
extern "C" int ccmp(const void*, const void*);                // ccmp() has C linkage

void f(char* v, int sz)
{
    qsort(v,sz,1,&compare); // error
    qsort(v,sz,1,&ccmp);           // OK

    isort(v,sz,1,&compare); // OK
    isort(v,sz,1,&ccmp);    // error
}

An implementation in which C and C++ use the same calling conventions might accept the declarations marked error as a language extension. However, even for compatible C and C++ implementations, std::function (§33.5.3) or lambdas with any form of capture (§11.4.3) cannot cross the language barrier.

15.3. Using Header Files

To illustrate the use of headers, I present a few alternative ways of expressing the physical structure of the calculator program (§10.2, §14.3.1).

15.3.1. Single-Header Organization

The simplest solution to the problem of partitioning a program into several files is to put the definitions in a suitable number of .cpp files and to declare the types, functions, classes, etc., needed for them to cooperate in a single .h file that each .cpp file #includes. That’s the initial organization I would use for a simple program for my own use; if something more elaborate turned out to be needed, I would reorganize later.

For the calculator program, we might use five .cpp files – lexer.cpp, parser.cpp, table.cpp, error.cpp, and main.cpp – to hold function and data definitions. The header dc.h holds the declarations of every name used in more than one .cpp file:

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// dc.h:

#include <map>
#include<string>
#include<iostream>

namespace Parser {
    double expr(bool);
    double term(bool);
    double prim(bool);
}

namespace Lexer {
    enum class Kind : char {
        name, number, end,
        plus='+', minus='-', mul='*', div='/', print=';', assign='=', lp='(', rp=')'
    };

    struct Token {
        Kind kind;
        string string_value;
        double number_value;
    };

    class Token_stream {
    public:
        Token(istream& s) : ip{&s}, owns(false}, ct{Kind::end} { }
        Token(istream*  p) : ip{p}, owns{true}, ct{Kind::end} { }

        ~Token() { close(); }

        Token get();           // read and return next token
        Token& current();      // most recently read token

        void set_input(istream& s) { close(); ip = &s; owns=false; }
        void set_input(istream*  p) { close(); ip = p; owns = true; }
    private:
        void close() { if (owns) delete ip; }

        istream*  ip;      // pointer to an input stream
        bool owns;                   // does the Token_stream own the istream?
        Token ct {Kind::end};        // current_token
    };

    extern Token_stream ts;
}
namespace Table {
    extern map<string,double> table;
}

namespace Error {
    extern int no_of_errors;
    double error(const string& s);
}

namespace Driver {
    void calculate();
}

The keyword extern is used for every variable declaration to ensure that multiple definitions do not occur as we #include dc.h in the various .cpp files. The corresponding definitions are found in the appropriate .cpp files.

I added standard-library headers as needed for the declarations in dc.h, but I did not add declarations (such as using-declarations) needed only for the convenience of an individual .cpp file.

Leaving out the actual code, lexer.cpp will look something like this:

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// lexer.cpp:

#include "dc.h"
#include <cctype>
#include <iostream>   // redundant: in dc.h

Lexer::Token_stream ts;

Lexer::Token Lexer::Token_stream::get() { /* ... */ }
Lexer::Token& Lexer::Token_stream::current() { /* ... */ }

I used explicit qualification, Lexer::, for the definitions rather that simply enclosing them all in

namespace Lexer { /* ... */ }

That avoids the possibility of accidentally adding new members to Lexer. On the other hand, had I wanted to add members to Lexer that were not part of its interface, I would have had to reopen the namespace (§14.2.5).

Using headers in this manner ensures that every declaration in a header will at some point be included in the file containing its definition. For example, when compiling lexer.cpp the compiler will be presented with:

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namespace Lexer { // from dc.h
    // ...
    class Token_stream {
    public:
         Token get();
         // ...
    };
}

// ...

Lexer::Token Lexer::Token_stream::get() { /* ... */ }

This ensures that the compiler will detect any inconsistencies in the types specified for a name. For example, had get() been declared to return a Token, but defined to return an int, the compilation of lexer.cpp would have failed with a type-mismatch error. If a definition is missing, the linker will catch the problem. If a declaration is missing, some .cpp files will fail to compile.

File parser.cpp will look like this:

// parser.cpp:

#include "dc.h"

double Parser::prim(bool get) { /* ... */ }
double Parser::term(bool get) { /* ... */ }
double Parser::expr(bool get) { /* ... */ }

File table.cpp will look like this:

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// table.cpp:

#include "dc.h"

std::map<std::string,double> Table::table;

The symbol table is a standard-library map.

File error.cpp becomes:

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// error.cpp:

#include "dg.h"
// any more #includes or declarations

int Error::no_of_errors;
double Error::error(const string& s) { /* ... */ }

Finally, file main.cpp will look like this:

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// main.cpp:

#include "dc.h"
#include <sstream>
#include <iostream>   // redundant: in dc.h

void Driver::calculate() { /* ... */ }

int main(int argc, char* argv[]) { /* ... */ }

To be recognized as the main() of the program, main() must be a global function (§2.2.1, §15.4), so no namespace is used here.

The physical structure of the system can be presented like this:

The headers on the top are all headers for standard-library facilities. For many forms of program analysis, these libraries can be ignored because they are well known and stable. For tiny programs, the structure can be simplified by moving all #include directives to the common header. Similarly, for a small program, separating out error.cpp and table.cpp from main.cpp would often be excessive.

This single-header style of physical partitioning is most useful when the program is small and its parts are not intended to be used separately. Note that when namespaces are used, the logical structure of the program is still represented within dc.h. If namespaces are not used, the structure is obscured, although comments can be a help.

For larger programs, the single-header-file approach is unworkable in a conventional file-based development environment. A change to the common header forces recompilation of the whole program, and updates of that single header by several programmers are error-prone. Unless strong emphasis is placed on programming styles relying heavily on namespaces and classes, the logical structure deteriorates as the program grows.

15.3.2. Multiple-Header Organization

An alternative physical organization lets each logical module have its own header defining the facilities it provides. Each .cpp file then has a corresponding .h file specifying what it provides (its interface). Each .cpp file includes its own .h file and usually also other .h files that specify what it needs from other modules in order to implement the services advertised in the interface. This physical organization corresponds to the logical organization of a module. The interface for users is put into its .h file, the interface for implementers is put into a file suffixed _impl.h, and the module’s definitions of functions, variables, etc., are placed in .cpp files. In this way, the parser is represented by three files. The parser’s user interface is provided by parser.h:

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// parser.h:

namespace Parser {          // interface for users
    double expr(bool get);
}

The shared environment for the functions expr(), prim(), and term(), implementing the parser is presented by parser_impl.h:

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// parser_impl.h:

#include "parser.h"
#include "error.h"
#include "lexer.h"

using Error::error;
using namespace Lexer;

namespace Parser {           // interface for implementers
    double prim(bool get);
    double term(bool get);
    double expr(bool get);
}

The distinction between the user interface and the interface for implementers would be even clearer had we used a Parser_impl namespace (§14.3.3).

The user’s interface in header parser.h is #included to give the compiler a chance to check consistency (§15.3.1).

The functions implementing the parser are stored in parser.cpp together with #include directives for the headers that the Parser functions need:

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// parser.cpp:

#include "parser_impl.h"
#include "table.h"

using Table::table;

double Parser::prim(bool get) { /* ... */ }
double Parser::term(bool get) { /* ... */ }
double Parser::expr(bool get) { /* ... */ }

Graphically, the parser and the driver’s use of it look like this:

As intended, this is a rather close match to the logical structure described in §14.3.1. To simplify this structure, we could have #included table.h in parser_impl.h rather than in parser.cpp. However, table.h is an example of something that is not necessary to express the shared context of the parser functions; it is needed only by their implementation. In fact, it is used by just one function, prim(), so if we were really keen on minimizing dependencies we could place prim() in its own .cpp file and #include table.h there only:

Such elaboration is not appropriate except for larger modules. For realistically sized modules, it is common to #include extra files where needed for individual functions. Furthermore, it is not uncommon to have more than one _impl.h, since different subsets of the module’s functions need different shared contexts.

Please note that the _impl.h notation is not a standard or even a common convention; it is simply the way I like to name things.

Why bother with this more complicated scheme of multiple header files? It clearly requires far less thought simply to throw every declaration into a single header, as was done for dc.h.

The multiple-header organization scales to modules several magnitudes larger than our toy parser and to programs several magnitudes larger than our calculator. The fundamental reason for using this type of organization is that it provides a better localization of concerns. When analyzing and modifying a large program, it is essential for a programmer to focus on a relatively small chunk of code. The multiple-header organization makes it easy to determine exactly what the parser code depends on and to ignore the rest of the program. The single-header approach forces us to look at every declaration used by any module and decide if it is relevant. The simple fact is that maintenance of code is invariably done with incomplete information and from a local perspective. The multiple-header organization allows us to work successfully “from the inside out” with only a local perspective. The single-header approach – like every other organization centered around a global repository of information – requires a top-down approach and will forever leave us wondering exactly what depends on what.

The better localization leads to less information needed to compile a module, and thus to faster compiles. The effect can be dramatic. I have seen compile times drop by a factor of 1000 as the result of a simple dependency analysis leading to a better use of headers.

15.3.2.1. Other Calculator Modules

The remaining calculator modules can be organized similarly to the parser. However, those modules are so small that they don’t require their own _impl.h files. Such files are needed only where the implementation of a logical module consists of many functions that need a shared context (in addition to what is provided to users).

The error handler provides its interface in error.h:

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// error.h:

#include<string>

namespace Error {
    int Error::number_of_errors;
    double Error::error(const std::string&);
}

The implementation is found in error.cpp:

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// error.cpp:

#include "error.h"

int Error::number_of_errors;
double Error::error(const std::string&) { /* ... */ }

The lexer provides a rather large and messy interface:

// lexer.h:

#include<string>
#include<iostream>

namespace Lexer {

    enum class Kind : char {/* ... */ };

    class Token { /* ... */ };
    class Token_stream { /* ... */ };

    extern Token_stream is;
}

In addition to lexer.h, the implementation of the lexer depends on error.h and on the character-classification functions in <cctype> (§36.2):

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// lexer.cpp:

#include "lexer.h"
#include "error.h"
#include <iostream>     // redundant: in lexer.h
#include <cctype>

Lexer::Token_stream is; // defaults to "read from cin"

Lexer::Token Lexer::Token_stream::get() { /* ... */ };
Lexer::Token& Lexer::Token_stream::current() { /* ... */ };

We could have factored out the #include directive for error.h as the Lexer’s _impl.h file. However, I considered that excessive for this tiny program.

As usual, we #include the interface offered by the module – in this case, lexer.h – in the module’s implementation to give the compiler a chance to check consistency.

The symbol table is essentially self-contained, although the standard-library header <map> could drag in all kinds of interesting stuff to implement an efficient map template class:

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// table.h:

#include <map>
#include <string>

namespace Table {
    extern std::map<std::string,double> table;
}

Because we assume that every header may be #included in several .cpp files, we must separate the declaration of table from its definition:

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// table.cpp:

#include "table.h"

std::map<std::string,double> Table::table;

I just stuck the driver into main.cpp:

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// main.cpp:

#include "parser.h"
#include "lexer.h"    // to be able to set ts
#include "error.h"
#include "table.h"    // to be able to predefine names
#include <sstream>    // to be able to put main()'s arguments into a string stream

namespace Driver {
   void calculate() { /* ... */ }
}

int main(int argc, char* argv[]) { /* ... */ }

For a larger system, it is usually worthwhile to separate out the driver and minimize what is done in main(). That way main() calls a driver function placed in a separate source file. This is particularly important for code intended to be used as a library. Then, we cannot rely on code in main() and must be prepared for the driver to be called from a variety of functions.

15.3.2.2. Use of Headers

The number of headers to use for a program is a function of many factors. Many of these factors have more to do with the way files are handled on your system than with C++. For example, if your editor/IDE does not make it convenient to look at several files simultaneously, then using many headers becomes less attractive.

A word of caution: a few dozen headers plus the standard headers for the program’s execution environment (which can often be counted in the hundreds) are usually manageable. However, if you partition the declarations of a large program into the logically minimal-size headers (putting each structure declaration in its own file, etc.), you can easily get an unmanageable mess of hundreds of files even for minor projects. I find that excessive.

For large projects, multiple headers are unavoidable. In such projects, hundreds of files (not counting standard headers) are the norm. The real confusion starts when they begin to be counted in the thousands. At that scale, the basic techniques discussed here still apply, but their management becomes a Herculean task. Tools, such as dependency analysers, can be of great help, but there is little they can do for compiler and linker performance if the program is an unstructured mess. Remember that for realistically sized programs, the single-header style is not an option. Such programs will have multiple headers. The choice between the two styles of organization occurs (repeatedly) for the parts that make up the program.

The single-header style and the multiple-header style are not really alternatives. They are complementary techniques that must be considered whenever a significant module is designed and must be reconsidered as a system evolves. It’s crucial to remember that one interface doesn’t serve all equally well. It is usually worthwhile to distinguish between the implementers’ interface and the users’ interface. In addition, many larger systems are structured so that providing a simple interface for the majority of users and a more extensive interface for expert users is a good idea. The expert users’ interfaces (“complete interfaces”) tend to #include many more features than the average user would ever want to know about. In fact, the average users’ interface can often be identified by eliminating features that require the inclusion of headers that define facilities that would be unknown to the average user. The term “average user” is not derogatory. In the fields in which I don’t have to be an expert, I strongly prefer to be an average user. In that way, I minimize hassles.

15.3.3. Include Guards

The idea of the multiple-header approach is to represent each logical module as a consistent, self-contained unit. Viewed from the program as a whole, many of the declarations needed to make each logical module complete are redundant. For larger programs, such redundancy can lead to errors, as a header containing class definitions or inline functions gets #included twice in the same compilation unit (§15.2.3).

We have two choices. We can

[1] reorganize our program to remove the redundancy, or

[2] find a way to allow repeated inclusion of headers.

The first approach – which led to the final version of the calculator – is tedious and impractical for realistically sized programs. We also need that redundancy to make the individual parts of the program comprehensible in isolation.

The benefits of an analysis of redundant #includes and the resulting simplifications of the program can be significant both from a logical point of view and by reducing compile times. However, it can rarely be complete, so some method of allowing redundant #includes must be applied. Preferably, it must be applied systematically, since there is no way of knowing how thorough an analysis a user will find worthwhile.

The traditional solution is to insert include guards in headers. For example:

// error.h:

#ifndef CALC_ERROR_H
#define CALC_ERROR_H

namespace Error {
    // ...
}

#endif   // CALC_ERROR_H

The contents of the file between the #ifndef and #endif are ignored by the compiler if CALC_ERROR_H is defined. Thus, the first time error.h is seen during a compilation, its contents are read and CALC_ERROR_H is given a value. Should the compiler be presented with error.h again during the compilation, the contents are ignored. This is a piece of macro hackery, but it works and it is pervasive in the C and C++ worlds. The standard headers all have include guards.

Header files are included in essentially arbitrary contexts, and there is no namespace protection against macro name clashes. Consequently, I choose rather long and ugly names for my include guards.

Once people get used to headers and include guards, they tend to include lots of headers directly and indirectly. Even with C++ implementations that optimize the processing of headers, this can be undesirable. It can cause unnecessarily long compile time, and it can bring lots of declarations and macros into scope. The latter might affect the meaning of the program in unpredictable and adverse ways. Headers should be included only when necessary.

15.4. Programs

A program is a collection of separately compiled units combined by a linker. Every function, object, type, etc., used in this collection must have a unique definition (§6.3, §15.2.3). A program must contain exactly one function called main() (§2.2.1). The main computation performed by the program starts with the invocation of the global function main() and ends with a return from main(). The return type of main() is int, and the following two versions of main() are supported by all implementations:

int main() { /* ... */ }
int main(int argc, char* argv[]) { /* ... */ }

A program can only provide one of those two alternatives. In addition, an implementation can allow other versions of main(). The argc, argv version is used to transmit arguments from the program’s environment; see §10.2.7.

The int returned by main() is passed to whatever system invoked main() as the result of the program. A nonzero return value from main() indicates an error.

This simple story must be elaborated on for programs that contain global variables (§15.4.1) or that throw an uncaught exception (§13.5.2.5).

15.4.1. Initialization of Nonlocal Variables

In principle, a variable defined outside any function (that is, global, namespace, and class static variables) is initialized before main() is invoked. Such nonlocal variables in a translation unit are initialized in their definition order. If such a variable has no explicit initializer, it is by default initialized to the default for its type (§17.3.3). The default initializer value for built-in types and enumerations is 0. For example:

double x = 2;      // nonlocal variables
double y;
double sqx = sqrt(x+y);

Here, x and y are initialized before sqx, so sqrt(2) is called.

There is no guaranteed order of initialization of global variables in different translation units. Consequently, it is unwise to create order dependencies between initializers of global variables in different compilation units. In addition, it is not possible to catch an exception thrown by the initializer of a global variable (§13.5.2.5). It is generally best to minimize the use of global variables and in particular to limit the use of global variables requiring complicated initialization.

Several techniques exist for enforcing an order of initialization of global variables in different translation units. However, none are both portable and efficient. In particular, dynamically linked libraries do not coexist happily with global variables that have complicated dependencies.

Often, a function returning a reference is a good alternative to a global variable. For example:

int& use_count()
{
    static int uc = 0;
    return uc;
}

A call use_count() now acts as a global variable except that it is initialized at its first use (§7.7). For example:

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void f()
{
    cout << ++use_count(); // read and increment
    // ...
}

Like other uses of static, this technique is not thread-safe. The initialization of a local static is thread-safe (§42.3.3). In this case, the initialization is even with a constant expression (§10.4), so that it is done at link time and not subject to data races (§42.3.3). However, the ++ can lead to a data race.

The initialization of nonlocal (statically allocated) variables is controlled by whatever mechanism an implementation uses to start up a C++ program. This mechanism is guaranteed to work properly only if main() is executed. Consequently, one should avoid nonlocal variables that require run-time initialization in C++ code intended for execution as a fragment of a non-C++ program.

Note that variables initialized by constant expressions (§10.4) cannot depend on the value of objects from other translation units and do not require run-time initialization. Such variables are therefore safe to use in all cases.

15.4.2. Initialization and Concurrency

Consider:

int x = 3;
int y = sqrt(++x);

What could be the values of x and y? The obvious answer is “3 and 2!” Why? The initialization of a statically allocated object with a constant expression is done at link time, so x becomes 3. However, y’s initializer is not a constant expression (sqrt() is no constexpr), so y is not initialized until run time. However, the order of initialization of statically allocated objects in a single translation unit is well defined: they are initialized in definition order (§15.4.1). So, y becomes 2.

The flaw in this argument is that if multiple threads are used (§5.3.1, §42.2), each will do the run-time initialization. No mutual exclusion is implicitly provided to prevent a data race. Then, sqrt(++x) in one thread may happen before or after the other thread manages to increment x. So, the value of y may be sqrt(4) or sqrt(5).

To avoid such problems, we should (as usual):

• Minimize the use of statically allocated objects and keep their initialization as simple as possible.

• Avoid dependencies on dynamically initialized objects in other translation units (§15.4.1).

In addition, to avoid data races in initialization, try these techniques in order:

[1] Initialize using constant expressions (note that built-in types without initializers are initialized to zero and that standard containers and strings are initialized to empty by link-time initialization).

[2] Initialize using expressions without side effects.

[3] Initialize in a known single-threaded “startup phase” of computation.

[4] Use some form of mutual exclusion (§5.3.4, §42.3).

15.4.3. Program Termination

A program can terminate in several ways:

[1] By returning from main()

[2] By calling exit()

[3] By calling abort()

[4] By throwing an uncaught exception

[5] By violating noexcept

[6] By calling quick_exit()

In addition, there are a variety of ill-behaved and implementation-dependent ways of making a program crash (e.g., dividing a double by zero).

If a program is terminated using the standard-library function exit(), the destructors for constructed static objects are called (§15.4.1, §16.2.12). However, if the program is terminated using the standard-library function abort(), they are not. Note that this implies that exit() does not terminate a program immediately. Calling exit() in a destructor may cause an infinite recursion. The type of exit() is:

void exit(int);

Like the return value of main() (§2.2.1), exit()’s argument is returned to “the system” as the value of the program. Zero indicates successful completion.

Calling exit() means that the local variables of the calling function and its callers will not have their destructors invoked. Throwing an exception and catching it ensures that local objects are properly destroyed (§13.5.1). Also, a call of exit() terminates the program without giving the caller of the function that called exit() a chance to deal with the problem. It is therefore often best to leave a context by throwing an exception and letting a handler decide what to do next. For example, main() may catch every exception (§13.5.2.2).

The C (and C++) standard-library function atexit() offers the possibility to have code executed at program termination. For example:

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void my_cleanup();

void somewhere()
{
    if (atexit(&my_cleanup)==0) {
         // my_cleanup will be called at normal termination
    }
    else {
         // oops: too many atexit functions
    }
}

This strongly resembles the automatic invocation of destructors for global variables at program termination (§15.4.1, §16.2.12). An argument to atexit() cannot take arguments or return a result, and there is an implementation-defined limit to the number of atexit functions. A nonzero value returned by atexit() indicates that the limit is reached. These limitations make atexit() less useful than it appears at first glance. Basically, atexit() is a C workaround for the lack of destructors.

The destructor of a constructed statically allocated object (§6.4.2) created before a call of atexit(f) will be invoked after f is invoked. The destructor of such an object created after a call of atexit(f) will be invoked before f is invoked.

The quick_exit() function is like exit() except that it does not invoke any destructors. You register functions to be invoked by quick_exit() using at_quick_exit().

The exit(), abort(), quick_exit(), atexit(), and at_quick_exit() functions are declared in <cstdlib>.

15.5. Advice

[1] Use header files to represent interfaces and to emphasize logical structure; §15.1, §15.3.2.

[2] #include a header in the source file that implements its functions; §15.3.1.

[3] Don’t define global entities with the same name and similar-but-different meanings in different translation units; §15.2.

[4] Avoid non-inline function definitions in headers; §15.2.2.

[5] Use #include only at global scope and in namespaces; §15.2.2.

[6] #include only complete declarations; §15.2.2.

[7] Use include guards; §15.3.3.

[8] #include C headers in namespaces to avoid global names; §14.4.9, §15.2.4.

[9] Make headers self-contained; §15.2.3.

[10] Distinguish between users’ interfaces and implementers’ interfaces; §15.3.2.

[11] Distinguish between average users’ interfaces and expert users’ interfaces; §15.3.2.

[12] Avoid nonlocal objects that require run-time initialization in code intended for use as part of non-C++ programs; §15.4.1.

Part III: Abstraction Mechanisms

This part describes C++’s facilities for defining and using new types. Techniques commonly called object-oriented programming and generic programming are presented.

Chapters

16 Classes

17 Construction, Cleanup, Copy, and Move

18 Operator Overloading

19 Special Operators

20 Derived Classes

21 Class Hierarchies

22 Run-Time Type Information

23 Templates

24 Generic Programming

25 Specialization

26 Instantiation

27 Templates and Hierarchies

28 Metaprogramming

29 A Matrix Design

“... there is nothing more difficult to carry out, nor more doubtful of success, nor more dangerous to handle, than to initiate a new order of things. For the reformer makes enemies of all those who profit by the old order, and only lukewarm defenders in all those who would profit by the new order...”

– Niccolò Machiavelli (“The Prince” §vi)

16. Classes

Those types are not “abstract”; they are as real as int and float.

– Doug McIlroy

• Introduction

• Class Basics

Member Functions; Default Copying; Access Control; class and struct; Constructors; explicit Constructors; In-Class Initializers; In-Class Function Definitions; Mutability; Self-Reference; Member Access; static Members; Member Types

• Concrete Classes

Member Functions; Helper Functions; Overloaded Operators; The Significance of Concrete Classes

• Advice

16.1. Introduction

C++ classes are a tool for creating new types that can be used as conveniently as the built-in types. In addition, derived classes (§3.2.4, Chapter 20) and templates (§3.4, Chapter 23) allow the programmer to express (hierachical and parametric) relationships among classes and to take advantage of such relationships.

A type is a concrete representation of a concept (an idea, a notion, etc.). For example, the C++ built-in type float with its operations +, –, *, etc., provides a concrete approximation of the mathematical concept of a real number. A class is a user-defined type. We design a new type to provide a definition of a concept that has no direct counterpart among the built-in types. For example, we might provide a type Trunk_line in a program dealing with telephony, a type Explosion for a video game, or a type list<Paragraph> for a text-processing program. A program that provides types that closely match the concepts of the application tends to be easier to understand, easier to reason about, and easier to modify than a program that does not. A well-chosen set of user-defined types also makes a program more concise. In addition, it makes many sorts of code analysis feasible. In particular, it enables the compiler to detect illegal uses of objects that would otherwise be found only through exhaustive testing.

The fundamental idea in defining a new type is to separate the incidental details of the implementation (e.g., the layout of the data used to store an object of the type) from the properties essential to the correct use of it (e.g., the complete list of functions that can access the data). Such a separation is best expressed by channeling all uses of the data structure and its internal housekeeping routines through a specific interface.

This chapter focuses on relatively simple “concrete” user-defined types that logically don’t differ much from built-in types:

§16.2 Class Basics introduces the basic facilities for defining a class and its members.

§16.3 Concrete Classes discusses the design of elegant and efficient concrete classes.

The following chapters go into greater detail and presents abstract classes and class hierarchies:

Chapter 17

Construction, Cleanup, Copy, and Move presents the variety of ways to control initialization of objects of a class, how to copy and move objects, and how to provide “cleanup actions” to be performed when an object is destroyed (e.g., goes out of scope).

Chapter 18

Operator Overloading explains how to define unary and binary operators (such as +, *, and !) for user-defined types and how to use them.

Chapter 19

Special Operators considers how to define and use operators (such as [], (), –>, new) that are “special” in that they are commonly used in ways that differ from arithmetic and logical operators. In particular, this chapter shows how to define a string class.

Chapter 20

Derived Classes introduces the basic language features supporting object-oriented programming. Base and derived classes, virtual functions, and access control are covered.

Chapter 21

Class Hierarchies focuses on the use of base and derived classes to effectively organize code around the notion of class hierarchies. Most of this chapter is devoted to discussion of programming techniques, but technical aspects of multiple inheritance (classes with more than one base class) are also covered.

Chapter 22

Run-Time Type Information describes the techniques for explicitly navigating class hierarchies. In particular, the type conversion operations dynamic_cast and static_cast are presented, as is the operation for determining the type of an object given one of its base classes (typeid).

16.2. Class Basics

Here is a very brief summary of classes:

• A class is a user-defined type.

• A class consists of a set of members. The most common kinds of members are data members and member functions.

• Member functions can define the meaning of initialization (creation), copy, move, and cleanup (destruction).

• Members are accessed using . (dot) for objects and –> (arrow) for pointers.

• Operators, such as +, !, and [], can be defined for a class.

• A class is a namespace containing its members.

• The public members provide the class’s interface and the private members provide implementation details.

• A struct is a class where members are by default public.

For example:

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class X {
private:                       // the representation (implementation) is private
     int m;
public:                        // the user interface is public
     X(int i =0) :m{i} { }     // a constructor (initialize the data member m)

     int mf(int i)             // a member function
     {
          int old = m;
          m = i;               // set a new value
          return old;          // return the old value
     }
};

X var {7}; // a variable of type X, initialized to 7

int user(X var, X* ptr)
{
    int x = var.mf(7);         // access using . (dot)
    int y = ptr–>mf(9);        // access using -> (arrow)
    int z = var.m;             // error: cannot access private member
}

The following sections expand on this and give rationale. The style is tutorial: a gradual development of ideas, with details postponed until later.

16.2.1. Member Functions

Consider implementing the concept of a date using a struct (§2.3.1, §8.2) to define the representation of a Date and a set of functions for manipulating variables of this type:

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struct Date {     // representation
    int d, m, y;
};

void init_date(Date& d, int, int, int); // initialize d
void add_year(Date& d, int n);          // add n years to d
void add_month(Date& d, int n);         // add n months to d
void add_day(Date& d, int n);           // add n days to d

There is no explicit connection between the data type, Date, and these functions. Such a connection can be established by declaring the functions as members:

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struct Date {
    int d, m, y;

    void init(int dd, int mm, int yy); // initialize
    void add_year(int n);              // add n years
    void add_month(int n);             // add n months
    void add_day(int n);               // add n days
};

Functions declared within a class definition (a struct is a kind of class; §16.2.4) are called member functions and can be invoked only for a specific variable of the appropriate type using the standard syntax for structure member access (§8.2). For example:

Date my_birthday;

void f()
{
     Date today;

     today.init(16,10,1996);
     my_birthday.init(30,12,1950);

     Date tomorrow = today;
     tomorrow.add_day(1);
    // ...
}

Because different structures can have member functions with the same name, we must specify the structure name when defining a member function:

void Date::init(int dd, int mm, int yy)
{
    d = dd;
    m = mm;
    y = yy;
}

In a member function, member names can be used without explicit reference to an object. In that case, the name refers to that member of the object for which the function was invoked. For example, when Date::init() is invoked for today, m=mm assigns to today.m. On the other hand, when Date::init() is invoked for my_birthday, m=mm assigns to my_birthday.m. A class member function “knows” for which object it was invoked. But see §16.2.12 for the notion of a static member.

16.2.2. Default Copying

By default, objects can be copied. In particular, a class object can be initialized with a copy of an object of its class. For example:

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Date d1 = my_birthday; // initialization by copy
Date d2 {my_birthday}; // initialization by copy

By default, the copy of a class object is a copy of each member. If that default is not the behavior wanted for a class X, a more appropriate behavior can be provided (§3.3, §17.5).

Similarly, class objects can by default be copied by assignment. For example:

void f(Date& d)
{
    d = my_birthday;
}

Again, the default semantics is memberwise copy. If that is not the right choice for a class X, the user can define an appropriate assignment operator (§3.3, §17.5).

16.2.3. Access Control

The declaration of Date in the previous subsection provides a set of functions for manipulating a Date. However, it does not specify that those functions should be the only ones to depend directly on Date’s representation and the only ones to directly access objects of class Date. This restriction can be expressed by using a class instead of a struct:

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class Date {
    int d, m, y;
public:
    void init(int dd, int mm, int yy); // initialize

    void add_year(int n);              // add n years
    void add_month(int n);             // add n months
    void add_day(int n);               // add n days
};

The public label separates the class body into two parts. The names in the first, private, part can be used only by member functions. The second, public, part constitutes the public interface to objects of the class. A struct is simply a class whose members are public by default (§16.2.4); member functions can be defined and used exactly as before. For example:

void Date::add_year(int n)
{
    y += n;
}

However, nonmember functions are barred from using private members. For example:

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void timewarp(Date& d)
{
    d.y –= 200;       // error: Date::y is private
}

The init() function is now essential because making the data private forces us to provide a way of initializing members. For example:

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Date dx;
dx.m = 3;           // error: m is private
dx.init(25,3,2011); // OK

There are several benefits to be obtained from restricting access to a data structure to an explicitly declared list of functions. For example, any error causing a Date to take on an illegal value (for example, December 36, 2016) must be caused by code in a member function. This implies that the first stage of debugging – localization – is completed before the program is even run. This is a special case of the general observation that any change to the behavior of the type Date can and must be effected by changes to its members. In particular, if we change the representation of a class, we need only change the member functions to take advantage of the new representation. User code directly depends only on the public interface and need not be rewritten (although it may need to be recompiled). Another advantage is that a potential user need examine only the definitions of the member functions in order to learn to use a class. A more subtle, but most significant, advantage is that focusing on the design of a good interface simply leads to better code because thoughts and time otherwise devoted to debugging are expended on concerns related to proper use.

The protection of private data relies on restriction of the use of the class member names. It can therefore be circumvented by address manipulation (§7.4.1) and explicit type conversion (§11.5). But this, of course, is cheating. C++ protects against accident rather than deliberate circumvention (fraud). Only hardware can offer perfect protection against malicious use of a general-purpose language, and even that is hard to do in realistic systems.

16.2.4. class and struct

The construct

class X { ... };

is called a class definition; it defines a type called X. For historical reasons, a class definition is often referred to as a class declaration. Also, like declarations that are not definitions, a class definition can be replicated in different source files using #include without violating the one-definition rule (§15.2.3).

By definition, a struct is a class in which members are by default public; that is,

struct S { /* ... */ };

is simply shorthand for

class S { public: /* ... */ };

These two definitions of S are interchangeable, though it is usually wise to stick to one style. Which style you use depends on circumstances and taste. I tend to use struct for classes that I think of as “just simple data structures.” If I think of a class as “a proper type with an invariant,” I use class. Constructors and access functions can be quite useful even for structs, but as a shorthand rather than guarantors of invariants (§2.4.3.2, §13.4).

By default, members of a class are private:

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class Date1 {
    int d, m, y;       // private by default
public:
    Date1(int dd, int mm, int yy);
    void add_year(int n);     // add n years
};

However, we can also use the access specifier private: to say that the members following are private, just as public: says that the members following are public:

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struct Date2 {
private:
    int d, m, y;
public:
    Date2(int dd, int mm, int yy);
    void add_year(int n);    // add n years
};

Except for the different name, Date1 and Date2 are equivalent.

It is not a requirement to declare data first in a class. In fact, it often makes sense to place data members last to emphasize the functions providing the public user interface. For example:

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class Date3 {
public:
    Date3(int dd, int mm, int yy);
    void add_year(int n);    // add n years
private:
    int d, m, y;
};

In real code, where both the public interface and the implementation details typically are more extensive than in tutorial examples, I usually prefer the style used for Date3.

Access specifiers can be used many times in a single class declaration. For example:

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class Date4 {
public:
    Date4(int dd, int mm, int yy);
private:
    int d, m, y;
public:
    void add_year(int n);     // add n years
};

Having more than one public section, as in Date4, tends to be messy, though, and might affect the object layout (§20.5). So does having more than one private section. However, allowing many access specifiers in a class is useful for machine-generated code.

16.2.5. Constructors

The use of functions such as init() to provide initialization for class objects is inelegant and error-prone. Because it is nowhere stated that an object must be initialized, a programmer can forget to do so – or do so twice (often with equally disastrous results). A better approach is to allow the programmer to declare a function with the explicit purpose of initializing objects. Because such a function constructs values of a given type, it is called a constructor. A constructor is recognized by having the same name as the class itself. For example:

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class Date {
    int d, m, y;
public:
    Date(int dd, int mm, int yy);    // constructor
    // ...
};

When a class has a constructor, all objects of that class will be initialized by a constructor call. If the constructor requires arguments, these arguments must be supplied:

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Date today = Date(23,6,1983);
Date xmas(25,12,1990);    // abbreviated form
Date my_birthday;         // error: initializer missing
Date release1_0(10,12);   // error: third argument missing

Since a constructor defines initialization for a class, we can use the {}-initializer notation:

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Date today = Date {23,6,1983};
Date xmas {25,12,1990};      // abbreviated form
Date release1_0 {10,12};     // error: third argument missing

I recommend the {} notation over the () notation for initialization because it is explicit about what is being done (initialization), avoids some potential mistakes, and can be used consistently (§2.2.2, §6.3.5). There are cases where () notation must be used (§4.4.1, §17.3.2.1), but they are rare.

By providing several constructors, we can provide a variety of ways of initializing objects of a type. For example:

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class Date {
    int d, m, y;
public:
    // ...

    Date(int, int, int);     // day, month, year
    Date(int, int);          // day, month, today's year
    Date(int);               // day, today's month and year
    Date();                  // default Date: today
    Date(const char*);       // date in string representation
};

Constructors obey the same overloading rules as do ordinary functions (§12.3). As long as the constructors differ sufficiently in their argument types, the compiler can select the correct one for a use:

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Date today {4};               // 4, today.m, today.y
Date july4 {"July 4, 1983"};
Date guy {5,11};              // 5, November, today.y
Date now;                     // default initialized as today
Date start {};                // default initialized as today

The proliferation of constructors in the Date example is typical. When designing a class, a programmer is always tempted to add features just because somebody might want them. It takes more thought to carefully decide what features are really needed and to include only those. However, that extra thought typically leads to smaller and more comprehensible programs. One way of reducing the number of related functions is to use default arguments (§12.2.5). For Date, each argument can be given a default value interpreted as “pick the default: today.”

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class Date {
    int d, m, y;
public:
    Date(int dd =0, int mm =0, int yy =0);
    // ...
};

Date::Date(int dd, int mm, int yy)
{
    d = dd ? dd : today.d;
    m = mm ? mm : today.m;
    y = yy ? yy : today.y;

    // check that the Date is valid
}

When an argument value is used to indicate “pick the default,” the value chosen must be outside the set of possible values for the argument. For day and month, this is clearly so, but for year, zero may not be an obvious choice. Fortunately, there is no year zero on the European calendar; 1AD (year==1) comes immediately after 1BC (year==–1).

Alternatively, we could use the default values directly as default arguments:

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class Date {
    int d, m, y;
public:
    Date(int dd =today.d, int mm =today.m, int yy =today.y);
    // ...
};

Date::Date(int dd, int mm, int yy)
{
    // check that the Date is valid
}

However, I chose to use 0 to avoid building actual values into Date’s interface. That way, we have the option to later improve the implementation of the default.

Note that by guaranteeing proper initialization of objects, the constructors greatly simplify the implementation of member functions. Given constructors, other member functions no longer have to deal with the possibility of uninitialized data (§16.3.1).

16.2.6. explicit Constructors

By default, a constructor invoked by a single argument acts as an implicit conversion from its argument type to its type. For example:

complex<double> d {1};     // d=={1,0} (§5.6.2)

Such implicit conversions can be extremely useful. Complex numbers are an example: if we leave out the imaginary part, we get a complex number on the real axis. That’s exactly what mathematics requires. However, in many cases, such conversions can be a significant source of confusion and errors. Consider Date:

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void my_fct(Date d);

void f()
{
    Date d {15}; // plausible: x becomes {15,today.m,today.y}
    // ...
    my_fct(15);  // obscure
    d = 15;      // obscure
    // ...
}

At best, this is obscure. There is no clear logical connection between the number 15 and a Date independently of the intricacies of our code.

Fortunately, we can specify that a constructor is not used as an implicit conversion. A constructor declared with the keyword explicit can only be used for initialization and explicit conversions. For example:

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class Date {
    int d, m, y;
public:
    explicit Date(int dd =0, int mm =0, int yy =0);
    // ...
};

Date d1 {15};          // OK: considered explicit
Date d2 = Date{15};    // OK: explicit
Date d3 = {15};        // error: = initialization does not do implicit conversions
Date d4 = 15;          // error: = initialization does not do implicit conversions

void f()
{
    my_fct(15);        // error: argument passing does not do implicit conversions
    my_fct({15});      // error: argument passing does not do implicit conversions
    my_fct(Date{15});  // OK: explicit
   // ...
}

An initialization with an = is considered a copy initialization. In principle, a copy of the initializer is placed into the initialized object. However, such a copy may be optimized away (elided), and a move operation (§3.3.2, §17.5.2) may be used if the initializer is an rvalue (§6.4.1). Leaving out the = makes the initialization explicit. Explicit initialization is known as direct initialization.

By default, declare a constructor that can be called with a single argument explicit. You need a good reason not to do so (as for complex). If you define an implicit constructor, it is best to document your reason or a maintainer may suspect that you were forgetful (or ignorant).

If a constructor is declared explicit and defined outside the class, that explicit cannot be repeated:

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class Date {
   int d, m, y;
public:
    explicit Date(int dd);
    // ...
};

Date::Date(int dd) { /* ... */ }               // OK
explicit Date::Date(int dd) { /* ... */ }      // error

Most examples where explicit is important involve a single constructor argument. However, explicit can also be useful for constructors with zero or more than one argument. For example:

struct X {
    explicit X();
    explicit X(int,int);
};

X x1 = {};             // error: implicit
X x2 = {1,2};          // error: implicit

X x3 {};               // OK: explicit
X x4 {1,2};            // OK: explicit

int f(X);

int i1 = f({});        // error: implicit
int i2 = f({1,2});     // error: implicit

int i3 = f(X{});       // OK: explicit
int i4 = f(X{1,2});    // OK: explicit

The distinction between direct and copy initialization is maintained for list initialization (§17.3.4.3).

16.2.7. In-Class Initializers

When we use several constructors, member initialization can become repetitive. For example:

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class Date {
     int d, m, y;
public:
     Date(int, int, int);        // day, month, year
     Date(int, int);             // day, month, today's year
     Date(int);                  // day, today's month and year
     Date();                     // default Date: today
     Date(const char*);          // date in string representation
    // ...
};

We can deal with that by introducing default arguments to reduce the number of constructors (§16.2.5). Alternatively, we can add initializers to data members:

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class Date {
     int d {today.d};
     int m {today.m};
     int y {today.y};
public:
     Date(int, int, int);        // day, month, year
     Date(int, int);             // day, month, today's year
     Date(int);                  // day, today's month and year
     Date();                     // default Date: today
     Date(const char*);          // date in string representation
     // ...

Now, each constructor has the d, m, and y initialized unless it does it itself. For example:

Date::Date(int dd)
     :d{dd}
{
     // check that the Date is valid
}

This is equivalent to:

Date::Date(int dd)
     :d{dd}, m{today.m}, y{today.y}
{
     // check that the Date is valid
}

16.2.8. In-Class Function Definitions

A member function defined within the class definition – rather than simply declared there – is taken to be an inline (§12.1.5) member function. That is, in-class definition of member functions is for small, rarely modified, frequently used functions. Like the class definition it is part of, a member function defined in-class can be replicated in several translation units using #include. Like the class itself, the member function’s meaning must be the same wherever it is #included (§15.2.3).

A member can refer to another member of its class independently of where that member is defined (§6.3.4). Consider:

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class Date {
public:
    void add_month(int n) { m+=n; }    // increment the Date's m
    // ...
private:
    int d, m, y;
};

That is, function and data member declarations are order independent. I could equivalently have written:

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class Date {
public:
     void add_month(int n) { m+=n; }    // increment the Date's m
     // ...
private:
     int d, m, y;
};

inline void Date::add_month(int n) // add n months
{
     m+=n;      // increment the Date's m
}

This latter style is often used to keep class definitions simple and easy to read. It also provides a textual separation of a class’s interface and implementation.

Obviously, I simplified the definition of Date::add_month; just adding n and hoping to hit a good date is too naive (§16.3.1).

16.2.9. Mutability

We can define a named object as a constant or as a variable. In other words, a name can refer to an object that holds an immutable or a mutable value. Since the precise terminology can be a bit clumsy, we end up referring to some variables as being constant or briefer still to const variables. However odd that may sound to a native English speaker, the concept is useful and deeply embedded in the C++ type system. Systematic use of immutable objects leads to more comprehensible code, to more errors being found early, and sometimes to improved performance. In particular, immutability is a most useful property in a multi-threaded program (§5.3, Chapter 41).

To be useful beyond the definition of simple constants of built-in types, we must be able to define functions that operate on const objects of user-defined types. For freestanding functions that means functions that take const T& arguments. For classes it means that we must be able to define member functions that work on const objects.

16.2.9.1. Constant Member Functions

The Date as defined so far provides member functions for giving a Date a value. Unfortunately, we didn’t provide a way of examining the value of a Date. This problem can easily be remedied by adding functions for reading the day, month, and year:

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class Date {
    int d, m, y;
public:
    int day() const { return d; }
    int month() const { return m; }
    int year() const;

    void add_year(int n);     //add n years
    // ...
};

The const after the (empty) argument list in the function declarations indicates that these functions do not modify the state of a Date.

Naturally, the compiler will catch accidental attempts to violate this promise. For example:

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int Date::year() const
{
     return ++y;    // error: attempt to change member value in const function
}

When a const member function is defined outside its class, the const suffix is required:

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int Date::year()     // error: const missing in member function type
{
     return y;
}

In other words, const is part of the type of Date::day(), Date::month(), and Date::year().

A const member function can be invoked for both const and non-const objects, whereas a non-const member function can be invoked only for non-const objects. For example:

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void f(Date& d, const Date& cd)
{
     int i = d.year();    // OK
     d.add_year(1);       // OK

     int j = cd.year();   // OK
     cd.add_year(1);      // error: cannot change value of a const Date
}

16.2.9.2. Physical and Logical Constness

Occasionally, a member function is logically const, but it still needs to change the value of a member. That is, to a user, the function appears not to change the state of its object, but some detail that the user cannot directly observe is updated. This is often called logical constness. For example, the Date class might have a function returning a string representation. Constructing this representation could be a relatively expensive operation. Therefore, it would make sense to keep a copy so that repeated requests would simply return the copy, unless the Date’s value had been changed. Caching values like that is more common for more complicated data structures, but let’s see how it can be achieved for a Date:

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class Date {
public:
    // ...
    string string_rep() const;    // string representation
private:
    bool cache_valid;
    string cache;
    void compute_cache_value(); // fill cache
    // ...
};

From a user’s point of view, string_rep doesn’t change the state of its Date, so it clearly should be a const member function. On the other hand, the cache and cache_valid members must change occasionally for the design to make sense.

Such problems could be solved through brute force using a cast, for example, a const_cast (§11.5.2). However, there are also reasonably elegant solutions that do not involve messing with type rules.

16.2.9.3. mutable

We can define a member of a class to be mutable, meaning that it can be modified even in a const object:

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class Date {
public:
    // ...
    string string_rep() const;          // string representation
private:
    mutable bool cache_valid;
    mutable string cache;
    void compute_cache_value() const;   // fill (mutable) cache
    // ...
};

Now we can define string_rep() in the obvious way:

string Date::string_rep() const
{
     if (!cache_valid) {
           compute_cache_value();
           cache_valid = true;
     }
     return cache;
}

We can now use string_rep() for both const and non-const objects. For example:

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void f(Date d, const Date cd)
{
     string s1 = d.string_rep();
     string s2 = cd.string_rep();      // OK!
     // ...
}

16.2.9.4. Mutability through Indirection

Declaring a member mutable is most appropriate when only a small part of a representation of a small object is allowed to change. More complicated cases are often better handled by placing the changing data in a separate object and accessing it indirectly. If that technique is used, the string-with-cache example becomes:

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struct cache {
     bool valid;
     string rep;
};

class Date {
public:
     // ...
     string string_rep() const;           // string representation
private:
     cache* c;                            // initialize in constructor
     void compute_cache_value() const;    // fill what cache refers to
     // ...
};

string Date::string_rep() const
{
     if (!c–>valid) {
           compute_cache_value();
           c–>valid = true;
     }
     return c–>rep;
}

The programming techniques that support a cache generalize to various forms of lazy evaluation.

Note that const does not apply (transitively) to objects accessed through pointers or references. The human reader may consider such an object as “a kind of subobject,” but the compiler does not know such pointers or references to be any different from any others. That is, a member pointer does not have any special semantics that distinguish it from other pointers.

16.2.10. Self-Reference

The state update functions add_year(), add_month(), and add_day() (§16.2.3) were defined not to return values. For such a set of related update functions, it is often useful to return a reference to the updated object so that the operations can be chained. For example, we would like to write:

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void f(Date& d)
{
    // ...
    d.add_day(1).add_month(1).add_year(1);
    // ...
}

to add a day, a month, and a year to d. To do this, each function must be declared to return a reference to a Date:

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class Date {
    // ...
    Date& add_year(int n);  // add n years
    Date& add_month(int n); // add n months
    Date& add_day(int n);   // add n days
};

Each (non-static) member function knows for which object it was invoked and can explicitly refer to it. For example:

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Date& Date::add_year(int n)
{
    if (d==29 && m==2 && !leapyear(y+n)) { // beware of February 29
          d = 1;
          m = 3;
    }
    y += n;
    return *this;
}

The expression *this refers to the object for which a member function is invoked.

In a non-static member function, the keyword this is a pointer to the object for which the function was invoked. In a non-const member function of class X, the type of this is X*. However, this is considered an rvalue, so it is not possible to take the address of this or to assign to this. In a const member function of class X, the type of this is const X* to prevent modification of the object itself (see also §7.5).

Most uses of this are implicit. In particular, every reference to a non-static member from within a class relies on an implicit use of this to get the member of the appropriate object. For example, the add_year function could equivalently, but tediously, have been defined like this:

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Date& Date::add_year(int n)
{
    if (this–>d==29 && this–>m==2 && !leapyear(this–>y+n)) {
          this–>d = 1;
          this–>m = 3;
    }
    this–>y += n;
    return *this;
}

One common explicit use of this is in linked-list manipulation. For example:

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struct Link {
    Link* pre;
    Link* suc;
    int data;

    Link* insert(int x)   // insert x before this
    {
        return pre = new Link{pre,this,x};
    }
    void remove() // remove and destroy this     
    {
        if (pre) pre–>suc = suc;
        if (suc) suc–>pre = pre;
        delete this;
    }

    // ...
};

Explicit use of this is required for access to members of base classes from a derived class that is a template (§26.3.7).

16.2.11. Member Access

A member of a class X can be accessed by applying the . (dot) operator to an object of class X or by applying the –> (arrow) operator to a pointer to an object of class X. For example:

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struct X {
     void f();
     int m;
};

void user(X x, X* px)
{
     m = 1;       // error: there is no m in scope
     x.m = 1;     // OK
     x–>m = 1;    // error: x is not a pointer
     px–>m = 1;   // OK
     px.m = 1;    // error: px is a pointer
}

Obviously, there is a bit of redundancy here: the compiler knows whether a name refers to an X or to an X*, so a single operator would have been sufficient. However, a programmer might be confused, so from the first days of C the rule has been to use separate operators.

From inside a class no operator is needed. For example:

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void X::f()
{
     m = 1;    // OK: "this->m = 1;" (§16.2.10)
}

That is, an unqualified member name acts as if it had been prefixed by this–>. Note that a member function can refer to the name of a member before it has been declared:

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struct X {
     int f() { return m; }   // fine: return this X's m
     int m;
};

If we want to refer to a member in general, rather than to a member of a particular object, we qualify by the class name followed by ::. For example:

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struct S {
     int m;
     int f();
     static int sm;
};

int X::f() { return m; }     // X's f
int X::sm {7};               // X's static member sm (§16.2.12)
int (S::*) pmf() {&S::f};    // X's member f

That last construct (a pointer to member) is fairly rare and esoteric; see §20.6. I mention it here just to emphasize the generality of the rule for ::.

16.2.12. [static] Members

The convenience of a default value for Dates was bought at the cost of a significant hidden problem. Our Date class became dependent on the global variable today. This Date class can be used only in a context in which today is defined and correctly used by every piece of code. This is the kind of constraint that causes a class to be useless outside the context in which it was first written. Users get too many unpleasant surprises trying to use such context-dependent classes, and maintenance becomes messy. Maybe “just one little global variable” isn’t too unmanageable, but that style leads to code that is useless except to its original programmer. It should be avoided.

Fortunately, we can get the convenience without the encumbrance of a publicly accessible global variable. A variable that is part of a class, yet is not part of an object of that class, is called a static member. There is exactly one copy of a static member instead of one copy per object, as for ordinary non-static members (§6.4.2). Similarly, a function that needs access to members of a class, yet doesn’t need to be invoked for a particular object, is called a static member function.

Here is a redesign that preserves the semantics of default constructor values for Date without the problems stemming from reliance on a global:

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class Date {
    int d, m, y;
    static Date default_date;
public:
    Date(int dd =0, int mm =0, int yy =0);
    // ...
    static void set_default(int dd, int mm, int yy); // set default_date to Date(dd,mm,yy)
};

We can now define the Date constructor to use default_date like this:

Date::Date(int dd, int mm, int yy)
{
    d = dd ? dd : default_date.d;
    m = mm ? mm : default_date.m;
    y = yy ? yy : default_date.y;

    // ... check that the Date is valid ...
}

Using set_default(), we can change the default date when appropriate. A static member can be referred to like any other member. In addition, a static member can be referred to without mentioning an object. Instead, its name is qualified by the name of its class. For example:

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void f()
{
     Date::set_default(4,5,1945);  // call Date's static member set_default()
}

If used, a static member – a function or data member – must be defined somewhere. The keyword static is not repeated in the definition of a static member. For example:

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Date Date::default_date {16,12,1770};         // definition of Date::default_date

void Date::set_default(int d, int m, int y)   // definition of Date::set_default
{
     default_date = {d,m,y};                  // assign new value to default_date
}

Now, the default value is Beethoven’s birth date – until someone decides otherwise.

Note that Date{} serves as a notation for the value of Date::default_date. For example:

Date copy_of_default_date = Date{};

void f(Date);

void g()
{
     f(Date{});
}

Consequently, we don’t need a separate function for reading the default date. Furthermore, where the target type is unambiguously a Date, plain {} is sufficient. For example:

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void f1(Date);

void f2(Date);
void f2(int);

void g()
{
     f1({});       // OK: equivalent to f1(Date{})
     f2({}):       // error: ambiguous: f2(int) or f2(Date)?
     f2(Date{});   // OK

In multi-threaded code, static data members require some kind of locking or access discipline to avoid race conditions (§5.3.4, §41.2.4). Since multi-threading is now very common, it is unfortunate that use of static data members was quite popular in older code. Older code tends to use static members in ways that imply race conditions.

16.2.13. Member Types

Types and type aliases can be members of a class. For example:

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template<typename T>
class Tree {
     using value_type = T;                 // member alias
     enum Policy { rb, splay, treeps };    // member enum
     class Node {                          // member class
          Node* right;
          Node* left;
          value_type value;
     public:
          void f(Tree*);
     };
     Node* top;
public:
     void g(const T&);
     // ...
};

A member class (often called a nested class) can refer to types and static members of its enclosing class. It can only refer to non-static members when it is given an object of the enclosing class to refer to. To avoid getting into the intricacies of binary trees, I use purely technical “f() and g()”-style examples.

A nested class has access to members of its enclosing class, even to private members (just as a member function has), but has no notion of a current object of the enclosing class. For example:

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template<typename T>
void Tree::Node::f(Tree* p)
{
     top = right;                          // error: no object of type Tree specified
     p–>top = right;                       // OK
     value_type v = left–>value;           // OK: value_type is not associated with an object
}

A class does not have any special access rights to the members of its nested class. For example:

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template<typename T>
void Tree::g(Tree::Node* p)
{
     value_type val = right–>value;           // error: no object of type Tree::Node
     value_type v = p–>right–>value;          // error: Node::right is private
     p–>f(this);                              // OK
}

Member classes are more a notational convenience than a feature of fundamental importance. On the other hand, member aliases are important as the basis of generic programming techniques relying on associated types (§28.2.4, §33.1.3). Member enums are often an alternative to enum classes when it comes to avoiding polluting an enclosing scope with the names of enumerators (§8.4.1).

16.3. Concrete Classes

The previous section discussed bits and pieces of the design of a Date class in the context of introducing the basic language features for defining classes. Here, I reverse the emphasis and discuss the design of a simple and efficient Date class and show how the language features support this design.

Small, heavily used abstractions are common in many applications. Examples are Latin characters, Chinese characters, integers, floating-point numbers, complex numbers, points, pointers, coordinates, transforms, (pointer,offset) pairs, dates, times, ranges, links, associations, nodes, (value,unit) pairs, disk locations, source code locations, currency values, lines, rectangles, scaled fixed-point numbers, numbers with fractions, character strings, vectors, and arrays. Every application uses several of these. Often, a few of these simple concrete types are used heavily. A typical application uses a few directly and many more indirectly from libraries.

C++ directly supports a few of these abstractions as built-in types. However, most are not, and cannot be, directly supported by the language because there are too many of them. Furthermore, the designer of a general-purpose programming language cannot foresee the detailed needs of every application. Consequently, mechanisms must be provided for the user to define small concrete types. Such types are called concrete types or concrete classes to distinguish them from abstract classes (§20.4) and classes in class hierarchies (§20.3, §21.2).

A class is called concrete (or a concrete class) if its representation is part of its definition. This distinguishes it from abstract classes (§3.2.2, §20.4) which provide an interface to a variety of implementations. Having the representation available allows us:

• To place objects on the stack, in statically allocated memory, and in other objects

• To copy and move objects (§3.3, §17.5)

• To refer directly to named objects (as opposed to accessing through pointers and references)

This makes concrete classes simple to reason about and easy for the compiler to generate optimal code for. Thus, we prefer concrete classes for small, frequently used, and performance-critical types, such as complex numbers (§5.6.2), smart pointers (§5.2.1), and containers (§4.4).

It was an early explicit aim of C++ to support the definition and efficient use of such user-defined types very well. They are a foundation of elegant programming. As usual, the simple and mundane is statistically far more significant than the complicated and sophisticated. In this light, let us build a better Date class:

Click here to view code image

namespace Chrono {

    enum class Month { jan=1, feb, mar, apr, may, jun, jul, aug, sep, oct, nov, dec };

    class Date {
    public:       // public interface:
         class Bad_date { }; // exception class

         explicit Date(int dd ={}, Month mm ={}, int yy ={});           // {} means "pick a default"
    // nonmodifying functions for examining the Date:
         int day() const;
         Month month() const;
         int year() const;

         string string_rep() const;                  // string representation
         void char_rep(char s[], in max) const;      // C-style string representation

   // (modifying) functions for changing the Date:
         Date& add_year(int n);                      // add n years
         Date& add_month(int n);                     // add n months
         Date& add_day(int n);                       // add n days
   private:
         bool is_valid();                            // check if this Date represents a date
         int d, m, y;                                // representation
   };

   bool is_date(int d, Month m, int y);              // true for valid date
   bool is_leapyear(int y);                          // true if y is a leap year

   bool operator==(const Date& a, const Date& b);
   bool operator!=(const Date& a, const Date& b);

   const Date& default_date();                     // the default date
   ostream& operator<<(ostream& os, const Date& d);       // print d to os
   istream& operator>>(istream& is, Date& d);             // read Date from is into d
} // Chrono

This set of operations is fairly typical for a user-defined type:

[1] A constructor specifying how objects/variables of the type are to be initialized (§16.2.5).

[2] A set of functions allowing a user to examine a Date. These functions are marked const to indicate that they don’t modify the state of the object/variable for which they are called.

[3] A set of functions allowing the user to modify Dates without actually having to know the details of the representation or fiddle with the intricacies of the semantics.

[4] Implicitly defined operations that allow Dates to be freely copied (§16.2.2).

[5] A class, Bad_date, to be used for reporting errors as exceptions.

[6] A set of useful helper functions. The helper functions are not members and have no direct access to the representation of a Date, but they are identified as related by the use of the namespace Chrono.

I defined a Month type to cope with the problem of remembering the month/day order, for example, to avoid confusion about whether the 7th of June is written {6,7} (American style) or {7,6} (European style).

I considered introducing separate types Day and Year to cope with possible confusion of Date{1995,Month::jul,27} and Date{27,Month::jul,1995}. However, these types would not be as useful as the Month type. Almost all such errors are caught at run time anyway – the 26th of July year 27 is not a common date in my work. Dealing with historical dates before year 1800 or so is a tricky issue best left to expert historians. Furthermore, the day of the month can’t be properly checked in isolation from its month and year.

To save the user from having to explicitly mention year and month even when they are implied by context, I added a mechanism for providing a default. Note that for Month the {} gives the (default) value 0 just as for integers even though it is not a valid Month (§8.4). However, in this case, that’s exactly what we want: an otherwise illegal value to represent “pick the default.” Providing a default (e.g., a default value for Date objects) is a tricky design problem. For some types, there is a conventional default (e.g., 0 for integers); for others, no default makes sense; and finally, there are some types (such as Date) where the question of whether to provide a default is nontrivial. In such cases, it is best – at least initially – not to provide a default value. I provide one for Date primarily to be able to discuss how to do so.

I omitted the cache technique from §16.2.9 as unnecessary for a type this simple. If needed, it can be added as an implementation detail without affecting the user interface.

Here is a small – and contrived – example of how Dates can be used:

Click here to view code image

void f(Date& d)
{
     Date lvb_day {16,Month::dec,d.year()};

     if (d.day()==29 && d.month()==Month::feb) {
           // ...
     }

     if (midnight()) d.add_day(1);

     cout << "day after:" << d+1 << '\n';

     Date dd; // initialized to the default date
     cin>>dd;
     if (dd==d) cout << "Hurray!\n";
}

This assumes that the addition operator, +, has been declared for Dates. I do that in §16.3.3.

Note the use of explicit qualification of dec and feb by Month. I used an enum class (§8.4.1) specifically to be able to use short names for the months, yet also ensure that their use would not be obscure or ambiguous.

Why is it worthwhile to define a specific type for something as simple as a date? After all, we could just define a simple data structure:

struct Date {
     int day, month, year;
};

Each programmer could then decide what to do with it. If we did that, though, every user would either have to manipulate the components of Dates directly or provide separate functions for doing so. In effect, the notion of a date would be scattered throughout the system, which would make it hard to understand, document, or change. Inevitably, providing a concept as only a simple structure causes extra work for every user of the structure.

Also, even though the Date type seems simple, it takes some thought to get right. For example, incrementing a Date must deal with leap years, with the fact that months are of different lengths, and so on. Also, the day-month-and-year representation is rather poor for many applications. If we decided to change it, we would need to modify only a designated set of functions. For example, to represent a Date as the number of days before or after January 1, 1970, we would need to change only Date’s member functions.

To simplify, I decided to eliminate the notion of changing the default date. Doing so eliminates some opportunities for confusion and the likelihood of race conditions in a multi-threaded program (§5.3.1). I seriously considered eliminating the notion of a default date altogether. That would have forced users to consistently explicitly initialize their Dates. However, that can be inconvenient and surprising, and more importantly common interfaces used for generic code require default construction (§17.3.3). That means that I, as the designer of Date, have to pick the default date. I chose January 1, 1970, because that is the starting point for the C and C++ standard-library time routines (§35.2, §43.6). Obviously, eliminating set_default_date() caused some loss of generality of Date. However, design – including class design – is about making decisions, rather than just deciding to postpone them or to leave all options open for users.

To preserve an opportunity for future refinement, I declared default_date() as a helper function:

const Date& Chrono::default_date();

That doesn’t say anything about how the default date is actually set.

16.3.1. Member Functions

Naturally, an implementation for each member function must be provided somewhere. For example:

Click here to view code image

Date::Date(int dd, Month mm, int yy)
     :d{dd}, m{mm}, y{yy}
{
     if (y == 0) y = default_date().year();
     if (m == Month{}) m = default_date().month();
     if (d == 0) d = default_date().day();

     if (!is_valid()) throw Bad_date();
}

The constructor checks that the data supplied denotes a valid Date. If not, say, for {30,Month::feb,1994}, it throws an exception (§2.4.3.1, Chapter 13), which indicates that something went wrong. If the data supplied is acceptable, the obvious initialization is done. Initialization is a relatively complicated operation because it involves data validation. This is fairly typical. On the other hand, once a Date has been created, it can be used and copied without further checking. In other words, the constructor establishes the invariant for the class (in this case, that it denotes a valid date). Other member functions can rely on that invariant and must maintain it. This design technique can simplify code immensely (see §2.4.3.2, §13.4).

I’m using the value Month{} – which doesn’t represent a month and has the integer value 0 – to represent “pick the default month.” I could have defined an enumerator in Month specifically to represent that. But I decided that it was better to use an obviously anomalous value to represent “pick the default month” rather than give the appearance that there were 13 months in a year. Note that Month{}, meaning 0, can be used because it is within the range guaranteed for the enumeration Month (§8.4).

I use the member initializer syntax (§17.4) to initialize the members. After that, I check for 0 and modify the values as needed. This clearly does not provide optimal performance in the (hopefully rare) case of an error, but the use of member initializers leaves the structure of the code obvious. This makes the style less error-prone and easier to maintain than alternatives. Had I aimed at optimal performance, I would have used three separate constructors rather than a single constructor with default arguments.

I considered making the validation function is_valid() public. However, I found the resulting user code more complicated and less robust than code relying on catching the exception:

Click here to view code image

void fill(vector<Date>& aa)
{
     while (cin) {
           Date d;
           try {
                cin >> d;
           }
           catch (Date::Bad_date) {
                // ... my error handling ...
                continue;
           }
           aa.push_back(d);       // see §4.4.2
     }
}

However, checking that a {d,m,y} set of values is a valid date is not a computation that depends on the representation of a Date, so I implemented is_valid() in terms of a helper function:

bool Date::is_valid()
{
     return is_date(d,m,y);
}

Why have both is_valid() and is_date()? In this simple example, we could manage with just one, but I can imagine systems where is_date() (as here) checks that a (d,m,y)-tuple represents a valid date and where is_valid() does an additional check on whether that date can be reasonably represented. For example, is_valid() might reject dates from before the modern calendar became commonly used.

As is common for such simple concrete types, the definitions of Date’s member functions vary between the trivial and the not-too-complicated. For example:

Click here to view code image

inline int Date::day() const
{
     return d;
}
Date& Date::add_month(int n)
{
     if (n==0) return *this;

     if (n>0) {
           int delta_y = n/12;                   // number of whole years
           int mm = static_cast<int>(m)+n%12;    // number of months ahead
           if (12 < mm) {                        // note: dec is represented by 12
                  ++delta_y;
                  mm –= 12;
           }

           // ... handle the cases where the month mm doesn't have day d ...

           y += delta_y;
           m = static_cast<Month>(mm);
           return *this;
     }

     // ... handle negative n ...

     return *this;
}

I wouldn’t call the code for add_month() pretty. In fact, if I added all the details, it might even approach the complexity of relatively simple real-world code. This points to a problem: adding a month is conceptually simple, so why is our code getting complicated? In this case, the reason is that the d,m,y representation isn’t as convenient for the computer as it is for us. A better representation (for many purposes) would be simply a number of days since a defined “day zero” (e.g., January 1, 1970). That would make computation on Dates simple at the expense of complexity in providing output fit for humans.

Note that assignment and copy initialization are provided by default (§16.2.2). Also, Date doesn’t need a destructor because a Date owns no resources and requires no cleanup when it goes out of scope (§3.2.1.2).

16.3.2. Helper Functions

Typically, a class has a number of functions associated with it that need not be defined in the class itself because they don’t need direct access to the representation. For example:

Click here to view code image

int diff(Date a, Date b); // number of days in the range [a,b) or [b,a)

bool is_leapyear(int y);
bool is_date(int d, Month m, int y);

const Date& default_date();
Date next_weekday(Date d);
Date next_saturday(Date d);

Defining such functions in the class itself would complicate the class interface and increase the number of functions that would potentially need to be examined when a change to the representation was considered.

How are such functions “associated” with class Date? In early C++, as in C, their declarations were simply placed in the same file as the declaration of class Date. Users who needed Dates would make them all available by including the file that defined the interface (§15.2.2). For example:

#include "Date.h"

In addition (or alternatively), we can make the association explicit by enclosing the class and its helper functions in a namespace (§14.3.1):

Click here to view code image

namespace Chrono {            // facilities for dealing with time

    class Date { /* ... */};

    int diff(Date a, Date b);
    bool is_leapyear(int y);
    bool is_date(int d, Month m, int y);
    const Date& default_date();
    Date next_weekday(Date d);
    Date next_saturday(Date d);
    // ...
}

The Chrono namespace would naturally also contain related classes, such as Time and Stopwatch, and their helper functions. Using a namespace to hold a single class is usually an overelaboration that leads to inconvenience.

Naturally, the helper function must be defined somewhere:

Click here to view code image

bool Chrono::is_date(int d, Month m, int y)
{
     int ndays;

     switch (m) {
     case Month::feb:
          ndays = 28+is_leapyear(y);
          break;
     case Month::apr: case Month::jun: case Month::sep: case Month::nov:
          ndays = 30;
          break;
     case Month::jan: case Month::mar: case Month::may: case Month::jul:
     case Month::aug: case Month::oct: case Month::dec:
          ndays = 31;
          break;
     default:
          return false;
     }

     return 1<=d && d<=ndays;
}

I’m deliberately being a bit paranoid here. A Month shouldn’t be outside the jan to dec range, but it is possible (someone might have been sloppy with a cast), so I check.

The troublesome default_date finally becomes:

const Date& Chrono::default_date()
{
    static Date d {1,Month::jan,1970};
    return d;
}

16.3.3. Overloaded Operators

It is often useful to add functions to enable conventional notation. For example, operator==() defines the equality operator, ==, to work for Dates:

Click here to view code image

inline bool operator==(Date a, Date b)      // equality
{
     return a.day()==b.day() && a.month()==b.month() && a.year()==b.year();
}

Other obvious candidates are:

Click here to view code image

bool operator!=(Date, Date);      // inequality
bool operator<(Date, Date);       // less than
bool operator>(Date, Date);       // greater than
// ...

Date& operator++(Date& d) { return d.add_day(1); }          // increase Date by one day
Date& operator––(Date& d) { return d.add_day(–1); }         // decrease Date by one day

Date& operator+=(Date& d, int n) { return d.add_day(n); }   // add n days
Date& operator–=(Date& d, int n) { return d.add_day(–n); }  // subtract n days

Date operator+(Date d, int n) { return d+=n; }              // add n days
Date operator–(Date d, int n) { return d+=n; }              // subtract n days

ostream& operator<<(ostream&, Date d);                      // output d
istream& operator>>(istream&, Date& d);                     // read into d

These operators are defined in Chrono together with Date to avoid overload problems and to benefit from argument-dependent lookup (§14.2.4).

For Date, these operators can be seen as mere conveniences. However, for many types – such as complex numbers (§18.3), vectors (§4.4.1), and function-like objects (§3.4.3, §19.2.2) – the use of conventional operators is so firmly entrenched in people’s minds that their definition is almost mandatory. Operator overloading is discussed in Chapter 18.

For Date, I was tempted to provide += and –= as member functions instead of add_day(). Had I done so, I would have followed a common idiom (§3.2.1.1).

Note that assignment and copy initialization are provided by default (§16.3, §17.3.3).

16.3.4. The Significance of Concrete Classes

I call simple user-defined types, such as Date, concrete types to distinguish them from abstract classes (§3.2.2) and class hierarchies (§20.4), and also to emphasize their similarity to built-in types such as int and char. Concrete classes are used just like built-in types. Concrete types have also been called value types and their use value-oriented programming. Their model of use and the “philosophy” behind their design are quite different from what is often called object-oriented programming (§3.2.4, Chapter 21).

The intent of a concrete type is to do a single, relatively simple thing well and efficiently. It is not usually the aim to provide the user with facilities to modify the behavior of a concrete type. In particular, concrete types are not intended to display run-time polymorphic behavior (see §3.2.3, §20.3.2).

If you don’t like some detail of a concrete type, you build a new one with the desired behavior. If you want to “reuse” a concrete type, you use it in the implementation of your new type exactly as you would have used an int. For example:

Click here to view code image

class Date_and_time {
private:
     Date d;
     Time t;
public:
     Date_and_time(Date d, Time t);
     Date_and_time(int d, Date::Month m, int y, Time t);
     // ...
};

Alternatively, the derived class mechanism discussed in Chapter 20 can be used to define new types from a concrete class by describing the desired differences. The definition of Vec from vector (§4.4.1.2) is an example of this. However, derivation from a concrete class should be done with care and only rarely because of the lack of virtual functions and run-time type information (§17.5.1.4, Chapter 22).

With a reasonably good compiler, a concrete class such as Date incurs no hidden overhead in time or space. In particular, no indirection through pointers is necessary for access to objects of concrete classes, and no “housekeeping” data is stored in objects of concrete classes. The size of a concrete type is known at compile time so that objects can be allocated on the run-time stack (that is, without free-store operations). The layout of an object is known at compile time so that inlining of operations is trivially achieved. Similarly, layout compatibility with other languages, such as C and Fortran, comes without special effort.

A good set of such types can provide a foundation for applications. In particular, they can be used to make interfaces more specific and less error-prone. For example:

Month do_something(Date d);

This is far less likely to be misunderstood or misused than:

int do_something(int d);

Lack of concrete types can lead to obscure programs and time wasted when each programmer writes code to directly manipulate “simple and frequently used” data structures represented as simple aggregates of built-in types. Alternatively, lack of suitable “small efficient types” in an application can lead to gross run-time and space inefficiencies when overly general and expensive classes are used.

16.4. Advice

[1] Represent concepts as classes; §16.1.

[2] Separate the interface of a class from its implementation; §16.1.

[3] Use public data (structs) only when it really is just data and no invariant is meaningful for the data members; §16.2.4.

[4] Define a constructor to handle initialization of objects; §16.2.5.

[5] By default declare single-argument constructors explicit; §16.2.6.

[6] Declare a member function that does not modify the state of its object const; §16.2.9.

[7] A concrete type is the simplest kind of class. Where applicable, prefer a concrete type over more complicated classes and over plain data structures; §16.3.

[8] Make a function a member only if it needs direct access to the representation of a class; §16.3.2.

[9] Use a namespace to make the association between a class and its helper functions explicit; §16.3.2.

[10] Make a member function that doesn’t modify the value of its object a const member function; §16.2.9.1.

[11] Make a function that needs access to the representation of a class but needn’t be called for a specific object a static member function; §16.2.12.

17. Construction, Cleanup, Copy, and Move

Ignorance more frequently begets confidence than does knowledge.

– Charles Darwin

• Introduction

• Constructors and Destructors

Constructors and Invariants; Destructors and Resources; Base and Member Destructors; Calling Constructors and Destructors; virtual Destructors

• Class Object Initialization

Initialization Without Constructors; Initialization Using Constructors; Default Constructors; Initializer-List Constructors

• Member and Base Initialization

Member Initialization; Base Initializers; Delegating Constructors; In-Class Initializers; static Member Initialization

• Copy and Move

Copy; Move

• Generating Default Operations

Explicit Defaults; Default Operations; Using Default Operations; deleted Functions

• Advice

17.1. Introduction

This chapter focuses on technical aspects of an object’s “life cycle”: How do we create an object, how do we copy it, how do we move it around, and how do we clean up after it when it goes away? What are proper definitions of “copy” and “move”? For example:

Click here to view code image

string ident(string arg)       // string passed by value (copied into arg)
{
     return arg;               // return string (move the value of arg out of ident() to a caller)
}

int main ()
{
     string s1 {"Adams"};      // initialize string (construct in s1).
     s1 = indet(s1);           // copy s1 into ident()
                               // move the result of ident(s1) into s1;
                               // s1's value is "Adams".
     string s2 {"Pratchett"};  // initialize string (construct in s2)
     s1 = s2;                  // copy the value of s2 into s1
                               // both s1 and s2 have the value "Pratchett".
}

Clearly, after the call of ident(), the value of s1 ought to be "Adams". We copy the value of s1 into the argument arg, then we move the value of arg out of the function call and (back) into s1. Next, we construct s2 with the value "Prachett" and copy it into s1. Finally, at the exit from main() we destroy the variables s1 and s2. The difference between move and copy is that after a copy two objects must have the same value, whereas after a move the source of the move is not required to have its original value. Moves can be used when the source object will not be used again. They are particularly useful for implementing the notion of moving a resource (§3.2.1.2, §5.2).

Several functions are used here:

• A constructor initializing a string with a string literal (used for s1 and s2)

• A copy constructor copying a string (into the function argument arg)

• A move constructor moving the value of a string (from arg out of ident() into a temporary variable holding the result of ident(s1))

• A move assignment moving the value of a string (from the temporary variable holding the result of ident(s1) into s1)

• A copy assignment copying a string (from s2 into s1)

• A destructor releasing the resources owned by s1, s2, and the temporary variable holding the result of ident(s1)

An optimizer can eliminate some of this work. For example, in this simple example the temporary variable is typically eliminated. However, in principle, these operations are executed.

Constructors, copy and move assignment operations, and destructors directly support a view of lifetime and resource management. An object is considered an object of its type after its constructor completes, and it remains an object of its type until its destructor starts executing. The interaction between object lifetime and errors is explored further in §13.2 and §13.3. In particular, this chapter doesn’t discuss the issue of half-constructed and half-destroyed objects.

Construction of objects plays a key role in many designs. This wide variety of uses is reflected in the range and flexibility of the language features supporting initialization.

Constructors, destructors, and copy and move operations for a type are not logically separate. We must define them as a matched set or suffer logical or performance problems. If a class X has a destructor that performs a nontrivial task, such as free-store deallocation or lock release, the class is likely to need the full complement of functions:

Click here to view code image

class X {
     X(Sometype);             // "ordinary constructor": create an object
     X();                     // default constructor
     X(const X&);             // copy constructor
     X(X&&);                  // move constructor
     X& operator=(const X&);  // copy assignment: clean up target and copy
     X& operator=(X&&);       // move assignment: clean up target and move
     ~X();                    // destructor: clean up
     // ...
};

There are five situations in which an object is copied or moved:

• As the source of an assignment

• As an object initializer

• As a function argument

• As a function return value

• As an exception

In all cases, the copy or move constructor will be applied (unless it can be optimized away).

In addition to the initialization of named objects and objects on the free store, constructors are used to initialize temporary objects (§6.4.2) and to implement explicit type conversion (§11.5).

Except for the “ordinary constructor,” these special member functions can be generated by the compiler; see §17.6.

This chapter is full of rules and technicalities. Those are necessary for a full understanding, but most people just learn the general rules from examples.

17.2. Constructors and Destructors

We can specify how an object of a class is to be initialized by defining a constructor (§16.2.5, §17.3). To complement constructors, we can define a destructor to ensure “cleanup” at the point of destruction of an object (e.g., when it goes out of scope). Some of the most effective techniques for resource management in C++ rely on constructor/destructor pairs. So do other techniques relying on a pair of actions, such as do/undo, start/stop, before/after, etc. For example:

Click here to view code image

struct Tracer {
     string mess;
     Tracer(const string& s) :mess{s} { clog << mess; }
     ~Tracer() {clog << "~" << mess; }
};

void f(const vector<int>& v)
{
     Tracer tr {"in f()\n"};
     for (auto x : v) {
          Tracer tr {string{"v loop "}+to<string>(x)+'\n'}; // §25.2.5.1
          // ...
     }
}

We could try a call:

f({2,3,5});

This would print to the logging stream:

in_f()
v loop 2
~v loop 2
v loop 3
~v loop 3
v loop 5
~v loop 5
~in_f()

17.2.1. Constructors and Invariants

A member with the same name as its class is called a constructor. For example:

class Vector {
public:
     Vector(int s);
     // ...
};

A constructor declaration specifies an argument list (exactly as for a function) but has no return type. The name of a class cannot be used for an ordinary member function, data member, member type, etc., within the class. For example:

Click here to view code image

struct S {
     S();                   // fine
     void S(int);           // error: no type can be specified for a constructor
     int S;                 // error: the class name must denote a constructor
     enum S { foo, bar };   // error: the class name must denote a constructor
};

A constructor’s job is to initialize an object of its class. Often, that initialization must establish a class invariant, that is, something that must hold whenever a member function is called (from outside the class). Consider:

Click here to view code image

class Vector {
public:
     Vector(int s);
     // ...
private:
     double* elem;  // elem points to an array of sz doubles
     int sz;        // sz is non-negative
};

Here (as is often the case), the invariant is stated as comments: “elem points to an array of sz doubles” and “sz is non-negative.” The constructor must make that true. For example:

Vector::Vector(int s)
{
     if (s<0) throw Bad_size{s};
     sz = s;
     elem = new double[s];
}

This constructor tries to establish the invariant and if it cannot, it throws an exception. If the constructor cannot establish the invariant, no object is created and the constructor must ensure that no resources are leaked (§5.2, §13.3). A resource is anything we need to acquire and eventually (explicitly or implicitly) give back (release) once we are finished with it. Examples of resources are memory (§3.2.1.2), locks (§5.3.4), file handles (§13.3), and thread handles (§5.3.1).

Why would you define an invariant?

• To focus the design effort for the class (§2.4.3.2)

• To clarify the behavior of the class (e.g., under error conditions; §13.2)

• To simplify the definition of member functions (§2.4.3.2, §16.3.1)

• To clarify the class’s management of resources (§13.3)

• To simplify the documentation of the class

On average, the effort to define an invariant ends up saving work.

17.2.2. Destructors and Resources

A constructor initializes an object. In other words, it creates the environment in which the member functions operate. Sometimes, creating that environment involves acquiring a resource – such as a file, a lock, or some memory – that must be released after use (§5.2, §13.3). Thus, some classes need a function that is guaranteed to be invoked when an object is destroyed in a manner similar to the way a constructor is guaranteed to be invoked when an object is created. Inevitably, such a function is called a destructor. The name of a destructor is ~ followed by the class name, for example ~Vector(). One meaning of ~ is “complement” (§11.1.2), and a destructor for a class complements its constructors. A destructor does not take an argument, and a class can have only one destructor. Destructors are called implicitly when an automatic variable goes out of scope, an object on the free store is deleted, etc. Only in very rare circumstances does the user need to call a destructor explicitly (§17.2.4).

Destructors typically clean up and release resources. For example:

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class Vector {
public:
     Vector(int s) :elem{new double[s]}, sz{s} { };           // constructor: acquire memory
     ~Vector() { delete[] elem; }                             // destructor: release memory
     // ...
private:
     double* elem;   // elem points to an array of sz doubles
     int sz;         // sz is non-negative
};

For example:

Vector* f(int s)
{
     Vector v1(s);
     // ...
     return new Vector(s+s);
}

void g(int ss)
{
     Vector* p = f(ss);
     // ...
     delete p;
}

Here, the Vector v1 is destroyed upon exit from f(). Also, the Vector created on the free store by f() using new is destroyed by the call of delete. In both cases, Vector’s destructor is invoked to free (deallocate) the memory allocated by the constructor.

What if the constructor failed to acquire enough memory? For example, s*sizeof(double) or (s+s)*sizeof(double) may be larger than the amount of available memory (measured in bytes). In that case, an exception std::bad_alloc (§11.2.3) is thrown by new and the exception-handling mechanism invokes the appropriate destructors so that all memory that has been acquired (and only that) is freed (§13.5.1).

This style of constructor/destructor-based resource management is called Resource Acquisition Is Initialization or simply RAII (§5.2, §13.3).

A matching constructor/destructor pair is the usual mechanism for implementing the notion of a variably sized object in C++. Standard-library containers, such as vector and unordered_map, use variants of this technique for providing storage for their elements.

A type that has no destructor declared, such as a built-in type, is considered to have a destructor that does nothing.

A programmer who declares a destructor for a class must also decide if objects of that class can be copied or moved (§17.6).

17.2.3. Base and Member Destructors

Constructors and destructors interact correctly with class hierarchies (§3.2.4, Chapter 20). A constructor builds a class object “from the bottom up”:

[1] first, the constructor invokes its base class constructors,

[2] then, it invokes the member constructors, and

[3] finally, it executes its own body.

A destructor “tears down” an object in the reverse order:

[1] first, the destructor executes its own body,

[2] then, it invokes its member destructors, and

[3] finally, it invokes its base class destructors.

In particular, a virtual base is constructed before any base that might use it and destroyed after all such bases (§21.3.5.1). This ordering ensures that a base or a member is not used before it has been initialized or used after it has been destroyed. The programmer can defeat this simple and essential rule, but only through deliberate circumvention involving passing pointers to uninitialized variables as arguments. Doing so violates language rules and the results are usually disastrous.

Constructors execute member and base constructors in declaration order (not the order of initializers): if two constructors used a different order, the destructor could not (without serious overhead) guarantee to destroy in the reverse order of construction. See also §17.4.

If a class is used so that a default constructor is needed, and if the class does not have other constructors, the compiler will try to generate a default constructor. For example:

struct S1 {
     string s;
};

S1 x;     // OK: x.s is initialized to ""

Similarly, memberwise initialization can be used if initializers are needed. For example:

struct X { X(int); };

struct S2 {
     X x;
};

S2 x1;     // error:
S2 x2 {1}; // OK: x2.x is initialized with 1

See also §17.3.1.

17.2.4. Calling Constructors and Destructors

A destructor is invoked implicitly upon exit from a scope or by delete. It is typically not only unnecessary to explicitly call a destructor; doing so would lead to nasty errors. However, there are rare (but important) cases where a destructor must be called explicitly. Consider a container that (like std::vector) maintains a pool of memory into which it can grow and shrink (e.g., using push_back() and pop_back()). When we add an element, the container must invoke its constructor for a specific address:

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void C::push_back(const X& a)
{
     // ...
     new(p) X{a};   // copy construct an X with the value a in address p
     // ...
}

This use of a constructor is known as “placement new” (§11.2.4).

Conversely, when we remove an element, the container needs to invoke its destructor:

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void C::pop_back()
{
     // ...
     p–>~X();      // destroy the X in address p
}

The p–>~X() notation invokes X’s destructor for *p. That notation should never be used for an object that is destroyed in the normal way (by its object going out of scope or being deleted).

For a more complete example of explicit management of objects in a memory area, see §13.6.1.

If declared for a class X, a destructor will be implicitly invoked whenever an X goes out of scope or is deleted. This implies that we can prevent destruction of an X by declaring its destructor =delete (§17.6.4) or private.

Of the two alternatives, using private is the more flexible. For example, we can create a class for which objects can be explicitly destroyed, but not implicitly:

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class Nonlocal {
public:
     // ...
     void destroy() { this–>~Nonlocal(); }     // explicit destruction
private:
     // ...
     ~Nonlocal();                                  // don't destroy implicitly
};

void user()
{
     Nonlocal x;               // error: cannot destroy a Nonlocal
     X* p = new Nonlocal;      // OK
     // ...
     delete p;                 // error: cannot destroy a Nonlocal
     p.destroy();              // OK
}

17.2.5. virtual Destructors

A destructor can be declared to be virtual, and usually should be for a class with a virtual function. For example:

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class Shape {
public:
     // ...
     virtual void draw() = 0;
     virtual ~Shape();
};

class Circle {
public:
     // ...
     void draw();
     ~Circle();        // overrides ~Shape()
     // ...
};

The reason we need a virtual destructor is that an object usually manipulated through the interface provided by a base class is often also deleted through that interface:

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void user(Shape* p)
{
     p–>draw();        // invoke the appropriate draw()
     // ...
     delete p;         // invoke the appropriate destructor
};

Had Shape’s destructor not been virtual that delete would have failed to invoke the appropriate derived class destructor (e.g., ~Circle()). That failure would cause the resources owned by the deleted object (if any) to be leaked.

17.3. Class Object Initialization

This section discusses how to initialize objects of a class with and without constructors. It also shows how to define constructors to accept arbitrarily sized homogeneous initializer lists (such as {1,2,3} and {1,2,3,4,5,6}).

17.3.1. Initialization Without Constructors

We cannot define a constructor for a built-in type, yet we can initialize it with a value of suitable type. For example:

int a {1};
char* p {nullptr};

Similarly, we can initialize objects of a class for which we have not defined a constructor using

• memberwise initialization,

• copy initialization, or

• default initialization (without an initializer or with an empty initializer list).

For example:

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struct Work {
     string author;
     string name;
     int year;
};

Work s9 { "Beethoven",
          "Symphony No. 9 in D minor, Op. 125; Choral",
          1824
      };                         // memberwise initialization

Work currently_playing { s9 };   // copy initialization
Work none {};                    // default initialization

The three members of currently_playing are copies of those of s9.

The default initialization of using {} is defined as initialization of each member by {}. So, none is initialized to {{},{},{}}, which is {"","",0} (§17.3.3).

Where no constructor requiring arguments is declared, it is also possible to leave out the initializer completely. For example:

Work alpha;

void f()
{
     Work beta;
     // ...
}

For this, the rules are not as clean as we might like. For statically allocated objects (§6.4.2), the rules are exactly as if you had used {}, so the value of alpha is {"","",0}. However, for local variables and free-store objects, the default initialization is done only for members of class type, and members of built-in type are left uninitialized, so the value of beta is {"","",unknown}.

The reason for this complication is to improve performance in rare critical cases. For example:

struct Buf {
     int count;
     char buf[16*1024];
};

You can use a Buf as a local variable without initializing it before using it as a target for an input operation. Most local variable initializations are not performance critical, and uninitialized local variables are a major source of errors. If you want guaranteed initialization or simply dislike surprises, supply an initializer, such as {}. For example:

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Buf buf0;       // statically allocated, so initialized by default

void f()
{
     Buf buf1;             // leave elements uninitialized
     Buf buf2 {};          // I really want to zero out those elements

     int* p1 = new int;    // *p1 is uninitialized
     int* p2 = new int{};  // *p2 == 0
     int* p3 = new int{7}; // *p3 == 7
   // ...
}

Naturally, memberwise initialization works only if we can access the members. For example:

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template<class T>
class Checked_pointer { // control access to T* member
public:
     T& operator*();   // check for nullptr and return value
// ...
};

Checked_pointer<int> p {new int{7}};  // error: can't access p.p

If a class has a private non-static data member, it needs a constructor to initialize it.

17.3.2. Initialization Using Constructors

Where memberwise copy is not sufficient or desirable, a constructor can be defined to initialize an object. In particular, a constructor is often used to establish an invariant for its class and to acquire resources necessary to do that (§17.2.1).

If a constructor is declared for a class, some constructor will be used for every object. It is an error to try to create an object without a proper initializer as required by the constructors. For example:

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struct X {
     X(int);
};

X x0;          // error: no initializer
X x1 {};       // error: empty initializer
X x2 {2};      // OK
X x3 {"two"};  // error: wrong initializer type
X x4 {1,2};    // error: wrong number of initializers
X x5 {x4};     // OK: a copy constructor is implicitly defined (§17.6)

Note that the default constructor (§17.3.3) disappears when you define a constructor requiring arguments; after all, X(int) states that an int is required to construct an X. However, the copy constructor does not disappear (§17.3.3); the assumption is that an object can be copied (once properly constructed). Where the latter might cause problems (§3.3.1), you can specifically disallow copying (§17.6.4).

I used the {} notation to make explicit the fact that I am initializing. I am not (just) assigning a value, calling a function, or declaring a function. The {} notation for initialization can be used to provide arguments to a constructor wherever an object can be constructed. For example:

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struct Y : X {
     X m {0};                     // provide default initializer for member m
     Y(int a) :X{a}, m{a} { };    // initialize base and member (§17.4)
     Y() : X{0} { };              // initialize base and member
};

X g {1};    // initialize global variable

void f(int a)
{
     X def {};                    // error: no default value for X
     Y de2 {};                    // OK: use default constructor
     X* p {nullptr};
     X var {2};                   // initialize local variable
     p = new X{4};                // initialize object on free store
     X a[] {1,2,3};               // initialize array elements
     vector<X> v {1,2,3,4};       // initialize vector elements
}

For this reason, {} initialization is sometimes referred to as universal initialization: the notation can be used everywhere. In addition, {} initialization is uniform: wherever you initialize an object of type X with a value v using the {v} notation, the same value of type X (X{v}) is created.

The = and () notations for initialization (§6.3.5) are not universal. For example:

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struct Y : X {
     X m;
     Y(int a) : X(a), m=a { }; // syntax error: can't use = for member initialization
};

X g(1);   // initialize global variable

void f(int a)
{
     X def();                  // function returning an X (surprise!?)
     X* p {nullptr};
     X var = 2;                // initialize local variable
     p = new X=4;              // syntax error: can't use = for new
     X a[](1,2,3);             // error: can't use () for array initialization
     vector<X> v(1,2,3,4);     // error: can't use () for list elements
}

The = and () notations for initialization are not uniform either, but fortunately the examples of that are obscure. If you insist on using = or () initialization, you have to remember where they are allowed and what they mean.

The usual overload resolution rules (§12.3) apply for constructors. For example:

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struct S {
     S(const char*);
     S(double*);
};

S s1 {"Napier"};             // S::S(const char*)
S s2 {new double{1.0}};      // S::S(double*);
S s3 {nullptr};              // ambiguous: S::S(const char*) or S::S(double*)?

Note that the {}-initializer notation does not allow narrowing (§2.2.2). That is another reason to prefer the {} style over () or =.

17.3.2.1. Initialization by Constructors

Using the () notation, you can request to use a constructor in an initialization. That is, you can ensure that for a class, you will get initialization by constructor and not get the memberwise initialization or initializer-list initialization (§17.3.4) that the {} notation also offers. For example:

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struct S1 {
     int a,b;                                          // no constructor
};

struct S2 {
     int a,b;
     S2(int a = 0, int b = 0) : a(aa), b(bb) {}        // constructor
};

S1 x11(1,2);    // error: no constructor
S1 x12 {1,2};   // OK: memberwise initialization

S1 x13(1);      // error: no constructor
S1 x14 {1};     // OK: x14.b becomes 0

S2 x21(1,2);    // OK: use constructor
S2 x22 {1,2};   // OK: use constructor

S2 x23(1);      // OK: use constructor and one default argument
S2 x24 {1};     // OK: use constructor and one default argument

The uniform use of {} initialization only became possible in C++11, so older C++ code uses () and = initialization. Consequently, the () and = may be more familiar to you. However, I don’t know any logical reason to prefer the () notation except in the rare case where you need to distinguish between initialization with a list of elements and a list of constructor arguments. For example:

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vector<int> v1 {77};      // one element with the value 77
vector<int> v2(77);       // 77 elements with the default value 0

This problem – and the need to choose – can occur when a type with an initializer-list constructor (§17.3.4), typically a container, also has an “ordinary constructor” accepting arguments of the element type. In particular, we occasionally must use ()initialization for vectors of integers and floating-point numbers but never need to for vectors of strings of pointers:

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vector<string> v1 {77};       // 77 elements with the default value ""
                              // (vector<string>(std::initializer_list<string>) doesn't accept {77})
vector<string> v2(77);        // 77 elements with the default value ""

vector<string> v3 {"Booh!"};  // one element with the value "Booh!"
vector<string> v4("Booh!");   // error: no constructor takes a string argument

vector<int*> v5 {100,0};      // 100 int*s initialized to nullptr (100 is not an int*)

vector<int*> v6 {0,0};        // 2 int*s initialized to nullptr
vector<int*> v7(0,0);         // empty vector (v7.size()==0)
vector<int*> v8;              // empty vector (v7.size()==0)

The v6 and v7 examples are only of interest to language lawyers and testers.

17.3.3. Default Constructors

A constructor that can be invoked without an argument is called a default constructor. Default constructors are very common. For example:

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class Vector {
public:
     Vector();     // default constructor: no elements
     // ...
};

A default constructor is used if no arguments are specified or if an empty initializer list is provided:

Vector v1;       // OK
Vector v2 {};    // OK

A default argument (§12.2.5) can make a constructor that takes arguments into a default constructor. For example:

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class String {
public:
     String(const char* p = "");     // default constructor: empty string
     // ...
};

String s1;         // OK
String s2 {};      // OK

The standard-library vector and string have such default constructors (§36.3.2, §31.3.2).

The built-in types are considered to have default and copy constructors. However, for a built-in type the default constructor is not invoked for uninitialized non-static variables (§17.3). The default value of a built-in type is 0 for integers, 0.0 for floating-point types, and nullptr for pointers. For example:

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void f()
{
     int a0;                // uninitialized
     int a1();              // function declaration (intended?)

     int a {};              // a becomes 0
     double d {};           // d becomes 0.0
     char* p {};            // p becomes nullptr

     int* p1 = new int;     // uninitialized int
     int* p2 = new int{};   // the int is initialized to 0
}

Constructors for built-in types are most often used for template arguments. For example:

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template<class T>
struct Handle {
     T* p;
     Handle(T* pp = new T{}) :p{pp} { }
     // ...
};

Handle<int> px;     // will generate int{}

The generated int will be initialized to 0.

References and consts must be initialized (§7.7, §7.5). Therefore, a class containing such members cannot be default constructed unless the programmer supplies in-class member initializers (§17.4.4) or defines a default constructor that initializes them (§17.4.1). For example:

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int glob {9};

struct X {
     const int a1 {7};     // OK
     const int a2;         // error: requires a user-defined constructor
     const int& r {9};     // OK
     int& r1 {glob};       // OK
     int& r2;              // error: requires a user-defined constructor
};

X x;      // error: no default constructor for X

An array, a standard-library vector, and similar containers can be declared to allocate a number of default-initialized elements. In such cases, a default constructor is obviously required for a class used as the element type of a vector or array. For example:

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struct S1 { S1(); };                 // has default constructor
struct S2 { S2(string); };           // no default constructor

S1 a1[10];                           // OK: 10 default elements
S2 a2[10];                           // error: cannot initialize elements
S2 a3[] { "alpha", "beta" };         // OK: two elements: S2{"alpha"}, S2{"beta"}

vector<S1> v1(10);                   // OK: 10 default elements
vector<S2> v2(10);                   // error: cannot initialize elements
vector<S2> v3 { "alpha", "beta" };   // OK: two elements: S2{"alpha"}, S2{"beta"}

vector<S2> v2(10,"");                // OK: 10 elements each initialized to S2{""}
vector<S2> v4;                       // OK: no elements

When should a class have a default constructor? A simple-minded technical answer is “when you use it as the element type for an array, etc.” However, a better question is “For what types does it make sense to have a default value?” or even “Does this type have a ‘special’ value we can ‘naturally’ use as a default?” String has the empty string, "", containers have the empty set, {}, and numeric values have zero. The trouble with deciding on a default Date (§16.3) arose because there is no “natural” default date (the Big Bang is too far in the past and not precisely associated with our everyday dates). It is a good idea not to be too clever when inventing default values. For example, the problem with containers of elements without default values is often best solved by not allocating elements until you have proper values for them (e.g., using push_back()).

17.3.4. Initializer-List Constructors

A constructor that takes a single argument of type std::initializer_list is called an initializer-list constructor. An initializer-list constructor is used to construct objects using a {}-list as its initializer value. Standard-library containers (e.g., vector and map) have initializer-list constructors, assignments, etc. (§31.3.2, §31.4.3). Consider:

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vector<double> v = { 1, 2, 3.456, 99.99 };

list<pair<string,string>> languages = {
     {"Nygaard","Simula"}, {"Richards","BCPL"}, {"Ritchie","C"}
};

map<vector<string>,vector<int>> years = {
     { {"Maurice","Vincent", "Wilkes"},{1913, 1945, 1951, 1967, 2000} },
     { {"Martin", "Richards"} {1982, 2003, 2007} },
     { {"David", "John", "Wheeler"}, {1927, 1947, 1951, 2004} }
};

The mechanism for accepting a {}-list is a function (often a constructor) taking an argument of type std::initializer_list<T>. For example:

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void f(initializer_list<int>);

f({1,2});
f({23,345,4567,56789});
f({});     // the empty list

f{1,2};    // error: function call () missing

years.insert({{"Bjarne","Stroustrup"},{1950, 1975, 1985}});

The initializer list can be of arbitrary length but must be homogeneous. That is, all elements must be of the template argument type, T, or implicitly convertible to T.

17.3.4.1. initializer_list Constructor Disambiguation

When you have several constructors for a class, the usual overload resolution rules (§12.3) are used to select the right one for a given set of arguments. For selecting a constructor, default and initializer lists take precedence. Consider:

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struct X {
     X(initializer_list<int>);
     X();
     X(int);
};

X x0 {};    // empty list: default constructor or initializer-list constructor? (the default constructor)
X x1 {1};   // one integer: an int argument or a list of one element? (the initializer-list constructor)

The rules are:

• If either a default constructor or an initializer-list constructor could be invoked, prefer the default constructor.

• If both an initializer-list constructor and an “ordinary constructor” could be invoked, prefer the initializer-list constructor.

The first rule, “prefer the default constructor,” is basically common sense: pick the simplest constructor when you can. Furthermore, if you define an initializer-list constructor to do something with an empty list that differs from what the default constructor does, you probably have a design error on your hands.

The second rule, “prefer the initializer-list constructor,” is necessary to avoid different resolutions based on different numbers of elements. Consider std::vector (§31.4):

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vector<int> v1 {1};         // one element
vector<int> v2 {1,2};       // two elements
vector<int> v3 {1,2,3};     // three elements

vector<string> vs1 {"one"};
vector<string> vs2 {"one", "two"};
vector<string> vs3 {"one", "two", "three"};

In every case, the initializer-list constructor is used. If we really want to invoke the constructor taking one or two integer arguments, we must use the () notation:

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vector<int> v1(1);    // one element with the default value (0)
vector<int> v2(1,2);  // one element with the value 2

17.3.4.2. Use of initializer_lists

A function with an initializer_list<T> argument can access it as a sequence using the member functions begin(), end(), and size(). For example:

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void f(initializer_list<int> args)
{
     for (int i = 0; i!=args.size(); ++i)
           cout << args.begin()[i] << "\n";
}

Unfortunately, initializer_list doesn’t provide subscripting.

An initializer_list<T> is passed by value. That is required by the overload resolution rules (§12.3) and does not impose overhead because an initializer_list<T> object is just a small handle (typically two words) to an array of Ts.

That loop could equivalently have been written:

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void f(initializer_list<int> args)
{
     for (auto p=args.begin(); p!=args.end(); ++p)
           cout << *p << "\n";
}

or:

void f(initializer_list<int> args)
{
     for (auto x : args)
           cout << x << "\n";
}

To explicitly use an initializer_list you must #include the header file in which it is defined: <initializer_list>. However, since vector, map, etc., use initializer_lists, their headers (<vector>, <map>, etc.) already #include <initializer_list>, so you rarely have to do so directly.

The elements of an initializer_list are immutable. Don’t even think about trying to modify their values. For example:

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int f(std::initializer_list<int> x, int val)
{
     *x.begin() = val;         // error: attempt to change the value of an initializer-list element
     return *x.begin();   // OK
}

void g()
{
     for (int i=0; i!=10; ++i)
           cout << f({1,2,3},i) << '\n';
}

Had the assignment in f() succeeded, it would have appeared that the value of 1 (in {1,2,3}) could change. That would have done serious damage to some of our most fundamental concepts. Because initializer_list elements are immutable, we cannot apply a move constructor (§3.3.2, §17.5.2) to them.

A container might implement an initializer-list constructor like this:

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template<class E>
class Vector {
public:
     Vector(std::initializer_list<E> s); // initializer-list constructor
     // ...
private:
     int sz;
     E* elem;
};

template<class E>
Vector::Vector(std::initializer_list<E> s)
     :sz{s.size()}                               // set vector size
{
     reserve(sz);                                // get the right amount of space
     uninitialized_copy(s.begin(), s.end(), elem);      // initialize elements in elem[0:s.size())
}

The initializer lists are part of the universal and uniform initialization design (§17.3).

17.3.4.3. Direct and Copy Initialization

The distinction between direct initialization and copy initialization (§16.2.6) is maintained for {} initialization. For a container, this implies that the distinction is applied to both the container and its elements:

• The container’s initializer-list constructor can be explicit or not.

• The constructor of the element type of the initializer list can be explicit or not.

For a vector<vector<double>>, we can see the direct initialization vs. copy initialization distinction applied to elements. For example:

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vector<vector<double>> vs = {
     {10,11,12,13,14},             // OK: vector of five elements
     {10},                         // OK: vector of one element
     10,                           // error: vector<double>(int) is explicit

     vector<double>{10,11,12,13},  // OK: vector of five elements
     vector<double>{10},           // OK: vector of one element with value 10.0
     vector<double>(10),           // OK: vector of 10 elements with value 0.0
};

A container can have some constructors explicit and some not. The standard-library vector is an example of that. For example, std::vector<int>(int) is explicit, but std::vector<int>(initialize_list<int>) is not:

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vector<double> v1(7);     // OK: v1 has 7 elements; note: uses () rather than {}
vector<double> v2 = 9;    // error: no conversion from int to vector

void f(const vector<double>&);
void g()
{
     v1 = 9;      // error: no conversion from int to vector
     f(9);        // error: no conversion from int to vector
}

By replacing () with {} we get:

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vector<double> v1 {7};          // OK: v1 has one element (with the value 7)
vector<double> v2 = {9};        // OK: v2 has one element (with the value 9)

void f(const vector<double>&);
void g()
 {
     v1 = {9};    // OK: v1 now has one element (with the value 9)
     f({9});      // OK: f is called with the list {9}
}

Obviously, the results are dramatically different.

This example was carefully crafted to give an example of the most confusing cases. Note that the apparent ambiguities (in the eyes of the human reader but not the compiler) do not emerge for longer lists. For example:

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vector<double> v1 {7,8,9};          // OK: v1 has three elements with values {7,8,9}
vector<double> v2 = {9,8,7};        // OK: v2 has three elements with values {9,8,7}
void f(const vector<double>&);
void g()
{
     v1 = {9,10,11};    // OK: v1 now has three elements with values {9,10,11}
     f({9,8,7,6,5,4});  // OK: f is called with the list {9,8,7,6,5,4}
}

Similarly, the potential ambiguities do not occur for lists of elements of nonintegral types:

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vector<string> v1 { "Anya"};       // OK: v1 has one element (with the value "Anya")
vector<string> v2 = {"Courtney"};  // OK: v2 has one element (with the value "Courtney")

void f(const vector<string>&);
void g()
{
     v1 = {"Gavin"};      // OK: v1 now has one element (with the value "Gavin")
     f({"Norah"});        // OK: f is called with the list {"Norah"}
}

17.4. Member and Base Initialization

Constructors can establish invariants and acquire resources. Generally, they do that by initializing class members and base classes.

17.4.1. Member Initialization

Consider a class that might be used to hold information for a small organization:

class Club {
     string name;
     vector<string> members;
     vector<string> officers;
     Date founded;
     // ...
     Club(const string& n, Date fd);
};

The Club’s constructor takes the name of the club and its founding date as arguments. Arguments for a member’s constructor are specified in a member initializer list in the definition of the constructor of the containing class. For example:

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Club::Club(const string& n, Date fd)
     : name{n}, members{}, officers{}, founded{fd}
{
     // ...
}

The member initializer list starts with a colon, and the individual member initializers are separated by commas.

The members’ constructors are called before the body of the containing class’s own constructor is executed (§17.2.3). The constructors are called in the order in which the members are declared in the class rather than the order in which the members appear in the initializer list. To avoid confusion, it is best to specify the initializers in the member declaration order. Hope for a compiler warning if you don’t get the order right. The member destructors are called in the reverse order of construction after the body of the class’s own destructor has been executed.

If a member constructor needs no arguments, the member need not be mentioned in the member initializer list. For example:

Club::Club(const string& n, Date fd)
     : name{n}, founded{fd}
{
     // ...
}

This constructor is equivalent to the previous version. In each case, Club::officers and Club::members are initialized to a vector with no elements.

It is usually a good idea to be explicit about initializing members. Note that an “implicitly initialized” member of a built-in type is left uninitialized (§17.3.1).

A constructor can initialize members and bases of its class, but not members or bases of its members or bases. For example:

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struct B { B(int); /* ... */};
struct BB : B { /* ... */ };
struct BBB : BB {
     BBB(int i) : B(i) { }; // error: trying to initialize base's base
     // ...
};

17.4.1.1. Member Initialization and Assignment

Member initializers are essential for types for which the meaning of initialization differs from that of assignment. For example:

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class X {
     const int i;
     Club cl;
     Club& rc;
     // ...
     X(int ii, const string& n, Date d, Club& c) : i{ii}, cl{n,d}, rc{c} { }
};

A reference member or a const member must be initialized (§7.5, §7.7, §17.3.3). However, for most types the programmer has a choice between using an initializer and using an assignment. In that case, I usually prefer to use the member initializer syntax to make it explicit that initialization is being done. Often, there also is an efficiency advantage to using the initializer syntax (compared to using an assignment). For example:

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class Person {
     string name;
     string address;
     // ...
     Person(const Person&);
     Person(const string& n, const string& a);
};

Person::Person(const string& n, const string& a)
     : name{n}
{
     address = a;
}

Here name is initialized with a copy of n. On the other hand, address is first initialized to the empty string and then a copy of a is assigned.

17.4.2. Base Initializers

Bases of a derived class are initialized in the same way non-data members are. That is, if a base requires an initializer, it must be provided as a base initializer in a constructor. If we want to, we can explicitly specify default construction. For example:

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class B1 { B1(); };     // has default constructor
class B2 { B2(int); }   // no default constructor

struct D1 : B1, B2 {
     D1(int i) :B1{}, B2{i} {}
};

struct D2 : B1, B2 {
     D2(int i) :B2{i} {}          // B1{} is used implicitly
};

struct D1 : B1, B2 {
     D1(int i) { }                // error: B2 requires an int initializer
};

As with members, the order of initialization is the declaration order, and it is recommended to specify base initializers in that order. Bases are initialized before members and destroyed after members (§17.2.3).

17.4.3. Delegating Constructors

If you want two constructors to do the same action, you can repeat yourself or define “an init() function” to perform the common action. Both “solutions” are common (because older versions of C++ didn’t offer anything better). For example:

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class X {
     int a;
     validate(int x) { if (0<x && x<=max) a=x; else throw Bad_X(x); }
public:
     X(int x) { validate(x); }
     X() { validate(42); }
     X(string s) { int x = to<int>(s); validate(x); } // §25.2.5.1
     // ...
};

Verbosity hinders readability and repetition is error-prone. Both get in the way of maintainability. The alternative is to define one constructor in terms of another:

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class X {
     int a;
public:
     X(int x) { if (0<x && x<=max) a=x; else throw Bad_X(x); }
     X() :X{42} { }
     X(string s) :X{to<int>(s)} { }        // §25.2.5.1
     // ...
};

That is, a member-style initializer using the class’s own name (its constructor name) calls another constructor as part of the construction. Such a constructor is called a delegating constructor (and occasionally a forwarding constructor).

You cannot both delegate and explicitly initialize a member. For example:

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class X {
     int a;
public:
     X(int x) { if (0<x && x<=max) a=x; else throw Bad_X(x); }
     X() :X{42}, a{56} { }     // error
     // ...
};

Delegating by calling another constructor in a constructor’s member and base initializer list is very different from explicitly calling a constructor in the body of a constructor. Consider:

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class X {
     int a;
public:
     X(int x) { if (0<x && x<=max) a=x; else throw Bad_X(x); }
     X() { X{42}; }    // likely error
     // ...
};

The X{42} simply creates a new unnamed object (a temporary) and does nothing with it. Such use is more often than not a bug. Hope for a compiler warning.

An object is not considered constructed until its constructor completes (§6.4.2). When using a delegating constructor, the object is not considered constructed until the delegating constructor completes – just completing the delegated-to constructor is not sufficient. A destructor will not be called for an object unless its original constructor completed.

If all you need is to set a member to a default value (that doesn’t depend on a constructor argument), a member initializer (§17.4.4) may be simpler.

17.4.4. In-Class Initializers

We can specify an initializer for a non-static data member in the class declaration. For example:

class A {
public:
     int a {7};
     int b = 77;
};

For pretty obscure technical reasons related to parsing and name lookup, the {} and = initializer notations can be used for in-class member initializers, but the () notation cannot.

By default, a constructor will use such an in-class initializer, so that example is equivalent to:

class A {
public:
     int a;
     int b;
     A() : a{7}, b{77} {}
};

Such use of in-class initializers can save a bit of typing, but the real benefits come in more complicated classes with multiple constructors. Often, several constructors use the same initializer for a member. For example:

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class A {
public:
     A() :a{7}, b{5}, algorithm{"MD5"}, state{"Constructor run"} {}
     A(int a_val) :a{a_val}, b{5}, algorithm{"MD5"}, state{"Constructor run"} {}
     A(D d) :a{7}, b{g(d)}, algorithm{"MD5"}, state{"Constructor run"} {}
     // ...
private:
     int a, b;
     HashFunction algorithm;       // cryptographic hash to be applied to all As
     string state;                 // string indicating state in object life cycle
};

The fact that algorithm and state have the same value in all constructors is lost in the mess of code and can easily become a maintenance problem. To make the common values explicit, we can factor out the unique initializer for data members:

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class A {
public:
     A() :a{7}, b{5} {}
     A(int a_val) :a{a_val}, b{5} {}
     A(D d) :a{7}, b{g(d)} {}
     // ...
private:
     int a, b;
     HashFunction algorithm {"MD5"};      // cryptographic hash to be applied to all As
     string state {"Constructor run"};    // string indicating state in object life cycle
};

If a member is initialized by both an in-class initializer and a constructor, only the constructor’s initialization is done (it “overrides” the default). So we can simplify further:

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class A {
public:
     A() {}
     A(int a_val) :a{a_val} {}
     A(D d) :b{g(d)} {}
     // ...
private:
     int a {7};                           // the meaning of 7 for a is ...
     int b {5};                           // the meaning of 5 for b is ...
     HashFunction algorithm {"MD5"};      // Cryptographic hash to be applied to all As
     string state {"Constructor run"};    // String indicating state in object lifecycle
};

As shown, default in-class initializers provide an opportunity for documentation of common cases.

An in-class member initializer can use names that are in scope at the point of their use in the member declaration. Consider the following headache-inducing technical example:

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int count = 0;
int count2 = 0;

int f(int i) { return i+count; }

struct S {
     int m1 {count2};         // that is, ::count2
     int m2 {f(m1)};          // that is, this->m1+::count; that is, ::count2+::count
     S() { ++count2; }        // very odd constructor
};

int main()
{
     S s1;     // {0,0}
     ++count;
     S s2;     // {1,2}
}

Member initialization is done in declaration order (§17.2.3), so first m1 is initialized to the value of a global variable count2. The value of the global variable is obtained at the point where the constructor for a new S object is run, so it can (and in this example does) change. Next, m2 is initialized by a call to the global f().

It is a bad idea to hide subtle dependencies on global data in member initializers.

17.4.5. static Member Initialization

A static class member is statically allocated rather than part of each object of the class. Generally, the static member declaration acts as a declaration for a definition outside the class. For example:

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class Node {
     // ...
     static int node_count;          // declaration
};

int Node::node_count = 0;            // definition

However, for a few simple special cases, it is possible to initialize a static member in the class declaration. The static member must be a const of an integral or enumeration type, or a constexpr of a literal type (§10.4.3), and the initializer must be a constant-expression. For example:

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class Curious {
public:
     static const int c1 = 7;        // OK
     static int c2 = 11;             // error: not const
     const int c3 = 13;              // OK, but not static (§17.4.4)
     static const int c4 = sqrt(9);  // error: in-class initializer not constant
     static const float c5 = 7.0;    // error: in-class not integral (use constexpr rather than const)
     // ...
};

If (and only if) you use an initialized member in a way that requires it to be stored as an object in memory, the member must be (uniquely) defined somewhere. The initializer may not be repeated:

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const int Curious::c1;              // don't repeat initializer here
const int* p = &Curious::c1;        // OK: Curious::c1 has been defined

The main use of member constants is to provide symbolic names for constants needed elsewhere in the class declaration. For example:

template<class T, int N>
class Fixed { // fixed-size array
public:
     static constexpr int max = N;
     // ...
private:
     T a[max];
};

For integers, enumerators (§8.4) offer an alternative for defining symbolic constants within a class declaration. For example:

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class X {
     enum { c1 = 7, c2 = 11, c3 = 13, c4 = 17 };
     // ...
};

17.5. Copy and Move

When we need to transfer a value from a to b, we usually have two logically distinct options:

• Copy is the conventional meaning of x=y; that is, the effect is that the values of x and y are both equal to y’s value before the assignment.

• Move leaves x with y’s former value and y with some moved-from state. For the most interesting cases, containers, that moved-from state is “empty.”

This simple logical distinction is confounded by tradition and by the fact that we use the same notation for both move and copy.

Typically, a move cannot throw, whereas a copy might (because it may need to acquire a resource), and a move is often more efficient than a copy. When you write a move operation, you should leave the source object in a valid but unspecified state because it will eventually be destroyed and the destructor cannot destroy an object left in an invalid state. Also, standard-library algorithms rely on being able to assign to (using move or copy) a moved-from object. So, design your moves not to throw, and to leave their source objects in a state that allows destruction and assignment.

To save us from tedious repetitive work, copy and move have default definitions (§17.6.2).

17.5.1. Copy

Copy for a class X is defined by two operations:

• Copy constructor: X(const X&)

• Copy assignment: X& operator=(const X&)

You can define these two operations with more adventurous argument types, such as volatile X&, but don’t; you’ll just confuse yourself and others. A copy constructor is supposed to make a copy of an object without modifying it. Similarly, you can use const X& as the return type of the copy assignment. My opinion is that doing so causes more confusion than it is worth, so my discussion of copy assumes that the two operations have the conventional types.

Consider a simple two-dimensional Matrix:

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template<class T>
class Matrix {
     array<int,2> dim;       // two dimensions
     T* elem;                // pointer to dim[0]*dim[1] elements of type T
public:
     Matrix(int d1, int d2) :dim{d1,d2}, elem{new T[d1*d2]} {}           // simplified (no error handling)
     int size() const { return dim[0]*dim[1]; }

     Matrix(const Matrix&);                // copy constructor
     Matrix& operator=(const Matrix&);     // copy assignment

     Matrix(Matrix&&);                     // move constructor
     Matrix& operator=(Matrix&&);          // move assignment

     ~Matrix() { delete[] elem; }
     // ...
};

First we note that the default copy (copy the members) would be disastrously wrong: the Matrix elements would not be copied, the Matrix copy would have a pointer to the same elements as the source, and the Matrix destructor would delete the (shared) elements twice (§3.3.1).

However, the programmer can define any suitable meaning for these copy operations, and the conventional one for a container is to copy the contained elements:

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template<class T>
Matrix:: Matrix(const Matrix& m)       // copy constructor
     : dim{m.dim},
     elem{new T[m.size()]}
{
     uninitialized_copy(m.elem,m.elem+m.size(),elem);       // copy elements
}

template<class T>
Matrix& Matrix::operator=(const Matrix& m)       // copy assignment
{
     if (dim[0]!=m.dim[0] || dim[1]!=m.dim[1])
           throw runtime_error("bad size in Matrix =");
     copy(m.elem,m.elem+m.size(),elem);     // copy elements
}

A copy constructor and a copy assignment differ in that a copy constructor initializes uninitialized memory, whereas the copy assignment operator must correctly deal with an object that has already been constructed and may own resources.

The Matrix copy assignment operator has the property that if a copy of an element throws an exception, the target of the assignment may be left with a mixture of its old value and the new. That is, that Matrix assignment provided the basic guarantee, but not the strong guarantee (§13.2). If that is not considered acceptable, we can avoid it by the fundamental technique of first making a copy and then swapping representations:

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Matrix& Matrix::operator=(const Matrix& m)          // copy assignment
{
     Matrix tmp {m};         // make a copy
     swap(tmp,*this);        // swap tmp's representation with *this's
     return *this;
}

The swap() will be done only if the copy was successful. Obviously, this operator=() works only if the implementation swap() does not use assignment (std::swap() does not); see §17.5.2.

Usually a copy constructor must copy every non-static member (§17.4.1). If a copy constructor cannot copy an element (e.g., because it needs to acquire an unavailable resource to do so), it can throw an exception.

Note that I did not protect Matrix’s copy assignment against self-assignment, m=m. The reason I did not test is that self-assignment of the members is already safe: both my implementations of Matrix’s copy assignment will work correctly and reasonably efficiently for m=m. Also, self-assignment is rare, so test for self-assignment in a copy assignment only if you are sure that you need to.

17.5.1.1. Beware of Default Constructors

When writing a copy operation, be sure to copy every base and member. Consider:

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class X {
     string s;
     string s2;
     vector<string> v;

     X(const X&)          // copy constructor
         :s{a.s}, v{a.v}  // probably sloppy and probably wrong
     {
     }
     // ...
};

Here, I “forgot” to copy s2, so it gets default initialized (to ""). This is unlikely to be right. It is also unlikely that I would make this mistake for a simple class. However, for larger classes the chances of forgetting go up. Worse, when someone long after the initial design adds a member to a class, it is easy to forget to add it to the list of members to be copied. This is one reason to prefer the default (compiler-generated) copy operations (§17.6).

17.5.1.2. Copy of Bases

For the purposes of copying, a base is just a member: to copy an object of a derived class you have to copy its bases. For example:

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struct B1 {
     B1();
     B1(const B1&);
     // ...
};

struct B2 {
     B2(int);
     B2(const B2&);
     // ...
};

struct D : B1, B2 {
     D(int i) :B1{}, B2{i}, m1{}, m2{2*i} {}
     D(const D& a) :B1{a}, B2{a}, m1{a.m1}, m2{a.m2} {}
     B1 m1;
     B2 m2;
};

D d {1};     // construct with int argument
D dd {d};    // copy construct

The order of initialization is the usual (base before member), but for copying the order had better not matter.

A virtual base (§21.3.5) may appear as a base of several classes in a hierarchy. A default copy constructor (§17.6) will correctly copy it. If you define your own copy constructor, the simplest technique is to repeatedly copy the virtual base. Where the base object is small and the virtual base occurs only a few times in a hierarchy, that can be more efficient than techniques for avoiding the replicated copies.

17.5.1.3. The Meaning of Copy

What does a copy constructor or copy assignment have to do to be considered “a proper copy operation”? In addition to be declared with a correct type, a copy operation must have the proper copy semantics. Consider a copy operation, x=y, of two objects of the same type. To be suitable for value-oriented programming in general (§16.3.4), and for use with the standard library in particular (§31.2.2), the operation must meet two criteria:

• Equivalence: After x=y, operations on x and y should give the same result. In particular, if == is defined for their type, we should have x==y and f(x)==f(y) for any function f() that depends only on the values of x and y (as opposed to having its behavior depend on the addresses of x and y).

• Independence: After x=y, operations on x should not implicitly change the state of y, that is f(x) does not change the value of y as long as f(x) doesn’t refer to y.

This is the behavior that int and vector offer. Copy operations that provide equivalence and independence lead to simpler and more maintainable code. This is worth stating because code that violate these simple rules is not uncommon, and programmers don’t always realize that such violations are the root cause of some of their nastier problems. A copy that provides equivalence and independence is part of the notion of a regular type (§24.3.1).

First consider the requirement of equivalence. People rarely violate this requirement deliberately, and the default copy operations do not violate it; they do memberwise copy (§17.3.1, §17.6.2). However, tricks, such as having the meaning of copy depend on “options,” occasionally appear and typically cause confusion. Also, it is not uncommon for an object to contain members that are not considered part of its value. For example, a copy of a standard container does not copy its allocator because the allocator is considered part of the container, rather than part of its value. Similarly, counters for statistics gathering and cached values are sometimes not simply copied. Such “non-value” parts of an object’s state should not affect the result of comparison operators. In particular, x=y should imply x==y. Furthermore, slicing (§17.5.1.4) can lead to “copies” that behave differently, and is most often a bad mistake.

Now consider the requirement of independence. Most of the problems related to (lack of) independence have to do with objects that contain pointers. The default meaning of copy is memberwise copy. A default copy operation copies a pointer member, but does not copy the object (if any) that it points to. For example:

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struct S {
     int* p;    // a pointer
};

S x {new int{0}};
void f()
{
     S y {x};              // "copy" x

     *y.p = 1;             // change y; affects x
     *x.p = 2;             // change x; affects y
     delete y.p;           // affects x and y
     y.p = new int{3};     // OK: change y; does not affect x
     *x.p = 4;             // oops: write to deallocated memory
}

Here I violated the rule of independence. After the “copy” of x into y, we can manipulate part of x’s state through y. This is sometimes called shallow copy and (too) often praised for “efficiency.” The obvious alternative of copying the complete state of an object is called deep copy. Often, the better alternative to deep copy is not a shallow copy, but a move operation, which minimizes copying without adding complexity (§3.3.2, §17.5.2).

A shallow copy leaves two objects (here, x and y) with a shared state, and has a huge potential for confusion and errors. We say that the objects x and y have become entangled when the requirement of independence have been violated. It is not possible to reason about an entangled object in isolation. For example, it is not obvious from the source code that the two assignments to *x.p can have dramatically different effects.

We can represent two entangled objects graphically:

Note that entanglement can arise in a variety of ways. Often, it is not obvious that entanglement has happened until probems arise. For example, a type like S may incautiously be used as a member of an otherwise well-behaved class. The original author of S may be aware of the entanglement and prepared to cope with it, but someone naively assuming that copying an S meant copying its complete value could be surprised, and someone who finds an S deeply nested in other classes could be very surprised.

We can address problems related to the lifetime of a shared subobject by introducing a form of garbage collection. For example:

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struct S2 {
     shared_ptr<int> p;
};

S2 x {new int{0}};
void f()
{
     S2 y {x};                  // "copy" x

     *y.p=1;                    // change y, affects x
     *x.p = 2;                  // change x; affects y
     y.p.reset(new int{3});     // change y; affects x
     *x.p = 4;                  // change x; affects y
}

In fact, shallow copy and such entangled objects are among the sources of demands for garbage collection. Entangled objects lead to code that is very hard to manage without some form of garbage collection (e.g., shared_ptrs).

However, a shared_ptr is still a pointer, so we cannot consider objects containing a shared_ptr in isolation. Who can update the pointed-to object? How? When? If we are running in a multithreaded system, is synchronization needed for access to the shared data? How can we be sure? Entangled objects (here, resulting from a shallow copy) is a source of complexity and errors that is at best partially solved by garbage collection (in any form).

Note that an immutable shared state is not a problem. Unless we compare addresses, we cannot tell whether two equal values happen to be represented as one or two copies. This is a useful observation because many copies are never modified. For example, objects passed by value are rarely written to. This observation leads to the notion of copy-on-write. The idea is that a copy doesn’t actually need independence until a shared state is written to, so we can delay the copying of the shared state until just before the first write to it. Consider:

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class Image {
public:
     // ...
     Image(const Image& a);         // copy constructor
     // ...
     void write_block(Descriptor);
     // ...
private:
     Representation* clone();       // copy *rep
     Representation* rep;
     bool shared;
};

Assume that a Representation can be huge and that a write_block() is expensive compared to testing a bool. Then, depending on the use of Images, it can make sense to implement the copy constructor as a shallow copy:

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Image::Image(const Image& a)      // do shallow copy and prepare for copy-on-write
     :rep{a.rep},
      shared{true}
{
}

We protect the argument to that copy constructor by copying the Representation before a write:

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void write_block(Descriptor d)
{
     if (shared) {
           rep =clone();       // make a copy of *rep
           shared = false;     // no more sharing
     }
     // ... now we can safely write to our own copy of rep ...
}

Like any other technique, copy-on-write is not a panacea, but it can be an effective combination of the simplicity of true copy and the efficiency of shallow copy.

17.5.1.4. Slicing

A pointer to a derived class implicitly converts to a pointer to its public base class. When applied to a copy operation, this simple and necessary rule (§3.2.4, §20.2) leads to a trap for the unwary. Consider:

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struct Base {
     int b;
     Base(const Base&);
     // ...
};

struct Derived : Base {
     int d;
     Derived(const Derived&);
     // ...
};

void naive(Base* p)
{
     B b2 = *p;    // may slice: invokes Base::Base(const Base&)
     // ...
}

void user()
{
     Derived d;
     naive(&d);
     Base bb = d;   // slices: invokes Base::Base(const Base&), not Derived::Derived(const Derived&)
     // ...
}

The variables b2 and bb contain copies of the Base part of d, that is, a copy of d.b. The member d.d is not copied. This phenomenon is called slicing. It may be exactly what you intended (e.g., see the copy constructor for D in §17.5.1.2 where we pass selected information to a base class), but typically it is a subtle bug. If you don’t want slicing, you have two major tools to prevent it:

[1] Prohibit copying of the base class: delete the copy operations (§17.6.4).

[2] Prevent conversion of a pointer to a derived to a pointer to a base: make the base class a private or protected base (§20.5).

The former would make the initializations of b2 and bb errors; the latter would make the call of naive() and the initialization of bb errors.

17.5.2. Move

The traditional way of getting a value from a to b is to copy it. For an integer in a computer’s memory, that’s just about the only thing that makes sense: that’s what the hardware can do with a single instruction. However, from a general and logical point of view that’s not so. Consider the obvious implementation of swap() exchanging the value of two objects:

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template<class T>
void swap(T& a, T& b)
{
     const T tmp = a;    // put a copy of a into tmp
     a = b;              // put a copy of b into a
     b = tmp;            // put a copy of tmp into b
};

After the initialization of tmp, we have two copies of a’s value. After the assignment to tmp, we have two copies of b’s value. After the assignment to b, we have two copies of tmp’s value (that is, the original value of a). Then we destroy tmp. That sounds like a lot of work, and it can be. For example:

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void f(string& s1, string& s2,
     vector<string>& vs1, vector<string>& vs2,
     Matrix& m1, Matrix& m2)
{

     swap(s1,s2);
     swap(vs1.vs2);
     swap(m1,m2);
}

What if s1 has a thousand characters? What if vs2 has a thousand elements each of a thousand characters? What if m1 is a 1000*1000 matrix of doubles? The cost of copying those data structures could be significant. In fact, the standard-library swap() has always been carefully designed to avoid such overhead for string and vector. That is, effort has been made to avoid copying (taking advantage of the fact that string and vector objects really are just handles to their elements). Similar work must be done to avoid a serious performance problem for swap() of Matrixes. If the only operation we have is copy, similar work must be done for huge numbers of functions and data structures that are not part of the standard.

The fundamental problem is that we really didn’t want to do any copying at all: we just wanted to exchange pairs of values.

We can also look at the issue of copying from a completely different point of view: we don’t usually copy physical things unless we absolutely have to. If you want to borrow my phone, I pass my phone to you rather than making you your own copy. If I lend you my car, I give you a key and you drive away in my car, rather than in your freshly made copy of my car. Once I have given you an object, you have it and I no longer do. Consequently, we talk about “giving away,” “handing over,” “transferring ownership of,” and “moving” physical objects. Many objects in a computer resemble physical objects (which we don’t copy without need and only at considerable cost) more than integer values (which we typically copy because that’s easier and cheaper than alternatives). Examples are locks, sockets, file handles, threads, long strings, and large vectors.

To allow the user to avoid the logical and performance problems of copying, C++ directly supports the notion of moving as well as the notion of copying. In particular, we can define move constructors and move assignments to move rather than copy their argument. Consider again the simple two-dimensional Matrix from §17.5.1:

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template<class T>
class Matrix {
     std::array<int,2> dim;
     T* elem; // pointer to sz elements of type T

     Matrix(int d1, int d2) :dim{d1,d2}, elem{new T[d1*d2]} {}
     int size() const { return dim[0]*dim[1]; }

     Matrix(const Matrix&);             // copy constructor
     Matrix(Matrix&&);                  // move constructor

     Matrix& operator=(const Matrix&);  // copy assignment
     Matrix& operator=(Matrix&&);       // move assignment

     ~Matrix(); // destructor
     // ...
};

The && indicates an rvalue reference (§7.7.2).

The idea behind a move assignment is to handle lvalues separately from rvalues: copy assignment and copy constructors take lvalues whereas move assignment and move constructors take rvalues. For a return value, the move constructor is chosen.

We can define Matrix’s move constructor to simply take the representation from its source and replace it with an empty Matrix (which is cheap to destroy). For example:

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template<class T>
Matrix<T>::Matrix(Matrix&& a)      // move constructor
     :dim{a.dim}, elem{a.elem}     // grab a's representation
{
     a.dim = {0,0};                // clear a's representation
     a.elem = nullptr;
}

For the move assignment, we can simply do a swap. The idea behind using a swap to implement a move assignment is that the source is just about to be destroyed, so we can just let the destructor for the source do the necessary cleanup work for us:

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template<class T>
Matrix<T>& Matrix<T>::operator=(Matrix&& a)           // move assignment
{
     swap(dim,a.dim);            // swap representations
     swap(elem,a.elem);
     return *this;
}

Move constructors and move assignments take non-const (rvalue) reference arguments: they can, and usually do, write to their argument. However, the argument of a move operation must always be left in a state that the destructor can cope with (and preferably deal with very cheaply and easily).

For resource handles, move operations tend to be significantly simpler and more efficient than copy operations. In particular, move operations typically do not throw exceptions; they don’t acquire resources or do complicated operations, so they don’t need to. In this, they differ from many copy operations (§17.5).

How does the compiler know when it can use a move operation rather than a copy operation? In a few cases, such as for a return value, the language rules say that it can (because the next action is defined to destroy the element). However, in general we have to tell it by giving an rvalue reference argument. For example:

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template<class T>
void swap(T& a, T& b)    // "perfect swap" (almost)
{
     T tmp = std::move(a);
     a = std::move(b);
     b = std::move(tmp);
}

The move() is a standard-library function returning an rvalue reference to its argument (§35.5.1): move(x) means “give me an rvalue reference to x.” That is, std::move(x) does not move anything; instead, it allows a user to move x. It would have been better if move() had been called rval(), but the name move() has been used for this operation for years.

Standard-library containers have move operations (§3.3.2, §35.5.1) and so have other standard-library types, such as pair (§5.4.3, §34.2.4.1) and unique_ptr (§5.2.1, §34.3.1). Furthermore, operations that insert new elements into standard-library containers, such as insert() and push_back(), have versions that take rvalue references (§7.7.2). The net result is that the standard containers and algorithms deliver better performance than they would have been able to if they had to copy.

What if we try to swap objects of a type that does not have a move constructor? We copy and pay the price. In general, a programmer is responsible for avoiding excessive copying. It is not the compiler’s job to decide what is excessive and what is necessary. To get the copy-to-move optimization for your own data structures, you have to provide move operations (either explicitly or implicitly; see §17.6).

Built-in types, such as int and double*, are considered to have move operations that simply copy. As usual, you have to be careful about data structures containing pointers (§3.3.1). In particular, don’t assume that a moved-from pointer is set to nullptr.

Having move operations affects the idiom for returning large objects from functions. Consider:

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Matrix operator+(const Matrix& a, const Matrix& b)
     // res[i][j] = a[i][j]+b[i][j] for each i and j
{
     if (a.dim[0]!=b.dim[0] || a.dim[1]!=b.dim[1])
            throw std::runtime_error("unequal Matrix sizes in +");

     Matrix res{a.dim[0],a.dim[1]};
     constexpr auto n = a.size();
     for (int i = 0; i!=n; ++i)
           res.elem[i] = a.elem[i]+b.elem[i];
     return res;
}

Matrix has a move constructor so that “return by value” is simple and efficient as well as “natural.” Without move operations, we have performance problems and must resort to workarounds. We might have considered:

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Matrix& operator+(const Matrix& a, const Matrix& b)        // beware!
{
     Matrix& res = *new Matrix;               // allocate on free store
     // res[i][j] = a[i][j]+b[i][j] for each i and j
     return res;
}

The use of new within operator+() is not obvious and forces the user of + to deal with tricky memory management issues:

• How does the object created by new get deleted?

• Do we need a garbage collector?

• Should we use a pool of Matrixes rather than the general new?

• Do we need use-counted Matrix representations?

• Should we redesign the interface of our Matrix addition?

• Must the caller of operator+() remember to delete the result?

• What happens to the newly allocated memory if the computation throws an exception?

None of the alternatives are elegant or general.

17.6. Generating Default Operations

Writing conventional operations, such as a copy and a destructor, can be tedious and error-prone, so the compiler can generate them for us as needed. By default, a class provides:

• A default constructor: X()

• A copy constructor: X(const X&)

• A copy assignment: X& operator=(const X&)

• A move constructor: X(X&&)

• A move assignment: X& operator=(X&&)

• A destructor: ~X()

By default, the compiler generates each of these operations if a program uses it. However, if the programmer takes control by defining one or more of those operations, the generation of related operations is suppressed:

• If the programmer declares any constructor for a class, the default constructor is not generated for that class.

• If the programmer declares a copy operation, a move operation, or a destructor for a class, no copy operation, move operation, or destructor is generated for that class.

Unfortunately, the second rule is only incompletely enforced: for backward compatibility, copy constructors and copy assignments are generated even if a destructor is defined. However, that generation is deprecated in the ISO standard (§iso.D), and you should expect a modern compiler to warn against it.

If necessary, we can be explicit about which functions are generated (§17.6.1) and which are not (§17.6.4).

17.6.1. Explicit Defaults

Since the generation of otherwise default operations can be suppressed, there has to be a way of getting back a default. Also, some people prefer to see a complete list of operations in the program text even if that complete list is not needed. For example, we can write:

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class gslice {
     valarray<size_t> size;
     valarray<size_t> stride;
     valarray<size_t> d1;
public:
     gslice() = default;
     ~gslice() = default;
     gslice(const gslice&) = default;
     gslice(gslice&&) = default;
     gslice& operator=(const gslice&) = default;
     gslice& operator=(gslice&&) = default;
     // ...
};

This fragment of the implementation of std::gslice (§40.5.6) is equivalent to:

class gslice {
     valarray<size_t> size;
     valarray<size_t> stride;
     valarray<size_t> d1;
public:
     // ...
};

I prefer the latter, but I can see the point of using the former in code bases maintained by less experienced C++ programmers: what you don’t see, you might forget about.

Using =default is always better than writing your own implementation of the default semantics. Someone assuming that it is better to write something, rather than nothing, might write:

class gslice {
     valarray<size_t> size;
     valarray<size_t> stride;
     valarray<size_t> d1;
public:
     // ...
     gslice(const gslice& a);
};

gslice::gslice(const gslice& a)
     : size{a.size },
     stride{a.stride},
     d1{a.d1}
{
}

This is not only verbose, making it harder to read the definition of gslice, but also opens the opportunity for making mistakes. For example, I might forget to copy one of the members and get it default initialized (rather than copied). Also, when the user provides a function, the compiler no longer knows the semantics of that function and some optimizations become inhibited. For the default operations, those optimizations can be significant.

17.6.2. Default Operations

The default meaning of each generated operation, as implemented when the compiler generates it, is to apply the operation to each base and non-static data member of the class. That is, we get memberwise copy, memberwise default construction, etc. For example:

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struct S {
     string a;
     int b;
};

S f(S arg)
{
     S s0 {};   // default construction: {"",0}
     S s1 {s0}; // copy construction
     s1 = arg;  // copy assignment
     return s1; // move construction
}

The copy construction of s1 copies s0.a and s0.b. The return of s1 moves s1.a and s1.b, leaving s1.a as the empty string and s1.b unchanged.

Note that the value of a moved-from object of a built-in type is unchanged. That’s the simplest and fastest thing for the compiler to do. If we want something else done for a member of a class, we have to write our move operations for that class.

The default moved-from state is one for which the default destructor and default copy assignment work correctly. It is not guaranteed (or required) that an arbitrary operation on a moved-from object will work correctly. If you need stronger guarantees, write your own operations.

17.6.3. Using Default Operations

This section presents a few examples demonstrating how copy, move, and destructors are logically linked. If they were not linked, errors that are obvious when you think about them would not be caught by the compiler.

17.6.3.1. Default Constructors

Consider:

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struct X {
     X(int);     // require an int to initialize an X
};

By declaring a constructor that requires an integer argument, the programmer clearly states that a user needs to provide an int to initialize an X. Had we allowed the default constructor to be generated, that simple rule would have been violated. We have:

X a {1};    // OK
X b {};     // error: no default constructor

If we also want the default constructor, we can define one or declare that we want the default generated by the compiler. For example:

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struct Y {
     string s;
     int n;
     Y(const string& s);  // initialize Y with a string
     Y() = default;       // allow default initialization with the default meaning
};

The default (i.e., generated) default constructor default constructs each member. Here, Y() sets s to the empty string. The “default initialization” of a built-in member leaves that member uninitialized. Sigh! Hope for a compiler warning.

17.6.3.2. Maintaining Invariants

Often, a class has an invariant. If so, we want copy and move operations to maintain it and the destructor to free any resources involved. Unfortunately, the compiler cannot in every case know what a programmer considers an invariant. Consider a somewhat far-fetched example:

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struct Z { // invariant:
           // my_favorite is the index of my favorite element of elem
           // largest points to the element with the highest value in elem
     vector<int> elem;
     int my_favorite;
     int* largest;
};

The programmer stated an invariant in the comment, but the compiler doesn’t read comments. Furthermore, the programmer did not leave a hint about how that invariant is to be established and maintained. In particular, there are no constructors or assignments declared. That invariant is implicit. The result is that a Z can be copied and moved using the default operations:

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Z v0;                             // no initialization (oops! possibility of undefined values)
Z val {{1,2,3},1,&val[2]};        // OK, but ugly and error-prone
Z v2 = val;                       // copies: v2.largest points into val
Z v3 = move(val);                 // moves: val.elem becomes empty; v3.my_favorite is out of range

This is a mess. The root problem is that Z is badly designed because critical information is “hidden” in a comment or completely missing. The rules for the generation of default operations are heuristic intended to catch common mistakes and to encourage a systematic approach to construction, copy, move, and destruction. Wherever possible

[1] Establish an invariant in a constructor (including possibly resource acquisition).

[2] Maintain the invariant with copy and move operations (with the usual names and types).

[3] Do any needed cleanup in the destructor (incl. possibly resource release).

17.6.3.3. Resource Invariants

Many of the most critical and obvious uses of invariants relate to resource management. Consider a simple Handle:

template<class T> class Handle {
     T* p;
public:
     Handle(T* pp) :p{pp} { }
     T& operator*() { return *p; }
     ~Handle() { delete p; }
};

The idea is that you construct a Handle given a pointer to an object allocated using new. The Handle provides access to the object pointed to and eventually deletes that object. For example:

void f1()
{
     Handle<int> h {new int{99}};
     // ...
}

Handle declares a constructor that takes an argument: this suppresses the generation of the default constructor. That’s good because a default constructor could leave Handle<T>::p uninitialized:

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void f2()
{
     Handle<int> h; // error: no default constructor
     // ...
}

The absence of a default constructor saves us from the possibility of a delete with a random memory address.

Also, Handle declares a destructor: this suppresses the generation of copy and move operations. Again, that saves us from a nasty problem. Consider:

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void f3()
{
     Handle<int> h1 {new int{7}};
     Handle<int> h2 {h1};           // error: no copy constructor
     // ...
}

Had Handle had a default copy constructor, both h1 and h2 would have had a copy of the pointer and both would have deleted it. The results would be undefined and most likely disastrous (§3.3.1). Caveat: the generation of copy operations is only deprecated, not banned, so if you ignore warnings, you might get this example past the compiler. In general, if a class has a pointer member, the default copy and move operations should be considered suspicious. If that pointer member represents ownership, memberwise copy is wrong. If that pointer member does not represent ownership and memberwise copy is appropriate, explicit =default and a comment are most likely a good idea.

If we wanted copy construction, we could define something like:

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template<class T>
class Handle {
     // ...
     Handle(const T& a) :p{new T{*a.p}} { }    // clone
};

17.6.3.4. Partially Specified Invariants

Troublesome examples that rely on invariants but only partially express them through constructors or destructors are rarer but not unheard of. Consider:

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class Tic_tac_toe {
public:
     Tic_tac_toe(): pos(9) {}    // always 9 positions

     Tic_tac_toe& operator=(const Tic_tac_toe& arg)
     {
         for(int i = 0; i<9; ++i)
               pos.at(i) = arg.pos.at(i);
         return *this;
     }

     // ... other operations ...

     enum State { empty, nought, cross };
private:
     vector<State> pos;
};

This was reported to have been part of a real program. It uses the “magic number” 9 to implement a copy assignment that accesses its argument arg without checking that the argument actually has nine elements. Also, it explicitly implements the copy assignment, but not the copy constructor. This is not what I consider good code.

We defined copy assignment, so we must also define the destructor. That destructor can be =default because all it needs to do is to ensure that the member pos is destroyed, which is what would have been done anyway had the copy assignment not been defined. At this point, we notice that the user-defined copy assignment is essentially the one we would have gotten by default, so we can =default that also. Add a copy constructor for completeness and we get:

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class Tic_tac_toe {
public:
     Tic_tac_toe(): pos(9) {}   // always 9 positions
     Tic_tac_toe(const Tic_tac_toe&) = default;
     Tic_tac_toe& operator=(const Tic_tac_toe& arg) = default;
     ~Tic_tac_toe() = default;

     // ... other operations ...

     enum State { empty, nought, cross };
private:
     vector<State> pos;
};

Looking at this, we realize that the net effect of these =defaults is just to eliminate move operations. Is that what we want? Probably not. When we made the copy assignment =default, we eliminated the nasty dependence on the magic constant 9. Unless other operations on Tic_tac_toe, not mentioned so far, are also “hardwired with magic numbers,” we can safely add move operations. The simplest way to do that is to remove the explicit =defaults, and then we see that Tic_tac_toe is really a perfectly ordinary type:

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class Tic_tac_toe {
public:
     // ... other operations ...
     enum State { empty, nought, cross };
private:
     vector<State> pos {Vector<State>(9)};        // always 9 positions
};

One conclusion that I draw from this and other examples where an “odd combination” of the default operations is defined is that we should be highly suspicious of such types: their irregularity often hides design flaws. For every class, we should ask:

[1] Is a default constructor needed (because the default one is not adequate or has been suppressed by another constructor)?

[2] Is a destructor needed (e.g., because some resource needs to be released)?

[3] Are copy operations needed (because the default copy semantics is not adequate, e.g., because the class is meant to be a base class or because it contains pointers to objects that must be deleted by the class)?

[4] Are move operations needed (because the default semantics is not adequate, e.g., because an empty object doesn’t make sense)?

In particular, we should never just consider one of these operations in isolation.

17.6.4. deleted Functions

We can “delete” a function; that is, we can state that a function does not exist so that it is an error to try to use it (implicitly or explicitly). The most obvious use is to eliminate otherwise defaulted functions. For example, it is common to want to prevent the copying of classes used as bases because such copying easily leads to slicing (§17.5.1.4):

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class Base {
     // ...
     Base& operator=(const Base&) = delete;// disallow copying
     Base(const Base&) = delete;

     Base& operator=(Base&&) = delete;          // disallow moving
     Base(Base&&) = delete;
};

Base x1;
Base x2 {x1};  // error: no copy constructor

Enabling and disabling copy and move is typically more conveniently done by saying what we want (using =default; §17.6.1) rather than saying what we don’t want (using =delete). However, we can delete any function that we can declare. For example, we can eliminate a specialization from the set of possible specializations of a function template:

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template<class T>
T* clone(T* p) // return copy of *p
{
     return new T{*p};
};

Foo* clone(Foo*) = delete;         // don't try to clone a Foo

void f(Shape* ps, Foo* pf)
{
     Shape* ps2 = clone(ps);       // fine
     Foo* pf2 = clone(pf);         // error: clone(Foo*) deleted
}

Another application is to eliminate an undesired conversion. For example:

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struct Z {
     // ...
     Z(double);            // can initialize with a double
     Z(int) = delete;      // but not with an integer
};

void f()
{
     Z z1 {1};        // error: Z(int) deleted
     Z z2 {1.0};      // OK
}

A further use is to control where a class can be allocated:

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class Not_on_stack {
     // ...
     ~Not_on_stack() = delete;
};

class Not_on_free_store {
     // ...
     void* operator new(size_t) = delete;
};

You can’t have a local variable that can’t be destroyed (§17.2.2), and you can’t allocate an object on the free store when you have =deleted its class’s memory allocation operator (§19.2.5). For example:

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void f()
{
     Not_on_stack v1;        // error: can't destroy
     Not_on_free_store v2;   // OK

     Not_on_stack* p1 = new Not_on_stack;             // OK
     Not_on_free_store* p2 = new Not_on_free_store;   // error: can't allocate
}

However, we can never delete that Not_on_stack object. The alternative technique of making the destructor private (§17.2.2) can address that problem.

Note the difference between a =deleted function and one that simply has not been declared. In the former case, the compiler notes that the programmer has tried to use the deleted function and gives an error. In the latter case, the compiler looks for alternatives, such as not invoking a destructor or using a global operator new().

17.7. Advice

[1] Design constructors, assignments, and the destructor as a matched set of operations; §17.1.

[2] Use a constructor to establish an invariant for a class; §17.2.1.

[3] If a constructor acquires a resource, its class needs a destructor to release the resource; §17.2.2.

[4] If a class has a virtual function, it needs a virtual destructor; §17.2.5.

[5] If a class does not have a constructor, it can be initialized by memberwise initialization; §17.3.1.

[6] Prefer {} initialization over = and () initialization; §17.3.2.

[7] Give a class a default constructor if and only if there is a “natural” default value; §17.3.3.

[8] If a class is a container, give it an initializer-list constructor; §17.3.4.

[9] Initialize members and bases in their order of declaration; §17.4.1.

[10] If a class has a reference member, it probably needs copy operations (copy constructor and copy assignment); §17.4.1.1.

[11] Prefer member initialization over assignment in a constructor; §17.4.1.1.

[12] Use in-class initializers to provide default values; §17.4.4.

[13] If a class is a resource handle, it probably needs copy and move operations; §17.5.

[14] When writing a copy constructor, be careful to copy every element that needs to be copied (beware of default initializers); §17.5.1.1.

[15] A copy operations should provide equivalence and independence; §17.5.1.3.

[16] Beware of entangled data structures; §17.5.1.3.

[17] Prefer move semantics and copy-on-write to shallow copy; §17.5.1.3.

[18] If a class is used as a base class, protect against slicing; §17.5.1.4.

[19] If a class needs a copy operation or a destructor, it probably needs a constructor, a destructor, a copy assignment, and a copy constructor; §17.6.

[20] If a class has a pointer member, it probably needs a destructor and non-default copy operations; §17.6.3.3.

[21] If a class is a resource handle, it needs a constructor, a destructor, and non-default copy operations; §17.6.3.3.

[22] If a default constructor, assignment, or destructor is appropriate, let the compiler generate it (don’t rewrite it yourself); §17.6.

[23] Be explicit about your invariants; use constructors to establish them and assignments to maintain them; §17.6.3.2.

[24] Make sure that copy assignments are safe for self-assignment; §17.5.1.

[25] When adding a new member to a class, check to see if there are user-defined constructors that need to be updated to initialize the member; §17.5.1.

18. Operator Overloading

When I use a word it means just what I choose it to mean – neither more nor less.

– Humpty Dumpty

• Introduction

• Operator Functions

Binary and Unary Operators; Predefined Meanings for Operators; Operators and User-Defined Types; Passing Objects; Operators in Namespaces

• A Complex Number Type

Member and Nonmember Operators; Mixed-Mode Arithmetic; Conversions; Literals; Accessor Functions; Helper Functions

• Type Conversion

Conversion Operators; explicit Conversion Operators; Ambiguities

• Advice

18.1. Introduction

Every technical field – and most nontechnical fields – has developed conventional shorthand notation to make convenient the presentation and discussion involving frequently used concepts. For example, because of long acquaintance,

x+y*z

is clearer to us than

multiply y by z and add the result to x

It is hard to overestimate the importance of concise notation for common operations.

Like most languages, C++ supports a set of operators for its built-in types. However, most concepts for which operators are conventionally used are not built-in types in C++, so they must be represented as user-defined types. For example, if you need complex arithmetic, matrix algebra, logic signals, or character strings in C++, you use classes to represent these notions. Defining operators for such classes sometimes allows a programmer to provide a more conventional and convenient notation for manipulating objects than could be achieved using only the basic functional notation. Consider:

Click here to view code image

class complex {             // very simplified complex
     double re, im;
public:
     complex(double r, double i) :re{r}, im{i} { }
     complex operator+(complex);
     complex operator*(complex);
};

This defines a simple implementation of the concept of complex numbers. A complex is represented by a pair of double-precision floating-point numbers manipulated by the operators + and *. The programmer defines complex::operator+() and complex::operator*() to provide meanings for + and *, respectively. For example, if b and c are of type complex, b+c means b.operator+(c). We can now approximate the conventional interpretation of complex expressions:

void f()
{
     complex a = complex{1,3.1};
     complex b {1.2, 2};
     complex c {b};

     a = b+c;
     b = b+c*a;
     c = a*b+complex(1,2);
}

The usual precedence rules hold, so the second statement means b=b+(c*a), not b=(b+c)*a.

Note that the C++ grammar is written so that the {} notation can only be used for initializers and on the right-hand side of an assignment:

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void g(complex a, complex b)
{
     a = {1,2};          // OK: right hand side of assignment
     a += {1,2};         // OK: right hand side of assignment
     b = a+{1,2};        // syntax error
     b = a+complex{1,2}; // OK
     g(a,{1,2});         // OK: a function argument is considered an initializer
     {a,b} = {b,a};      // syntax error
}

There seems to be no fundamental reason not to use {} in more places, but the technical problems of writing a grammar allowing {} everywhere in an expression (e.g., how would you know if a { after a semicolon was the start of an expression or a block?) and also giving good error messages led to a more limited use of {} in expressions.

Many of the most obvious uses of operator overloading are for numeric types. However, the usefulness of user-defined operators is not restricted to numeric types. For example, the design of general and abstract interfaces often leads to the use of operators such as –>, [], and ().

18.2. Operator Functions

Functions defining meanings for the following operators (§10.3) can be declared:

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+         -         *        /         %         ^        &
|         ~         !        =         <         >        +=
-=        *=        /=       %=        ^=        &=       |=
<<        >>        >>=      <<=       ==        !=       <=
>=        &&        ||       ++        --        ->*      ,
->        []        ()       new       new[]     delete   delete[]

The following operators cannot be defined by a user:

::      scope resolution (§6.3.4, §16.2.12)

.        member selection (§8.2)

.*      member selection through pointer to member (§20.6)

They take a name, rather than a value, as their second operand and provide the primary means of referring to members. Allowing them to be overloaded would lead to subtleties [Stroustrup,1994]. The named “operators”cannot be overloaded because they report fundamental facts about their operands:

sizeof     size of object (§6.2.8)

alignof  alignment of object (§6.2.9)

typeid  type_info of an object (§22.5)

Finally, the ternary conditional expression operator cannot be overloaded (for no particularly fundamental reason):

?:        conditional evaluation (§9.4.1)

In addition, user-defined literals (§19.2.6) are defined by using the operator"" notation. This is a kind of syntactic subterfuge because there is no operator called "". Similarly, operator T() defines a conversion to a type T (§18.4).

It is not possible to define new operator tokens, but you can use the function call notation when this set of operators is not adequate. For example, use pow(), not **. These restrictions may seem Draconian, but more flexible rules can easily lead to ambiguities. For example, defining an operator ** to mean exponentiation may seem an obvious and easy task, but think again. Should ** bind to the left (as in Fortran) or to the right (as in Algol)? Should the expression a**p be interpreted as a*(*p) or as (a)**(p)? There are solutions to all such technical questions. However, it is most uncertain if applying subtle technical rules will lead to more readable and maintainable code. If in doubt, use a named function.

The name of an operator function is the keyword operator followed by the operator itself, for example, operator<<. An operator function is declared and can be called like any other function. A use of the operator is only a shorthand for an explicit call of the operator function. For example:

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void f(complex a, complex b)
{
  complex c = a + b;           // shorthand
  complex d = a.operator+(b);  // explicit call
}

Given the previous definition of complex, the two initializers are synonymous.

18.2.1. Binary and Unary Operators

A binary operator can be defined by either a non-static member function taking one argument or a nonmember function taking two arguments. For any binary operator @, aa@bb can be interpreted as either aa.operator@(bb) or operator@(aa,bb). If both are defined, overload resolution (§12.3) determines which, if any, interpretation is used. For example:

class X {
public:
     void operator+(int);
     X(int);
};

void operator+(X,X);
void operator+(X,double);

void f(X a)
{
     a+1;     // a.operator+(1)
     1+a;     // ::operator+(X(1),a)
     a+1.0;   // ::operator+(a,1.0)
}

A unary operator, whether prefix or postfix, can be defined by either a non-static member function taking no arguments or a nonmember function taking one argument. For any prefix unary operator @, @aa can be interpreted as either aa.operator@() or operator@(aa). If both are defined, overload resolution (§12.3) determines which, if any, interpretation is used. For any postfix unary operator @, aa@ can be interpreted as either aa.operator@(int) or operator@(aa,int). This is explained further in §19.2.4. If both are defined, overload resolution (§12.3) determines which, if any, interpretation is used. An operator can be declared only for the syntax defined for it in the grammar (§iso.A). For example, a user cannot define a unary % or a ternary +. Consider:

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class X {
public:     // members (with implicit this pointer):

    X* operator&();         // prefix unary & (address of)
    X operator&(X);         // binary & (and)
    X operator++(int);      // postfix increment (see §19.2.4)
    X operator&(X,X);       // error: ternary
    X operator/();          // error: unary /
};
    // nonmember functions :

    X operator–(X);         // prefix unary minus
    X operator–(X,X);       // binary minus
    X operator––(X&,int);   // postfix decrement
    X operator–();          // error: no operand
    X operator–(X,X,X);     // error: ternary
    X operator%(X);         // error: unary %

Operator [] is described in §19.2.1, operator () in §19.2.2, operator –> in §19.2.3, operators ++ and –– in §19.2.4, and the allocation and deallocation operators in §11.2.4 and §19.2.5.

The operators operator= (§18.2.2), operator[] (§19.2.1), operator() (§19.2.2), and operator–> (§19.2.3) must be non-static member functions.

The default meaning of &&, ||, and , (comma) involves sequencing: the first operand is evaluated before the second (and for && and || the second operand is not always evaluated). This special rule does not hold for user-defined versions of &&, ||, and , (comma); instead these operators are treated exactly like other binary operators.

18.2.2. Predefined Meanings for Operators

The meanings of some built-in operators are defined to be equivalent to some combination of other operators on the same arguments. For example, if a is an int, ++a means a+=1, which in turn means a=a+1. Such relations do not hold for user-defined operators unless the user defines them to. For example, a compiler will not generate a definition of Z::operator+=() from the definitions of Z::operator+() and Z::operator=().

The operators = (assignment), & (address-of), and , (sequencing; §10.3.2) have predefined meanings when applied to class objects. These predefined meanings can be eliminated (“deleted”; §17.6.4):

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class X {
public:
     // ...
     void operator=(const X&) = delete;
     void operator&() = delete;
     void operator,(const X&) = delete;
     // ...
};

void f(X a, X b)
{
     a = b;    // error: no operator=()
     &a;       // error: no operator&()
     a,b;      // error: no operator,()
}

Alternatively, they can be given new meanings by suitable definitions.

18.2.3. Operators and User-Defined Types

An operator function must either be a member or take at least one argument of a user-defined type (functions redefining the new and delete operators need not). This rule ensures that a user cannot change the meaning of an expression unless the expression contains an object of a user-defined type. In particular, it is not possible to define an operator function that operates exclusively on pointers. This ensures that C++ is extensible but not mutable (with the exception of operators =, &, and , for class objects).

An operator function intended to accept a built-in type (§6.2.1) as its first operand cannot be a member function. For example, consider adding a complex variable aa to the integer 2: aa+2 can, with a suitably declared member function, be interpreted as aa.operator+(2), but 2+aa cannot because there is no class int for which to define + to mean 2.operator+(aa). Even if there were, two different member functions would be needed to cope with 2+aa and aa+2. Because the compiler does not know the meaning of a user-defined +, it cannot assume that the operator is commutative and so interpret 2+aa as aa+2. This example is trivially handled using one or more nonmember functions (§18.3.2, §19.4).

Enumerations are user-defined types so that we can define operators for them. For example:

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enum Day { sun, mon, tue, wed, thu, fri, sat };

Day& operator++(Day& d)
{
    return d = (sat==d) ? sun: static_cast<Day>(d+1);
}

Every expression is checked for ambiguities. Where a user-defined operator provides a possible interpretation, the expression is checked according to the overload resolution rules in §12.3.

18.2.4. Passing Objects

When we define an operator, we typically want to provide a conventional notation, for example, a=b+c. Consequently, we have limited choices of how to pass arguments to the operator function and how it returns its value. For example, we cannot require pointer arguments and expect programmers to use the address-of operator or return a pointer and expect the user to dereference it: *a=&b+&c is not acceptable.

For arguments, we have two main choices (§12.2):

• Pass-by-value

• Pass-by-reference

For small objects, say, one to four words, call-by-value is typically a viable alternative and often the one that gives the best performance. However, performance of argument passing and use depends on machine architecture, compiler interface conventions (Application Binary Interfaces; ABIs), and the number of times an argument is accessed (it almost always is faster to access an argument passed by value than one passed by reference). For example, assume that a Point is represented as a pair of ints:

void Point::operator+=(Point delta);   // pass-by-value

Larger objects, we pass by reference. For example, because a Matrix (a simple matrix of doubles; §17.5.1) is most likely larger than a few words, we use pass-by-reference:

Matrix operator+(const Matrix&, const Matrix&);  // pass-by-const-reference

In particular, we use const references to pass large objects that are not meant to be modified by the called function (§12.2.1).

Typically, an operator returns a result. Returning a pointer or a reference to a newly created object is usually a very bad idea: using a pointer gives notational problems, and referring to an object on the free store (whether by a pointer or by a reference) results in memory management problems. Instead, return objects by value. For large objects, such as a Matrix, define move operations to make such transfers of values efficient (§3.3.2, §17.5.2). For example:

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Matrix operator+(const Matrix& a, const Matrix& b)  // return-by-value
{
     Matrix res {a};
     return res+=b;
}

Note that operators that return one of their argument objects can – and usually do – return a reference. For example, we could define Matrix’s operator += like this:

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Matrix& Matrix::operator+=(const Matrix& a)       // return-by-reference
{
     if (dim[0]!=a.dim[0] || dim[1]!=a.dim[1])
           throw std::exception("bad Matrix += argument");

     double* p = elem;
     double* q = a.elem;
     double* end = *p+dim[0]*dim[1];
     while(p!=end)
           *p++ += *q++

     return *this;
 }

This is particularly common for operator functions that are implemented as members.

If a function simply passes an object to another function, an rvalue reference argument should be used (§17.4.3, §23.5.2.1, §28.6.3).

18.2.5. Operators in Namespaces

An operator is either a member of a class or defined in some namespace (possibly the global namespace). Consider this simplified version of string I/O from the standard library:

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namespace std {     // simplified std

    class string {
        // ...
    };
     class ostream {
       // ...
       ostream& operator<<(const char*);           // output C-style string
    };

    extern ostream cout;

    ostream& operator<<(ostream&, const string&);  // output std::string
} // namespace std

int main()
{
    const char* p = "Hello";
    std::string s = "world";
    std::cout << p << ", " << s << "!\n";
}

Naturally, this writes out Hello, world!. But why? Note that I didn’t make everything from std accessible by writing:

using namespace std;

Instead, I used the std:: prefix for string and cout. In other words, I was on my best behavior and didn’t pollute the global namespace or in other ways introduce unnecessary dependencies.

The output operator for C-style strings is a member of std::ostream, so by definition

std::cout << p

means

std::cout.operator<<(p)

However, std::ostream doesn’t have a member function to output a std::string, so

std::cout << s

means

operator<<(std::cout,s)

Operators defined in namespaces can be found based on their operand types just as functions can be found based on their argument types (§14.2.4). In particular, cout is in namespace std, so std is considered when looking for a suitable definition of <<. In that way, the compiler finds and uses:

std::operator<<(std::ostream&, const std::string&)

Consider a binary operator @. If x is of type X and y is of type Y, x@y is resolved like this:

• If X is a class, look for operator@ as a member of X or as a member of a base of X; and

• look for declarations of operator@ in the context surrounding x@y; and

• if X is defined in namespace N, look for declarations of operator@ in N; and

• if Y is defined in namespace M, look for declarations of operator@ in M.

Declarations for several operator@s may be found and overload resolution rules (§12.3) are used to find the best match, if any. This lookup mechanism is applied only if the operator has at least one operand of a user-defined type. Therefore, user-defined conversions (§18.3.2, §18.4) will be considered. Note that a type alias is just a synonym and not a separate user-defined type (§6.5).

Unary operators are resolved analogously.

Note that in operator lookup no preference is given to members over nonmembers. This differs from lookup of named functions (§14.2.4). The lack of hiding of operators ensures that built-in operators are never inaccessible and that users can supply new meanings for an operator without modifying existing class declarations. For example:

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X operator!(X);

struct Z {
     Z operator!();                          // does not hide ::operator!()
     X f(X x) { /* ... */ return !x; }       // invoke ::operator!(X)
     int f(int x) { /* ... */ return !x; }   // invoke the built-in ! for ints
};

In particular, the standard iostream library defines << member functions to output built-in types, and a user can define << to output user-defined types without modifying class ostream (§38.4.2).

18.3. A Complex Number Type

The implementation of complex numbers presented in §18.1 is too restrictive to please anyone. For example, we would expect this to work:

void f()
{
      complex a {1,2};
      complex b {3};
      complex c {a+2.3};
      complex d {2+b};
      b = c*2*c;
}

In addition, we would expect to be provided with a few additional operators, such as == for comparison and << for output, and a suitable set of mathematical functions, such as sin() and sqrt().

Class complex is a concrete type, so its design follows the guidelines from §16.3. In addition, users of complex arithmetic rely so heavily on operators that the definition of complex brings into play most of the basic rules for operator overloading.

The complex type developed in this section uses double for its scalars and is roughly equivalent to the standard-library complex<double> (§40.4).

18.3.1. Member and Nonmember Operators

I prefer to minimize the number of functions that directly manipulate the representation of an object. This can be achieved by defining only operators that inherently modify the value of their first argument, such as +=, in the class itself. Operators that simply produce a new value based on the values of their arguments, such as +, are then defined outside the class and use the essential operators in their implementation:

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class complex {
      double re, im;
public:
      complex& operator+=(complex a); // needs access to representation
     // ...
};

complex operator+(complex a, complex b)
{
      return a += b; // access representation through +=
}

The arguments to this operator+() are passed by value, so a+b does not modify its operands.

Given these declarations, we can write:

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void f(complex x, complex y, complex z)
{
     complex r1 {x+y+z}; // r1 = operator+(operator+(x,y),z)

     complex r2 {x};     // r2 = x
     r2 += y;            // r2.operator+=(y)
     r2 += z;            // r2.operator+=(z)
}

Except for possible efficiency differences, the computations of r1 and r2 are equivalent.

Composite assignment operators such as += and *= tend to be simpler to define than their “simple” counterparts + and *. This surprises most people at first, but it follows from the fact that three objects are involved in a + operation (the two operands and the result), whereas only two objects are involved in a += operation. In the latter case, run-time efficiency is improved by eliminating the need for temporary variables. For example:

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inline complex& complex::operator+=(complex a)
{
     re += a.re;
     im += a.im;
     return *this;
}

This does not require a temporary variable to hold the result of the addition and is simple for a compiler to inline perfectly.

A good optimizer will generate close to optimal code for uses of the plain + operator also. However, we don’t always have a good optimizer, and not all types are as simple as complex, so §19.4 discusses ways of defining operators with direct access to the representation of classes.

18.3.2. Mixed-Mode Arithmetic

To cope with 2+z, where z is a complex, we need to define operator + to accept operands of different types. In Fortran terminology, we need mixed-mode arithmetic. We can achieve that simply by adding appropriate versions of the operators:

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class complex {
     double re, im;
public:
     complex& operator+=(complex a)
     {
         re += a.re;
         im += a.im;
         return *this;
     }

     complex& operator+=(double a)
     {
         re += a;
         return *this;
     }

     // ...
};

The three variants of operator+() can be defined outside complex:

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complex operator+(complex a, complex b)
{
    return a += b; // calls complex::operator+=(complex)
}

complex operator+(complex a, double b)
{
    return {a.real()+b,a.imag()};
}

complex operator+(double a, complex b)
{
    return {a+b.real(),b.imag()};
}

The access functions real() and imag() are defined in §18.3.6.

Given these declarations of +, we can write:

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void f(complex x, complex y)
{
     auto r1 = x+y; // calls operator+(complex,complex)
     auto r2 = x+2; // calls operator+(complex,double)
     auto r3 = 2+x; // calls operator+(double,complex)
     auto r4 = 2+3; // built-in integer addition
}

I added the integer addition for completeness.

18.3.3. Conversions

To cope with assignments and initialization of complex variables with scalars, we need a conversion of a scalar (integer or floating-point number) to a complex. For example:

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complex b {3}; // should mean b.re=3, b.im=0

void comp(complex x)
{
     x = 4;    // should mean x.re=4, x.im=0
    // ...
}

We can achieve that by providing a constructor that takes a single argument. A constructor taking a single argument specifies a conversion from its argument type to the constructor’s type. For example:

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class complex {
     double re, im;
public:
     complex(double r) :re{r}, im{0} { } // build a complex from a double
     // ...
};

The constructor specifies the traditional embedding of the real line in the complex plane.

A constructor is a prescription for creating a value of a given type. The constructor is used when a value of a type is expected and when such a value can be created by a constructor from the value supplied as an initializer or assigned value. Thus, a constructor requiring a single argument need not be called explicitly. For example:

complex b {3};

means

complex b {3,0};

A user-defined conversion is implicitly applied only if it is unique (§12.3). If you don’t want a constructor to be used implicitly, declare it explicit (§16.2.6).

Naturally, we still need the constructor that takes two doubles, and a default constructor initializing a complex to {0,0} is also useful:

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class complex {
     double re, im;
public:
     complex() : re{0}, im{0} { }
     complex(double r) : re{r}, im{0} { }
     complex(double r, double i) : re{r}, im{i} { }
     // ...
};

Using default arguments, we can abbreviate:

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class complex {
      double re, im;
public:
      complex(double r =0, double i =0) : re{r}, im{i} { }
      // ...
};

By default, copying complex values is defined as copying the real and imaginary parts (§16.2.2). For example:

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void f()
{
     complex z;
     complex x {1,2};
     complex y {x}; // y also has the value {1,2}
     z = x;         // z also has the value {1,2}
}

18.3.3.1. Conversions of Operands

We defined three versions of each of the four standard arithmetic operators:

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complex operator+(complex,complex);
complex operator+(complex,double);
complex operator+(double,complex);
// ...

This can get tedious, and what is tedious easily becomes error-prone. What if we had three alternatives for the type of each argument for each function? We would need three versions of each single-argument function, nine versions of each two-argument function, 27 versions of each three-argument function, etc. Often these variants are very similar. In fact, almost all variants involve a simple conversion of arguments to a common type followed by a standard algorithm.

The alternative to providing different versions of a function for each combination of arguments is to rely on conversions. For example, our complex class provides a constructor that converts a double to a complex. Consequently, we could simply declare only one version of the equality operator for complex:

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bool operator==(complex,complex);

void f(complex x, complex y)
{
     x==y;    // means operator==(x,y)
     x==3;    // means operator==(x,complex(3))
     3==y;    // means operator==(complex(3),y)
}

There can be reasons for preferring to define separate functions. For example, in some cases the conversion can impose overhead, and in other cases, a simpler algorithm can be used for specific argument types. Where such issues are not significant, relying on conversions and providing only the most general variant of a function – plus possibly a few critical variants – contain the combinatorial explosion of variants that can arise from mixed-mode arithmetic.

Where several variants of a function or an operator exist, the compiler must pick “the right” variant based on the argument types and the available (standard and user-defined) conversions. Unless a best match exists, an expression is ambiguous and is an error (see §12.3).

An object constructed by explicit or implicit use of a constructor in an expression is automatic and will be destroyed at the first opportunity (see §10.3.4).

No implicit user-defined conversions are applied to the left-hand side of a . (or a –>). This is the case even when the . is implicit. For example:

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void g(complex z)
{
     3+z;               // OK: complex(3)+z
     3.operator+=(z);         // error: 3 is not a class object
     3+=z;              // error: 3 is not a class object
}

Thus, you can approximate the notion that an operator requires an lvalue as its left-hand operand by making that operator a member. However, that is only an approximation because it is possible to access a temporary with a modifying operation, such as operator+=():

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complex x {4,5}
complex z {sqrt(x)+={1,2}};       // like tmp=sqrt(x), tmp+={1,2}

If we don’t want implicit conversions, we can use explicit to suppress them (§16.2.6, §18.4.2).

18.3.4. Literals

We have literals of built-in types. For example, 1.2 and 12e3 are literals of type double. For complex, we can come pretty close to that by declaring constructors constexpr (§10.4). For example:

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class complex {
public:
     constexpr complex(double r =0, double i =0) : re{r}, im{i} { }
     // ...
}

Given that, a complex can be constructed from its constituent parts at compile time just like a literal from a built-in type. For example:

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complex z1 {1.2,12e3};
constexpr complex z2 {1.2,12e3};   // guaranteed compile-time initialization

When constructors are simple and inline, and especially when they are constexpr, it is quite reasonable to think of constructor invocations with literal arguments as literals.

It is possible to go further and introduce a user-defined literal (§19.2.6) in support of our complex type. In particular, we could define i to be a suffix meaning “imaginary.” For example:

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constexpr complex<double> operator "" i(long double d)  // imaginary literal
{
     return {0,d}; // complex is a literal type
}

This would allow us to write:

complex z1 {1.2+12e3i};

complex f(double d)
{
    auto x {2.3i};
    return x+sqrt(d+12e3i)+12e3i;
}

This user-defined literal gives us one advantage over what we get from constexpr constructors: we can use user-defined literals in the middle of expressions where the {} notation can only be used when qualified by a type name. The example above is roughly equivalent to:

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complex z1 {1.2,12e3};

complex f(double d)
{
    complex x {0,2.3};
    return x+sqrt(complex{d,12e3})+complex{0,12e3};
}

I suspect that the choice of style of literal depends on your sense of aesthetics and the conventions of your field of work. The standard-library complex uses constexpr constructors rather than a user-defined literal.

18.3.5. Accessor Functions

So far, we have provided class complex with constructors and arithmetic operators only. That is not quite sufficient for real use. In particular, we often need to be able to examine and change the value of the real and imaginary parts:

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class complex {
     double re, im;
public:
     constexpr double real() const { return re; }
     constexpr double imag() const { return im; }

     void real(double r) { re = r; }
     void imag(double i) { im = i; }
     // ...
};

I don’t consider it a good idea to provide individual access to all members of a class; in general, it is not. For many types, individual access (sometimes referred to as get-and-set functions) is an invitation to disaster. If we are not careful, individual access could compromise an invariant, and it typically complicates changes to the representation. For example, consider the opportunities for misuse from providing getters and setters for every member of the Date from §16.3 or (even more so) for the String from §19.3. However, for complex, real() and imag() are semantically significant: some algorithms are most cleanly written if they can set the real and imaginary parts independently.

For example, given real() and imag(), we can simplify simple, common, and useful operations, such as ==, as nonmember functions (without compromising performance):

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inline bool operator==(complex a, complex b)
{
      return a.real()==b.real() && a.imag()==b.imag();
}

18.3.6. Helper Functions

If we put all the bits and pieces together, the complex class becomes:

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class complex {
     double re, im;
public:
     constexpr complex(double r =0, double i =0) : re(r), im(i) { }

     constexpr double real() const { return re; }
     constexpr double imag() const { return im; }

     void real(double r) { re = r; }
     void imag(double i) { im = i; }

     complex& operator+=(complex);
     complex& operator+=(double);

     // -=, *=, and /=
};

In addition, we must provide a number of helper functions:

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complex operator+(complex,complex);
complex operator+(complex,double);
complex operator+(double,complex);

// binary -, *, and /

complex operator–(complex); // unary minus 
complex operator+(complex); // unary plus

bool operator==(complex,complex);
bool operator!=(complex,complex);

istream& operator>>(istream&,complex&); // input
ostream& operator<<(ostream&,complex);  // output

Note that the members real() and imag() are essential for defining the comparisons. The definitions of most of the following helper functions similarly rely on real() and imag().

We might provide functions to allow users to think in terms of polar coordinates:

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complex polar(double rho, double theta);
complex conj(complex);

double abs(complex);
double arg(complex);
double norm(complex);

double real(complex);        // for notational convenience
double imag(complex);        // for notational convenience

Finally, we must provide an appropriate set of standard mathematical functions:

complex acos(complex);
complex asin(complex);
complex atan(complex);
// ...

From a user’s point of view, the complex type presented here is almost identical to the complex<double> found in <complex> in the standard library (§5.6.2, §40.4).

18.4. Type Conversion

Type conversion can be accomplished by

• A constructor taking a single argument (§16.2.5)

• A conversion operator (§18.4.1)

In either case the conversion can be

• explicit; that is, the conversion is only performed in a direct initialization (§16.2.6), i.e., as an initializer not using a =.

• Implicit; that is, it will be applied wherever it can be used unambiguously (§18.4.3), e.g., as a function argument.

18.4.1. Conversion Operators

Using a constructor taking a single argument to specify type conversion is convenient but has implications that can be undesirable. Also, a constructor cannot specify

[1] an implicit conversion from a user-defined type to a built-in type (because the built-in types are not classes), or

[2] a conversion from a new class to a previously defined class (without modifying the declaration for the old class).

These problems can be handled by defining a conversion operator for the source type. A member function X::operator T(), where T is a type name, defines a conversion from X to T. For example, we could define a 6-bit non-negative integer, Tiny, that can mix freely with integers in arithmetic operations. Tiny throws Bad_range if its operations overflow or underflow:

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class Tiny {
     char v;
     void assign(int i) { if (i&~077) throw Bad_range(); v=i; }
public:
     class Bad_range { };

     Tiny(int i) { assign(i); }
     Tiny& operator=(int i) { assign(i); return *this; }

     operator int() const { return v; }    // conversion to int function
};

The range is checked whenever a Tiny is initialized by an int and whenever an int is assigned to one. No range check is needed when we copy a Tiny, so the default copy constructor and assignment are just right.

To enable the usual integer operations on Tiny variables, we define the implicit conversion from Tiny to int, Tiny::operator int(). Note that the type being converted to is part of the name of the operator and cannot be repeated as the return value of the conversion function:

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Tiny::operator int() const { return v; }      // right
int Tiny::operator int() const { return v; }  // error

In this respect also, a conversion operator resembles a constructor.

Whenever a Tiny appears where an int is needed, the appropriate int is used. For example:

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int main()
{
     Tiny c1 = 2;
     Tiny c2 = 62;
     Tiny c3 = c2–c1;  // c3 = 60
     Tiny c4 = c3;     // no range check (not necessary)
     int i = c1+c2;    // i = 64

     c1 = c1+c2;       // range error: c1 can't be 64
     i = c3–64;        // i = -4
     c2 = c3–64;       // range error: c2 can't be -4
     c3 = c4;          // no range check (not necessary)
}

Conversion functions appear to be particularly useful for handling data structures when reading (implemented by a conversion operator) is trivial, while assignment and initialization are distinctly less trivial.

The istream and ostream types rely on a conversion function to enable statements such as:

while (cin>>x)
      cout<<x;

The input operation cin>>x returns an istream&. That value is implicitly converted to a value indicating the state of cin. This value can then be tested by the while (see §38.4.4). However, it is typically not a good idea to define an implicit conversion from one type to another in such a way that information is lost in the conversion.

In general, it is wise to be sparing in the introduction of conversion operators. When used in excess, they lead to ambiguities. Such ambiguities are caught by the compiler, but they can be a nuisance to resolve. Probably the best idea is initially to do conversions by named functions, such as X::make_int(). If such a function becomes popular enough to make explicit use inelegant, it can be replaced by a conversion operator X::operator int().

If both user-defined conversions and user-defined operators are defined, it is possible to get ambiguities between the user-defined operators and the built-in operators. For example:

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int operator+(Tiny,Tiny);

void f(Tiny t, int i)
{
     t+i; // error, ambiguous: "operator+(t,Tiny(i))" or "int(t)+i"?
}

It is therefore often best to rely on user-defined conversions or user-defined operators for a given type, but not both.

18.4.2. explicit Conversion Operators

Conversion operators tend to be defined so that they can be used everywhere. However, it is possible to declare a conversion operator explicit and have it apply only for direct initialization (§16.2.6), where an equivalent explicit constructor would have been used. For example, the standard-library unique_ptr (§5.2.1, §34.3.1) has an explicit conversion to bool:

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template <typename T, typename D = default_delete<T>>
class unique_ptr {
public:
    // ...
    explicit operator bool() const noexcept;   // does *this hold a pointer (that is not nullptr)?
    // ...
};

The reason to declare this conversion operator explicit is to avoid its use in surprising contexts. Consider:

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void use(unique_ptr<Record> p, unique_ptr<int> q)
{
     if (!p)       // OK: we want this use
           throw Invalid_uninque_ptr{};

     bool b = p;   // error; suspicious use
     int x = p+q;  // error; we definitly don't want this
}

Had unique_ptr’s conversion to bool not been explicit, the last two definitions would have compiled. The value of b would have become true and the value of x would have become 1 or 2 (depending on whether q was valid or not).

18.4.3. Ambiguities

An assignment of a value of type V to an object of class X is legal if there is an assignment operator X::operator=(Z) so that V is Z or there is a unique conversion of V to Z. Initialization is treated equivalently.

In some cases, a value of the desired type can be constructed by repeated use of constructors or conversion operators. This must be handled by explicit conversions; only one level of user-defined implicit conversion is legal. In some cases, a value of the desired type can be constructed in more than one way; such cases are illegal. For example:

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class X { /* ... */ X(int); X(const char*); };
class Y { /* ... */ Y(int); };
class Z { /* ... */ Z(X); };

X f(X);
Y f(Y);

Z g(Z);

void k1()
{
     f(1);                   // error: ambiguous f(X(1)) or f(Y(1))?
     f(X{1});                // OK
     f(Y{1});                // OK

     g("Mack");              // error: two user-defined conversions needed; g(Z{X{"Mack"}}) not tried
     g(X{"Doc"});            // OK: g(Z{X{"Doc"}})
     g(Z{"Suzy"});           // OK: g(Z{X{"Suzy"}})
}

User-defined conversions are considered only if a call cannot be resolved without them (i.e., using only built-in conversions). For example:

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class XX { /* ... */ XX(int); };

void h(double);
void h(XX);

void k2()
{
     h(1); // h(double{1}) or h(XX{1})? h(double{1})!
}

The call h(1) means h(double(1)) because that alternative uses only a standard conversion rather than a user-defined conversion (§12.3).

The rules for conversion are neither the simplest to implement, nor the simplest to document, nor the most general that could be devised. They are, however, considerably safer, and the resulting resolutions are typically less surprising than alternatives. It is far easier to manually resolve an ambiguity than to find an error caused by an unsuspected conversion.

The insistence on strict bottom-up analysis implies that the return type is not used in overloading resolution. For example:

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class Quad {
public:
     Quad(double);
     // ...
};

Quad operator+(Quad,Quad);

void f(double a1, double a2)
{
     Quad r1 = a1+a2;       // double-precision floating-point add
     Quad r2 = Quad{a1}+a2; // force quad arithmetic
}

The reason for this design choice is partly that strict bottom-up analysis is more comprehensible and partly that it is not considered the compiler’s job to decide which precision the programmer might want for the addition.

Once the types of both sides of an initialization or assignment have been determined, both types are used to resolve the initialization or assignment. For example:

class Real {
public:
     operator double();
     operator int();
     // ...
};

void g(Real a)
{
     double d = a;   // d = a.double();
     int i = a;      // i = a.int();

     d = a;          // d = a.double();
     i = a;          // i = a.int();
}

In these cases, the type analysis is still bottom-up, with only a single operator and its argument types considered at any one time.

18.5. Advice

[1] Define operators primarily to mimic conventional usage; §18.1.

[2] Redefine or prohibit copying if the default is not appropriate for a type; §18.2.2.

[3] For large operands, use const reference argument types; §18.2.4.

[4] For large results, use a move constructor; §18.2.4.

[5] Prefer member functions over nonmembers for operations that need access to the representation; §18.3.1.

[6] Prefer nonmember functions over members for operations that do not need access to the representation; §18.3.2.

[7] Use namespaces to associate helper functions with “their” class; §18.2.5.

[8] Use nonmember functions for symmetric operators; §18.3.2.

[9] Use member functions to express operators that require an lvalue as their left-hand operand; §18.3.3.1.

[10] Use user-defined literals to mimic conventional notation; §18.3.4.

[11] Provide “set() and get() functions” for a data member only if the fundamental semantics of a class require them; §18.3.5.

[12] Be cautious about introducing implicit conversions; §18.4.

[13] Avoid value-destroying (“narrowing”) conversions; §18.4.1.

[14] Do not define the same conversion as both a constructor and a conversion operator; §18.4.3.

19. Special Operators

We are all special cases.

– Albert Camus

• Introduction

• Special Operators

Subscripting; Function Call; Dereferencing; Increment and Decrement; Allocation and Deallocation; User-Defined Literals

• A String Class

Essential Operations; Access to Characters; Representation; Member Functions; Helper Functions; Using Our String

• Friends

Finding Friends; Friends and Members

• Advice

19.1. Introduction

Overloading is not just for arithmetic and logical operations. In fact, operators are crucial in the design of containers (e.g., vector and map; §4.4), “smart pointers” (e.g., unique_ptr and shared_ptr; §5.2.1), iterators (§4.5), and other classes concerned with resource management.

19.2. Special Operators

The operators

[] () –> ++ –– new delete

are special only in that the mapping from their use in the code to a programmer’s definition differs slightly from that used for conventional unary and binary operators, such as +, <, and ~ (§18.2.3). The [] (subscript) and () (call) operators are among the most useful user-defined operators.

19.2.1. Subscripting

An operator[] function can be used to give subscripts a meaning for class objects. The second argument (the subscript) of an operator[] function may be of any type. This makes it possible to define vectors, associative arrays, etc.

As an example, we can define a simple associative array type like this:

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struct Assoc {
     vector<pair<string,int>> vec; // vector of {name,value} pairs

     const int& operator[] (const string&) const;
     int& operator[](const string&);
};

An Assoc keeps a vector of std::pairs. The implementation uses the same trivial and inefficient search method as in §7.7:

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int& Assoc::operator[](const string& s)
     // search for s; return a reference to its value if found;
     // otherwise, make a new pair {s,0} and return a reference to its value
{
     for (auto x : vec)
          if (s == x.first) return x.second;

     vec.push_back({s,0});             // initial value: 0

     return vec.back().second;         // return last element (§31.2.2)
}

We can use Assoc like this:

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int main()    // count the occurrences of each word on input
{
     Assoc values;
     string buf;
     while (cin>>buf) ++values[buf];
     for (auto x : values.vec)
           cout << '{' << x.first << ',' << x.second << "}\n";
}

The standard-library map and unordered_map are further developments of the idea of an associative array (§4.4.3, §31.4.3) with less naive implementations.

An operator[]() must be a non-static member function.

19.2.2. Function Call

Function call, that is, the notation expression(expression-list), can be interpreted as a binary operation with the expression as the left-hand operand and the expression-list as the right-hand operand. The call operator, (), can be overloaded in the same way as other operators can. For example:

struct Action {
     int operator()(int);
     pair<int,int> operator()(int,int);
     double operator()(double);
     // ...
};

void f(Action act)
{
     int x = act(2);
     auto y = act(3,4);
     double z = act(2.3);
     // ...
};

An argument list for an operator()() is evaluated and checked according to the usual argument-passing rules. Overloading the function call operator seems to be useful primarily for defining types that have only a single operation and for types for which one operation is predominant. The call operator is also known as the application operator.

The most obvious and also the most important, use of the () operator is to provide the usual function call syntax for objects that in some way behave like functions. An object that acts like a function is often called a function-like object or simply a function object (§3.4.3). Such function objects allow us to write code that takes nontrivial operations as parameters. In many cases, it is essential that function objects can hold data needed to perform their operation. For example, we can define a class with an operator()() that adds a stored value to its argument:

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class Add {
     complex val;
public:
     Add(complex c) :val{c} { }                         // save a value
     Add(double r, double i) :val{{r,i}} { }

     void operator()(complex& c) const { c += val; }    // add a value to argument
};

An object of class Add is initialized with a complex number, and when invoked using (), it adds that number to its argument. For example:

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void h(vector<complex>& vec, list<complex>& lst, complex z)
{
     for_each(vec.begin(),vec.end(),Add{2,3});
     for_each(lst.begin(),lst.end(),Add{z});
}

This will add complex{2,3} to every element of the vector and z to every element of the list. Note that Add{z} constructs an object that is used repeatedly by for_each(): Add{z}’s operator()() is called for each element of the sequence.

This all works because for_each is a template that applies () to its third argument without caring exactly what that third argument really is:

template<typename Iter, typename Fct>
Fct for_each(Iter b, Iter e, Fct f)
{
     while (b != e) f(*b++);
     return f;
}

At first glance, this technique may look esoteric, but it is simple, efficient, and extremely useful (§3.4.3, §33.4).

Note that a lambda expression (§3.4.3, §11.4) is basically a syntax for defining a function object. For example, we could have written:

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void h2(vector<complex>& vec, list<complex>& lst, complex z)
{
     for_each(vec.begin(),vec.end(),[](complex& a){ a+={2,3}; });
     for_each(lst.begin(),lst.end(),[](complex& a){ a+=z; });
}

In this case, each of the lambda expressions generates the equivalent of the function object Add.

Other popular uses of operator()() are as a substring operator and as a subscripting operator for multidimensional arrays (§29.2.2, §40.5.2).

An operator()() must be a non-static member function.

Function call operators are often templates (§29.2.2, §33.5.3).

19.2.3. Dereferencing

The dereferencing operator, –> (also known as the arrow operator), can be defined as a unary postfix operator. For example:

class Ptr {
     // ...
     X* operator–>();
};

Objects of class Ptr can be used to access members of class X in a very similar manner to the way pointers are used. For example:

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void f(Ptr p)
{
     p–>m = 7;     // (p.operator->())->m = 7
}

The transformation of the object p into the pointer p.operator–>() does not depend on the member m pointed to. That is the sense in which operator–>() is a unary postfix operator. However, there is no new syntax introduced, so a member name is still required after the –>. For example:

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void g(Ptr p)
{
     X* q1 = p–>;              // syntax error
     X* q2 = p.operator–>();   // OK
}

Overloading –> is primarily useful for creating “smart pointers,” that is, objects that act like pointers and in addition perform some action whenever an object is accessed through them. The standard-library “smart pointers” unique_ptr and shared_ptr (§5.2.1) provide operator –>.

As an example, we could define a class Disk_ptr for accessing objects stored on disk. Disk_ptr’s constructor takes a name that can be used to find the object on disk, Disk_ptr::operator–>() brings the object into main memory when accessed through its Disk_ptr, and Disk_ptr’s destructor eventually writes the updated object back out to disk:

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template<typename T>
class Disk_ptr {
     string identifier;
     T* in_core_address;
     // ...
public:
     Disk_ptr(const string& s) : identifier{s}, in_core_address{nullptr} { }
     ~Disk_ptr() { write_to_disk(in_core_address,identifier); }

     T* operator–>()
     {
          if (in_core_address == nullptr)
                in_core_address = read_from_disk(identifier);
          return in_core_address;
     }
};

Disk_ptr might be used like this:

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struct Rec {
     string name;
     // ...
};

void update(const string& s)
{
     Disk_ptr<Rec> p {s};        // get Disk_ptr for s

     p–>name = "Roscoe";         // update s; if necessary, first retrieve from disk
     // ...
}                                // p's destructor writes back to disk

Naturally, a realistic program would contain error-handling code and use a less naive way of interacting with the disk.

For ordinary pointers, use of –> is synonymous with some uses of unary * and []. Given a class Y for which –>, *, and [] have their default meaning and a Y* called p, then:

p–>m == (*p).m         // is true
(*p).m == p[0].m       // is true
p–>m == p[0].m         // is true

As usual, no such guarantee is provided for user-defined operators. The equivalence can be provided where desired:

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template<typename T>
class Ptr {
     Y* p;
public:
     Y* operator–>() { return p; }          // dereference to access member
     Y& operator*() { return *p; }          // dereference to access whole object
     Y& operator[](int i) { return p[i]; }  // dereference to access element
     // ...
};

If you provide more than one of these operators, it might be wise to provide the equivalence, just as it is wise to ensure that ++x and x+=1 have the same effect as x=x+1 for a simple variable x of some class X if ++, +=, =, and + are provided.

The overloading of –> is important to a class of interesting programs and is not just a minor curiosity. The reason is that indirection is a key concept and that overloading –> provides a clean, direct, and efficient way of representing indirection in a program. Iterators (Chapter 33) provide an important example of this.

Operator –> must be a non-static member function. If used, its return type must be a pointer or an object of a class to which you can apply –>. The body of a template class member function is only checked if the function is used (§26.2.1), so we can define operator–>() without worrying about types, such as Ptr<int>, for which –> does not make sense.

Despite the similarity between –> and . (dot), there is no way of overloading operator . (dot).

19.2.4. Increment and Decrement

Once people invent “smart pointers,” they often decide to provide the increment operator ++ and the decrement operator –– to mirror these operators’ use for built-in types. This is especially obvious and necessary where the aim is to replace an ordinary pointer type with a “smart pointer” type that has the same semantics, except that it adds a bit of run-time error checking. For example, consider a troublesome traditional program:

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void f1(X a)            // traditional use
{
     X v[200];
     X* p = &v[0];
     p––;
     *p = a;   // oops: p out of range, uncaught
     ++p;
     *p = a;   // OK
}

Here, we might want to replace the X* with an object of a class Ptr<X> that can be dereferenced only if it actually points to an X. We would also like to ensure that p can be incremented and decremented only if it points to an object within an array and the increment and decrement operations yield an object within that array. That is, we would like something like this:

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void f2(Ptr<X> a)          // checked
{
     X v[200];
     Ptr<X> p(&v[0],v);
     p––;
     *p = a;  // run-time error: p out of range
     ++p;
     *p = a;  // OK
}

The increment and decrement operators are unique among C++ operators in that they can be used as both prefix and postfix operators. Consequently, we must define prefix and postfix increment and decrement for Ptr<T>. For example:

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template<typename T>
class Ptr {
     T* ptr;
     T* array;
     int sz;
public:
     template<int N>
         Ptr(T* p, T(&a)[N]);       // bind to array a, sz==N, initial value p
     Ptr(T* p, T* a, int s);        // bind to array a of size s, initial value p
     Ptr(T* p);                     // bind to single object, sz==0, initial value p

     Ptr& operator++();             // prefix
     Ptr operator++(int);           // postfix

     Ptr& operator––();             // prefix
     Ptr operator––(int);           // postfix

     T& operator*();                // prefix
};

The int argument is used to indicate that the function is to be invoked for postfix application of ++. This int is never used; the argument is simply a dummy used to distinguish between prefix and postfix application. The way to remember which version of an operator++ is prefix is to note that the version without the dummy argument is prefix, exactly like all the other unary arithmetic and logical operators. The dummy argument is used only for the “odd” postfix ++ and ––.

Consider omitting postfix ++ and –– in a design. They are not only odd syntactically, they tend to be marginally harder to implement than the postfix versions, less efficient, and less frequently used. For example:

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template<typename T>
Ptr& Ptr<T>::operator++()               // return the current object after incrementing
{
     // ... check that ptr+1 can be pointed to ...
     return *++ptr;
}

template<typename T>
Ptr Ptr<T>::operator++(int)            // increment and return a Ptr with the old value
{
     // ... check that ptr+1 can be pointed to ...
     Ptr<T> old {ptr,array,sz};
     ++ptr;
     return old;
}

The pre-increment operator can return a reference to its object. The post-increment operator must make a new object to return.

Using Ptr, the example is equivalent to:

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void f3(T a)       // checked
{
     T v[200];
     Ptr<T> p(&v[0],v,200);
     p.operator––(0);        // suffix: p--
     p.operator*() = a;      // run-time error: p out of range
     p.operator++();         // prefix: ++p
     p.operator*() = a;      // OK
}

Completing class Ptr is left as an exercise. A pointer template that behaves correctly with respect to inheritance is presented in §27.2.2.

19.2.5. Allocation and Deallocation

Operator new (§11.2.3) acquires its memory by calling an operator new(). Similarly, operator delete frees its memory by calling an operator delete(). A user can redefine the global operator new() and operator delete() or define operator new() and operator delete() for a particular class.

Using the standard-library type alias size_t (§6.2.8) for sizes, the declarations of the global versions look like this:

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void* operator new(size_t);               // use for individual object
void* operator new[](size_t);             // use for array
void operator delete(void*, size_t);      // use for individual object
void operator delete[](void*, size_t);    // use for array

// for more versions, see §11.2.4

That is, when new needs memory on the free store for an object of type X, it calls operator new(sizeof(X)). Similarly, when new needs memory on the free store for an array of N objects of type X, it calls operator new[](N*sizeof(X)). A new expression may ask for more memory than is indicated by N*sizeof(X), but it will always do so in terms of a number of characters (i.e., a number of bytes). Replacing the global operator new() and operator delete() is not for the fainthearted and not recommended. After all, someone else might rely on some aspect of the default behavior or might even have supplied other versions of these functions.

A more selective, and often better, approach is to supply these operations for a specific class. This class might be the base for many derived classes. For example, we might like to have a class Employee provide a specialized allocator and deallocator for itself and all of its derived classes:

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class Employee {
public:
     // ...

     void* operator new(size_t);
     void operator delete(void*, size_t);

     void* operator new[](size_t);
     void operator delete[](void*, size_t);
};

Member operator new()s and operator delete()s are implicitly static members. Consequently, they don’t have a this pointer and do not modify an object. They provide storage that a constructor can initialize and a destructor can clean up.

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void* Employee::operator new(size_t s)
{
     // allocate s bytes of memory and return a pointer to it
}

void Employee::operator delete(void* p, size_t s)
{
     if (p) {    // delete only if p!=0; see §11.2, §11.2.3
            // assume p points to s bytes of memory allocated by Employee::operator new()
            // and free that memory for reuse
     }
}

The use of the hitherto mysterious size_t argument now becomes obvious. It is the size of the object being deleted. Deleting a “plain” Employee gives an argument value of sizeof(Employee); deleting a Manager derived from Employee that does not have its own operator delete() gives an argument value of sizeof(Manager). This allows a class-specific allocator to avoid storing size information with each allocation. Naturally, a class-specific allocator can store such information (as a general-purpose allocator must) and ignore the size_t argument to operator delete(). However, doing so makes it harder to improve significantly on the speed and memory consumption of a general-purpose allocator.

How does a compiler know how to supply the right size to operator delete()? The type specified in the delete operation matches the type of the object being deleted. If we delete an object through a pointer to a base class, that base class must have a virtual destructor (§17.2.5) for the correct size to be given:

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Employee* p = new Manager; // potential trouble (the exact type is lost)
// ...
delete p;                  // hope Employee has a virtual destructor

In principle, deallocation is then done by the destructor (which knows the size of its class).

19.2.6. User-defined Literals

C++ provides literals for a variety of built-in types (§6.2.6):

123        // int
1.2        // double
1.2F       // float
'a'        // char
1ULL       // unsigned long long
0xD0       // hexadecimal unsigned
"as"       // C-style string (const char[3])

In addition, we can define literals for user-defined types and new forms of literals for built-in types. For example:

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"Hi!"s                // string, not "zero-terminated array of char"
1.2i                  // imaginary
101010111000101b      // binary
123s                  // seconds
123.56km              // not miles! (units)
1234567890123456789012345678901234567890x   // extended-precision

Such user-defined literals are supported through the notion of literal operators that map literals with a given suffix into a desired type. The name of a literal operator is operator"" followed by the suffix. For example:

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constexpr complex<double> operator"" i(long double d)     // imaginary literal
{
    return {0,d}; // complex is a literal type
}

std::string operator"" s(const char* p, size_t n)     // std::string literal
{
     return string{p,n};  // requires free-store allocation
}

These two operators define suffixes i and s, respectively. I use constexpr to enable compile-time evaluation. Given those, we can write:

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template<typename T> void f(const T&);

void g()
{
     f("Hello");     // pass pointer to char*
     f("Hello"s);    // pass (five-character) string object
     f("Hello\n"s);  // pass (six-character) string object

     auto z = 2+1i;  // complex{2,1}
}

The basic (implementation) idea is that after parsing what could be a literal, the compiler always checks for a suffix. The user-defined literal mechanism simply allows the user to specify a new suffix and define what is to be done with the literal before it. It is not possible to redefine the meaning of a built-in literal suffix or to augment the syntax of literals.

There are four kinds of literals that can be suffixed to make a user-defined literal (§iso.2.14.8):

• An integer literal (§6.2.4.1): accepted by a literal operator taking an unsigned long long or a const char* argument or by a template literal operator, for example, 123m or 12345678901234567890X

• A floating-point literal (§6.2.5.1): accepted by a literal operator taking a long double or a const char* argument or by a template literal operator, for example, 12345678901234567890.976543210x or 3.99s

• A string literal (§7.3.2): accepted by a literal operator taking a (const char*, size_t) pair of arguments, for example, "string"s and R"(Foo\bar)"_path

• A character literal (§6.2.3.2): accepted by a literal operator taking a character argument of type char, wchar_t, char16_t, or char32_t, for example, 'f'_runic or u'BEEF'_w.

For example, we could define a literal operator to collect digits for integer values that cannot be represented in any of the built-in integer types:

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Bignum operator"" x(const char* p)
{
    return Bignum(p);
}

void f(Bignum);

f(123456789012345678901234567890123456789012345x);

Here, the C-style string "123456789012345678901234567890123456789012345" is passed to operator"" x(). Note that I did not put those digits in double quotes. I requested a C-style string for my operator, and the compiler delivered it from the digits provided.

To get a C-style string from the program source text into a literal operator, we request both the string and its number of characters. For example:

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string operator"" s(const char* p, size_t n);

string s12 = "one two"s;      // calls operator ""("one two",7)
string s22 = "two\ntwo"s;     // calls operator ""("two\ntwo",7)
string sxx = R"(two\ntwo)"s;  // calls operator ""("two\\ntwo",8)

In the raw string (§7.3.2.1), "\n" represents the two characters '\' and 'n'.

The rationale for requiring the number of characters is that if we want to have “a different kind of string,” we almost always want to know the number of characters anyway.

A literal operator that takes just a const char* argument (and no size) can be applied to integer and floating-point literals. For example:

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string operator"" SS(const char* p);     // warning: this will not work as expected

string s12 = "one two"SS;                // error: no applicable literal operator
string s13 = 13SS;                       // OK, but why would anyone do that?

A literal operator converting numerical values to strings could be quite confusing.

A template literal operator is a literal operator that takes its argument as a template parameter pack, rather than as a function argument. For example:

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template<char...>
constexpr int operator"" _b3();             // base 3, i.e., ternary

Given that, we get:

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201_b3   // means operator"" b3<'2','0','1'>(); so 9*2+0*3+1 == 19
241_b3   // means operator"" b3<'2','4','1'>(); so error: 4 isn't a ternary digit

The variadic template techniques (§28.6) can be disconcerting, but it is the only way of assigning nonstandard meanings to digits at compile time.

To define operator"" _b3(), we need some helper functions:

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constexpr int ipow(int x, int n) // x to the nth power for n>=0
{
    return (n>0) ? x*ipow(n–1) : 1;
}
template<char c>         // handle the single ternary digit case
constexpr int b3_helper()
{
    static_assert(c<'3',"not a ternary digit");
    return c;
}

template<char c, char... tail>   // peel off one ternary digit
constexpr int b3_helper()
{
    static_assert(c<'3',"not a ternary digit");
    return ipow(3,sizeof...(tail))*(c–'0')+b3_helper(tail...);
}

Given that, we can define our base 3 literal operator:

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template<char... chars>
constexpr int operator"" _b3()     // base 3, i.e., ternary
{
    return b3_helper(chars...);
}

Many suffixes will be short (e.g., s for std::string, i for imaginary, m for meter (§28.7.3), and x for extended), so different uses could easily clash. Use namespaces to prevent clashes:

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namespace Numerics {
    // ...

    class Bignum { /* ... */ };

    namespace literals {
        Bignum operator"" x(char const*);
    }
    // ...
}

using namespace Numerics::literals;

The standard library reserves all suffixes not starting with an initial underscore, so define your suffixes starting with an underscore or risk your code breaking in the future:

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123km       // reserved by the standard library
123_km      // available for your use

19.3. A String Class

The relatively simple string class presented in this section illustrates several techniques that are useful for the design and implementation of classes using conventionally defined operators. This String is a simplified version of the standard-library string (§4.2, Chapter 36). String provides value semantics, checked and unchecked access to characters, stream I/O, support for range-for loops, equality operations, and concatenation operators. I also added a String literal, which std::string does not (yet) have.

To allow simple interoperability with C-style strings (including string literals (§7.3.2)), I represent strings as zero-terminated arrays of characters. For realism, I implement the short string optimization. That is, a String with only a few characters stores those characters in the class object itself, rather than on the free store. This optimizes string usage for small strings. Experience shows that for a huge number of applications most strings are short. This optimization is particularly important in multi-threaded systems where sharing through pointers (or references) is infeasible and free-store allocation and deallocation relatively expensive.

To allow Strings to efficiently “grow” by adding characters at the end, I implement a scheme for keeping extra space for such growth similar to the one used for vector (§13.6.1). This makes String a suitable target for various forms of input.

Writing a better string class and/or one that provides more facilities is a good exercise. That done, we can throw away our exercises and use std::string (Chapter 36).

19.3.1. Essential Operations

Class String provides the usual set of constructors, a destructor, and assignment operations (§17.1):

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class String {
public:
     String();                                           // default constructor: x{""}

     explicit String(const char* p);                     // constructor from C-style string: x{"Euler"}

     String(const String&);                              // copy constructor
     String& operator=(const String&);                   // copy assignment

     String(String&& x);                                 // move constructor
     String& operator=(String&& x);                      // move assignment

     ~String() { if (short_max<sz) delete[] ptr; }       // destructor
     // ...
};

This String has value semantics. That is, after an assignment s1=s2, the two strings s1 and s2 are fully distinct, and subsequent changes to one have no effect on the other. The alternative would be to give String pointer semantics. That would be to let changes to s2 after s1=s2 also affect the value of s1. Where it makes sense, I prefer value semantics; examples are complex, vector, Matrix, and string. However, for value semantics to be affordable, we need to pass Strings by reference when we don’t need copies and to implement move semantics (§3.3.2, §17.5.2) to optimize returns.

The slightly nontrivial representation of String is presented in §19.3.3. Note that it requires user-defined versions of the copy and move operations.

19.3.2. Access to Characters

The design of access operators for a string is a difficult topic because ideally access is by conventional notation (that is, using []), maximally efficient, and range checked. Unfortunately, you cannot have all of these properties simultaneously. Here, I follow the standard library by providing efficient unchecked operations with the conventional [] subscript notation plus range-checked at() operations:

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class String {
public:
     // ...

     char& operator[](int n) { return ptr[n]; }                 // unchecked element access
     char operator[](int n) const { return ptr[n]; }

     char& at(int n) { check(n); return ptr[n]; }               // range-checked element access
     char at(int n) const { check(n); return ptr[n]; }

     String& operator+=(char c);                                // add c at end

     const char* c_str() { return ptr; }                        // C-style string access
     const char* c_str() const { return ptr; }

     int size() const { return sz; }                            // number of elements
     int capacity() const                                       // elements plus available space
           { return (sz<=short_max) ? short_max : sz+space; }
     // ...
};

The idea is to use [] for ordinary use. For example:

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int hash(const String& s)
{
     int h {s[0]};
     for (int i {1}; i!=s.size(); i++) h ^= s[i]>>1;       // unchecked access to s
     return h;
}

Here, using the checked at() would be redundant because we correctly access s only from 0 to s.size()–1.

We can use at() where we see a possibility of mistakes. For example:

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void print_in_order(const String& s,const vector<int>& index)
{
     for (x : index) cout << s.at(x) << '\n';
}

Unfortunately, assuming that people will use at() consistently where mistakes can be made is overly optimistic, so some implementations of std::string (from which the []/at() convention is borrowed) also check []. I personally prefer a checked [] at least during development. However, for serious string manipulation tasks, a range check on each character access could impose quite noticeable overhead.

I provide const and non-const versions of the access functions to allow them to be used for const as well as other objects.

19.3.3. Representation

The representation for String was chosen to meet three goals:

• To make it easy to convert a C-style string (e.g., a string literal) to a String and to allow easy access to the characters of a String as a C-style string

• To minimize the use of the free store

• To make adding characters to the end of a String efficient

The result is clearly messier than a simple {pointer,size} representation, but much more realistic:

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class String {
/*
     A simple string that implements the short string optimization

     size()==sz is the number of elements
     if size()<= short_max, the characters are held in the String object itself;
     otherwise the free store is used.

     ptr points to the start of the character sequence
     the character sequence is kept zero-terminated: ptr[size()]==0;
     this allows us to use C library string functions and to easily return a C-style string: c_str()

     To allow efficient addition of characters at end, String grows by doubling its allocation;
     capacity() is the amount of space available for characters
     (excluding the terminating 0): sz+space
*/

public:
     // ...
private:
     static const int short_max = 15;
     int sz;                       // number of characters
     char* ptr;
     union {
         int space;                // unused allocated space
         char ch[short_max+1];     // leave space for terminating 0
     };

     void check(int n) const       // range check
     {
         if (n<0 || sz<=n)
               throw std::out_of_range("String::at()");
     }

     // ancillary member functions:
     void copy_from(const String& x);
     void move_from(String& x);
};

This supports what is known as the short string optimization by using two string representations:

• If sz<=short_max, the characters are stored in the String object itself, in the array named ch.

• If !(sz<=short_max), the characters are stored on the free store and we may allocate extra space for expansion. The member named space is the number of such characters.

In both cases, the number of elements is kept in sz and we look at sz, to determine which implementation scheme is used for a given string.

In both cases, ptr points to the elements. This is essential for performance: the access functions do not need to test which representation is used; they simply use ptr. Only the constructors, assignments, moves, and the destructor (§19.3.4) must care about the two alternatives.

We use the array ch only if sz<=short_max and the integer space only if !(sz<=short_max). Consequently, it would be a waste to allocate space for both ch and space in a String object. To avoid such waste, I use a union (§8.3). In particular, I used a form of union called an anonymous union (§8.3.2), which is specifically designed to allow a class to manage alternative representations of objects. All members of an anonymous union are allocated in the same memory, starting at the same address. Only one member may be used at any one time, but otherwise they are accessed and used exactly as if they were separate members of the scope surrounding the anonymous union. It is the programmer’s job to make sure that they are never misused. For example, all member functions of String that use space must make sure that it really was space that was set and not ch. That is done by looking at sz<=short_max. In other words, Shape is (among other things) a discriminated union with sz<=short_max as the discriminant.

19.3.3.1. Ancillary Functions

In addition to functions intended for general use, I found that my code became cleaner when I provided three ancillary functions as “building blocks” to help me with the somewhat tricky representation and to minimize code replication. Two of those need to access the representation of String, so I made them members. However, I made them private members because they don’t represent operations that are generally useful and safe to use. For many interesting classes, the implementation is not just the representation plus the public functions. Ancillary functions can lead to less duplication of code, better design, and improved maintainability.

The first such function moves characters into newly allocated memory:

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char* expand(const char* ptr, int n)      // expand into free store
{
     char* p = new char[n];
     strcpy(p,ptr);           // §43.4
     return p;
}

This function does not access the String representation, so I did not make it a member.

The second implementation function is used by copy operations to give a String a copy of the members of another:

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void String::copy_from(const String& x)
     // make *this a copy of x
{
     if (x.sz<=short_max) {                // copy *this
           memcpy(this,&x,sizeof(x));      // §43.5
           ptr = ch;
     }
     else {                                // copy the elements
           ptr = expand(x.ptr,x.sz+1);
           sz = x.sz;
           space = 0;
     }
}

Any necessary cleanup of the target String is the task of callers of copy_from(); copy_from() unconditionally overwrites its target. I use the standard-library memcpy() (§43.5) to copy the bytes of the source into the target. That’s a low-level and sometimes pretty nasty function. It should be used only where there are no objects with constructors or destructors in the copied memory because memcpy() knows nothing about types. Both String copy operations use copy_from().

The corresponding function for move operations is:

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void String::move_from(String& x)
{
     if (x.sz<=short_max) {              // copy *this
           memcpy(this,&x,sizeof(x));    // §43.5
           ptr = ch;
     }

     else {                              // grab the elements
           ptr = x.ptr;
           sz = x.sz;
           space = x.space;
           x.ptr = x.ch;                 // x = ""
           x.sz = 0;
           x.ch[0]=0;
     }
}

It too unconditionally makes its target a copy of its argument. However, it does not leave its argument owning any free store. I could also have used memcpy() in the long string case, but since a long string representation uses only part of String’s representation, I decided to copy the used members individually.

19.3.4. Member Functions

The default constructor defines a String to be empty:

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String::String()               // default constructor: x{""}
           : sz{0}, ptr{ch}    // ptr points to elements, ch is an initial location (§19.3.3)
     {
           ch[0] = 0;          // terminating 0
     }

Given copy_from() and move_from(), the constructors, moves, and assignments are fairly simple to implement. The constructor that takes a C-style string argument must determine the number of characters and store them appropriately:

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String::String(const char* p)
     :sz{strlen(p)},
     ptr{(sz<=short_max) ? ch : new char[sz+1]},
     space{0}
{
     strcpy(ptr,p);  // copy characters into ptr from p
}

If the argument is a short string, ptr is set to point to ch; otherwise, space is allocated on the free store. In either case, the characters are copied from the argument string into the memory managed by String.

The copy constructor simply copies the representation of its arguments:

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String::String(const String& x)    // copy constructor
{
     copy_from(x);  // copy representation from x
}

I didn’t bother trying to optimize the case where the size of the source equals the size of the target (as was done for vector; §13.6.3). I don’t know if that would be worthwhile.

Similarly, the move constructor moves the representation from its source (and possibly sets it argument to be the empty string):

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String::String(String&& x)   // move constructor
{
     move_from(x);
}

Like the copy constructor, the copy assignment uses copy_from() to clone its argument’s representation. In addition, it has to delete any free store owned by the target and make sure it does not get into trouble with self-assignment (e.g., s=s):

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String& String::operator=(const String& x)
{
     if (this==&x) return *this;         // deal with self-assignment
     char* p = (short_max<sz) ? ptr : 0;
     copy_from(x);
     delete[] p;
     return *this;
}

The String move assignment deletes its target’s free store (if there is any) and then moves:

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String& String::operator=(String&& x)
{
     if (this==&x) return *this;        // deal with self-assignment (x = move(x) is insanity)
     if (short_max<sz) delete[] ptr;    // delete target
     move_from(x);                      // does not throw
     return *this;
}

It is logically possible to move a source into itself (e.g., s=std::move(s)), so again we have to protect against self-assignment (however unlikely).

The logically most complicated String operation is +=, which adds a character to the end of the string, increasing its size by one:

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String& String::operator+=(char c)
{
     if (sz==short_max) {       // expand to long string
           int n = sz+sz+2;     // double the allocation (+2 because of the terminating 0)
           ptr = expand(ptr,n);
           space = n–sz–2;
     }
     else if (short_max<sz) {
          if (space==0) {           // expand in free store
                int n = sz+sz+2;    // double the allocation (+2 because of the terminating 0)
                char* p = expand(ptr,n);
                delete[] ptr;
                ptr = p;
                space = n–sz–2;
           }
           else
                ––space;
     }
     ptr[sz] = c;       // add c at end
     ptr[++sz] = 0;     // increase size and set terminator

     return *this;
}

There is a lot going on here: operator+=() has to keep track of which representation (short or long) is used and whether there is extra space available to expand into. If more space is needed, expand() is called to allocate that space and move the old characters into the new space. If there was an old allocation that needs deleting, it is returned, so that += can delete it. Once enough space is available, it is trivial to put the new character c into it and to add the terminating 0.

Note the calculation of available memory for space. Of all the String implementation that took the longest to get right: its a messy little calculation prone to off-by-one errors. That repeated constant 2 feels awfully like a “magic constant.”

All String members take care not to modify a new representation before they are certain that a new one can be put in place. In particular, they don’t delete until after any possible new operations have been done. In fact, the String members provide the strong exception guarantee (§13.2).

If you don’t like the kind of fiddly code presented as part of the implementation of String, simply use std::string. To a large extent, the standard-library facilities exist to save us from programming at this low level most of the time. Stronger: writing a string class, a vector class, or a map is an excellent exercise. However, once the exercise is done, one outcome should be an appreciation of what the standard offers and a desire not to maintain your own version.

19.3.5. Helper Functions

To complete class String, I provide a set of useful functions, stream I/O, support for range-for loops, comparison, and concatenation. These all mirror the design choices used for std::string. In particular, << just prints the characters without added formatting, and >> skips initial whitespace before reading until it finds terminating whitespace (or the end of the stream):

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ostream& operator<<(ostream& os, const String& s)
{
     return os << s.c_str(); // §36.3.3
}

istream& operator>>(istream& is, String& s)
{
     s = "";    // clear the target string
     is>>ws;    // skip whitespace (§38.4.5.1)
     char ch = ' ';
     while(is.get(ch) && !isspace(ch))
          s += ch;
     return is;
}

I provide == and != for comparison:

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bool operator==(const String& a, const String& b)
{
     if (a.size()!=b.size())
           return false;
     for (int i = 0; i!=a.size(); ++i)
           if (a[i]!=b[i])
                 return false;
     return true;
}

bool operator!=(const String& a, const String& b)
{
     return !(a==b);
}

Adding <, etc., would be trivial.

To support the range-for loop, we need begin() and end() (§9.5.1). Again, we can provide those as freestanding (nonmember) functions without direct access to the String implementation:

Click here to view code image

char* begin(String& x)          // C-string-style access
{
     return x.c_str();
}

char* end(String& x)
{
     return x.c_str()+x.size();
}

const char* begin(const String& x)
{
     return x.c_str();
}

const char* end(const String& x)
{
     return x.c_str()+x.size();
}

Given the member function += that adds a character at the end, concatenation operators are easily provided as nonmember functions:

Click here to view code image

String& operator+=(String& a, const String& b)      // concatenation
{
     for (auto x : b)
           a+=x;
     return a;
}
String operator+(const String& a, const String& b)  // concatenation
{
     String res {a};
     res += b;
     return res;
}

I feel that I may have slightly “cheated” here. Should I have provided a member += that added a C-style string to the end? The standard-library string does, but without it, concatenation with a C-style string still works. For example:

Click here to view code image

String s = "Njal ";
s += "Gunnar";      // concatenate: add to the end of s

This use of += is interpreted as operator+=(s,String("Gunnar")). My guess is that I could provide a more efficient String::operator+=(const char*), but I have no idea if the added performance would be worthwhile in real-world code. In such cases, I try to be conservative and deliver the minimal design. Being able to do something is not by itself a good reason for doing it.

Similarly, I do not try to optimize += by taking the size of a source string into account.

Adding _s as a string literal suffix meaning String is trivial:

Click here to view code image

String operator"" _s(const char* p, size_t)
{
     return String{p};
}

We can now write:

Click here to view code image

void f(const char*);        // C-style string
void f(const String&);      // our string

void g()
{
     f("Madden's");               // f(const char*)
     f("Christopher's"_s);        // f(const String&);
}

19.3.6. Using Our String

The main program simply exercises the String operators a bit:

Click here to view code image

int main()
{
     String s ("abcdefghij");
     cout << s << '\n';
     s += 'k';
     s += 'l';
     s += 'm';
     s += 'n';
     cout << s << '\n';
     String s2 = "Hell";
     s2 += " and high water";
     cout << s2 << '\n';

     String s3 = "qwerty";
     s3 = s3;
     String s4 ="the quick brown fox jumped over the lazy dog";
     s4 = s4;
     cout << s3 << " " << s4 << "\n";
     cout << s + ". " + s3 + String(". ") + "Horsefeathers\n";

     String buf;
     while (cin>>buf && buf!="quit")
           cout << buf << " " << buf.size() << " " << buf.capacity() << '\n';
}

This String lacks many features that you might consider important or even essential. However, for what it does it closely resembles std::string (Chapter 36) and illustrates techniques used for the implementation of the standard-library string.

19.4. Friends

An ordinary member function declaration specifies three logically distinct things:

[1] The function can access the private part of the class declaration.

[2] The function is in the scope of the class.

[3] The function must be invoked on an object (has a this pointer).

By declaring a member function static (§16.2.12), we can give it the first two properties only. By declaring a nonmember function a friend, we can give it the first property only. That is, a function declared friend is granted access to the implementation of a class just like a member function but is otherwise independent of that class.

For example, we could define an operator that multiplies a Matrix by a Vector. Naturally, Vector and Matrix hide their respective representations and provide a complete set of operations for manipulating objects of their type. However, our multiplication routine cannot be a member of both. Also, we don’t really want to provide low-level access functions to allow every user to both read and write the complete representation of both Matrix and Vector. To avoid this, we declare the operator* a friend of both:

Click here to view code image

constexpr rc_max {4}; // row and column size

class Matrix;

class Vector {
     float v[rc_max];
     // ...
     friend Vector operator*(const Matrix&, const Vector&);
};

class Matrix {
     Vector v[rc_max];
     // ...
     friend Vector operator*(const Matrix&, const Vector&);
};

Now operator*() can reach into the implementation of both Vector and Matrix. That would allow sophisticated implementation techniques, but a simple implementation would be:

Click here to view code image

Vector operator*(const Matrix& m, const Vector& v)
{
     Vector r;
     for (int i = 0; i!=rc_max; i++) {           // r[i] = m[i] * v;
           r.v[i] = 0;
           for (int j = 0; j!=rc_max; j++)
                  r.v[i] += m.v[i].v[j] *v.v[j];
     }
     return r;
}

A friend declaration can be placed in either the private or the public part of a class declaration; it does not matter where. Like a member function, a friend function is explicitly declared in the declaration of the class of which it is a friend. It is therefore as much a part of that interface as is a member function.

A member function of one class can be the friend of another. For example:

class List_iterator {
     // ...
     int* next();
};

class List {
     friend int* List_iterator::next();
     // ...
};

There is a shorthand for making all functions of one class friends of another. For example:

class List {
     friend class List_iterator;
     // ...
};

This friend declaration makes all of List_iterator’s member functions friends of List.

Declaring a class a friend grants access to every function of that class. That implies that we cannot know the set of functions that can access the granting class’s representation just by looking at the class itself. In this, a friend class declaration differs from the declaration of a member function and a friend function. Clearly, friend classes should be used with caution and only to express closely connected concepts.

It is possible to make a template argument a friend:

template<typename T>
class X {
     friend T;
     friend class T;   // redundant "class"
     // ...
};

Often, there is a choice between making a class a member (a nested class) or a nonmember friend (§18.3.1).

19.4.1. Finding Friends

A friend must be previously declared in an enclosing scope or defined in the non-class scope immediately enclosing the class that is declaring it to be a friend. Scopes outside the innermost enclosing namespace scope are not considered for a name first declared as a friend (§iso.7.3.1.2). Consider a technical example:

Click here to view code image

class C1 { };     // will become friend of N::C
void f1();        // will become friend of N::C

namespace N {
     class C2 { };          // will become friend of C
     void f2() { }          // will become friend of C

     class C {
          int x;
     public:
           friend class C1;        // OK (previously defined)
           friend void f1();

           friend class C3;        // OK (defined in enclosing namespace)
           friend void f3();
           friend class C4;        // First declared in N and assumed to be in N
           friend void f4();
     };

     class C3 { };                 // friend of C
     void f3() { C x; x.x = 1; }   // OK: friend of C
} // namespace N

class C4 { };                      // not friend of N::C
void f4() { N::C x; x.x = 1; }     // error: x is private and f4() is not a friend of N::C

A friend function can be found through its arguments (§14.2.4) even if it was not declared in the immediately enclosing scope. For example:

Click here to view code image

void f(Matrix& m)
{
     invert(m);     // Matrix's friend invert()
}

Thus, a friend function should be explicitly declared in an enclosing scope or take an argument of its class or a class derived from that. If not, the friend cannot be called. For example:

Click here to view code image

// no f() in this scope

class X {
     friend void f();          // useless
     friend void h(const X&);  // can be found through its argument
};

void g(const X& x)
{
     f();     // no f() in scope
     h(x);    // X's friend h()
}

19.4.2. Friends and Members

When should we use a friend function, and when is a member function the better choice for specifying an operation? First, we try to minimize the number of functions that access the representation of a class and try to make the set of access functions as appropriate as possible. Therefore, the first question is not “Should it be a member, a static member, or a friend?” but rather “Does it really need access?” Typically, the set of functions that need access is smaller than we are willing to believe at first. Some operations must be members – for example, constructors, destructors, and virtual functions (§3.2.3, §17.2.5) – but typically there is a choice. Because member names are local to the class, a function that requires direct access to the representation should be a member unless there is a specific reason for it to be a nonmember.

Consider a class X supplying alternative ways of presenting an operation:

Click here to view code image

class X {
     // ...
     X(int);

     int m1();               // member
     int m2() const;

     friend int f1(X&);      // friend, not member
     friend int f2(const X&);
     friend int f3(X);
};

Member functions can be invoked for objects of their class only; no user-defined conversions are applied to the leftmost operand of a . or –> (but see §19.2.3). For example:

Click here to view code image

void g()
{
     99.m1();    // error: X(99).m1() not tried
     99.m2();    // error: X(99).m2() not tried
}

The global function f1() has a similar property because implicit conversions are not used for non-const reference arguments (§7.7). However, conversions may be applied to the arguments of f2() and f3():

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void h()
{
     f1(99);    // error: f1(X(99)) not tried: non-const X& argument
     f2(99);    // OK: f2(X(99)); const X& argument
     f3(99);    // OK: f3(X(99)); X argument
}

An operation modifying the state of a class object should therefore be a member or a function taking a non-const reference argument (or a non-const pointer argument).

Operators that modify an operand (e.g., =, *=, and ++) are most naturally defined as members for user-defined types. Conversely, if implicit type conversion is desired for all operands of an operation, the function implementing it must be a nonmember function taking a const reference argument or a non-reference argument. This is often the case for the functions implementing operators that do not require lvalue operands when applied to fundamental types (e.g., +, –, and ||). However, such operators often need access to the representations of their operand class. Consequently, binary operators are the most common source of friend functions.

Unless type conversions are defined, there appears to be no compelling reason to choose a member over a friend taking a reference argument, or vice versa. In some cases, the programmer may have a preference for one call syntax over another. For example, most people seem to prefer the notation m2=inv(m) for producing a inverted Matrix from m to the alternative m2=m.inv(). On the other hand, if inv() inverts m itself, rather than producing a new Matrix that is the inverse of m, it should be a member.

All other things considered equal, implement operations that need direct access to a representation as member functions:

• It is not possible to know if someone someday will define a conversion operator.

• The member function call syntax makes it clear to the user that the object may be modified; a reference argument is far less obvious.

• Expressions in the body of a member can be noticeably shorter than the equivalent expressions in a global function; a nonmember function must use an explicit argument, whereas the member can use this implicitly.

• Member names are local to a class, so they tend to be shorter than the names of nonmember functions.

• If we have defined a member f() and we later feel the need for a nonmember f(x), we can simply define it to mean x.f().

Conversely, operations that do not need direct access to a representation are often best represented as nonmember functions, possibly in a namespace that makes their relationship with the class explicit (§18.3.6).

19.5. Advice

[1] Use operator[]() for subscripting and for selection based on a single value; §19.2.1.

[2] Use operator()() for call semantics, for subscripting, and for selection based on multiple values; §19.2.2.

[3] Use operator–>() to dereference “smart pointers”; §19.2.3.

[4] Prefer prefix ++ over suffix ++; §19.2.4.

[5] Define the global operator new() and operator delete() only if you really have to; §19.2.5.

[6] Define member operator new() and member operator delete() to control allocation and deallocation of objects of a specific class or hierarchy of classes; §19.2.5.

[7] Use user-defined literals to mimic conventional notation; §19.2.6.

[8] Place literal operators in separate namespaces to allow selective use; §19.2.6.

[9] For nonspecialized uses, prefer the standard string (Chapter 36) to the result of your own exercises; §19.3.

[10] Use a friend function if you need a nonmember function to have access to the representation of a class (e.g., to improve notation or to access the representation of two classes); §19.4.

[11] Prefer member functions to friend functions for granting access to the implementation of a class; §19.4.2.

20. Derived Classes

Do not multiply objects without necessity.

– William Occam

• Introduction

• Derived Classes

Member Functions; Constructors and Destructors

• Class Hierarchies

Type Fields; Virtual Functions; Explicit Qualification; Override Control; using Base Members; Return Type Relaxation

• Abstract Classes

• Access Control

protected Members; Access to Base Classes; using-Declarations and Access Control

• Pointers to Members

Pointers to Function Members; Pointers to Data Members; Base and Derived Members

• Advice

20.1. Introduction

From Simula, C++ borrowed the ideas of classes and class hierarchies. In addition, it borrowed the design idea that classes should be used to model concepts in the programmer’s and the application’s world. C++ provides language constructs that directly support these design notions. Conversely, using the language features in support of design ideas distinguishes effective use of C++. Using language constructs as just notational props for traditional types of programming is to miss key strengths of C++.

A concept (idea, notion, etc.) does not exist in isolation. It coexists with related concepts and derives much of its power from relationships with other concepts. For example, try to explain what a car is. Soon you’ll have introduced the notions of wheels, engines, drivers, pedestrians, trucks, ambulances, roads, oil, speeding tickets, motels, etc. Since we use classes to represent concepts, the issue becomes how to represent relationships among concepts. However, we can’t express arbitrary relationships directly in a programming language. Even if we could, we wouldn’t want to. To be useful, our classes should be more narrowly defined than our everyday concepts – and more precise.

The notion of a derived class and its associated language mechanisms are provided to express hierarchical relationships, that is, to express commonality between classes. For example, the concepts of a circle and a triangle are related in that they are both shapes; that is, they have the concept of a shape in common. Thus, we explicitly define class Circle and class Triangle to have class Shape in common. In that case, the common class, here Shape, is referred to as the base class or superclass and classes derived from that, here Circle and Triangle, are referred to as derived classes or subclasses. Representing a circle and a triangle in a program without involving the notion of a shape would be to miss something essential. This chapter is an exploration of the implications of this simple idea, which is the basis for what is commonly called object-oriented programming. The language features support building new classes from existing ones:

• Implementation inheritance: to save implementation effort by sharing facilities provided by a base class

• Interface inheritance: to allow different derived classes to be used interchangeably through the interface provided by a common base class Interface inheritance is often referred to as run-time polymorphism (or dynamic polymorphism).

In contrast, the uniform use of classes not related by inheritance provided by templates (§3.4, Chapter 23) is often referred to as compile-time polymorphism (or static polymorphism).

The discussion of class hierarchies is organized into three chapters:

• Derived Classes (Chapter 20): This chapter introduces the basic language features supporting object-oriented programming. Base and derived classes, virtual functions, and access control are covered.

• Class Hierarchies (Chapter 21): This chapter focuses on the use of base and derived classes to effectively organize code around the notion of class hierarchies. Most of this chapter is devoted to discussion of programming techniques, but technical aspects of multiple inheritance (classes with more than one base class) are also covered.

• Run-time Type Identification (Chapter 22): This chapter describes the techniques for explicitly navigating class hierarchies. In particular, the type conversion operations dynamic_cast and static_cast are presented, as is the operation for determining the type of an object given one of its base classes (typeid).

A brief introduction to the basic idea of hierarchical organization of types can be found in Chapter 3: base and derived classes (§3.2.2) and virtual functions (§3.2.3). These chapters examine these fundamental features and their associated programming and design techniques in greater detail.

20.2. Derived Classes

Consider building a program dealing with people employed by a firm. Such a program might have a data structure like this:

struct Employee {
     string first_name, family_name;
     char middle_initial;
     Date hiring_date;
     short department;
     // ...
};

Next, we might try to define a manager:

Click here to view code image

struct Manager {
     Employee emp;               // manager's employee record
     list<Employee*> group; // people managed
     short level;
     // ...
};

A manager is also an employee; the Employee data is stored in the emp member of a Manager object. This may be obvious to a human reader – especially a careful reader – but there is nothing that tells the compiler and other tools that Manager is also an Employee. A Manager* is not an Employee*, so one cannot simply use one where the other is required. In particular, one cannot put a Manager onto a list of Employees without writing special code. We could either use explicit type conversion on a Manager* or put the address of the emp member onto a list of employees. However, both solutions are inelegant and can be quite obscure. The correct approach is to explicitly state that a Manager is an Employee, with a few pieces of information added:

Click here to view code image

struct Manager : public Employee {
     list<Employee*> group;
     short level;
     // ...
};

The Manager is derived from Employee, and conversely, Employee is a base class for Manager. The class Manager has the members of class Employee (first_name, department, etc.) in addition to its own members (group, level, etc.).

Derivation is often represented graphically by a pointer from the derived class to its base class indicating that the derived class refers to its base (rather than the other way around):

A derived class is often said to inherit properties from its base, so the relationship is also called inheritance. A base class is sometimes called a superclass and a derived class a subclass. This terminology, however, is confusing to people who observe that the data in a derived class object is a superset of the data of an object of its base class. A derived class is typically larger (and never smaller) than its base class in the sense that it holds more data and provides more functions.

A popular and efficient implementation of the notion of derived classes has an object of the derived class represented as an object of the base class, with the information belonging specifically to the derived class added at the end. For example:

No memory overhead is implied by deriving a class. The space required is just the space required by the members.

Deriving Manager from Employee in this way makes Manager a subtype of Employee, so that a Manager can be used wherever an Employee is acceptable. For example, we can now create a list of Employees, some of whom are Managers:

Click here to view code image

void f(Manager m1, Employee e1)
{
     list<Employee*> elist {&m1,&e1);
     // ...
}

A Manager is (also) an Employee, so a Manager* can be used as an Employee*. Similarly, a Manager& can be used as an Employee&. However, an Employee is not necessarily a Manager, so an Employee* cannot be used as a Manager*. In general, if a class Derived has a public base class (§20.5) Base, then a Derived* can be assigned to a variable of type Base* without the use of explicit type conversion. The opposite conversion, from Base* to Derived*, must be explicit. For example:

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void g(Manager mm, Employee ee)
{
     Employee* pe = &mm;               // OK: every Manager is an Employee
     Manager* pm = &ee;                // error: not every Employee is a Manager

     pm–>level = 2;                    // disaster: ee doesn't have a level

     pm = static_cast<Manager*>(pe);   // brute force: works because pe points
                                       // to the Manager mm

     pm–>level = 2;                    // fine: pm points to the Manager mm that has a level
}

In other words, an object of a derived class can be treated as an object of its base class when manipulated through pointers and references. The opposite is not true. The use of static_cast and dynamic_cast is discussed in §22.2.

Using a class as a base is equivalent to defining an (unnamed) object of that class. Consequently, a class must be defined in order to be used as a base (§8.2.2):

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class Employee;     // declaration only, no definition

class Manager : public Employee { // error: Employee not defined
     // ...
};

20.2.1. Member Functions

Simple data structures, such as Employee and Manager, are really not that interesting and often not particularly useful. We need to provide a proper type with a suitable set of operations, and we need to do so without being tied to the details of a particular representation. For example:

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class Employee {
public:
     void print() const;
     string full_name() const { return first_name + ' ' + middle_initial + ' ' + family_name; }
     // ...
private:
     string first_name, family_name;
     char middle_initial;
     // ...
};

class Manager : public Employee {
public:
     void print() const;
     // ...
};

A member of a derived class can use the public – and protected (see §20.5) – members of a base class as if they were declared in the derived class itself. For example:

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void Manager::print() const
{
     cout << "name is " << full_name() << '\n';
     // ...
}

However, a derived class cannot access private members of a base class:

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void Manager::print() const
{
     cout << " name is " << family_name << '\n';   // error!
     // ...
}

This second version of Manager::print() will not compile because family_name is not accessible to Manager::print().

This comes as a surprise to some, but consider the alternative: that a member function of a derived class could access the private members of its base class. The concept of a private member would be rendered meaningless by allowing a programmer to gain access to the private part of a class simply by deriving a new class from it. Furthermore, one could no longer find all uses of a private name by looking at the functions declared as members and friends of that class. One would have to examine every source file of the complete program for derived classes, then examine every function of those classes, then find every class derived from those classes, etc. This is, at best, tedious and often impractical. Where it is acceptable, protected – rather than private – members can be used (§20.5).

Typically, the cleanest solution is for the derived class to use only the public members of its base class. For example:

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void Manager::print() const
{
     Employee::print();     // print Employee information
     cout << level;         // print Manager-specific information
     // ...
}

Note that :: must be used because print() has been redefined in Manager. Such reuse of names is typical. The unwary might write this:

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void Manager::print() const
{
     print();   // oops!
     // print Manager-specific information
}

The result is a sequence of recursive calls ending with some form of program crash.

20.2.2. Constructors and Destructors

As usual, constructors and destructors are as essential:

• Objects are constructed from the bottom up (base before member and member before derived) and destroyed top-down (derived before member and member before base); §17.2.3.

• Each class can initialize its members and bases (but not directly members or bases of its bases); §17.4.1.

• Typically, destructors in a hierarchy need to be virtual; §17.2.5.

• Copy constructors of classes in a hierarchy should be used with care (if at all) to avoid slicing; §17.5.1.4.

• The resolution of a virtual function call, a dynamic_cast, or a typeid() in a constructor or destructor reflects the stage of construction and destruction (rather than the type of the yet-to-be-completed object); §22.4.

In computer science “up” and “down” can get very confused. In source text, definitions of base classes must occur before the definitions of their derived classes. This implies that for small examples, the bases appear above the derived classes on a screen. Furthermore, we tend to draw trees with the root on top. However, when I talk about constructing objects from the bottom up, I mean starting with the most fundamental (e.g., base classes) and building what depends on that (e.g., derived classes) later. We build from the roots (base classes) toward the leaves (derived classes).

20.3. Class Hierarchies

A derived class can itself be a base class. For example:

Click here to view code image

class Employee { /* ... */ };
class Manager : public Employee { /* ... */ };
class Director : public Manager { /* ... */ };

Such a set of related classes is traditionally called a class hierarchy. Such a hierarchy is most often a tree, but it can also be a more general graph structure. For example:

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class Temporary { /* ... */ };
class Assistant : public Employee { /* ... */ };
class Temp : public Temporary, public Assistant { /* ... */ };
class Consultant : public Temporary, public Manager { /* ... */ };

or graphically:

Thus, as is explained in detail in §21.3, C++ can express a directed acyclic graph of classes.

20.3.1. Type Fields

To use derived classes as more than a convenient shorthand in declarations, we must solve the following problem: Given a pointer of type Base*, to which derived type does the object pointed to really belong? There are four fundamental solutions:

[1] Ensure that only objects of a single type are pointed to (§3.4, Chapter 23).

[2] Place a type field in the base class for the functions to inspect.

[3] Use dynamic_cast (§22.2, §22.6).

[4] Use virtual functions (§3.2.3, §20.3.2).

Unless you have used final (§20.3.4.2), solution 1 relies on more knowledge about the types involved than is available to the compiler. In general, it is not a good idea to try to be smarter than the type system, but (especially in combination with the use of templates) it can be used to implement homogeneous containers (e.g., the standard-library vector and map) with unsurpassed performance. Solutions [2], [3], and [4] can be used to build heterogeneous lists, that is, lists of (pointers to) objects of several different types. Solution [3] is a language-supported variant of solution [2]. Solution [4] is a special type-safe variation of solution [2]. Combinations of solutions [1] and [4] are particularly interesting and powerful; in almost all situations, they yield cleaner code than do solutions [2] and [3].

Let us first examine the simple type-field solution to see why it is typically best avoided. The manager/employee example could be redefined like this:

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struct Employee {
     enum Empl_type { man, empl };
     Empl_type type;

     Employee() : type{empl} { }

     string first_name, family_name;
     char middle_initial;

     Date hiring_date;
     short department;
     // ...
};

struct Manager : public Employee {
     Manager() { type = man; }

     list<Employee*> group; // people managed
     short level;
     // ...
};

Given this, we can now write a function that prints information about each Employee:

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void print_employee(const Employee* e)
{
     switch (e–>type) {
     case Employee::empl:
          cout << e–>family_name << '\t' << e–>department << '\n';
          // ...
          break;
     case Employee::man:
     {    cout << e–>family_name << '\t' << e–>department << '\n';
          // ...
          const Manager* p = static_cast<const Manager*>(e);
          cout << " level " << p–>level << '\n';
          // ...
          break;
     }
     }
}

and use it to print a list of Employees, like this:

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void print_list(const list<Employee*>& elist)
{
     for (auto x : elist)
           print_employee(x);
}

This works fine, especially in a small program maintained by a single person. However, it has a fundamental weakness in that it depends on the programmer manipulating types in a way that cannot be checked by the compiler. This problem is usually made worse because functions such as print_employee() are often organized to take advantage of the commonality of the classes involved:

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void print_employee(const Employee* e)
{
     cout << e–>family_name << '\t' << e–>department << '\n';
     // ...
     if (e–>type == Employee::man) {
           const Manager* p = static_cast<const Manager*>(e);
           cout << " level " << p–>level << '\n';
           // ...
     }
}

Finding all such tests on the type field buried in a large function that handles many derived classes can be difficult. Even when they have been found, understanding what is going on can be difficult. Furthermore, any addition of a new kind of Employee involves a change to all the key functions in a system – the ones containing the tests on the type field. The programmer must consider every function that could conceivably need a test on the type field after a change. This implies the need to access critical source code and the resulting necessary overhead of testing the affected code. The use of an explicit type conversion is a strong hint that improvement is possible.

In other words, use of a type field is an error-prone technique that leads to maintenance problems. The problems increase in severity as the size of the program increases because the use of a type field causes a violation of the ideals of modularity and data hiding. Each function using a type field must know about the representation and other details of the implementation of every class derived from the one containing the type field.

It also seems that any common data accessible from every derived class, such as a type field, tempts people to add more such data. The common base thus becomes the repository of all kinds of “useful information.” This, in turn, gets the implementation of the base and derived classes intertwined in ways that are most undesirable. In a large class hierarchy, accessible (not private) data in a common base class becomes the “global variables” of the hierarchy. For clean design and simpler maintenance, we want to keep separate issues separate and avoid mutual dependencies.

20.3.2. Virtual Functions

Virtual functions overcome the problems with the type-field solution by allowing the programmer to declare functions in a base class that can be redefined in each derived class. The compiler and linker will guarantee the correct correspondence between objects and the functions applied to them. For example:

Click here to view code image

class Employee {
public:
     Employee(const string& name, int dept);
     virtual void print() const;
     // ...
private:
     string first_name, family_name;
     short department;
     // ...
};

The keyword virtual indicates that print() can act as an interface to the print() function defined in this class and print() functions defined in classes derived from it. Where such print() functions are defined in derived classes, the compiler ensures that the right print() for the given Employee object is invoked in each case.

To allow a virtual function declaration to act as an interface to functions defined in derived classes, the argument types specified for a function in a derived class cannot differ from the argument types declared in the base, and only very slight changes are allowed for the return type (§20.3.6). A virtual member function is sometimes called a method.

A virtual function must be defined for the class in which it is first declared (unless it is declared to be a pure virtual function; see §20.4). For example:

Click here to view code image

void Employee::print() const
{
     cout << family_name << '\t' << department << '\n';
     // ...
}

A virtual function can be used even if no class is derived from its class, and a derived class that does not need its own version of a virtual function need not provide one. When deriving a class, simply provide an appropriate function if it is needed. For example:

Click here to view code image

class Manager : public Employee {
public:
     Manager(const string& name, int dept, int lvl);
     void print() const;
     // ...
private:
     list<Employee*> group;
     short level;
     // ...
};

void Manager::print() const
{
     Employee::print();
     cout << "\tlevel " << level << '\n';
     // ...
}

A function from a derived class with the same name and the same set of argument types as a virtual function in a base is said to override the base class version of the virtual function. Furthermore, it is possible to override a virtual function from a base with a more derived return type (§20.3.6).

Except where we explicitly say which version of a virtual function is called (as in the call Employee::print()), the overriding function is chosen as the most appropriate for the object for which it is called. Independently of which base class (interface) is used to access an object, we always get the same function when we use the virtual function call mechanism.

The global function print_employee() (§20.3.1) is now unnecessary because the print() member functions have taken its place. A list of Employees can be printed like this:

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void print_list(const list<Employee*>& s)
{
     for (auto x : s)
           x–>print();
}

Each Employee will be written out according to its type. For example:

int main()
{
     Employee e {"Brown",1234};
     Manager m {"Smith",1234,2};

     print_list({&e,&m});
}

produced:

Smith 1234
    level 2
Brown 1234

Note that this will work even if print_list() was written and compiled before the specific derived class Manager was even conceived of! This is a key aspect of classes. When used properly, it becomes the cornerstone of object-oriented designs and provides a degree of stability to an evolving program.

Getting “the right” behavior from Employee’s functions independently of exactly what kind of Employee is actually used is called polymorphism. A type with virtual functions is called a polymorphic type or (more precisely) a run-time polymorphic type. To get runtime polymorphic behavior in C++, the member functions called must be virtual and objects must be manipulated through pointers or references. When manipulating an object directly (rather than through a pointer or reference), its exact type is known by the compiler so that run-time polymorphism is not needed.

By default, a function that overrides a virtual function itself becomes virtual. We can, but do not have to, repeat virtual in a derived class. I don’t recommend repeating virtual. If you want to be explicit, use override (§20.3.4.1).

Clearly, to implement polymorphism, the compiler must store some kind of type information in each object of class Employee and use it to call the right version of the virtual function print(). In a typical implementation, the space taken is just enough to hold a pointer (§3.2.3): the usual implementation technique is for the compiler to convert the name of a virtual function into an index into a table of pointers to functions. That table is usually called the virtual function table or simply the vtbl. Each class with virtual functions has its own vtbl identifying its virtual functions. This can be represented graphically like this:

The functions in the vtbl allow the object to be used correctly even when the size of the object and the layout of its data are unknown to the caller. The implementation of a caller need only know the location of the vtbl in an Employee and the index used for each virtual function. This virtual call mechanism can be made almost as efficient as the “normal function call” mechanism (within 25%), so efficiency concerns should not deter anyone from using a virtual function where an ordinary function call would be acceptably efficient. Its space overhead is one pointer in each object of a class with virtual functions plus one vtbl for each such class. You pay this overhead only for objects of a class with a virtual function. You choose to pay this overhead only if you need the added functionality virtual functions provide. Had you chosen to use the alternative type-field solution, a comparable amount of space would have been needed for the type field.

A virtual function invoked from a constructor or a destructor reflects that the object is partially constructed or partially destroyed (§22.4). It is therefore typically a bad idea to call a virtual function from a constructor or a destructor.

20.3.3. Explicit Qualification

Calling a function using the scope resolution operator, ::, as is done in Manager::print() ensures that the virtual mechanism is not used:

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void Manager::print() const
{
     Employee::print();   // not a virtual call
     cout << "\tlevel " << level << '\n';
     // ...
}

Otherwise, Manager::print() would suffer an infinite recursion. The use of a qualified name has another desirable effect. That is, if a virtual function is also inline (as is not uncommon), then inline substitution can be used for calls specified using ::. This provides the programmer with an efficient way to handle some important special cases in which one virtual function calls another for the same object. The Manager::print() function is an example of this. Because the type of the object is determined in the call of Manager::print(), it need not be dynamically determined again for the resulting call of Employee::print().

20.3.4. Override Control

If you declare a function in a derived class that has exactly the same name and type as a virtual function in a base class, then the function in the derived class overrides the one in the base class. That’s a simple and effective rule. However, for larger class hierarchies it can be difficult to be sure that you actually override the function you meant to override. Consider:

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struct B0 {
     void f(int) const;
     virtual void g(double);
};

struct B1 : B0 { /* ... */ };
struct B2 : B1 { /* ... */ };
struct B3 : B2 { /* ... */ };
struct B4 : B3 { /* ... */ };
struct B5 : B4 { /* ... */ };

struct D : B5 {
     void f(int) const;        // override f() in base class
     void g(int);              // override g() in base class
     virtual int h();          // override h() in base class
};

This illustrates three errors that are far from obvious when they appear in a real class hierarchy where the classes B0...B5 have many members each and are scattered over many header files. Here:

• B0::f() is not virtual, so you can’t override it, only hide it (§20.3.5).

• D::g() doesn’t have the same argument type as B0::g(), so if it overrides anything it’s not the virtual function B0::g(). Most likely, D::g() just hides B0::g().

• There is no function called h() in B0, if D::h() overrides anything, it is not a function from B0. Most likely, it is introducing a brand-new virtual function.

I didn’t show you what was in B1...B5, so maybe something completely different is going on because of declarations in those classes. I personally don’t (redundantly) use virtual for a function that’s meant to override. For smaller programs (especially with a compiler with decent warnings against common mistakes) getting overriding done correctly isn’t hard. However, for larger hierarchies more specific controls are useful:

• virtual: The function may be overridden (§20.3.2).

• =0: The function must be virtual and must be overridden (§20.4).

• override: The function is meant to override a virtual function in a base class (§20.3.4.1).

• final: The function is not meant to be overridden (§20.3.4.2).

In the absence of any of these controls, a non-static member function is virtual if and only if it overrides a virtual function in a base class (§20.3.2).

A compiler can warn against inconsistent use of explicit override controls. For example, a class declaration that uses override for seven out of nine virtual base class functions could be confusing to maintainers.

20.3.4.1. override

We can be explicit about our desire to override:

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struct D : B5 {
     void f(int) const override;      // error: B0::f() is not virtual
     void g(int) override;            // error: B0::f() takes a double argument
     virtual int h() override;        // error: no function h() to override
};

Given this definition (and assuming that the intermediate base classes B1...B5 do not provide relevant functions), all three declarations give errors.

In a large or complicated class hierarchy with many virtual functions, it is best to use virtual only to introduce a new virtual function and to use override on all functions intended as overriders. Using override is a bit verbose but clarifies the programmer’s intent.

The override specifier comes last in a declaration, after all other parts. For example:

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void f(int) const noexcept override;// OK (if there is a suitable f() to override)
override void f(int) const noexcept;// syntax error
void f(int) override const noexcept;// syntax error

And yes, it’s illogical that virtual is a prefix and override is a suffix. This is part of the price we pay for compatibility and stability over decades.

An override specifier is not part of the type of a function and cannot be repeated in an out-of-class definition. For example:

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class Derived : public Base {
     void f() override;       // OK if Base has a virtual f()
     void g() override;       // OK if Base has a virtual g()
};

void Derived::f() override    // error: override out of class
{
     // ...
}

void g()                      // OK
{
      // ...
}

Curiously, override is not a keyword; it is what is called a contextual keyword. That is, override has a special meaning in a few contexts but can be used as an identifier elsewhere. For example:

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int override = 7;

struct Dx : Base {
     int override;

     int f() override
     {
           return override + ::override;
     }
};

Don’t indulge in such cleverness; it complicates maintenance. The only reason that override is a contextual keyword, rather than an ordinary keyword, is that there exists a significant amount of code that has used override as an ordinary identifier for decades. The other contextual keyword is final (§20.3.4.2).

20.3.4.2. final

When we declare a member function, we have a choice between virtual and not virtual (the default). We use virtual for functions we want writers of derived classes to be able to define or redefine. We base our choice on the meaning (semantics) of our class:

• Can we imagine the need for further derived classes?

• Does a designer of a derived class need to redefine the function to achieve a plausible aim?

• Is overriding a function error-prone (i.e., is it hard for an overriding function to provide the expected semantics of a virtual function)?

If the answer is “no” to all three questions, we can leave the function non-virtual to gain simplicity of design and occasionally some performance (mostly from inlining). The standard library is full of examples of this.

Far more rarely, we have a class hierarchy that starts out with virtual functions, but after the definition of a set of derived classes, one of the answers becomes “no.” For example, we can imagine an abstract syntax tree for a language where all language constructs have been defined as concrete node classes derived from a few interfaces. We only need to derive a new class if we change the language. In that case, we might want to prevent our users from overriding virtual functions because the only thing such overrides could do would be to change the semantics of our language. That is, we might want to close our design to modification from its users. For example:

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struct Node {  // interface class
     virtual Type type() = 0;
     // ...
};

class If_statement : public Node {
public:
     Type type() override final;    // prevent further overriding
     // ...
};

In a realistic class hierarchy, there would be several intermediate classes between the general interface (here, Node) and the derived class representing a specific language construct (here, If_statement). However, the key point about this example is that Node::type() is meant to be overridden (that’s why it’s declared virtual) and its overrider If_statement::type() is not (that’s why it’s declared final). After using final for a member function, it can no longer be overridden and an attempt to do so is an error. For example:

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class Modified_if_statement : public If_statement {
public:
     Type type() override;    // error: If_statement::type() is final
     // ...
};

We can make every virtual member function of a class final; just add final after the class name. For example:

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class For_statement final : public Node {
public:
     Type type() override;
     // ...
};

class Modified_for_statement : public For_statement {   // error: For_statement is final
      Type type() override;
      // ...
};

For good and bad, adding final to the class not only prevents overriding, it also prevents further derivation from a class. There are people who use final to try to gain performance – after all, a non-virtual function is faster than a virtual one (by maybe 25% on a modern implementation) and offers greater opportunities for inlining (§12.1.5). However, do not blindly use final as an optimization aid; it affects the class hierarchy design (often negatively), and the performance improvements are rarely significant. Do some serious measurements before claiming efficiency improvements. Use final where it clearly reflects a class hierarchy design that you consider proper. That is, use final to reflect a semantic need.

A final specifier is not part of the type of a function and cannot be repeated in an out-of-class definition. For example:

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class Derived : public Base {
     void f() final;     // OK if Base has a virtual f()
     void g() final;     // OK if Base has a virtual g()
     // ...
};

void Derived::f() final  // error: final out of class
{
     // ...
}
void g() final           // OK
{
     // ...
}

Like override (§20.3.4.1), final is a contextual keyword. That is, final has a special meaning in a few contexts but can be used as an ordinary identifier elsewhere. For example:

Click here to view code image

int final = 7;

struct Dx : Base {
     int final;

     int f() final
     {
           return final + ::final;
     }
};

Don’t indulge in such cleverness; it complicates maintenance. The only reason that final is a contextual keyword, rather than an ordinary keyword, is that there exist a significant amount of code that has used final as an ordinary identifier for decades. The other contextual keyword is override (§20.3.4.1).

20.3.5. using Base Members

Functions do not overload across scopes (§12.3.3). For example:

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struct Base {
     void f(int);
};

struct Derived : Base {
     void f(double);
};

void use(Derived d)
{
     d.f(1);         // call Derived::f(double)
     Base& br = d
     br.f(1);        // call Base::f(int)
}

This can surprise people, and sometimes we want overloading to ensure that the best matching member function is used. As for namespaces, using-declarations can be used to add a function to a scope. For example:

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struct D2 : Base {
     using Base::f;    // bring all fs from Base into D2
     void f(double);
};
void use2(D2 d)
{
     d.f(1);           // call D2::f(int), that is, Base::f(int)
     Base& br = d
     br.f(1);          // call Base::f(int)
}

This is a simple consequence of a class also being considered a namespace (§16.2).

Several using-declarations can bring in names from multiple base classes. For example:

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struct B1 {
     void f(int);
};

struct B2 {
     void f(double);
};

struct D : B1, B2 {
     using B1::f;
     using B2::f;
     void f(char);
};

void use(D d)
{
     d.f(1);      // call D::f(int), that is, B1::f(int)
     d.f('a');    // call D::f(char)
     d.f(1.0);    // call D::f(double), that is, B2::f(double)
}

We can bring constructors into a derived class scope; see §20.3.5.1. A name brought into a derived class scope by a using-declaration has its access determined by the placement of the using-declaration; see §20.5.3. We cannot use using-directives to bring all members of a base class into a derived class.

20.3.5.1. Inheriting Constructors

Say I want a vector that’s just like std::vector, but with guaranteed range checking. I can try this:

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template<class T>
struct Vector : std::vector<T> {
     T& operator[](size_type i) { check(i); return this–>elem(i); }
     const T& operator[](size_type i) const { check(i); return this–>elem(i); }

     void check(size_type i) { if (this–>size()<i) throw range_error{"Vector::check() failed"}; }
};

Unfortunately, we would soon find out that this definition is rather incomplete. For example:

Vector<int> v { 1, 2, 3, 5, 8 };   // error: no initializer-list constructor

A quick check will show that Vector failed to inherit any constructors from std::vector.

That’s not an unreasonable rule: if a class adds data members to a base or requires a stricter class invariant, it would be a disaster to inherit constructors. However, Vector did not do anything like that.

We solve the problem by simply saying that the constructors should be inherited:

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template<class T>
struct Vector : std::vector<T> {
     using vector<T>::vector;       // inherit constructors

     T& operator=[](size_type i) { check(i); return this–>elem(i); }
     const T& operator=(size_type i) const { check(i); return this–>elem(i); }

     void check(size_type i) { if (this–>size()<i) throw Bad_index(i); }
};

Vector<int> v { 1, 2, 3, 5, 8 };    // OK: use initializer-list constructor from std::vector

This use of using is exactly equivalent to its use for ordinary functions (§14.4.5, §20.3.5).

If you so choose, you can shoot yourself in the foot by inheriting constructors in a derived class in which you define new member variables needing explicit initialization:

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struct B1 {
     B1(int) { }
};

struct D1 : B1 {
     using B1::B1; // implicitly declares D1(int)
     string s;     // string has a default constructor
     int x;        // we "forgot" to provide for initialization of x
};

void test() {
     D1 d {6};     // oops: d.x is not initialized
     D1 e;         // error: D1 has no default constructor
}

The reason that D1::s is initialized and D1::x is not is that the inheriting constructor is equivalent to a constructor that simply initializes the base. In this case, we might equivalently have written:

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struct D1 : B1 {
     D1(int i) : B1(i) { }
     string s;         // string has a default constructor
     int x;            // we "forgot" to provide for initialization of x
};

One way to remove the bullet from your foot is by adding an in-class member initializer (§17.4.4):

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struct D1 : B1 {
     using B1::B1;  // implicitly declares D1(int)
     int x {0};     // note: x is initialized
};

void test()
{
     D1 d {6}; // d.x is zero
}

Most often it is best to avoid being clever and restrict the use of inheriting constructors to the simple cases where no data members are added.

20.3.6. Return Type Relaxation

There is a relaxation of the rule that the type of an overriding function must be the same as the type of the virtual function it overrides. That is, if the original return type was B*, then the return type of the overriding function may be D*, provided B is a public base of D. Similarly, a return type of B& may be relaxed to D&. This is sometimes called the covariant return rule.

This relaxation applies only to return types that are pointers or references, and not to “smart pointers” such as unique_ptr (§5.2.1). In particular, there is not a similar relaxation of the rules for argument types because that would lead to type violations.

Consider a class hierarchy representing different kinds of expressions. In addition to the operations for manipulating expressions, the base class Expr would provide facilities for making new expression objects of the various expression types:

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class Expr {
public:
     Expr();                  // default constructor
     Expr(const Expr&);       // copy constructor
     virtual Expr* new_expr() =0;
     virtual Expr* clone() =0;
     // ...
};

The idea is that new_expr() makes a default object of the type of the expression and clone() makes a copy of the object. Both will return an object of some specific class derived from Expr. They can never just return a “plain Expr” because Expr was deliberately and appropriately declared to be an abstract class.

A derived class can override new_expr() and/or clone() to return an object of its own type:

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class Cond : public Expr {
public:
     Cond();
     Cond(const Cond&);
     Cond* new_expr() override { return new Cond(); }
     Cond* clone() override { return new Cond(*this); }
     // ...
};

This means that given an object of class Expr, a user can create a new object of “just the same type.” For example:

void user(Expr* p)
{
     Expr* p2 = p–>new_expr();
     // ...
}

The pointer assigned to p2 is declared to point to a “plain Expr,” but it will point to an object of a type derived from Expr, such as Cond.

The return type of Cond::new_expr() and Cond::clone() is Cond* rather than Expr*. This allows a Cond to be cloned without loss of type information. Similarly, a derived class Addition would have a clone() returning a Addition*. For example:

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void user2(Cond* pc, Addition* pa)
{
     Cond* p1 = pc–>clone();
     Addition* p2 = pa–>clone();
     // ...
}

If we use clone() for an Expr we only know that the result is an Expr*:

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void user3(Cond* pc, Expr* pe)
{
     Cond* p1 = pc–>clone();
     Cond* p2 = pe–>clone();    // error: Expr::clone() returns an Expr*
     // ...
}

Because functions such as new_expr() and clone() are virtual and they (indirectly) construct objects, they are often called virtual constructors. Each simply uses a constructor to create a suitable object.

To make an object, a constructor needs the exact type of the object it is to create. Consequently, a constructor cannot be virtual. Furthermore, a constructor is not quite an ordinary function. In particular, it interacts with memory management routines in ways ordinary member functions don’t. So, you cannot take a pointer to a constructor and pass that to an object creation function.

Both of these restrictions can be circumvented by defining a function that calls a constructor and returns a constructed object. This is fortunate because creating a new object without knowing its exact type is often useful. The Ival_box_maker (§21.2.4) is an example of a class designed specifically to do that.

20.4. Abstract Classes

Many classes resemble class Employee in that they are useful as themselves, as interfaces for derived classes, and as part of the implementation of derived classes. For such classes, the techniques described in §20.3.2 suffice. However, not all classes follow that pattern. Some classes, such as a class Shape, represent abstract concepts for which objects cannot exist. A Shape makes sense only as the base of some class derived from it. This can be seen from the fact that it is not possible to provide sensible definitions for its virtual functions:

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class Shape {
public:
     virtual void rotate(int) { throw runtime_error{"Shape::rotate"}; }   // inelegant
     virtual void draw() const { throw runtime_error{"Shape::draw"}; }
     // ...
};

Trying to make a shape of this unspecified kind is silly but legal:

Shape s; // silly: "shapeless shape"

It is silly because every operation on s will result in an error.

A better alternative is to declare the virtual functions of class Shape to be pure virtual functions. A virtual function is “made pure” by the “pseudo initializer” = 0:

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class Shape {         // abstract class
public:
     virtual void rotate(int) = 0;          // pure virtual function
     virtual void draw() const = 0;         // pure virtual function
     virtual bool is_closed() const = 0;    // pure virtual function
     // ...
     virtual ~Shape();                      // virtual
};

A class with one or more pure virtual functions is an abstract class, and no objects of that abstract class can be created:

Shape s; // error: variable of abstract class Shape

An abstract class is intended as an interface to objects accessed through pointers and references (to preserve polymorphic behavior). Consequently, it is usually important for an abstract class to have a virtual destructor (§3.2.4, §21.2.2). Because the interface provided by an abstract class cannot be used to create objects using a constructor, abstract classes don’t usually have constructors.

An abstract class can be used only as an interface to other classes. For example:

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class Point { /* ... */ };

class Circle : public Shape {
public:
     void rotate(int) override { }
     void draw() const override;
     bool is_closed() const override { return true; }

     Circle(Point p, int r);
private:
     Point center;
     int radius;
};

A pure virtual function that is not defined in a derived class remains a pure virtual function, so the derived class is also an abstract class. This allows us to build implementations in stages:

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class Polygon : public Shape {           // abstract class
public:
     bool is_closed() const override { return true; }
     // ... draw and rotate not overridden ...
};

Polygon b {p1,p2,p3,p4};          // error: declaration of object of abstract class Polygon

Polygon is still abstract because we did not override draw() and rotate(). Only when that is done do we have a class from which we can create objects:

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class Irregular_polygon : public Polygon {
     list<Point> lp;
public:
     Irregular_polygon(initializer_list<Point>);

     void draw() const override;
     void rotate(int) override;
     // ...
};

Irregular_polygon poly {p1,p2,p3,p4};   // assume that p1 .. p4 are Points defined somewhere

An abstract class provides an interface without exposing implementation details. For example, an operating system might hide the details of its device drivers behind an abstract class:

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class Character_device {
public:
     virtual int open(int opt) = 0;
     virtual int close(int opt) = 0;
     virtual int read(char* p, int n) = 0;
     virtual int write(const char* p, int n) = 0;
     virtual int ioctl(int ...) = 0;       // device I/O control

     virtual ~Character_device() { }      // virtual destructor
};

We can then specify drivers as classes derived from Character_device and manipulate a variety of drivers through that interface.

The design style supported by abstract classes is called interface inheritance in contrast to the implementation inheritance supported by base classes with state and/or defined member functions. Combinations of the two approaches are possible. That is, we can define and use base classes with both state and pure virtual functions. However, such mixtures of approaches can be confusing and require extra care.

With the introduction of abstract classes, we have the basic facilities for writing a complete program in a modular fashion using classes as building blocks.

20.5. Access Control

A member of a class can be private, protected, or public:

• If it is private, its name can be used only by member functions and friends of the class in which it is declared.

• If it is protected, its name can be used only by member functions and friends of the class in which it is declared and by member functions and friends of classes derived from this class (see §19.4).

• If it is public, its name can be used by any function.

This reflects the view that there are three kinds of functions accessing a class: functions implementing the class (its friends and members), functions implementing a derived class (the derived class’s friends and members), and other functions. This can be presented graphically:

The access control is applied uniformly to names. What a name refers to does not affect the control of its use. This means that we can have private member functions, types, constants, etc., as well as private data members. For example, an efficient nonintrusive list class often requires data structures to keep track of elements. A list is nonintrusive if it does not require modification to its elements (e.g., by requiring element types to have link fields). The information and data structures used to organize the list can be kept private:

Click here to view code image

template<class T>
class List {
public:
     void insert(T);
     T get();
     // ...
private:
     struct Link { T val; Link* next; };

     struct Chunk {
          enum { chunk_size = 15};
          Link v[chunk_size];
          Chunk* next;
     };
     Chunk* allocated;
     Link* free;
     Link* get_free();
     Link* head;
};

The definitions of the public functions are pretty strainghtforward:

Click here to view code image

template<class T>
void List<T>::insert(T val)
{
     Link* lnk = get_free();
     lnk–>val = val;
     lnk–>next = head;
     head = lnk;
}

template<class T>
T List<T>::get()
{
     if (head == 0)
           throw Underflow{}; // Underflow is my exception class

     Link* p= head;
     head = p–>next;
     p–>next = free;
     free = p;
     return p–>val;
}

As is common, the definition of the supporting (here, private) functions are a bit more tricky:

Click here to view code image

template<class T>
typename List<T>::Link* List<T>::get_free()
{
     if (free == 0) {
           // ... allocate a new chunk and place its Links on the free list ...
     }
     Link* p = free;
     free = free–>next;
     return p;
}

The List<T> scope is entered by saying List<T>:: in a member function definition. However, because the return type of get_free() is mentioned before the name List<T>::get_free() is mentioned, the full name List<T>::Link must be used instead of the abbreviation Link. The alternative is to use the suffix notation for return types (§12.1.4):

template<class T>
auto List<T>::get_free() –> Link*
{
     // ...
}

Nonmember functions (except friends) do not have such access:

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template<typename T>
void would_be_meddler(List<T>* p)
{
     List<T>::Link* q = 0;                        // error: List<T>::Link is private
     // ...
     q = p–>free;                                 // error: List<T>::free is private
     // ...
     if (List<T>::Chunk::chunk_size > 31) {       // error: List<T>::Chunk::chunk_size is private
          // ...
     }
}

In a class, members are by default private; in a struct, members are by default public (§16.2.4).

The obvious alternative to using a member type is to place the type in the surrounding namespace. For example:

template<class T>
struct Link2 {
     T val;
     Link2* next;
};

template<class T>
class List {
private:
     Link2<T>* free;
     // ...
};

Link is implicitly parameterized with List<T>’s parameter T. For Link2, we must make that explicit.

If a member type does not depend on all the template class’s parameters, the nonmember version can be preferable; see §23.4.6.3.

If the nested class is not generally useful by itself and the enclosing class needs access to its representation, declaring the member class a friend (§19.4.2) may be a good idea:

Click here to view code image

template<class T> class List;

template<class T>
class Link3 {
     friend class List<T>;     // only List<T> can access Link<T>
     T val;
     Link3* next;
};
template<class T>
class List {
private:
     Link3<T>* free;
     // ...
};

A compiler may reorder sections of a class with separate access specifiers (§8.2.6). For example:

class S {
public:
     int m1;
public:
     int m2;
};

The compiler may decide for m2 to precede m1 in the layout of an S object. Such reordering could come as a surprise to the programmer and is implementation-dependent, so don’t use multiple access specifiers for data members without good reason.

20.5.1. protected Members

When designing a class hierarchy, we sometimes provide functions designed to be used by implementers of derived classes but not by the general user. For example, we may provide an (efficient) unchecked access function for derived class implementers and (safe) checked access for others. Declaring the unchecked version protected achieves that. For example:

Click here to view code image

class Buffer {
public:
     char& operator[](int i);     // checked access
     // ...
protected:
     char& access(int i);         // unchecked access
     // ...
};

class Circular_buffer : public Buffer {
public:
     void reallocate(char* p, int s);     // change location and size
     // ...
};

void Circular_buffer::reallocate(char* p, int s)// change location and size
{
     // ...
     for (int i=0; i!=old_sz; ++i)
           p[i] = access(i);     // no redundant checking
     // ...
}
void f(Buffer& b)
{
     b[3] = 'b';            // OK (checked)
     b.access(3) = 'c';     // error: Buffer::access() is protected
}

For another example, see Window_with_border in §21.3.5.2.

A derived class can access a base class’s protected members only for objects of its own type:

Click here to view code image

class Buffer {
protected:
     char a[128];
     // ...
};

class Linked_buffer : public Buffer {
     // ...
};

class Circular_buffer : public Buffer {
     // ...
     void f(Linked_buffer* p)
     {
           a[0] = 0;      // OK: access to Circular_buffer's own protected member
           p–>a[0] = 0;   // error: access to protected member of different type
     }
};

This prevents subtle errors that would otherwise occur when one derived class corrupts data belonging to other derived classes.

20.5.1.1. Use of protected Members

The simple private/public model of data hiding serves the notion of concrete types (§16.3) well. However, when derived classes are used, there are two kinds of users of a class: derived classes and “the general public.” The members and friends that implement the operations on the class operate on the class objects on behalf of these users. The private/public model allows the programmer to distinguish clearly between the implementers and the general public, but it does not provide a way of catering specifically to derived classes.

Members declared protected are far more open to abuse than members declared private. In particular, declaring data members protected is usually a design error. Placing significant amounts of data in a common class for all derived classes to use leaves that data open to corruption. Worse, protected data, like public data, cannot easily be restructured because there is no good way of finding every use. Thus, protected data becomes a software maintenance problem.

Fortunately, you don’t have to use protected data; private is the default in classes and is usually the better choice. In my experience, there have always been alternatives to placing significant amounts of information in a common base class for derived classes to use directly.

However, none of these objections are significant for protected member functions; protected is a fine way of specifying operations for use in derived classes. The Ival_slider in §21.2.2 is an example of this. Had the implementation class been private in this example, further derivation would have been infeasible. On the other hand, making bases providing implementation details public invites mistakes and misuse.

20.5.2. Access to Base Classes

Like a member, a base class can be declared private, protected, or public. For example:

class X : public B { /* ... */ };
class Y : protected B { /* ... */ };
class Z : private B { /* ... */ };

The different access specifiers serve different design needs:

• public derivation makes the derived class a subtype of its base. For example, X is a kind of B. This is the most common form of derivation.

• private bases are most useful when defining a class by restricting the interface to a base so that stronger guarantees can be provided. For example, B is an implementation detail of Z. The Vector of pointers template that adds type checking to its Vector<void*> base from §25.3 is a good example.

• protected bases are useful in class hierarchies in which further derivation is the norm. Like private derivation, protected derivation is used to represent implementation details. The Ival_slider from §21.2.2 is a good example.

The access specifier for a base class can be left out. In that case, the base defaults to a private base for a class and a public base for a struct. For example:

Click here to view code image

class XX : B { /* ... */ };    // B is a private base
struct YY : B { /* ... */ };   // B is a public base

People expect base classes to be public (that is, to express a subtype relationship), so the absence of an access specifier for a base is likely to be surprising for a class but not for a struct.

The access specifier for a base class controls the access to members of the base class and the conversion of pointers and references from the derived class type to the base class type. Consider a class D derived from a base class B:

• If B is a private base, its public and protected members can be used only by member functions and friends of D. Only friends and members of D can convert a D* to a B*.

• If B is a protected base, its public and protected members can be used only by member functions and friends of D and by member functions and friends of classes derived from D. Only friends and members of D and friends and members of classes derived from D can convert a D* to a B*.

• If B is a public base, its public members can be used by any function. In addition, its protected members can be used by members and friends of D and members and friends of classes derived from D. Any function can convert a D* to a B*.

This basically restates the rules for member access (§20.5). When designing a class, we choose access for bases in the same way as we do for members. For an example, see Ival_slider in §21.2.2.

20.5.2.1. Multiple Inheritance and Access Control

If the name of a base class can be reached through multiple paths in a multiple-inheritance lattice (§21.3), it is accessible if it is accessible through any path. For example:

Click here to view code image

struct B {
     int m;
     static int sm;
     // ...
};

class D1 : public virtual B { /* ... */ } ;
class D2 : public virtual B { /* ... */ } ;
class D12 : public D1, private D2 { /* ... */ };

D12* pd = new D12;
B* pb = pd;       // OK: accessible through D1
int i1 = pd–>m;   // OK: accessible through D1

If a single entity is reachable through several paths, we can still refer to it without ambiguity. For example:

Click here to view code image

class X1 : public B { /* ... */ } ;
class X2 : public B { /* ... */ } ;
class XX : public X1, public X2 { /* ... */ };

XX* pxx = new XX;
int i1 = pxx–>m;         // error, ambiguous: XX::X1::B::m or XX::X2::B::m?
int i2 = pxx–>sm;        // OK: there is only one B::sm in an XX (sm is a static member)

20.5.3. using-Declarations and Access Control

A using-declaration (§14.2.2, §20.3.5) cannot be used to gain access to additional information. It is simply a mechanism for making accessible information more convenient to use. On the other hand, once access is available, it can be granted to other users. For example:

Click here to view code image

class B {
private:
     int a;
protected:
     int b;
public:
     int c;
};

class D : public B {
public:
     using B::a;      // error: B::a is private
     using B::b;      // make B::b publicly available through D
};

When a using-declaration is combined with private or protected derivation, it can be used to specify interfaces to some, but not all, of the facilities usually offered by a class. For example:

Click here to view code image

class BB : private B {    // give access to B::b and B::c, but not B::a
public:
     using B::b;
     using B::c;
};

See also §20.3.5.

20.6. Pointers to Members

A pointer to member is an offset-like construct that allows a programmer to indirectly refer to a member of a class. The operators –>* and . * are arguably the most specialized and least used C++ operators. Using –>, we can access a member of a class, m, by naming it: p–>m. Using –>*, we can access a member that (conceptually) has its name stored in a pointer to member, ptom: p–> ptom. This allows us to access members with their names passed as arguments. In both cases, p must be a pointer to an object of an appropriate class.

A pointer to member cannot be assigned to a void* or any other ordinary pointer. A null pointer (e.g., nullptr) can be assigned to a pointer to member and then represents “no member.”

20.6.1. Pointers to Function Members

Many classes provide simple, very general interfaces intended to be invoked in several different ways. For example, many “object-oriented” user interfaces define a set of requests to which every object represented on the screen should be prepared to respond. In addition, such requests can be presented directly or indirectly from programs. Consider a simple variant of this idea:

Click here to view code image

class Std_interface {
public:
     virtual void start() = 0;
     virtual void suspend() = 0;
     virtual void resume() = 0;
     virtual void quit() = 0;
     virtual void full_size() = 0;
     virtual void small() = 0;

     virtual ~Std_interface() {}
};

The exact meaning of each operation is defined by the object on which it is invoked. Often, there is a layer of software between the person or program issuing the request and the object receiving it. Ideally, such intermediate layers of software should not have to know anything about the individual operations such as resume() and full_size(). If they did, the intermediate layers would have to be updated each time an operation changed. Consequently, such intermediate layers simply transmit data representing the operation to be invoked from the source of the request to its recipient.

One simple way of doing that is to send a string representing the operation to be invoked. For example, to invoke suspend() we could send the string "suspend". However, someone has to create that string and someone has to decode it to determine to which operation it corresponds – if any. Often, that seems indirect and tedious. Instead, we might simply send an integer representing the operation. For example, 2 might be used to mean suspend(). However, while an integer may be convenient for machines to deal with, it can get pretty obscure for people. We still have to write code to determine that 2 means suspend() and to invoke suspend().

However, we can use a pointer to member to indirectly refer to a member of a class. Consider Std_interface. If I want to invoke suspend() for some object without mentioning suspend() directly, I need a pointer to member referring to Std_interface::suspend(). I also need a pointer or reference to the object I want to suspend. Consider a trivial example:

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using Pstd_mem = void (Std_interface::*)();   // pointer-to-member type

void f(Std_interface* p)
{
     Pstd_mem s = &Std_interface::suspend;           // pointer to suspend()
     p–>suspend();                                   // direct call
     p–>*s();                                        // call through pointer to member
}

A pointer to member can be obtained by applying the address-of operator, &, to a fully qualified class member name, for example, &Std_interface::suspend. A variable of type “pointer to member of class X” is declared using a declarator of the form X::*.

The use of an alias to compensate for the lack of readability of the C declarator syntax is typical. However, please note how the X::* declarator matches the traditional * declarator exactly.

A pointer to member m can be used in combination with an object. The operators –>* and .* allow the programmer to express such combinations. For example, p–>*m binds m to the object pointed to by p, and obj.*m binds m to the object obj. The result can be used in accordance with m’s type. It is not possible to store the result of a –>* or a .* operation for later use.

Naturally, if we knew which member we wanted to call, we would invoke it directly rather than mess with pointers to members. Just like ordinary pointers to functions, pointers to member functions are used when we need to refer to a function without having to know its name. However, a pointer to member isn’t a pointer to a piece of memory the way a pointer to a variable or a pointer to a function is. It is more like an offset into a structure or an index into an array, but of course an implementation takes into account the differences between data members, virtual functions, nonvirtual functions, etc. When a pointer to member is combined with a pointer to an object of the right type, it yields something that identifies a particular member of a particular object.

The p–>*s() call can be represented graphically like this:

Because a pointer to a virtual member (s in this example) is a kind of offset, it does not depend on an object’s location in memory. A pointer to a virtual member can therefore be passed between different address spaces as long as the same object layout is used in both. Like pointers to ordinary functions, pointers to non-virtual member functions cannot be exchanged between address spaces.

Note that the function invoked through the pointer to function can be virtual. For example, when we call suspend() through a pointer to function, we get the right suspend() for the object to which the pointer to function is applied. This is an essential aspect of pointers to functions.

When writing an interpreter, we might use pointers to members to invoke functions presented as strings:

Click here to view code image

map<string,Std_interface*> variable;
map<string,Pstd_mem> operation;

void call_member(string var, string oper)
{
     (variable[var]–>*operation[oper])(); // var.oper()
}

A static member isn’t associated with a particular object, so a pointer to a static member is simply an ordinary pointer. For example:

Click here to view code image

class Task {
     // ...
     static void schedule();
};

void (*p)() = &Task::schedule;            // OK
void (Task::* pm)() = &Task::schedule;    // error: ordinary pointer assigned
                                          // to pointer to member

Pointers to data members are described in §20.6.2.

20.6.2. Pointers to Data Members

Naturally, the notion of pointer to member applies to data members and to member functions with arguments and return types. For example:

Click here to view code image

struct C {
     const char* val;
     int i;

     void print(int x) { cout << val << x << '\n'; }
     int f1(int);
     void f2();
     C(const char* v) { val = v; }
};

using Pmfi = void (C::*)(int);  // pointer to member function of C taking an int
using Pm = const char* C::*    // pointer to char* data member of C
void f(C& z1, C& z2)
{
     C* p = &z2;
     Pmfi pf = &C::print;
     Pm pm = &C::val;

     z1.print(1);
     (z1.*pf)(2);
     z1.*pm = "nv1 ";
     p–>*pm = "nv2 ";
     z2.print(3);
     (p–>*pf)(4);

     pf = &C::f1;   // error: return type mismatch
     pf = &C::f2;   // error: argument type mismatch
     pm = &C::i;    // error: type mismatch
     pm = pf;       // error: type mismatch
}

The type of a pointer to function is checked just like any other type.

20.6.3. Base and Derived Members

A derived class has at least the members that it inherits from its base classes. Often it has more. This implies that we can safely assign a pointer to a member of a base class to a pointer to a member of a derived class, but not the other way around. This property is often called contravariance. For example:

Click here to view code image

class Text : public Std_interface {
public:
     void start();
     void suspend();
     // ...
     virtual void print();
private:
     vector s;
};

void (Std_interface::* pmi)() = &Text::print;   // error
void (Text::*pmt)() = &Std_interface::start;    // OK

This contravariance rule appears to be the opposite of the rule that says we can assign a pointer to a derived class to a pointer to its base class. In fact, both rules exist to preserve the fundamental guarantee that a pointer may never point to an object that doesn’t at least have the properties that the pointer promises. In this case, Std_interface::* can be applied to any Std_interface, and most such objects presumably are not of type Text. Consequently, they do not have the member Text::print with which we tried to initialize pmi. By refusing the initialization, the compiler saves us from a run-time error.

20.7. Advice

[1] Avoid type fields; §20.3.1.

[2] Access polymorphic objects through pointers and references; §20.3.2.

[3] Use abstract classes to focus design on the provision of clean interfaces; §20.4.

[4] Use override to make overriding explicit in large class hierarchies; §20.3.4.1.

[5] Use final only sparingly; §20.3.4.2.

[6] Use abstract classes to specify interfaces; §20.4.

[7] Use abstract classes to keep implementation details out of interfaces; §20.4.

[8] A class with a virtual function should have a virtual destructor; §20.4.

[9] An abstract class typically doesn’t need a constructor; §20.4.

[10] Prefer private members for implementation details; §20.5.

[11] Prefer public members for interfaces; §20.5.

[12] Use protected members only carefully when really needed; §20.5.1.1.

[13] Don’t declare data members protected; §20.5.1.1.

21. Class Hierarchies

Abstraction is selective ignorance.

– Andrew Koenig

• Introduction

• Design of Class Hierarchies

Implementation Inheritance; Interface Inheritance; Alternative Implementations; Localizing Object Creation

• Multiple Inheritance

Multiple Interfaces; Multiple Implementation Classes; Ambiguity Resolution; Repeated Use of a Base Class; Virtual Base Classes; Replicated vs. Virtual Bases

• Advice

21.1. Introduction

The primary focus of this chapter is design techniques, rather than language features. The examples are taken from user-interface design, but I avoid the topic of event-driven programming as commonly used for graphical user interface (GUI) systems. A discussion of exactly how an action on the screen is transformed into a call of a member function would add little to the issues of class hierarchy design and has a huge potential for distraction: it is an interesting and important topic in its own right. For an understanding of GUI, have a look at one of the many C++ GUI libraries.

21.2. Design of Class Hierarchies

Consider a simple design problem: Provide a way for a program (“an application”) to get an integer value from a user. This can be done in a bewildering number of ways. To insulate our program from this variety, and also to get a chance to explore the possible design choices, let us start by defining our program’s model of this simple input operation.

The idea is to have a class Ival_box (“integer value input box”) that knows what range of input values it will accept. A program can ask an Ival_box for its value and ask it to prompt the user if necessary. In addition, a program can ask an Ival_box if a user changed the value since the program last looked at it:

Because there are many ways of implementing this basic idea, we must assume that there will be many different kinds of Ival_boxes, such as sliders, plain boxes in which a user can type a number, dials, and voice interaction.

The general approach is to build a “virtual user-interface system” for the application to use. This system provides some of the services provided by existing user-interface systems. It can be implemented on a wide variety of systems to ensure the portability of application code. Naturally, there are other ways of insulating an application from a user-interface system. I chose this approach because it is general, because it allows me to demonstrate a variety of techniques and design tradeoffs, because those techniques are also the ones used to build “real” user-interface systems, and – most important – because these techniques are applicable to problems far beyond the narrow domain of interface systems.

In addition to ignoring the topic of how to map user actions (events) to library calls, I also ignore the need for locking in a multi-threaded GUI system.

21.2.1. Implementation Inheritance

Our first solution is a class hierarchy using implementation inheritance (as is commonly found in older programs).

Class Ival_box defines the basic interface to all Ival_boxes and specifies a default implementation that more specific kinds of Ival_boxes can override with their own versions. In addition, we declare the data needed to implement the basic notion:

Click here to view code image

class Ival_box {
protected:
     int val;
     int low, high;
     bool changed {false};             // changed by user using set_value()
public:
     Ival_box(int ll, int hh) :val{ll}, low{ll}, high{hh} { }

     virtual int get_value() { changed = false; return val; }      // for application
     virtual void set_value(int i) { changed = true; val = i; }    // for user
     virtual void reset_value(int i) { changed = false; val = i; } // for application
     virtual void prompt() { }
     virtual bool was_changed() const { return changed; }

     virtual ~Ival_box() {};
};

The default implementation of the functions is pretty sloppy and is provided here primarily to illustrate the intended semantics. A realistic class would, for example, provide some range checking.

A programmer might use these “ival classes” like this:

Click here to view code image

void interact(Ival_box* pb)
{
     pb–>prompt(); // alert user
     // ...
     int i = pb–>get_value();
     if (pb–>was_changed()) {
           // ... new value; do something ...
     }
     else {
          // ... do something else ...
     }
}

void some_fct()
{
     unique_ptr<Ival_box> p1 {new Ival_slider{0,5}};   // Ival_slider derived from Ival_box
     interact(p1.get());

     unique_ptr<Ival_box> p2 {new Ival_dial{1,12}};
     interact(p2.get());
}

Most application code is written in terms of (pointers to) plain Ival_boxes the way interact() is. That way, the application doesn’t have to know about the potentially large number of variants of the Ival_box concept. The knowledge of such specialized classes is isolated in the relatively few functions that create such objects. This isolates users from changes in the implementations of the derived classes. Most code can be oblivious to the fact that there are different kinds of Ival_boxes.

I use unique_ptr (§5.2.1, §34.3.1) to avoid forgetting to delete the ival_boxes.

To simplify the discussion, I do not address issues of how a program waits for input. Maybe the program really does wait for the user in get_value() (e.g., using a get() on a future; §5.3.5.1), maybe the program associates the Ival_box with an event and prepares to respond to a callback, or maybe the program spawns a thread for the Ival_box and later inquires about the state of that thread. Such decisions are crucial in the design of user-interface systems. However, discussing them here in any realistic detail would simply distract from the presentation of programming techniques and language facilities. The design techniques described here and the language facilities that support them are not specific to user interfaces. They apply to a far greater range of problems.

The different kinds of Ival_boxes are defined as classes derived from Ival_box. For example:

Click here to view code image

class Ival_slider : public Ival_box {
private:
     // ... graphics stuff to define what the slider looks like, etc. ...
public:
     Ival_slider(int, int);
     int get_value() override;  // get value from user and deposit it in val
     void prompt() override;
};

The data members of Ival_box were declared protected to allow access from derived classes. Thus, Ival_slider::get_value() can deposit a value in Ival_box::val. A protected member is accessible from a class’s own members and from members of derived classes, but not to general users (see §20.5).

In addition to Ival_slider, we would define other variants of the Ival_box concept. These could include Ival_dial, which lets you select a value by turning a knob; Flashing_ival_slider, which flashes when you ask it to prompt(); and Popup_ival_slider, which responds to prompt() by appearing in some prominent place, thus making it hard for the user to ignore.

From where would we get the graphics stuff? Most user-interface systems provide a class defining the basic properties of being an entity on the screen. So, if we use the system from “Big Bucks Inc.,” we would have to make each of our Ival_slider, Ival_dial, etc., classes a kind of BBwidget. This would most simply be achieved by rewriting our Ival_box so that it derives from BBwidget. In that way, all our classes inherit all the properties of a BBwidget. For example, every Ival_box can be placed on the screen, obey the graphical style rules, be resized, be dragged around, etc., according to the standard set by the BBwidget system. Our class hierarchy would look like this:

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class Ival_box : public BBwidget { /* ... */ }; // rewritten to use BBwidget
class Ival_slider : public Ival_box { /* ... */ };
class Ival_dial : public Ival_box { /* ... */ };
class Flashing_ival_slider : public Ival_slider { /* ... */ };
class Popup_ival_slider : public Ival_slider { /* ... */ };

or graphically:

21.2.1.1. Critique

This design works well in many ways, and for many problems this kind of hierarchy is a good solution. However, there are some awkward details that could lead us to look for alternative designs.

We retrofitted BBwidget as the base of Ival_box. This is not quite right (even if this style is common in real-world systems). The use of BBwidget isn’t part of our basic notion of an Ival_box; it is an implementation detail. Deriving Ival_box from BBwidget elevated an implementation detail to a first-level design decision. That can be right. For example, using the environment defined by “Big Bucks Inc.” may be a key decision based on how our organization conducts its business. However, what if we also wanted to have implementations of our Ival_boxes for systems from “Imperial Bananas,” “Liberated Software,” and “Compiler Whizzes”? We would have to maintain four distinct versions of our program:

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class Ival_box : public BBwidget { /* ... */ };      // BB version
class Ival_box : public CWwidget { /* ... */ };      // CW version
class Ival_box : public IBwidget { /* ... */ };      // IB version
class Ival_box : public LSwindow { /* ... */ };      // LS version

Having many versions could result in a version control nightmare.

In reality, we are unlikely to find a simple, coherent, two-letter prefix scheme. More likely, the libraries from different purveyors would be in different namespaces and use different terminologies for similar concepts, such as BigBucks::Widget, Wizzies::control, and LS::window. But that does not affect our class hierarchy design discussion, so to simplify I ignore naming and namespace issues.

Another problem is that every derived class shares the basic data declared in Ival_box. That data is, of course, an implementation detail that also crept into our Ival_box interface. From a practical point of view, it is also the wrong data in many cases. For example, an Ival_slider doesn’t need the value stored specifically. It can easily be calculated from the position of the slider when someone executes get_value(). In general, keeping two related, but different, sets of data is asking for trouble. Sooner or later someone will get them out of sync. Also, experience shows that novice programmers tend to mess with protected data in ways that are unnecessary and that cause maintenance problems. Data members are better kept private so that writers of derived classes cannot mess with them. Better still, data should be in the derived classes, where it can be defined to match requirements exactly and cannot complicate the life of unrelated derived classes. In almost all cases, a protected interface should contain only functions, types, and constants.

Deriving from BBwidget gives the benefit of making the facilities provided by BBwidget available to users of Ival_box. Unfortunately, it also means that changes to class BBwidget may force users to recompile or even rewrite their code to recover from such changes. In particular, the way most C++ implementations work implies that a change in the size of a base class requires a recompilation of all derived classes.

Finally, our program may have to run in a mixed environment in which windows of different user-interface systems coexist. This could happen either because two systems somehow share a screen or because our program needs to communicate with users on different systems. Having our user-interface systems “wired in” as the one and only base of our one and only Ival_box interface just isn’t flexible enough to handle those situations.

21.2.2. Interface Inheritance

So, let’s start again and build a new class hierarchy that solves the problems presented in the critique of the traditional hierarchy:

[1] The user-interface system should be an implementation detail that is hidden from users who don’t want to know about it.

[2] The Ival_box class should contain no data.

[3] No recompilation of code using the Ival_box family of classes should be required after a change of the user-interface system.

[4] Ival_boxes for different interface systems should be able to coexist in our program.

Several alternative approaches can be taken to achieve this. Here, I present one that maps cleanly into the C++ language.

First, I specify class Ival_box as a pure interface:

Click here to view code image

class Ival_box {
public:
     virtual int get_value() = 0;
     virtual void set_value(int i) = 0;
     virtual void reset_value(int i) = 0;
     virtual void prompt() = 0;
     virtual bool was_changed() const = 0;
     virtual ~Ival_box() { }
};

This is much cleaner than the original declaration of Ival_box. The data is gone and so are the simplistic implementations of the member functions. Gone, too, is the constructor, since there is no data for it to initialize. Instead, I added a virtual destructor to ensure proper cleanup of the data that will be defined in the derived classes.

The definition of Ival_slider might look like this:

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class Ival_slider : public Ival_box, protected BBwidget {
public:
     Ival_slider(int,int);
     ~Ival_slider() override;

     int get_value() override;
     void set_value(int i) override;
     // ...
protected:
     // ... functions overriding BBwidget virtual functions
     // e.g., BBwidget::draw(), BBwidget::mouse1hit() ...
private:
     // ... data needed for slider ...
};

The derived class Ival_slider inherits from an abstract class (Ival_box) that requires it to implement the base class’s pure virtual functions. It also inherits from BBwidget which provides it with the means of doing so. Since Ival_box provides the interface for the derived class, it is derived using public. Since BBwidget is only an implementation aid, it is derived using protected (§20.5.2). This implies that a programmer using Ival_slider cannot directly use facilities defined by BBwidget. The interface provided by Ival_slider is the one inherited from Ival_box, plus what Ival_slider explicitly declares. I used protected derivation instead of the more restrictive (and usually safer) private derivation to make BBwidget available to classes derived from Ival_slider. I used explicit override because this “widget hierarchy” is exactly the kind of large, complicated hierachy where being explicit can help minimize confusion.

Deriving directly from more than one class is usually called multiple inheritance (§21.3). Note that Ival_slider must override functions from both Ival_box and BBwidget. Therefore, it must be derived directly or indirectly from both. As shown in §21.2.1.1, deriving Ival_slider indirectly from BBwidget by making BBwidget a base of Ival_box is possible, but doing so has undesirable side effects. Similarly, making the “implementation class” BBwidget a member of Ival_box is not a solution because a class cannot override virtual functions of its members. Representing the window by a BBwidget* member in Ival_box leads to a completely different design with a separate set of tradeoffs.

To some people, the words “multiple inheritance” indicate something complicated and scary. However, the use of one base class for implementation details and another for interface (the abstract class) is common to all languages supporting inheritance and compile-time checked interfaces. In particular, the use of the abstract class Ival_box is almost identical to the use of an interface in Java or C#.

Interestingly, this declaration of Ival_slider allows application code to be written exactly as before. All we have done is to restructure the implementation details in a more logical way.

Many classes require some form of cleanup for an object before it goes away. Since the abstract class Ival_box cannot know if a derived class requires such cleanup, it must assume that it does require some. We ensure proper cleanup by defining a virtual destructor Ival_box::~Ival_box() in the base and overriding it suitably in derived classes. For example:

void f(Ival_box* p)
{
     // ...
     delete p;
}

The delete operator explicitly destroys the object pointed to by p. We have no way of knowing exactly to which class the object pointed to by p belongs, but thanks to Ival_box’s virtual destructor, proper cleanup as (optionally) defined by that class’ destructor will be done.

The Ival_box hierarchy can now be defined like this:

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class Ival_box { /* ... */ };
class Ival_slider
     : public Ival_box, protected BBwidget { /* ... */ };
class Ival_dial
     : public Ival_box, protected BBwidget { /* ... */ };
class Flashing_ival_slider
     : public Ival_slider { /* ... */ };
class Popup_ival_slider
     : public Ival_slider { /* ... */ };

or graphically:

I used a dashed line to represent protected inheritance (§20.5.1). General users cannot access the protected bases because they are (correctly) considered part of the implementation.

21.2.3. Alternative Implementations

This design is cleaner and more easily maintainable than the traditional one – and no less efficient. However, it still fails to solve the version control problem:

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class Ival_box { /* ... */ }; // common
class Ival_slider
     : public Ival_box, protected BBwidget { /* ... */ }; // for BB
class Ival_slider
     : public Ival_box, protected CWwidget { /* ... */ }; // for CW
// ...

There is no way of having the Ival_slider for BBwidgets coexist with the Ival_slider for CWwidgets, even if the two user-interface systems could themselves coexist. The obvious solution is to define several different Ival_slider classes with separate names:

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class Ival_box { /* ... */ };
class BB_ival_slider
     : public Ival_box, protected BBwidget { /* ... */ };
class CW_ival_slider
     : public Ival_box, protected CWwidget { /* ... */ };
// ...

or graphically:

To further insulate our application-oriented Ival_box classes from implementation details, we can derive an abstract Ival_slider class from Ival_box and then derive the system-specific Ival_sliders from that:

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class Ival_box { /* ... */ };
class Ival_slider
     : public Ival_box { /* ... */ };
class BB_ival_slider
     : public Ival_slider, protected BBwidget { /* ... */ };
class CW_ival_slider
     : public Ival_slider, protected CWwidget { /* ... */ };
// ...

or graphically:

Usually, we can do better yet by utilizing more specific classes in the implementation hierarchy. For example, if the “Big Bucks Inc.” system has a slider class, we can derive our Ival_slider directly from the BBslider:

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class BB_ival_slider
     : public Ival_slider, protected BBslider { /* ... */ };
class CW_ival_slider
     : public Ival_slider, protected CWslider { /* ... */ };

or graphically:

This improvement becomes significant where – as is not uncommon – our abstractions are not too different from the ones provided by the system used for implementation. In that case, programming is reduced to mapping between similar concepts. Derivation from general base classes, such as BBwidget, is then done only rarely.

The complete hierarchy will consist of our original application-oriented conceptual hierarchy of interfaces expressed as derived classes:

class Ival_box { /* ... */ };
class Ival_slider
     : public Ival_box { /* ... */ };
class Ival_dial
     : public Ival_box { /* ... */ };
class Flashing_ival_slider
     : public Ival_slider { /* ... */ };
class Popup_ival_slider
     : public Ival_slider { /* ... */ };

followed by the implementations of this hierarchy for various graphical user interface systems, expressed as derived classes:

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class BB_ival_slider
     : public Ival_slider, protected BBslider { /* ... */ };
class BB_flashing_ival_slider
     : public Flashing_ival_slider, protected BBwidget_with_bells_and_whistles { /* ... */ };
class BB_popup_ival_slider
     : public Popup_ival_slider, protected BBslider { /* ... */ }; class CW_ival_slider
     : public Ival_slider, protected CWslider { /* ... */ };
// ...

Using obvious abbreviations, this hierarchy can be represented graphically like this:

The original Ival_box class hierarchy appears unchanged surrounded by implementation classes.

21.2.3.1. Critique

The abstract class design is flexible and almost as simple to deal with as the equivalent design that relies on a common base defining the user-interface system. In the latter design, the windows class is the root of a tree. In the former, the original application class hierarchy appears unchanged as the root of classes that supply its implementations. From the application’s point of view, these designs are equivalent in the strong sense that almost all code works unchanged and in the same way in the two cases. In either case, you can look at the Ival_box family of classes without bothering with the window-related implementation details most of the time. For example, we would not need to rewrite interact() from §21.2.1 if we switched from one class hierarchy to the other.

In either case, the implementation of each Ival_box class must be rewritten when the public interface of the user-interface system changes. However, in the abstract class design, almost all user code is protected against changes to the implementation hierarchy and requires no recompilation after such a change. This is especially important when the supplier of the implementation hierarchy issues a new “almost compatible” release. In addition, users of the abstract class hierarchy are in less danger of being locked into a proprietary implementation than are users of a classical hierarchy. Users of the Ival_box abstract class application hierarchy cannot accidentally use facilities from the implementation because only facilities explicitly specified in the Ival_box hierarchy are accessible; nothing is implicitly inherited from an implementation-specific base class.

The logical conclusion of this line of thought is a system represented to users as a hierarchy of abstract classes and implemented by a classical hierarchy. In other words:

• Use abstract classes to support interface inheritance (§3.2.3, §20.1).

• Use base classes with implementations of virtual functions to support implementation inheritance (§3.2.3, §20.1).

21.2.4. Localizing Object Creation

Most of an application can be written using the Ival_box interface. Further, should the derived interfaces evolve to provide more facilities than plain Ival_box, then most of an application can be written using the Ival_box, Ival_slider, etc., interfaces. However, the creation of objects must be done using implementation-specific names such as CW_ival_dial and BB_flashing_ival_slider. We would like to minimize the number of places where such specific names occur, and object creation is hard to localize unless it is done systematically.

As usual, the solution is to introduce an indirection. This can be done in many ways. A simple one is to introduce an abstract class to represent the set of creation operations:

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class Ival_maker {
public:
     virtual Ival_dial* dial(int, int) =0;                   // make dial
     virtual Popup_ival_slider* popup_slider(int, int) =0;   // make popup slider
     // ...
};

For each interface from the Ival_box family of classes that a user should know about, class Ival_maker provides a function that makes an object. Such a class is sometimes called a factory, and its functions are (somewhat misleadingly) sometimes called virtual constructors (§20.3.6).

We now represent each user-interface system by a class derived from Ival_maker:

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class BB_maker : public Ival_maker {        // make BB versions
public:
     Ival_dial* dial(int, int) override;
     Popup_ival_slider* popup_slider(int, int) override;
     // ...
};

class LS_maker : public Ival_maker {       // make LS versions
public:
     Ival_dial* dial(int, int) override;
     Popup_ival_slider* popup_slider(int, int) override;
     // ...
};

Each function creates an object of the desired interface and implementation type. For example:

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Ival_dial* BB_maker::dial(int a, int b)
{
     return new BB_ival_dial(a,b);
}

Ival_dial* LS_maker::dial(int a, int b)
{
     return new LS_ival_dial(a,b);
}

Given an Ival_maker, a user can now create objects without having to know exactly which user-interface system is used. For example:

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void user(Ival_maker& im)
{
     unique_ptr<Ival_box> pb {im.dial(0,99)};    // create appropriate dial
     // ...
}

BB_maker BB_impl;      // for BB users
LS_maker LS_impl;      // for LS users

void driver()
{
     user(BB_impl);    // use BB
     user(LS_impl);    // use LS
}

Passing arguments to such “virtual constructors” is a bit tricky. In particular, we cannot override the base class functions that represent the interface with different arguments in different derived classes. This implies that a fair bit of foresight is required to design the factory class’s interface.

21.3. Multiple Inheritance

As described in §20.1, inheritance aims to provide one of two benefits:

• Shared interfaces: leading to less replication of code using classes and making such code more uniform. This is often called run-time polymorphism or interface inheritance.

• Shared implementation: leading to less code and more uniform implementation code. This is often called implementation inheritance.

A class can combine aspects of these two styles.

Here, we explore more general uses of multiple base classes and examine more technical issues related to combining and accessing features from multiple base classes.

21.3.1. Multiple Interfaces

An abstract class (e.g., Ival_box; §21.2.2) is the obvious way to represent an interface. For an abstract class without mutable state, there really is little difference between single and multiple uses of a base class in a class hierarchy. The resolution of potential ambiguities is discussed in §21.3.3, §21.3.4, and §21.3.5. In fact, any class without mutable state can be used as an interface in a multiple-inheritance lattice without significant complications and overhead. The key observation is that a class without mutable state can be replicated if necessary or shared if that is desired.

The use of multiple abstract classes as interfaces is almost universal in object-oriented designs (in any language with a notion of an interface).

21.3.2. Multiple Implementation Classes

Consider a simulation of bodies orbiting the Earth in which orbiting objects are represented as object of class Satellite. A Satellite object would contain orbital, size, shape, albedo, density parameters, etc., and provide operations for orbital calculations, modifying attributes, etc. Examples of satellites would be rocks, debris from old space vehicles, communication satellites, and the International Space Station. These kinds of satellites would be objects of classes derived from Satellite. Such derived classes would add data members and functions and would override some of Satellite’s virtual functions to adjust their meaning suitably.

Now assume that I want to display the results of these simulations graphically and that I had available a graphics system that used the (not uncommon) strategy of deriving objects to be displayed from a common base class holding graphical information. This graphics class would provide operations for placement on the screen, scaling, etc. For generality, simplicity, and to hide the details of the actual graphics system, I will refer to the class providing graphical (or in fact alternatively nongraphical) output Display.

We can now define a class of simulated communication satellites, class Comm_sat:

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class Comm_sat : public Satellite, public Displayed {
public:
     // ...
};

or graphically:

In addition to whatever operations are defined specifically for a Comm_sat, the union of operations on Satellite and Displayed can be applied. For example:

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void f(Comm_sat& s)
{
     s.draw();           // Displayed::draw()
     Pos p = s.center(); // Satellite::center()
     s.transmit();       // Comm_sat::transmit()
}

Similarly, a Comm_sat can be passed to a function that expects a Satellite and to a function that expects Displayed. For example:

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void highlight(Displayed*);
Pos center_of_gravity(const Satellite*);

void g(Comm_sat* p)
{
     highlight(p);                  // pass a pointer to the Displayed part of the Comm_sat
     Pos x = center_of_gravity(p);  // pass a pointer to the Satellite part of the Comm_sat
}

The implementation of this clearly involves some (simple) compiler technique to ensure that functions expecting a Satellite see a different part of a Comm_sat than do functions expecting a Displayed. Virtual functions work as usual. For example:

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class Satellite {
public:
     virtual Pos center() const = 0;        // center of gravity
     // ...
};

class Displayed {
public:
     virtual void draw() = 0;
     // ...
};

class Comm_sat : public Satellite, public Displayed {
public:
     Pos center() const override;    // override Satellite::center()
     void draw() override;           // override Displayed::draw()
     // ...
};

This ensures that Comm_sat::center() and Displayed::draw() will be called for a Comm_sat treated as a Comm_sat and a Displayed, respectively.

Why didn’t I just keep the Satellite and Displayed parts of a Comm_sat completely separate? I could have defined Comm_sat to have a Satellite member and a Displayed member. Alternatively, I could have defined Comm_sat to have a Satellite* member and a Displayed* member and let its constructor set up the proper connections. For many design problems, I would do just that. However, the system that inspired this example was built on the idea of a Satellite class with virtual functions and a (separately designed) Displayed class with virtual functions. You provided your own satellites and your own displayed objects through derivation. In particular, you had to override Satellite virtual member functions and Displayed virtual member functions to specify the behavior of your own objects. That is the situation in which multiple inheritance of base classes with state and implementation is hard to avoid. Workarounds can be painful and hard to maintain.

The use of multiple inheritance to “glue” two otherwise unrelated classes together as part of the implementation of a third class is crude, effective, and relatively important, but not very interesting. Basically, it saves the programmer from writing a lot of forwarding functions (to compensate for the fact that we can only override functions defined in bases). This technique does not affect the overall design of a program significantly and can occasionally clash with the wish to keep implementation details hidden. However, a technique doesn’t have to be clever to be useful.

I generally prefer to have a single implementation hierarchy and (where needed) several abstract classes providing interfaces. This is typically more flexible and leads to systems that are easier to evolve. However, you can’t always get that – especially if you need to use existing classes that you don’t want to modify (e.g., because they are parts of someone else’s library).

Note that with single inheritance (only), the programmer’s choices for implementing the classes Displayed, Satellite, and Comm_sat would be limited. A Comm_sat could be a Satellite or a Displayed, but not both (unless Satellite was derived from Displayed or vice versa). Either alternative involves a loss of flexibility.

Why would anyone want a class Comm_sat? Contrary to some people’s conjectures, the Satellite example is real. There really was – and maybe there still is – a program constructed along the lines used to describe multiple implementation inheritance here. It was used to study the design of communication systems involving satellites, ground stations, etc. In fact, Satellite was derived from an early notion of a concurrent task. Given such a simulation, we can answer questions about communication traffic flow, determine proper responses to a ground station that is being blocked by a rainstorm, consider tradeoffs between satellite connections and Earth-bound connections, etc.

21.3.3. Ambiguity Resolution

Two base classes may have member functions with the same name. For example:

class Satellite {
public:
     virtual Debug_info get_debug();
     // ...
};

class Displayed {
public:
     virtual Debug_info get_debug();
     // ...
};

When a Comm_sat is used, these functions must be disambiguated. This can be done simply by qualifying a member name by its class name:

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void f(Comm_sat& cs)
{
     Debug_info di = cs.get_debug();      // error: ambiguous
     di = cs.Satellite::get_debug();      // OK
     di = cs.Displayed::get_debug();      // OK
}

However, explicit disambiguation is messy, so it is usually best to resolve such problems by defining a new function in the derived class:

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class Comm_sat : public Satellite, public Displayed {
public:
     Debug_info get_debug()  // override Comm_sat::get_debug() and Displayed::get_debug()
     {
          Debug_info di1 = Satellite::get_debug();
          Debug_info di2 = Displayed::get_debug();
          return merge_info(di1,di2);
     }
     // ...
};

A function declared in a derived class overrides all functions of the same name and type in its base classes. Typically, that is exactly the right thing to do because it is generally a bad idea to use the same name for operations with different semantics in a single class. The ideal for virtual is for a call to have the same effect independently of which interface was used to find the function (§20.3.2).

In the implementation of an overriding function, it is often necessary to explicitly qualify the name to get the right version from a base class. A qualified name, such as Telstar::draw, can refer to a draw declared either in Telstar or in one of its base classes. For example:

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class Telstar : public Comm_sat {
public:
     void draw()
     {
          Comm_sat::draw();       // finds Displayed::draw
          // ... own stuff ...
     }
     // ...
};

or graphically:

If Comm_sat::draw doesn’t resolve to a draw declared in Comm_sat, the compiler recursively looks in its base classes; that is, it looks for Satellite::draw and Displayed::draw, and if necessary looks in their base classes. If exactly one match is found, that name will be used. Otherwise, Comm_sat::draw is either not found or is ambiguous.

If, in Telstar::draw(), I had said plain draw(), the result would have been an “infinite” recursive call of Telstar::draw().

I could have said Displayed::draw(), but now the code would be subtly broken if someone added a Comm_sat::draw(); it is generally better to refer to a direct base class than to an indirect base class. I could have said Comm_sat::Displayed::draw(), but that would have been redundant. Had I said Satellite::draw(), the result would have been an error because the draw is over on the Displayed branch of the class hierarchy.

The get_debug() example basically assumes that at least some parts of Satellite and Displayed have been designed together. Getting an exact match of names, return types, argument types, and semantics by accident is extremely unlikely. It is far more likely that similar functionality is provided in different ways so that it takes effort to merge it into something that can be used together. We might originally have been presented with two classes SimObj and Widget that we could not modify, didn’t exactly provide what we needed, and where they did provide what we needed, did so through incompatible interfaces. In that case, we might have designed Satellite and Displayed as our interface classes, providing a “mapping layer” for our higher-level classes to use:

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class Satellite : public SimObj {
     // map SimObj facilities to something easier to use for Satellite simulation
public:
     virtual Debug_info get_debug();      // call SimObj::DBinf() and extract information
     // ...
};

class Displayed : public Widget {
     // map Widget facilities to something easier to use to display Satellite simulation results
public:
     virtual Debug_info get_debug();     // read Widget data and compose Debug_info
     // ...
};

or graphically:

Interestingly enough, this is exactly the technique we would use to disambiguate in the unlikely case where two base classes provided operations with exactly the same name, but with different semantics: add an interface layer. Consider the classical (but mostly hypothetical/theoretical) example of a class of a draw() member function in a video game involving cowboys:

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class Window {
public:
     void draw();      // display image
     // ...
};

class Cowboy {
public:
     void draw();      // pull gun from holster
     // ...
};

class Cowboy_window : public Cowboy, public Window {
     // ...
};

How do we override Cowboy::draw() and Window::draw()? These two functions have radically different meanings (semantics) but are identical in name and type; we need to override them by two separate functions. There is no direct language solution to this (exotic) problem, but adding intermediate classes will do:

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struct WWindow : Window {
     using Window::Window;                            // inherit constructors
     virtual void win_draw() = 0;                     // force derived class to override
     void draw() override final { win_draw(); }       // display image
};

struct CCowboy : Cowboy{
     using Cowboy::Cowboy;                            // inherit constructors
     virtual void cow_draw() = 0;                     // force derived class to override
     void draw() override final { cow_draw(); }             // pull gun from holster
};

class Cowboy_window : public CCowboy, public WWindow {
public:
     void cow_draw() override;
     void win_draw() override;
     // ...
};

Or graphically:

Had the designer of Window been a bit more careful and specified draw() to be const, the whole problem would have evaporated. I find that fairly typical.

21.3.4. Repeated Use of a Base Class

When each class has only one direct base class, the class hierarchy will be a tree, and a class can only occur once in the tree. When a class can have multiple base classes, a class can appear multiple times in the resulting hierarchy. Consider a class providing facilities for storing state in a file (e.g., for breakpointing, debug information, or persistence) and restoring it later:

struct Storable {    // persistent storage
     virtual string get_file() = 0;
     virtual void read() = 0;
     virtual void write() = 0;

     virtual ~Storable() { }
};

Such a useful class will naturally be used in several places in a class hierarchy. For example:

Click here to view code image

class Transmitter : public Storable {
public:
     void write() override;
     // ...
};

class Receiver : public Storable {
public:
     void write() override;
     // ...
};

class Radio : public Transmitter, public Receiver {
public:
     string get_file() override;
     void read() override;
     void write() override;
     // ...
};

Given that, we could imagine two cases:

[1] A Radio object has two subobjects of class Storable (one for Transmitter and one for Receiver).

[2] A Radio object has one subobject of class Storable (shared by Transmitter and Receiver).

The default, provided for the example as written, is two subobjects. Unless you state otherwise, you get one copy for each time you mention a class as a base. Graphically, we can represent that like this:

A virtual function of a replicated base class can be overridden by a (single) function in a derived class. Typically, an overriding function calls its base class versions and then does the work specific to the derived class:

Click here to view code image

void Radio::write()
{
     Transmitter::write();
     Receiver::write();
     // ... write radio-specific information ...
}

Casting from a replicated base class to a derived class is discussed in §22.2. For a technique for overriding each of the write() functions with separate functions from derived classes, see §21.3.3.

21.3.5. Virtual Base Classes

The Radio example in the previous subsection works because class Storable can be safely, conveniently, and efficiently replicated. The reason for that is simply that Storable is an abstract class providing a pure interface. A Storable object holds no data of its own. This is the simplest case and the one that offers the best separation of interface and implementation concerns. In fact, a class could not without some difficulty determine that there were two Storable subobjects on a Radio.

What if Storable did hold data and it was important that it should not be replicated? For example, we might define Storable to hold the name of the file to be used for storing the object:

Click here to view code image

class Storable {
public:
     Storable(const string& s);    // store in file named s
     virtual void read() = 0;
     virtual void write() = 0;
     virtual ~Storable();
protected:
     string file_name;

     Storable(const Storable&) = delete;
     Storable& operator=(const Storable&) = delete;
};

Given this apparently minor change to Storable, we must change the design of Radio. All parts of an object must share a single copy of Storable. Otherwise, we could get two parts of something derived from Storable multiple times using different files. We avoid replication by declaring a base virtual: every virtual base of a derived class is represented by the same (shared) object. For example:

Click here to view code image

class Transmitter : public virtual Storable {
public:
     void write() override;
     // ...
};

class Receiver : public virtual Storable {
public:
     void write() override;
     // ...
};

class Radio : public Transmitter, public Receiver {
public:
     void write() override;
     // ...
};

Or graphically:

Compare this diagram with the drawing of the Storable object in §21.3.4 to see the difference between ordinary inheritance and virtual inheritance. In an inheritance graph, every base class of a given name that is specified to be virtual will be represented by a single object of that class. On the other hand, each base class not specified virtual will have its own subobject representing it.

Why would someone want to use a virtual base containing data? I can think of three obvious ways for two classes in a class hierarchy to share data:

[1] Make the data nonlocal (outside the class as a global or namespace variable).

[2] Put the data in a base class.

[3] Allocate an object somewhere and give each of the two classes a pointer.

Option [1], nonlocal data, is usually a poor choice because we cannot control what code accesses the data and how. It breaks all notions of encapsulation and locality.

Option [2], put the data in a base class, is usually the simplest. However, for single inheritance that solution makes useful data (and functions) “bubble up” to a common base class; often it “bubbles” all the way to the root of an inheritance tree. This means that every member of the class hierarchy gets access. That is logically very similar to using nonlocal data and suffers from the same problems. So we need a common base that is not the root of a tree – that is, a virtual base.

Option [3], sharing an object accessed through pointers, makes sense. However, then constructor(s) need to set aside memory for that shared object, initialize it, and provide pointers to the shared object to objects needing access. That is roughly what constructors do to implement a virtual base.

If you don’t need sharing, you can do without virtual bases, and your code is often better and typically simpler for it. However, if you do need sharing within a general class hierarchy, you basically have a choice between using a virtual base and laboriously constructing your own variants of the idea.

We can represent an object of a class with a virtual base like this:

The “pointers” to the shared object representing the virtual base, Storable, will be offsets, and often one of those can be optimized away by placing Storable in a fixed position relative to either the Receiver or the Transmitter subobject. Expect a storage overhead of one word for each virtual base.

21.3.5.1. Constructing Virtual Bases

Using virtual bases you can create complicated lattices. Naturally, we would prefer to keep the lattices simple, but however complicated we make them, the language ensures that a constructor of a virtual base is called exactly once. Furthermore, the constructor of a base (whether virtual or not) is called before its derived classes. Anything else would cause chaos (that is, an object might be used before it had been initialized). To avoid such chaos, the constructor of every virtual base is invoked (implicitly or explicitly) from the constructor for the complete object (the constructor for the most derived class). In particular, this ensures that a virtual base is constructed exactly once even if it is mentioned in many places in the class hierarchy. For example:

Click here to view code image

struct V {
     V(int i);
     // ...
};

struct A {
     A();     // default constructor
     // ...
};

struct B : virtual V, virtual A {
     B() :V{1} { /* ... */ }; // default constructor; must initialize base V
     // ...
};

class C : virtual V {
public:
     C(int i) : V{i} { /* ... */ }; // must initialize base V
     // ...
};

class D : virtual public B, virtual public C {
     // implicitly gets the virtual base V from B and C
     // implicitly gets virtual base A from B
public:
     D() { /* ... */ }                      // error: no default constructor for C or V
     D(int i) :C{i} { /* ... */ };          // error: no default constructor for V
     D(int i, int j) :V{i}, C{j} { /* ... */ }     // OK
     // ...
};

Note that D can and must provide an initializer for V. The fact that V wasn’t explicitly mentioned as a base of D is irrelevant. Knowledge of a virtual base and the obligation to initialize it “bubbles up” to the most derived class. A virtual base is always considered a direct base of its most derived class. The fact that both B and C initialized V is irrelevant because the compiler has no idea which of those two initializers to prefer. Thus, only the initializer provided by the most derived class is used.

The constructor for a virtual base is called before the constructors for its derived classes.

In practice, this is not quite as localized as we would prefer. In particular, if we derive another class, DD, from D, then DD has to do work to initialize the virtual bases. Unless we can simply inherit D’s constructors (§20.3.5.1), that can be a nuisance. That ought to encourage us not to overuse virtual base classes.

This logical problem with constructors does not exist for destructors. They are simply invoked in reverse order of construction (§20.2.2). In particular, a destructor for a virtual base is invoked exactly once.

21.3.5.2. Calling a Virtual Class Member Once Only

When defining the functions for a class with a virtual base, the programmer in general cannot know whether the base will be shared with other derived classes. This can be a problem when implementing a service that requires a base class function to be called exactly once for each call of a derived function. Where needed, the programmer can simulate the scheme used for constructors by calling a virtual base class function only from the most derived class. For example, assume we have a basic Window class that knows how to draw its contents:

class Window {
public:
     // basic stuff
     virtual void draw();
};

In addition, we have various ways of decorating a window and adding facilities:

Click here to view code image

class Window_with_border : public virtual Window {
     // border stuff
protected:
     void own_draw();    // display the border
public:
     void draw() override;
};

class Window_with_menu : public virtual Window {
     // menu stuff
protected:
     void own_draw();   // display the menu
public:
     void draw() override;
};

The own_draw() functions need not be virtual because they are meant to be called from within a virtual draw() function that “knows” the type of the object for which it was called.

From this, we can compose a plausible Clock class:

Click here to view code image

class Clock : public Window_with_border, public Window_with_menu {
     // clock stuff
protected:
     void own_draw();   // display the clock face and hands
public:
     void draw() override;
};

or graphically:

The draw() functions can now be defined using the own_draw() functions, so that a caller of any draw() gets Window::draw() invoked exactly once. This is done independently of the kind of Window for which draw() is invoked:

Click here to view code image

void Window_with_border::draw()
{
     Window::draw();
     own_draw();   // display the border
}

void Window_with_menu::draw()
{
     Window::draw();
     own_draw();   // display the menu
}

void Clock::draw()
{
     Window::draw();
     Window_with_border::own_draw();
     Window_with_menu::own_draw();
     own_draw();  // display the clock face and hands
}

Note that a qualified call, such as Window::draw(), does not use the virtual call mechanism. Instead, it directly calls the explicitly named function, thus avoiding nasty infinite recursion.

Casting from a virtual base class to a derived class is discussed in §22.2.

21.3.6. Replicated vs. Virtual Bases

Using multiple inheritance to provide implementations for abstract classes representing pure interfaces affects the way a program is designed. Class BB_ival_slider (§21.2.3) is an example:

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class BB_ival_slider
   : public Ival_slider,        // interface
     protected BBslider         // implementation
{
   // implementation of functions required by Ival_slider and BBslider, using facilities from BBslider
};

In this example, the two base classes play logically distinct roles. One base is a public abstract class providing the interface, and the other is a protected concrete class providing implementation “details.” These roles are reflected in both the style of the classes and in the access control (§20.5) provided. The use of multiple inheritance is close to essential here because the derived class needs to override virtual functions from both the interface and the implementation.

For example, consider again the Ival_box classes from §21.2.1. In the end (§21.2.2), I made all the Ival_box classes abstract to reflect their role as pure interfaces. Doing that allowed me to place all implementation details in specific implementation classes. Also, all sharing of implementation details was done in the classical hierarchy of the windows system used for the implementation.

When using an abstract class (without any shared data) as an interface, we have a choice:

• Replicate the interface class (one object per mention in the class hierarchy).

• Make the interface class virtual to share a simple object among all classes in the hierarchy that mention it.

Using Ival_slider as a virtual base gives us:

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class BB_ival_slider
     : public virtual Ival_slider, protected BBslider { /* ... */ };
class Popup_ival_slider
     : public virtual Ival_slider { /* ... */ };
class BB_popup_ival_slider
     : public virtual Popup_ival_slider, protected BB_ival_slider { /* ... */ };

or graphically:

It is easy to imagine further interfaces derived from Popup_ival_slider and further implementation classes derived from such classes and BB_popup_ival_slider.

However, we also have this alternative using replicated Ival_slider objects:

Click here to view code image

class BB_ival_slider
     : public Ival_slider, protected BBslider { /* ... */ };
class Popup_ival_slider
     : public Ival_slider { /* ... */ };
class BB_popup_ival_slider
     : public Popup_ival_slider, protected BB_ival_slider { /* ... */ };

or graphically:

Surprisingly, there are no fundamental run-time or space advantages to one design over the other. There are logical differences, though. In the replicated Ival_slider design, a BB_popup_ival_slider can’t be implicitly converted to an Ival_slider (because that would be ambiguous):

Click here to view code image

void f(Ival_slider* p);

void g(BB_popup_ival_slider* p)
{
     f(p); // error: Popup_ival_slider::Ival_slider or BB_ival_slider::Ival_slider?
}

On the other hand, it is possible to construct plausible scenarios where the sharing implied in the virtual base design causes ambiguities for casts from the base class (§22.2). However, such ambiguities are easily dealt with.

How do we choose between virtual base classes and replicated base classes for our interfaces? Most often, of course, we don’t get a choice because we have to conform to an existing design. When we do have a choice, we can take into account that (surprisingly) the replicated base solution tends to lead to slightly smaller objects (because there is no need for data structures supporting sharing) and that we often get our interface objects from “virtual constructors” or “factory functions” (§21.2.4). For example:

Click here to view code image

Popup_ival_slider* popup_slider_factory(args)
{
    // ...
    return new BB_popup_ival_slider(args);
    // ...
}

No explicit conversion is needed to get from an implementation (here, BB_popup_ival_slider) to its direct interfaces (here, Popup_ival_slider).

21.3.6.1. Overriding Virtual Base Functions

A derived class can override a virtual function of its direct or indirect virtual base class. In particular, two different classes might override different virtual functions from the virtual base. In that way, several derived classes can contribute implementations to the interface presented by a virtual base class. For example, the Window class might have functions set_color() and prompt(). In that case, Window_with_border might override set_color() as part of controlling the color scheme, and Window_with_menu might override prompt() as part of its control of user interactions:

Click here to view code image

class Window {
     // ...
     virtual void set_color(Color) = 0;       // set background color
     virtual void prompt() = 0;
};

class Window_with_border : public virtual Window {
     // ...
     void set_color(Color) override;          // control background color
};

class Window_with_menu : public virtual Window {
     // ...
     void prompt() override;              // control user interactions
};

class My_window : public Window_with_menu, public Window_with_border {
     // ...
};

What if different derived classes override the same function? This is allowed if and only if some overriding class is derived from every other class that overrides the function. That is, one function must override all others. For example, My_window could override prompt() to improve on what Window_with_menu provides:

Click here to view code image

class My_window : public Window_with_menu, public Window_with_border {
     // ...
     void prompt() override; // don't leave user interactions to base
};

or graphically:

If two classes override a base class function, but neither overrides the other, the class hierarchy is an error. The reason is that no single function can be used to give a consistent meaning for all calls independently of which class they use as an interface. Or, using implementation terminology, no virtual function table can be constructed because a call to that function on the complete object would be ambiguous. For example, had Radio in §21.3.5 not declared write(), the declarations of write() in Receiver and Transmitter would have caused an error when defining Radio. As with Radio, such a conflict is resolved by adding an overriding function to the most derived class.

A class that provides some – but not all – of the implementation for a virtual base class is often called a mixin.

21.4. Advice

[1] Use unique_ptr or shared_ptr to avoid forgetting to delete objects created using new; §21.2.1.

[2] Avoid date members in base classes intended as interfaces; §21.2.1.1.

[3] Use abstract classes to express interfaces; §21.2.2.

[4] Give an abstract class a virtual destructor to ensure proper cleanup; §21.2.2.

[5] Use override to make overriding explicit in large class hierarchies; §21.2.2.

[6] Use abstract classes to support interface inheritance; §21.2.2.

[7] Use base classes with data members to support implementation inheritance; §21.2.2.

[8] Use ordinary multiple inheritance to express a union of features; §21.3.

[9] Use multiple inheritance to separate implementation from interface; §21.3.

[10] Use a virtual base to represent something common to some, but not all, classes in a hierarchy; §21.3.5.

22. Run-Time Type Information

Premature optimization is the root of all evil.

– Donald Knuth

On the other hand, we cannot ignore efficiency.

– Jon Bentley

• Introduction

• Class Hierarchy Navigation

dynamic cast; Multiple Inheritance; static_cast and dynamic_cast; Recovering an Interface

• Double Dispatch and Visitors

Double Dispatch; Visitors

• Construction and Destruction

• Type Identification

Extended Type Information

• Uses and Misuses of RTII

• Advice

22.1. Introduction

In general, a class is constructed from a lattice of base classes. Such a class lattice is often called a class hierarchy. We try to design classes so that users need not be unduly concerned about the way a class is composed out of other classes. In particular, the virtual call mechanism ensures that when we call a function f() on an object, the same function is called whichever class in the hierarchy provided the declaration of f() used for the call and whichever class defined it. This chapter explains how to gain information about the total object given only the interface provided by a base class.

22.2. Class Hierarchy Navigation

A plausible use of the Ival_boxes defined in §21.2 would be to hand them to a system that controlled a screen and have that system hand objects back to the application program whenever some activity had occurred. We will refer to the combination of GUI library and operating system facilities that control the screen as the system. Objects passed back and forth between the system and the application are commonly referred to as widgets or controls. This is how many user interfaces work. From a language point of view, it is important that the system does not know about our Ival_boxes. The system’s interfaces are specified in terms of the system’s own classes and objects rather than our application’s classes. This is necessary and proper. However, it does have the unpleasant effect that we lose information about the type of objects passed to the system and later returned to us.

Recovering the “lost” type of an object requires us to somehow ask the object to reveal its type. Any operation on an object requires us to have a pointer or reference of a suitable type for the object. Consequently, the most obvious and useful operation for inspecting the type of an object at run time is a type conversion operation that returns a valid pointer if the object is of the expected type and a null pointer if it isn’t. The dynamic_cast operator does exactly that. For example, assume that “the system” invokes my_event_handler() with a pointer to a BBwindow, where an activity has occurred. I then might invoke my application code using Ival_box’s do_something():

Click here to view code image

void my_event_handler(BBwindow* pw)
{
     if (auto pb = dynamic_cast<Ival_box*>(pw)) { // does pw point to an Ival_box?
          // ...
          int x = pb–>get_value(); // use the Ival_box
          // ...
     }
     else {
          // ... oops! cope with unexpected event ...
     }
}

One way of explaining what is going on here is that dynamic_cast translates from the implementation-oriented language of the user-interface system to the language of the application. It is important to note what is not mentioned in this example: the actual type of the object. The object will be a particular kind of Ival_box, say, an Ival_slider, implemented by a particular kind of BBwindow, say, a BBslider. It is neither necessary nor desirable to make the actual type of the object explicit in this interaction between “the system” and the application. An interface exists to represent the essentials of an interaction. In particular, a well-designed interface hides inessential details.

Graphically, the action of pb=dynamic_cast<Ival_box*>(pw) can be represented like this:

The arrows from pw and pb represent the pointers into the object passed, whereas the rest of the arrows represent the inheritance relationships between the different parts of the object passed.

The use of type information at run time is conventionally referred to as “run-time type information,” often abbreviated to RTTI.

Casting from a base class to a derived class is often called a downcast because of the convention of drawing inheritance trees growing from the root down. Similarly, a cast from a derived class to a base is called an upcast. A cast that goes from a base to a sibling class, like the cast from BBwindow to Ival_box, is called a crosscast.

22.2.1. dynamic_cast

The dynamic_cast operator takes two operands: a type bracketed by < and >, and a pointer or reference bracketed by ( and ). Consider first the pointer case:

dynamic_cast<T*>(p)

If p is of type T* or of a type D* where T is a base class of D, the result is exactly as if we had simply assigned p to a T*. For example:

Click here to view code image

class BB_ival_slider : public Ival_slider, protected BBslider {
     // ...
};

void f(BB_ival_slider* p)
{
     Ival_slider* pi1 = p;                                     // OK
     Ival_slider* pi2 = dynamic_cast<Ival_slider*>(p);         // OK

     BBslider* pbb1 = p;                                       // error: BBslider is a protected base
     BBslider* pbb2 = dynamic_cast<BBslider*>(p);              // OK: pbb2 becomes nullptr
}

This (the upcast) is the uninteresting case. However, it is reassuring to know that dynamic_cast doesn’t allow accidental violation of the protection of private and protected base classes. Since a dynamic_cast used as an upcast is exactly like a simple assignment, it implies no overhead and is sensitive to its lexical context.

The purpose of dynamic_cast is to deal with the case in which the correctness of the conversion cannot be determined by the compiler. In that case, dynamic_cast<T*>(p) looks at the object pointed to by p (if any). If that object is of class T or has a unique base class of type T, then dynamic_cast returns a pointer of type T* to that object; otherwise, nullptr is returned. If the value of p is nullptr, dynamic_cast<T*>(p) returns nullptr. Note the requirement that the conversion must be to a uniquely identified object. It is possible to construct examples where the conversion fails and nullptr is returned because the object pointed to by p has more than one subobject representing bases of type T (§22.2).

A dynamic_cast requires a pointer or a reference to a polymorphic type in order to do a downcast or a crosscast. For example:

Click here to view code image

class My_slider: public Ival_slider {    // polymorphic base (Ival_slider has virtual functions)
     // ...
};

class My_date : public Date {            // base not polymorphic (Date has no virtual functions)
     // ...
};

void g(Ival_box* pb, Date* pd)
{
     My_slider* pd1 = dynamic_cast<My_slider*>(pb);     // OK
     My_date* pd2 = dynamic_cast<My_date*>(pd);         // error: Date not polymorphic
}

Requiring the pointer’s type to be polymorphic simplifies the implementation of dynamic_cast because it makes it easy to find a place to hold the necessary information about the object’s type. A typical implementation will attach a “type information object” (§22.5) to an object by placing a pointer to the type information in the virtual function table for the object’s class (§3.2.3). For example:

The dashed arrow represents an offset that allows the start of the complete object to be found given only a pointer to a polymorphic subobject. It is clear that dynamic_cast can be efficiently implemented. All that is involved are a few comparisons of type_info objects representing base classes; no expensive lookups or string comparisons are needed.

Restricting dynamic_cast to polymorphic types also makes sense from a logical point of view. That is, if an object has no virtual functions, it cannot safely be manipulated without knowledge of its exact type. Consequently, care should be taken not to get such an object into a context in which its type isn’t known. If its type is known, we don’t need to use dynamic_cast.

The target type of dynamic_cast need not be polymorphic. This allows us to wrap a concrete type in a polymorphic type, say, for transmission through an object I/O system (§22.2.4), and then “unwrap” the concrete type later. For example:

Click here to view code image

class Io_obj {            // base class for object I/O system
     virtual Io_obj* clone() = 0;
};

class Io_date : public Date, public Io_obj { };

void f(Io_obj* pio)
{
     Date* pd = dynamic_cast<Date*>(pio);
     // ...
}

A dynamic_cast to void* can be used to determine the address of the beginning of an object of polymorphic type. For example:

Click here to view code image

void g(Ival_box* pb, Date* pd)
{
     void* pb2 = dynamic_cast<void*>(pb);   // OK
     void* pd2 = dynamic_cast<void*>(pd);   // error: Date not polymorphic
}

The object representing a base class, such as Ival_box, in a derived class object is not necessarily the first subobject in that object of the most derived class. So, pb does not necessarily hold the same address as pb2.

Such casts are only useful for interaction with very low-level functions (only such functions deal with void*s). There is no dynamic_cast from void* (because there would be no way of knowing where to find the vptr; §22.2.3).

22.2.1.1. dynamic_cast to Reference

To get polymorphic behavior, an object must be manipulated through a pointer or a reference. When a dynamic_cast is used for a pointer type, a nullptr indicates failure. That is neither feasible nor desirable for references.

Given a pointer result, we must consider the possibility that the result is nullptr, that is, that the pointer doesn’t point to an object. Consequently, the result of a dynamic_cast of a pointer should always be explicitly tested. For a pointer p, dynamic_cast<T*>(p) can be seen as the question “Is the object pointed to by p, if any, of type T?” For example:

Click here to view code image

void fp(Ival_box* p)
{
     if (Ival_slider* is = dynamic_cast<Ival_slider*>(p)) {   // does p point to an Ival_slider?
          // ... use is ...
     }
     else {
          // ... *p not a slider; handle alternatives ...
     }
}

On the other hand, we may legitimately assume that a reference refers to an object (§7.7.4). Consequently, dynamic_cast<T&>(r) of a reference r is not a question but an assertion: “The object referred to by r is of type T.” The result of a dynamic_cast for a reference is implicitly tested by the implementation of dynamic_cast itself. If the operand of a dynamic_cast to a reference isn’t of the expected type, a bad_cast exception is thrown. For example:

Click here to view code image

void fr(Ival_box& r)
{
     Ival_slider& is = dynamic_cast<Ival_slider&>(r);     // r references an Ival_slider!
     // ... use is ...
}

The difference in results of a failed dynamic pointer cast and a failed dynamic reference cast reflects a fundamental difference between references and pointers. If a user wants to protect against bad casts to references, a suitable handler must be provided. For example:

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void g(BB_ival_slider& slider, BB_ival_dial& dial)
{
     try {
           fp(&slider);     // pointer to BB_ival_slider passed as Ival_box*
           fr(slider);      // reference to BB_ival_slider passed as Ival_box&
           fp(&dial);       // pointer to BB_ival_dial passed as Ival_box*
           fr(dial);        // dial passed as Ival_box
     }
     catch (bad_cast) { // §30.4.1.1
           // ...
     }
}

The calls to fp() and the first call to fr() will return normally (assuming that fp() really can cope with a BB_ival_dial), but the second call of fr() will cause a bad_cast exception that will be caught by g().

Explicit tests against nullptr can easily be accidentally omitted. If that worries you, you can write a conversion function that throws an exception instead of returning nullptr in case of failure.

22.2.2. Multiple Inheritance

When only single inheritance is used, a class and its base classes constitute a tree rooted in a single base class. This is simple but often constraining. When multiple inheritance is used, there is no single root. In itself, this doesn’t complicate matters much. However, if a class appears more than once in a hierarchy, we must be a bit careful when we refer to the object or objects that represent that class.

Naturally, we try to keep hierarchies as simple as our application allows (and no simpler). However, once a nontrivial hierarchy has been constructed, we sometimes need to navigate it to find a specific class to use. This need occurs in two variants:

• Sometimes, we want to explicitly name a base class for use as an interface, for example, to resolve an ambiguity or to call a specific function without relying on the virtual function mechanism (an explicitly qualified call; §21.3.3).

• Sometimes, we want to obtain a pointer to a subobject of a hierarchy given a pointer to another, for example, to get a pointer to the complete derived class object from a pointer to a base (a downcast; §22.2.1) or to get a pointer to a base class object from a pointer to another base (a crosscast; §22.2.4).

Here, we consider how to navigate a class hierarchy using type conversions (casts) to gain a pointer of the desired type. To illustrate the mechanisms available and the rules that guide them, consider a lattice containing both a replicated base and a virtual base:

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class Component
     : public virtual Storable { /* ... */ };
class Receiver
     : public Component { /* ... */ };
class Transmitter
     : public Component { /* ... */ };
class Radio
     : public Receiver, public Transmitter { /* ... */ };

or graphically:

Here, a Radio object has two subobjects of class Component. Consequently, a dynamic_cast from Storable to Component within a Radio will be ambiguous and return a 0. There is simply no way of knowing which Component the programmer wanted:

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void h1(Radio& r)
{
     Storable* ps = &r; // a Radio has a unique Storable
     // ...
     Component* pc = dynamic_cast<Component*>(ps);          // pc = 0; a Radio has two Components
     // ...
}

In general – and typically – a programmer (and a compiler looking at a single translation unit) does not know the complete class lattice. Instead, code is written with the knowledge of some sublattice. For example, a programmer might know only about the Transmitter part of a Radio and write:

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void h2(Storable* ps)       // ps might or might not point to a Component
{
     if (Component* pc = dynamic_cast<Component*>(ps)) {
          // we have a component!
     }
     else {
          // it wasn't a Component
     }
}

The ambiguity for a pointer to a Radio object is not in general detectable at compile time.

This kind of run-time ambiguity detection is needed only for virtual bases. For ordinary bases, there is always a unique subobject of a given cast (or none) when downcasting (that is, toward a derived class; §22.2). The equivalent ambiguity for virtual bases occurs when upcasting (that is, toward a base), but such ambiguities are caught at compile time.

22.2.3. static_cast and dynamic_cast

A dynamic_cast can cast from a polymorphic virtual base class to a derived class or a sibling class (§22.2.1). A static_cast (§11.5.2) does not examine the object it casts from, so it cannot:

Click here to view code image

void g(Radio& r)
{
     Receiver* prec = &r;                     // Receiver is an ordinary base of Radio
     Radio* pr = static_cast<Radio*>(prec);   // OK, unchecked
     pr = dynamic_cast<Radio*>(prec);         // OK, run-time checked

     Storable* ps = &r;                       // Storable is a virtual base of Radio
     pr = static_cast<Radio*>(ps);            // error: cannot cast from virtual base
     pr = dynamic_cast<Radio* >(ps);          // OK, run-time checked
}

The dynamic_cast requires a polymorphic operand because there is no information stored in a non-polymorphic object that can be used to find the objects for which it represents a base. In particular, an object of a type with layout constraints determined by some other language – such as Fortran or C – may be used as a virtual base class. For objects of such types, only static type information will be available. However, the information needed to provide run-time type identification includes the information needed to implement the dynamic_cast.

Why would anyone want to use a static_cast for class hierarchy navigation? There is a run-time cost associated with the use of a dynamic_cast (§22.2.1). More significantly, there are millions of lines of code that were written before dynamic_cast became available. This code relies on alternative ways of making sure that a cast is valid, so the checking done by dynamic_cast is seen as redundant. However, such code is typically written using the C-style cast (§11.5.3); often obscure errors remain. Where possible, use the safer dynamic_cast.

The compiler cannot assume anything about the memory pointed to by a void*. This implies that dynamic_cast – which must look into an object to determine its type – cannot cast from a void*. For that, a static_cast is needed. For example:

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Radio* f1(void* p)
{
     Storable* ps = static_cast<Storable*>(p);     // trust the programmer
     return dynamic_cast<Radio*>(ps);
}

Both dynamic_cast and static_cast respect const and access controls. For example:

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class Users : private set<Person> { /* ... */ };

void f2(Users* pu, const Receiver* pcr)
{
     static_cast<set<Person>*>(pu);             // error: access violation
     dynamic_cast<set<Person>*>(pu);            // error: access violation
     static_cast<Receiver*>(pcr);               // error: can't cast away const
     dynamic_cast<Receiver*>(pcr);              // error: can't cast away const

     Receiver* pr = const_cast<Receiver*>(pcr); // OK
     // ...
}

It is not possible to cast to a private base class using static_cast or reinterpret_cast, and “casting away const” (or volatile) requires a const_cast (§11.5.2). Even then, using the result is safe only provided the object wasn’t originally declared const (or volatile) (§16.2.9).

22.2.4. Recovering an Interface

From a design perspective, dynamic_cast (§22.2.1) can be seen as a mechanism for asking an object if it provides a given interface.

As an example, consider a simple object I/O system. Users want to read objects from a stream, determine that they are of the expected types, and then use them. For example:

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void user()
{
     // ... open file assumed to hold shapes, and attach ss as an istream for that file ...

     unique_ptr<Io_obj> p {get_obj(ss)}; // read object from stream

     if (auto sp = dynamic_cast<Shape*>(p.get())) {
           sp–>draw();   // use the Shape
           // ...
     }
     else {
           // oops: non-shape in Shape file
     }
}

The function user() deals with shapes exclusively through the abstract class Shape and can therefore use every kind of shape. The use of dynamic_cast is essential because the object I/O system can deal with many other kinds of objects, and the user may accidentally have opened a file containing perfectly good objects of classes that the user has never heard of.

I used unique_ptr<Io_obj> (§5.2.1, §34.3.1) so that I would not forget to delete the object allocated by get_obj().

This object I/O system assumes that every object read or written is of a class derived from Io_obj. Class Io_obj must be a polymorphic type to allow the user of get_obj() to use dynamic_cast to recover the “true type” of a returned object. For example:

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class Io_obj {
public:
     virtual Io_obj* clone() const =0;   // polymorphic
     virtual ~Io_obj() {}
};

The critical function in the object I/O system is get_obj(), which reads data from an istream and creates class objects based on that data. Assume that the data representing an object on an input stream is prefixed by a string identifying the object’s class. The job of get_obj() is to read that string and call a function capable of reading and creating an object of the right class. For example:

using Pf = Io_obj*(istream&);      // pointer to function returning an Io_obj*

map<string,Pf> io_map;             // maps strings to creation functions

string get_word(istream& is);      // read a word from is; throw Read_error if the read failed

Io_obj* get_obj(istream& is)
{
     string str = get_word(is);    // read initial word
     if (auto f = io_map[str])     // look up str to get function
          return f(is);            // call function
     throw Unknown_class{};        // no match for str
}

The map called io_map holds pairs of name strings and functions that can construct objects of the class with that name.

We could derive class Shape from Io_obj as needed by user():

class Shape : public Io_obj {
     // ...
};

However, it would be more interesting (and in many cases more realistic) to use an already defined Shape (§3.2.4) unchanged:

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struct Io_circle : Circle, Io_obj {
     Io_circle(istream&);                                                 // initialize from input stream
     Io_circle* clone() const { return new Io_circle{*this}; }            // use copy constructor
     static Io_obj* new_circle(istream& is) { return new Io_circle{is}; } // for io_map
};

This is an example of how a class can be fitted into a hierarchy using an abstract class with less foresight than would have been required to build it as a node class in the first place (§21.2.2).

The Io_circle(istream&) constructor initializes an object with data from its istream argument. The new_circle() function is the one put into the io_map to make the class known to the object I/O system. For example:

io_map["Io_circle"]=&Io_circle::new_circle;   // somewhere

Other shapes are constructed in the same way:

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class Io_triangle : public Triangle, public Io_obj {
     // ...
};

io_map["Io_triangle"]=&Io_circle::new_triangle;     // somewhere

If the provision of the object I/O scaffolding becomes tedious, a template might help:

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template<class T>
struct Io : T, Io_obj {
public:
     Io(istream&);                                            // initialize from input stream
     Io* clone() const override { return new Io{*this}; }
     static Io* new_io(istream& is) { return new Io{is}; }    // for io_map
};

Given this, we can define Io_circle:

using Io_circle = Io<Circle>;

We still need to define Io<Circle>::Io(istream&) explicitly, though, because it needs to know about the details of Circle. Note that Io<Circle>::Io(istream&) does not have access to T’s private or protected data. The idea is that the transmission format for a type X is what is needed to construct an X using one of X’s constructors. The information of the stream is not necessarily the sequence of X’s member values.

The Io template is an example of a way to fit concrete types into a class hierarchy by providing a handle that is a node in that hierarchy. It derives from its template parameter to allow casting from Io_obj. For example:

void f(io<Shape>& ios)
{
     Shape* ps = &ios;
     // ...
}

Unfortunately, deriving from the template argument precludes using Io for a built-in type:

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using Io_date = Io<Date>;      // wrap concrete type
using Io_int = Io<int>;        // error: cannot derive from built-in type

This problem can be handled by making the user’s object a member of Io_obj:

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template<class T>
struct Io :Io_obj {
     T val;

     Io(istream&);                                             // initialize from input stream
     Io* clone() const override { return new Io{*this}; }
     static Io* new_io(istream& is) { return new Io{is}; }     // for io_map
};

Now we can handle

using Io_int = Io<int>;     // wrap built-in type

Having made the value a member rather than a base, we can no longer directly cast an Io_obj<X> to an X, so we provide a function to do that:

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template<typename T>
T* get_val<T>(Io_obj* p)
{
     if (auto pp = dynamic_cast<Io<T>*>(p))
          return &pp–>val;
     return nullptr;
}

The user() function now becomes:

Click here to view code image

void user()
{
     // ... open file assumed to hold shapes, and attach ss as an istream for that file ...

     unique_ptr<Io_obj> p {get_obj(ss)}; // read object from stream

     if (auto sp = get_val<Shape>(p.get())) {
          sp–>draw();     // use the Shape
          // ...
     }
     else {
          // ... oops: cope with non-shape in Shape file ...
     }
}

This simple object I/O system does not do everything anyone ever wanted, but it almost fits on a single page and the key mechanisms have many uses. It is a blueprint for the “receiver end” of a system for transmitting arbitrary objects across a communication channel in a type-safe manner. More generally, these techniques can be used to invoke a function based on a string supplied by a user and to manipulate objects of unknown type through interfaces discovered through run-time type identification.

In general, the sender part of such an object I/O system will also use RTTI. Consider:

class Face : public Shape {
public:
     Shape* outline;
     array<Shape*> eyes;
     Shape* mouth;

     // ...
};

To correctly write out the Shape pointed to by outline, we need to figure out which kind of Shape it is. That’s a job for typeid() (§22.5). In general, we must also keep a table of (pointer,unique identifier) pairs to be able to transmit linked data structures and to avoid duplicating objects pointed to by more than one pointer (or reference).

22.3. Double Dispatch and Visitors

Classical object-oriented programming is based on selecting a virtual function based on the dynamic type (the type of the most derived class) of an object given only a pointer or a reference to an interface (a base class). In particular, C++ can do this run-time lookup (also called a dynamic dispatch) for one type at a time. In this, C++ resembles Simula and Smalltalk and more recent languages, such as Java and C#. Not being able to select a function based on two dynamic types can be a serious limitation. Also, a virtual function must be a member function. This implies that we cannot add a virtual function to a class hierarchy without modifying the base class(es) that provides the interface and all derived classes that should be affected. This too can be a serious problem. This section describes the basic workarounds for these problems:

§22.3.1 Double Dispatch shows how to select a virtual function based on two types.

§22.3.2 Visitors shows how to use double dispatch to add multiple functions to a class hierarchy with only a single additional virtual function in the hierarchy.

Most realistic examples of these techniques occur when we deal with data structures, such as vectors or graphs or pointers to objects of polymorphic types. In such cases, the actual type of an object (e.g., a vector element or a graph node) can only be known dynamically by (implicitly or explicitly) inspecting the interface provided by a base class.

22.3.1. Double Dispatch

Consider how to select a function based on two arguments. For example:

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void do_someting(Shape& s1, Shape& s2)
{
     if (s1.intersect(s2)) {
           // the two shapes overlap
     }
     // ...
}

We would like this to work for any two classes in the class hierarchy rooted in Shape, such as Circle and Triangle.

The basic strategy is to do a virtual function call to select the right function for s1 and then do a second call to select the right function for s2. To simplify, I will leave out the calculation of whether the two shapes actually intersect and just write the code skeleton for selecting the right functions. First we define Shape with a function for intersection:

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class Circle;
class Triangle;

class Shape {
public:
     virtual bool intersect(const Shape&) const =0;
     virtual bool intersect(const Circle&) const =0;
     virtual bool intersect(const Triangle&) const =0;
};

Next we need to define Circle and Triangle to override those virtual functions:

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class Circle : public Shape {
public:
     bool intersect(const Shape&) const override;
     virtual bool intersect(const Circle&) const override;
     virtual bool intersect(const Triangle&) const override

};

class Triangle : public Shape {
public:
     bool intersect(const Shape&) const override;
     virtual bool intersect(const Circle&) const override;
     virtual bool intersect(const Triangle&) const override;
};

Now each class can handle all possible classes in the Shape hierarchy, so we just have to decide what should be done for each combination:

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bool Circle::intersect(const Shape& s) const { return s.intersect(*this); }
bool Circle::intersect(const Circle&) const { cout <<"intersect(circle,circle)\n"; return true; }
bool Circle::intersect(const Triangle&) const { cout <<"intersect(circle,triangle)\n"; return true; }

bool Triangle::intersect(const Shape& s) const { return s.intersect(*this); }
bool Triangle::intersect(const Circle&) const { cout <<"intersect(triangle,circle)\n"; return true; }
bool Triangle::intersect(const Triangle&) const { cout <<"intersect(triangle,triangle)\n"; return true; }

The interesting functions here are Circle::intersect(const Shape&) and Triangle::intersect(const Shape&). These need to handle a Shape& argument because that argument must refer to a derived class. The trick/technique is to simply do a virtual call with the arguments in the reverse order. That done, we are in one of the four functions that can actually do an intersection calculation.

We can test this by making a vector of all pairs of Shape* values and calling intersect() for those:

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void test(Triangle& t, Circle& c)
{
     vector<pair<Shape*,Shape*>> vs { {&t,&t}, {&t,&c}, {&c,&t}, {&c,&c} };
     for (auto p : vs)
           p.first–>intersect(*p.second);
}

Using Shape*s ensures that we rely on run-time resolution of the types. We get:

intersect(triangle,triangle)
intersect(triangle,circle)
intersect(circle,triangle)
intersect(circle,circle)

If you consider this elegant, you need to raise your standards, but it gets the task done. As the class hierarchy grows, the need for virtual functions grows exponentially. That is not acceptable in most cases. Expanding this to three or more arguments is trivial, but tedious. Worst of all, each new operation and each new derived class require a modification to every class in the hierarchy: this double-dispatch technique is highly intrusive. Ideally, I would have preferred a simple intercept(Shape&,Shape&) function with overriders specified for the desired combinations of particular shapes. That is possible [Pirkelbauer,2009], but not in C++11.

The awkwardness of double dispatch does not make the problem it is trying to address less important. It is not unusual to want an action, such as intersect(x,y), that depends on the types of two (or more) operands. Workarounds abound. For example, finding the intersection of rectangles is simple and efficient. So, for many applications, people have found it sufficient to define a “bounding box” for each shape and then calculate intersections on bounding boxes. For example:

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class Shape {
public:
     virtual Rectangle box() const = 0;      // the rectangle encloses the shape
     // ...
};

class Circle : public Shape {
public:
     Rectangle box() const override;
     // ...
};

class Triangle : public Shape {
public:
     Rectangle box() const override;
     // ...
};

bool intersect(const Rectangle&, const Rectangle&);    // simple to calculate

bool intersect(const Shape& s1, const Shape& s2)
{
     return intersect(s1.box(),s2.box());
}

Another technique is to precompute a lookup table for combinations of types [Stroustrup,1994]:

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bool intersect(const Shape& s1, const Shape& s2)
{
     auto i = index(type_id(s1),type_id(s2));
     return intersect_tbl[i](s1,s2);
}

Variations of this idea are widely used. Many variants use precomputed values stored in objects to speed up type identification (§27.4.2).

22.3.2. Visitors

The visitor pattern [Gamma,1994] is a partial solution to the exponential growth of virtual functions and overriders and the unpleasent intrusiveness of the (too) simple double-dispatch technique.

Consider how to apply two (or more) operations to every class in a class hierarchy. Basically, we will do a double dispatch for a hierarchy of nodes and a hierarchy of operations to select the correct operation for the correct node. The operations are called visitors; here they are defined in classes derived from class Visitor. The nodes are a hierarchy of classes with a virtual function accept() that takes Visitor&s. For this example, I use a hierarchy of Nodes that describe language constructs, as is common in tools based on abstract syntax trees (ASTs):

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class Visitor;

class Node {
public:
     virtual void accept(Visitor&) = 0;
};

class Expr : public Node {
public:
     void accept(Visitor&) override;
};

class Stmt : public Node {
public:
     void accept(Visitor&) override;
};

So far, so good: the Node hierarchy simply provides a virtual function accept() that takes a Visitor& argument representing what should be done to a Node of a given type.

I do not use const here, because in general an operation from a Visitor may update either the Node “visited” or the Visitor itself.

Now the Node’s accept() performs the double-dispatch trick and passes the Node itself to the Visitor’s accept():

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void Expr::accept(Visitor& v) { v.accept(*this); }
void Stmt::accept(Visitor& v) { v.accept(*this); }

The Visitor declares a set of operations:

class Visitor {
public:
     virtual void accept(Expr&) = 0;
     virtual void accept(Stmt&) = 0;
};

We can then define sets of operations by deriving from Visitor and overriding its accept() functions. For example:

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class Do1_visitor : public Visitor {
     void accept(Expr&) { cout << "do1 to Expr\n"; }
     void accept(Stmt&) { cout << "do1 to Stmt\n"; }
};

class Do2_visitor : public Visitor {
     void accept(Expr&) { cout << "do2 to Expr\n"; }
     void accept(Stmt&) { cout << "do2 to Stmt\n"; }
};

We can test by making a vector of pairs of pointers to ensure that run-time type resolution is used:

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void test(Expr& e, Stmt& s)
{
     vector<pair<Node*,Visitor*>> vn {&e,&do1}, {&s,&do1}, {&e,&do2}, {&s,&do2}};
     for (auto p : vn)
           p.first–>accept(*p.second);
}

We get:

do1 to Expr
do1 to Stmt
do2 to Expr
do2 to Stmt

As opposed to the simple double dispatch, the visitor pattern is heavily used in real-world programming. It is only mildly intrusive (the accept() function), and many variations on the basic idea are used. However, many operations on class hierarchies are hard to express as visitors. For example, an operation that needs access to multiple nodes of different types in a graph cannot be trivially implemented as a visitor. So, I consider the visitor pattern an inelegant workaround. Alternatives exist, for example, [Solodkyy,2012], but not in plain C++11.

Most alternatives to visitors in C++ are based on the idea of explicit iteration over a homogeneous data structure (e.g., a vector or a graph of nodes containing pointers to polymorphic types). At each element or node, a call of a virtual function can perform the desired operation, or some optimization based on stored data can be applied (e.g., see §27.4.2).

22.4. Construction and Destruction

A class object is more than simply a region of memory (§6.4). A class object is built from “raw memory” by its constructors, and it reverts to “raw memory” as its destructors are executed. Construction is bottom-up, destruction is top-down, and a class object is an object to the extent that it has been constructed or destroyed. This order is necessary to ensure that an object is not accessed before it has been initialized. It is unwise to try to access base and member objects early or out of order through “clever” pointer manipulation (§17.2.3). The order of construction and destruction is reflected in the rules for RTTI, exception handling (§13.3), and virtual functions (§20.3.2).

It is unwise to rely on details of the order of construction and destruction, but you can observe that order by calling virtual functions, dynamic_cast (§22.2), or typeid (§22.5) at a point where the object isn’t complete. At such a point in a constructor, the (dynamic) type of the object reflects only what is constructed so far. For example, if the constructor for Component in the hierarchy from §22.2.2 calls a virtual function, it will invoke a version defined for Storable or Component, but not one from Receiver, Transmitter, or Radio. At that point of construction, the object isn’t yet a Radio. Similarly, calling a virtual function from a destructor will reflect only what is still not destroyed. It is best to avoid calling virtual functions during construction and destruction.

22.5. Type Identification

The dynamic_cast operator serves most needs for information about the type of an object at run time. Importantly, it ensures that code written using it works correctly with classes derived from those explicitly mentioned by the programmer. Thus, dynamic_cast preserves flexibility and extensibility in a manner similar to virtual functions.

However, it is occasionally essential to know the exact type of an object. For example, we might like to know the name of the object’s class or its layout. The typeid operator serves this purpose by yielding an object representing the type of its operand. Had typeid() been a function, its declaration would have looked something like this:

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class type_info;
const type_info& typeid(expression);     // pseudo declaration

That is, typeid() returns a reference to a standard-library type called type_info defined in <typeinfo>:

• Given the name of a type as its operand, typeid(type_name) returns a reference to a type_info that represents the type_name; type_name must be a completely defined type (§8.2.2).

• Given an expression as its operand, typeid(expr) returns a reference to a type_info that represents the type of the object denoted by the expr; the expr must refer to a completely defined type (§8.2.2). If the value of expr is nullptr, typeid(expr) throws a std::bad_typeid.

A typeid() can find the type of an object referred to by a reference or a pointer:

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void f(Shape& r, Shape* p)
{
     typeid(r);      // type of the object referred to by r
     typeid(*p);     // type of the object pointed to by p
     typeid(p);      // type of the pointer, that is, Shape* (uncommon, except as a mistake)
}

If the operand of typeid() is a pointer or a reference of a polymorphic type with the value nullptr, typeid() throws a std::bad_typeid. If the operand of typeid() has a nonpolymorphic type or is not an lvalue, the result is determined at compile time without evaluating the operand expression.

If the object denoted by a dereferenced pointer or a reference to a polymorphic type, the type_info returned is that of the most derived class for the object, that is, the type used when the object was defined. For example:

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struct Poly {   // polymorphic base class
     virtual void f();
     // ...
};

struct Non_poly { /* ... */ }; // no virtual functions

struct D1
     : Poly{ /* ... */ };
struct D2
     : Non_poly { /* ... */ };
void f(Non_poly& npr, Poly& pr)
{
     cout << typeid(npr).name() << '\n';  // writes something like "Non_poly"
     cout << typeid(pr).name() << '\n';   // name of Poly or a class derived from Poly
}

void g()
{
     D1 d1;
     D2 d2;
     f(d2,d1);  // writes "Non_poly D1"
     f(*static_cast<Poly*>(nullptr),*static_cast<Null_poly*>(nullptr)); // oops!
}

That last call will print just Non_poly (because typeid(npr) is not evaluated) before throwing a bad_typeid.

The definition of type_info looks like this:

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class type_info {
     // data
public:
     virtual ~type_info();                                      // is polymorphic

     bool operator==(const type_info&) const noexcept;    // can be compared
     bool operator!=(const type_info&) const noexcept;

     bool before(const type_info&) const noexcept;        // ordering
     size_t hash_code() const noexcept;                   // for use by unordered_map and the like
     const char* name() const noexcept;                   // name of type

     type_info(const type_info&) = delete;                // prevent copying
     type_info& operator=(const type_info&) = delete;     // prevent copying
};

The before() function allows type_infos to be sorted. In particular, it allows type_ids to be used as keys for ordered containers (such as map). There is no relation between the relationships defined by before and inheritance relationships. The hash_code() function allows type_ids be used as keys for hash tables (such as unordered_map).

It is not guaranteed that there is only one type_info object for each type in the system. In fact, where dynamically linked libraries are used, it can be hard for an implementation to avoid duplicate type_info objects. Consequently, we should use == on type_info objects to test equality, rather than == on pointers to such objects.

We sometimes want to know the exact type of an object so as to perform some service on the whole object (and not just on one of its bases). Ideally, such services are presented as virtual functions so that the exact type needn’t be known. In some cases, no common interface can be assumed for every object manipulated, so the detour through the exact type becomes necessary (§22.5.1). Another, much simpler use has been to obtain the name of a class for diagnostic output:

#include<typeinfo>

void g(Component* p)
{
     cout << typeid(*p).name();
}

The character representation of a class’s name is implementation-defined. This C-style string resides in memory owned by the system, so the programmer should not attempt to delete[] it.

22.5.1. Extended Type Information

A type_info object contains only minimal information. Therefore, finding the exact type of an object is often just the first step to acquiring and using more detailed information about that type.

Consider how an implementation or a tool could make information about types available to users at run time. Suppose I have a tool that generates descriptions of object layouts for each class used. I can put these descriptors into a map to allow user code to find the layout information:

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#include <typeinfo>

map<string, Layout> layout_table;

void f(B* p)
{
     Layout& x = layout_table[typeid(*p).name()]; // find the Layout based on *p's name
     // ... use x ...
}

The resulting data structure looks like this:

Someone else might provide a completely different kind of information:

Click here to view code image

unordered_map<type_index,Icon> icon_table;     // §31.4.3.2

void g(B* p)
{
     Icon& i = icon_table[type_index{typeid(*p)}];
     // ... use i ...
}

The type_index is a standard-library type for comparing and hashing type_info objects (§35.5.4).

The resulting data structure looks like this:

Associating typeids with information without modifying system headers allows several people or tools to associate different information with types independently of each other. This is important because the likelihood that someone can come up with a single set of information that satisfies every user is close to zero.

22.6. Uses and Misuses of RTTI

We should use explicit run-time type information only when necessary. Static (compile-time) checking is safer, implies less overhead, and – where applicable – leads to better-structured programs. Interfaces based on virtual functions combine static type checking with a run-time lookup in a way that gives both type safety and flexibility. However, programmers sometimes overlook these alternatives and use RTTI where it is unsuitable. For example, RTTI can be used to write thinly disguised switch-statements:

Click here to view code image

// misuse of run-time type information:

void rotate(const Shape& r)
{
     if (typeid(r) == typeid(Circle)) {
           // do nothing
     }
     else if (typeid(r) == typeid(Triangle)) {
           // ... rotate triangle ...
     }
     else if (typeid(r) == typeid(Square)) {
           // ... rotate square ...
     }
     // ...
}

Using dynamic_cast rather than typeid would improve this code only marginally. Either way, this code is syntactically ugly and also inefficient in that it performs an expensive operation repeatedly.

Unfortunately, this is not a strawman example; such code really does get written. For many people trained in languages without equivalents to class hierachies and virtual functions, there is an almost irresistible urge to organize software as a set of switch-statements. This urge should usually be resisted. Use virtual functions (§3.2.3, §20.3.2) rather than RTTI to handle most cases when run-time discrimination based on type is needed.

Many examples of proper use of RTTI arise when some service code is expressed in terms of one class and a user wants to add functionality through derivation. The use of Ival_box in §22.2 is an example of this. If the user is willing and able to modify the definitions of the library classes, say BBwindow, then the use of RTTI can be avoided; otherwise, it is needed. Even if the user is willing to modify the base classes (e.g., to add a virtual function), such modification may cause its own problems. For example, it may be necessary to introduce dummy implementations of virtual functions in classes for which those functions are not needed or not meaningful. A use of RTTI to implement a simple object I/O system can be found in §22.2.4.

For people with a background in languages that rely heavily on dynamic type checking, such as Smalltalk, pre-generics Java, or Lisp, it is tempting to use RTTI in conjunction with overly general types. Consider:

Click here to view code image

// misuse of run-time type information:

class Object {  // polymorphic
     // ...
};

class Container : public Object {
public:
     void put(Object*);
     Object* get();
     // ...
};

class Ship : public Object { /* ... */ };

Ship* f(Ship* ps, Container* c)
{
     c–>put(ps);                               // put the Ship into the container
     // ...
     Object* p = c–>get();                     // retrieve an Object from the container
     if (Ship* q = dynamic_cast<Ship*>(p)) {   // run-time check that the Object is a Ship
           return q;
     }
     else {
            // ... do something else (typically, error handling) ...
     }
}

Here, class Object is an unnecessary implementation artifact. It is overly general because it does not correspond to an abstraction in the application domain and forces the application programmer to use an implementation-level abstraction (Object). Problems of this kind are often better solved by using container templates that hold only a single kind of pointer:

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Ship* f(Ship* ps, vector<Ship*>& c)
{
     c.push_back(ps);          // put the Ship into the container
     // ...
     return c.pop_back();      // retrieve a Ship from the container
}

This style of code is less error-prone (better statically type checked) and less verbose than a pure-Object-based alternative. Combined with the use of virtual functions, this technique handles most cases. In a template, a template argument T takes the place of Object and enables static type checking (§27.2).

22.7. Advice

[1] Use virtual functions to ensure that the same operation is performed independently of which interface is used for an object; §22.1.

[2] Use dynamic_cast where class hierarchy navigation is unavoidable; §22.2.

[3] Use dynamic_cast for type-safe explicit navigation of a class hierarchy; §22.2.1.

[4] Use dynamic_cast to a reference type when failure to find the required class is considered a failure; §22.2.1.1.

[5] Use dynamic_cast to a pointer type when failure to find the required class is considered a valid alternative; §22.2.1.1.

[6] Use double dispatch or the visitor pattern to express operations on two dynamic types (unless you need an optimized lookup); §22.3.1.

[7] Don’t call virtual functions during construction or destruction; §22.4.

[8] Use typeid to implement extended type information; §22.5.1.

[9] Use typeid to find the type of an object (and not to find an interface to an object); §22.5.

[10] Prefer virtual functions to repeated switch-statements based on typeid or dynamic_cast; §22.6.

23. Templates

Your quote here.

– B. Stroustrup

• Introduction and Overview

• A Simple String Template

Defining a Template; Template Instantiation

• Type Checking

Type Equivalence; Error Detection

• Class Template Members

Data Members; Member Functions; Member Type Aliases; static Members; Member Types; Member Templates; Friends

• Function Templates

Function Template Arguments; Function Template Argument Deduction; Function Template Overloading

• Template Aliases

• Source Code Organization

Linkage

• Advice

23.1. Introduction and Overview

Templates provide direct support for generic programming (§3.4) in the form of programming using types as parameters. The C++ template mechanism allows a type or a value to be a parameter in the definition of a class, a function, or a type alias. Templates provide a straightforward way to represent a wide range of general concepts and simple ways to combine them. The resulting classes and functions can match handwritten, less general code in run-time and space efficiency.

A template depends only on the properties that it actually uses from its parameter types and does not require types used as arguments to be explicitly related. In particular, the argument types used for a template need not be part of an inheritance hierarchy. Built-in types are acceptable and very common as template arguments.

The composition offered by templates is type-safe (no object can be implicitly used in a way that disagrees with its definition), but unfortunately, a template’s requirements on its arguments cannot be simply and directly stated in code (§24.3).

Every major standard-library abstraction is represented as a template (for example, string, ostream, regex, complex, list, map, unique_ptr, thread, future, tuple, and function), and so are the key operations (for example, string comparisons, the output operator <<, complex arithmetic operations, list insertions and deletions, and sort()). This makes the library chapters (Part IV) of this book a rich source of examples of templates and programming techniques relying on them.

Here, templates are introduced with the primary focus on techniques needed for the design, implementation, and use of the standard library. The standard library requires a greater degree of generality, flexibility, and efficiency than does most software. Consequently, techniques that can be used in the design and implementation of the standard library are effective and efficient in the design of solutions to a wide variety of problems. These techniques enable an implementer to hide sophisticated implementations behind simple interfaces and to expose complexity to the user when the user has a specific need for it.

Templates and the fundamental techniques for using them are the focus of this and the following six chapters. This chapter focuses on the most basic template facilities and fundamental programming techniques for using them:

§23.2   A Simple String Template: The basic mechanisms for defining and using class templates are introduced through the example of a string template.

§23.3   Type Checking: The basic rules of type equivalence and type checking as they apply to templates.

§23.4   Class Template Members: How members of a class template are defined and used.

§23.5   Function Templates: How to define and use function templates. How overloading is resolved for function templates and ordinary functions.

§23.6   Template Aliases: Template aliases provide a powerful mechanism for hiding implementation details and cleaning up the notation used for templates.

§23.7   Source Code Organization: How to organize templates into source files.

Chapter 24, Generic Programming, presents the basic technique of generic programming, and the fundamental idea of concepts (requirements on template arguments) is explored:

§24.2   Algorithms and Lifting: An example of the basic technique for developing a generic algorithm from concrete examples.

§24.3   Concepts: Introduces and discusses the fundamental notion of a concept, that is, a set of requirements that a template can impose on its template arguments.

§24.4   Making Concepts Concrete: Presents techniques for using concepts expressed as compile-time predicates.

Chapter 25, Specialization, discusses template argument passing and the notion of specialization:

§25.2   Template Parameters and Arguments: What can be a template argument: types, values, and templates. How to specify and use default template arguments.

§25.3   Specialization: Special versions, called specializations, of a template for a specific set of template arguments can be generated from the templates by the compiler or be provided by the programmer.

Chapter 26, Instantiation, presents issues related to generation of template specialization (instances) and name binding:

§26.2   Template Instantiation: The rules for when and how a compiler generates specializations from a template definition and how to specify them manually.

§26.3   Name Binding: The rules for determining to which entity a name used in a template definition refers.

Chapter 27, Templates and Hierarchies, discusses the relation between the generic programming techniques supported by templates and the object-oriented techniques supported by class hierarchies. The emphasis is on how to use them in combination:

§27.2   Parameterization and Hierarchy: Templates and class hierarchies are two ways of representing sets of related abstractions. How do we choose between them?

§27.3   Hierarchies of Class Templates: Why it is usually a bad idea simply to add template parameters to an existing class hierarchy?

§27.4   Template Parameters as Base Classes: Presents techniques for composing interfaces and data structures for type safety and performance.

Chapter 28, Metaprogramming, concentrates on the use of templates as a means of generating functions and classes:

§28.2   Type Functions: Functions that take types as arguments or return types as results.

§28.3   Compile-time Control Structures: How to express selection and recursion for type functions, and some rules of thumb for their use.

§28.4   Conditional Definition: enable_if: How to conditionally define functions and overload templates using (almost) arbitrary predicates.

§28.5   A Compile-time List: Tuple: How to build and access lists with elements of (almost) arbitrary types.

§28.6   Variadic templates: How (in a statically type-safe manner) to define templates that take arbitrary numbers of template arguments of arbitrary types.

§28.7   SI Units Example: This example uses simple metaprogramming techniques in combination with other programming techniques to provide a library for computations that are (at compile time) checked for correct use of the meters, kilograms, and seconds system of units.

Chapter 29, A Matrix Design, demonstrates how various template features can be used in combination to address a challenging design task:

§29.2   A Matrix Template: How to define an N-dimensional matrix with flexible and type-safe initialization, subscription, and submatrices.

§29.3   Matrix Arithmetic Operations: How to provide simple arithmetic operations on an N-dimensional matrix.

§29.4   Matrix Implementation: Some useful implementation techniques.

§29.5   Solving Linear Equations: An example of simple matrix use.

Templates were introduced early (§3.4.1, §3.4.2) and used throughout this book, so I assume that you have some familiarity with them.

23.2. A Simple String Template

Consider a string of characters. A string is a class that holds characters and provides operations such as subscripting, concatenation, and comparison that we usually associate with the notion of a “string.” We would like to provide that behavior for many different kinds of characters. For example, strings of signed characters, of unsigned characters, of Chinese characters, of Greek characters, etc., are useful in various contexts. Thus, we want to represent the notion of “string” with minimal dependence on a specific kind of character. The definition of a string relies on the fact that a character can be copied, and little else (§24.3). Thus, we can make a more general string type by taking the string of char from §19.3 and making the character type a parameter:

Click here to view code image

template<typename C>
class String {
public:
     String();
     explicit String(const C*);
     String(const String&);
     String operator=(const String&);
     // ...
     C& operator[](int n) { return ptr[n]; }      // unchecked element access
     String& operator+=(C c);                     // add c at end
     // ...
private:
     static const int short_max = 15;             // for the short string optimization
     int sz;
     C* ptr;     // ptr points to sz Cs
};

The template<typename C> prefix specifies that a template is being declared and that a type argument C will be used in the declaration. After its introduction, C is used exactly like other type names. The scope of C extends to the end of the declaration prefixed by template<typename C>. You may prefer the shorter and equivalent form template<class C>. In either case, C is a type name; it need not be the name of a class. Mathematicians will recognize template<typename C> as a variant of the traditional “for all C” or more specifically “for all types C” or even “for all C, such that C is a type.” If you think along those lines, you will note that C++ lacks a fully general mechanism for specifying the required properties of a template parameter C. That is, we can’t say “for all C, such that ...” where the “...” is a set of requirements for C. In other words, C++ does not offer a direct way to say what kind of type a template argument C is supposed to be (§24.3).

The name of a class template followed by a type bracketed by < > is the name of a class (as defined by the template) and can be used exactly like other class names. For example:

Click here to view code image

String<char> cs;
String<unsigned char> us;
String<wchar_t> ws;

struct Jchar { /* ... */ };   // Japanese character

String<Jchar> js;

Except for the special syntax of its name, String<char> works exactly as if it had been defined using the definition of class String in §19.3. Making String a template allows us to provide the facilities we had for String of char for Strings of any kind of character. For example, if we use the standard-library map and the String template, the word-counting example from §19.2.1 becomes:

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int main() // count the occurrences of each word on input
{
     map<String<char>,int> m;
     for (String<char> buf; cin>>buf;)
           ++m[buf];
     // ... write out result ...
}

The version for our Japanese-character type Jchar would be:

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int main() // count the occurrences of each word on input
{
     map<String<Jchar>,int> m;
     for (String<Jchar> buf; cin>>buf;)
           ++m[buf];
     // ... write out result ...
}

The standard library provides the template class basic_string that is similar to the templatized String (§19.3, §36.3). In the standard library, string is a synonym for basic_string<char> (§36.3):

using string = std::basic_string<char>;

This allows us to write the word-counting program like this:

Click here to view code image

int main() // count the occurrences of each word on input
{
     map<string,int> m;
     for (string buf; cin>>buf;)
           ++m[buf];
     // ... write out result ...
}

In general, type aliases (§6.5) are useful for shortening the long names of classes generated from templates. Also, we often prefer not to know the details of how a type is defined, and an alias allows us to hide the fact that a type is generated from a template.

23.2.1. Defining a Template

A class generated from a class template is a perfectly ordinary class. Thus, use of a template does not imply any run-time mechanisms beyond what is used for an equivalent “handwritten” class. In fact, using a template can lead to a decrease of code generated because code for a member function of a class template is only generated if that member is used (§26.2.1).

In addition to class templates, C++ offers function templates (§3.4.2, §23.5). I will introduce most of the “mechanics” of templates in the context of class templates and postpone detailed discussion of function templates to §23.5. A template is a specification of how to generate something given suitable template arguments; the language mechanisms for doing that generation (instantiation (§26.2) and specialization (§25.3)) don’t care much whether a class or a function is generated. So, unless otherwise stated, the rules for templates apply equally to class templates and function templates. Templates can also be defined as aliases (§23.6), but other plausible constructs, such as namespace templates, are not provided.

There are people who make semantic distinctions between the terms class template and template class. I don’t; that would be too subtle: please consider those terms interchangeable. Similarly, I consider function template interchangeable with template function.

When designing a class template, it is usually a good idea to debug a particular class, such as String, before turning it into a template such as String<C>. By doing so, we handle many design problems and most of the code errors in the context of a concrete example. This kind of debugging is familiar to all programmers, and most people cope better with a concrete example than with an abstract concept. Later, we can deal with any problems that might arise from generalization without being distracted by more conventional errors. Similarly, when trying to understand a template, it is often useful to imagine its behavior for a particular type argument such as char before trying to comprehend the template in its full generality. This also fits with the philosophy that a generic component should be developed as a generalization of one or more concrete examples, rather than simply being designed from first principles (§24.2).

Members of a class template are declared and defined exactly as they would have been for a non-template class. A template member need not be defined within the template class itself. In that case, its definition must be provided somewhere else, just as for non-template class members (§16.2.1). Members of a template class are themselves templates parameterized by the parameters of their template class. When such a member is defined outside its class, it must explicitly be declared a template. For example:

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template<typename C>
String<C>::String() // String<C>'s constructor
     :sz{0}, ptr{ch}
{
     ch[0] = {}; // terminating 0 of the appropriate character type
}

template<typename C>
String& String<C>::operator+=(C c)
{
     // ... add c to the end of this string ...
     return *this;
}

A template parameter, such as C, is a parameter rather than the name of a specific type. However, that doesn’t affect the way we write the template code using the name. Within the scope of String<C>, qualification with <C> is redundant for the name of the template itself, so String<C>::String is the name for the constructor.

Just as there can be only one function defining a class member function in a program, there can be only one function template defining a class template member function in a program. However, specialization (§25.3) enables us to provide alternative implementations for a template given specific template arguments. For functions, we can also use overloading to provide different definitions for different argument types (§23.5.3).

It is not possible to overload a class template name, so if a class template is declared in a scope, no other entity can be declared there with the same name. For example:

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template<typename T>
class String { /* ... */ };

class String { /* ... */ };    // error: double definition

A type used as a template argument must provide the interface expected by the template. For example, a type used as an argument to String must provide the usual copy operations (§17.5, §36.2.2). Note that there is no requirement that different arguments for the same template parameter should be related by inheritance. See also §25.2.1 (template type parameters), §23.5.2 (template parameter deduction), and §24.3 (requirements on template arguments).

23.2.2. Template Instantiation

The process of generating a class or a function from a template plus a template argument list is often called template instantiation (§26.2). A version of a template for a specific template argument list is called a specialization.

In general, it is the implementation’s job – not the programmer’s – to ensure that specializations of a template are generated for each template argument list used. For example:

Click here to view code image

String<char> cs;

void f()
{
     String<Jchar> js;

     cs = "It's the implementation's job to figure out what code needs to be generated";
}

For this, the implementation generates declarations for classes String<char> and String<Jchar>, for their destructors and default constructors, and for String<char>::operator=(char*). Other member functions are not used and will not be generated. Generated classes are perfectly ordinary classes that obey all the usual rules for classes. Similarly, generated functions are ordinary functions that obey all the usual rules for functions.

Obviously, templates provide a powerful way of generating lots of code from relatively short definitions. Consequently, a certain amount of caution is in order to avoid flooding memory with almost identical function definitions (§25.3). On the other hand, templates can be written to enable otherwise unachievable quality of generated code. In particular, composition using templates combined with simple inlining can be used to eliminate many direct and indirect function calls. For example, that is how simple operations on critical data structures (such as < in a sort() and + for scalars in a matrix computation) are reduced to single machine instructions in heavily parameterized libraries. Thus, incautious use of templates leading to the generation of very similar large functions can cause code bloat, whereas use of templates to enable inlining of tiny functions can lead to significant code shrinkage (and speedup) compared to alternatives. In particular, the code generated for a simple < or [] is often a single machine instruction, which is both much faster than any function call and smaller than the code needed to invoke a function and receive its result.

23.3. Type Checking

Template instantiation takes a template plus a set of template arguments and generates code from them. Because so much information is available at instantiation time, weaving together the information from the template definition and the template argument types provides wonderful degrees of flexibility and can yield unparalleled run-time performance. Unfortunately, this flexibility also implies complexity of type checking and difficulties for accurate reporting of type errors.

Type checking is done on the code generated by template instantiation (exactly as if the programmer had expanded the templates by hand). This generated code may contain much that the user of a template has never heard of (such as names of details of a template implementation) and often happens uncomfortably late in the build process. This mismatch between what the programmer sees/writes and what the compiler type checks can be a major problem, and we need to design our programs to minimize its consequences.

The fundamental weakness of the template mechanism is that it is not possible to directly express requirements on a template argument. For example, we cannot say:

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template<Container Cont, typename Elem>
    requires Equal_comparable<Cont::value_type,Elem>()   // requirements for types Cont and Elem
int find_index(Cont& c, Elem e);                         // find the index of e in c

That is, we have no way in C++ itself to directly say that Cont should be a type that can act as a container and that the type Elem should be a type that allows us to compare a value to an element of Cont. Work is being done to make this possible in future versions of C++ (without loss of flexibility, without loss of run-time performance, and without significant increases in compile time [Sutton,2011]), but for now we will have to do without.

The first step in dealing effectively with problems related to template argument passing is to establish a framework and vocabulary for discussing requirements. Think of a set of requirements on template arguments as a predicate. For example, we can think of “C must be a container” as a predicate that takes a type, C, as an argument and returns true if C is a container (however we may have defined “container”) and false if it is not. For example, Container<vector<int>>() and Container<list<string>>() should be true whereas Container<int>() and Container<shared_ptr<string>>() should be false. We call such a predicate a concept. A concept is not (yet) a language construct in C++; it is a notion that we can use to reason about requirements on template arguments, use in comments, and sometimes support with our own code (§24.3).

For starters, think of a concept as a design tool: specify Container<T>() as a set of comments saying what properties a type T must have for Container<T>() to be true. For example:

• T must have a subscript operator ([]).

• T must have a size() member function.

• T must have a member type value_type which is the type of its elements.

Note that this list is incomplete (e.g., what does [] take as an argument and what does it return?) and fails to address most semantic issues (e.g., what does [] actually do?). However, even a partial set of requirements can be useful; even something very simple allows us to hand-check our uses and catch obvious errors. For example, Container<int>() is obviously false because int does not have a subscript operator. I will return to the design of concepts (§24.3), consider techniques for supporting concepts in code (§24.4), and give an example of a set of useful concepts (§24.3.2). For now, just note that C++ does not directly support concepts, but that does not mean that concepts don’t exist: for every working template, the designer had some concepts in mind for its arguments. Dennis Ritchie famously said, “C is a strongly typed, weakly checked language.” You could say the same about C++’s templates, except that the checking of template argument requirements (concepts) is actually done, but it is done too late in the compilation process and at an unhelpfully low level of abstraction.

23.3.1. Type Equivalence

Given a template, we can generate types by supplying template arguments. For example:

Click here to view code image

String<char> s1;
String<unsigned char> s2;
String<int> s3;

using Uchar = unsigned char;
using uchar = unsigned char;

String<Uchar> s4;
String<uchar> s5;
String<char> s6;

template<typename T, int N>         // §25.2.2
    class Buffer;
Buffer<String<char>,10> b1;
Buffer<char,10> b2;
Buffer<char,20–10> b3;

When using the same set of template arguments for a template, we always refer to the same generated type. However, what does “the same” mean in this context? Aliases do not introduce new types, so String<Uchar> and String<uchar> are the same type as String<unsigned char>. Conversely, because char and unsigned char are different types (§6.2.3), String<char> and String<unsigned char> are different types.

The compiler can evaluate constant expressions (§10.4), so Buffer<char,20–10> is recognized to be the same type as Buffer<char,10>.

Types generated from a single template by different template arguments are different types. In particular, generated types from related arguments are not automatically related. For example, assume that a Circle is a kind of Shape:

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Shape* p {new Circle(p,100)};              // Circle* converts to Shape*
vector<Shape>* q {new vector<Circle>{}};   // error: no vector<Circle>* to vector<Shape>* conversion
vector<Shape> vs {vector<Circle>{}};       // error: no vector<Circle> to vector<Shape> conversion
vector<Shape*> vs {vector<Circle*>{}};     // error: no vector<Circle*> to vector<Shape*> conversion

Had such conversions been allowed, type errors would have resulted (§27.2.1). If conversions between generated classes are needed, the programmer can define them (§27.2.2).

23.3.2. Error Detection

A template is defined and then later used in combination with a set of template arguments. When the template is defined, the definition is checked for syntax errors and possibly also for other errors that can be detected in isolation from a particular set of template arguments. For example:

Click here to view code image

template<typename T>
struct Link {
     Link* pre;
     Link* suc                // syntax error: missing semicolon
     T val;
};

template<typename T>
class List {
     Link<T>* head;
public:
     List() :head{7} { }                                 // error: pointer initialized with int
     List(const T& t) : head{new Link<T>{0,o,t}} { }     // error: undefined identifier o
     // ...
     void print_all() const;
};

A compiler can catch simple semantic errors at the point of definition or later at the point of use. Users generally prefer early detection, but not all “simple” errors are easy to detect. Here, I made three “mistakes”:

• A simple syntax error: Leaving out a semicolon at the end of a declaration.

• A simple type error: Independently of what the template parameter is, a pointer cannot be initialized by the integer 7.

• A name lookup error: The identifier o (a mistyped 0, of course) cannot be an argument to Link<T>’s constructor because there is no such name in scope.

A name used in a template definition must either be in scope or in some reasonably obvious way depend on a template parameter (§26.3). The most common and obvious ways of depending on a template parameter T are to explicitly use the name T, to use a member of a T, and to take an argument of type T. For example:

Click here to view code image

template<typename T>
void List<T>::print_all() const
{
     for (Link<T>* p = head; p; p=p–>suc)    // p depends on T
           cout << *p;                       // << depends on T
}

Errors that relate to the use of template parameters cannot be detected until the template is used. For example:

Click here to view code image

class Rec {
     string name;
     string address;
};

void f(const List<int>& li, const List<Rec>& lr)
{
     li.print_all();
     lr.print_all();
}

The li.print_all() checks out fine, but lr.print_all() gives a type error because there is no << output operator defined for Rec. The earliest that errors relating to a template parameter can be detected is at the first point of use of the template for a particular template argument. That point is called the first point of instantiation (§26.3.3). The implementation is allowed to postpone essentially all checking until the program is linked, and for some errors link time is also the earliest point when complete checking is possible. Independently of when checking is done, the same set of rules is checked. Naturally, users prefer early checking.

23.4. Class Template Members

Exactly like a class, a template class can have members of several kinds:

• Data members (variable and constant); §23.4.1

• Member functions; §23.4.2

• Member type aliases; §23.6

• static members (function and data); §23.4.4

• Member types (e.g., a member class); §23.4.5

• Member templates (e.g., a member class template); §23.4.6.3

In addition, a class template can declare friends, just as an “ordinary class” can; §23.4.7.

The rules for class template members are those for their generated classes. That is, if you want to know what the rules of a template member are, just look for the rules for a member of an ordinary class (Chapter 16, Chapter 17, and Chapter 20); that will answer most questions.

23.4.1. Data Members

As for an “ordinary class,” a class template can have data members of any type. A non-static data member can be initialized in its definition (§17.4.4) or in a constructor (§16.2.5). For example:

template<typename T>
struct X {
     int m1 = 7;
     T m2;
     X(const T& x) :m2{x} { }
};

X<int> xi {9};
X<string> xs {"Rapperswil"};

Non-static data members can be const, but unfortunately not constexpr.

23.4.2. Member Functions

As for an “ordinary class,” a non-static member function of a class template can be defined in-class or outside the class. For example:

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template<typename T>
struct X {
     void mf1() { /* ... */ }           // defined in-class
     void mf2();
};

template<typename T>
void X<T>::mf2() { /* ... */ }          // defined out of class

Similarly, a member function of a template can be virtual or not. However, a virtual member function cannot also be a member function template (§23.4.6.2).

23.4.3. Member Type Aliases

Member type aliases, whether introduced using using or typedef (§6.5), play a major role in the design of class templates. They define related types of a class in a way that is easy to access from outside the class. For example, we specify a container’s iterator and element types as aliases:

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template<typename T>
class Vector {
public:
     using value_type = T;
     using iterator = Vector_iter<T>;    // Vector_iter is defined elsewhere
     // ...
};

The template argument name, T, is only accessible to the template itself, so for other code to refer to the element type, we must provide an alias.

Type aliases play a major role in generic programming by allowing the designer of classes to provide common names for types in different classes (and class templates) with common semantics. Type names as member aliases are often referred to as associated types. The value_type and iterator names are borrowed from the standard library’s container design (§33.1.3). If a class is missing a desired member alias, a trait can be used to compensate (§28.2.4).

23.4.4. static Members

A static data or function member that is not defined in-class must have a unique definition in a program. For example:

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template<typename T>
struct X {
     static constexpr Point p {100,250}; // Point must be a literal type (§10.4.3)
     static const int m1 = 7;
     static int m2 = 8;                  // error: not const
     static int m3;
     static void f1() { /* ... */ }
     static void f2();
};

template<typename T> int X<T>::m1 = 88;          // error: two initializers
template<typename T> int X<T>::m3 = 99;

template<typename T> void X::<T>::f2() { /* ... */ }

As for non-template classes, a const or conexpr static data member of literal type can be initialized in-class and need not be defined outside the class (§17.4.5, §iso.9.2).

A static member need only be defined if it is used (§iso.3.2, §iso.9.4.2, §16.2.12). For example:

template<typename T>
struct X {
     static int a;
     static int b;
};

int* p = &X<int>::a;

If this is all the mention of X<int> in a program, we will get a “not defined” error for X<int>::a, but not for X<int>::b.

23.4.5. Member Types

As for an “ordinary class,” we can define types as members. As usual, such a type can be a class or an enumeration. For example:

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template<typename T>
struct X {
     enum E1 { a, b };
     enum E2;                 // error: underlying type not known
     enum class E3;
     enum E4 : char;

     struct C1 { /* ... */ };
     struct C2;
};

template<typename T>
enum class X<T>::E3 { a, b };           // needed

template<typename T>
enum class X<T>::E4 : char { x, y };    // needed

template<typename T>
struct X<T>::C2 { /* ... */ };          // needed

The out-of-class definition of a member enumeration is only allowed for an enumeration for which we know the underlying type (§8.4).

As usual, the enumerators of a non-class enum are placed in the scope of the enumeration; that is, for a member enumeration, the enumerators are in the scope of its class.

23.4.6. Member Templates

A class or a class template can have members that are themselves templates. This allows us to represent related types with a pleasing degree of control and flexibility. For example, complex numbers are best represented as pairs of values of some scalar type:

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template<typename Scalar>
class complex {
     Scalar re, im;
public:
     complex() :re{}, im{} {}                    // default constructor
     template<typename T>
     complex(T rr, T ii =0) :re{rr}, im{ii} { }

     complex(const complex&) = default;          // copy constructor
     template<typename T>
           complex(const complex<T>& c) : re{c.real()}, im{c.imag()} { }
     // ...
};

This allows mathematically meaningful conversions among complex types, while prohibiting the undesirable narrowing conversions (§10.5.2.6):

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complex<float> cf;                    // default value
complex<double> cd {cf};              // OK: uses float to double conversion
complex<float> cf2 {cd};              // error: no implicit double->float conversion

complex<float> cf3 {2.0,3.0};         // error: no implicit double->float conversion
complex<double> cd2 {2.0F,3.0F};      // OK: uses float to double conversion

class Quad {
     // no conversion to int
};

complex<Quad> cq;
complex<int> ci {cq};               // error: no Quad to int conversion

Given this definition of complex, we can construct a complex<T1> from a complex<T2> or from a pair of T2 values if and only if we can construct a T1 from a T2. That seems reasonable.

Be warned that the narrowing error in the complex<double> to complex<float> case will not be caught until the instantiation of complex<float>’s template constructors and then only because I used the {} initialization syntax (§6.3.5) in the constructor’s member initializers. That syntax does not allow narrowing.

Using the (old) () syntax would leave us open to narrowing errors. For example:

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template<typename Scalar>
class complex {                // old style
     Scalar re, im;
public:
     complex() :re(0), im(0) { }
     template<typename T>
     complex(T rr, T ii =0) :re(rr), im(ii) { }

     complex(const complex&) = default;             // copyconstructor
     template<typename T>
         complex(const complex<T>& c) : re(c.real()), im(c.imag()) { }
     // ...
};

complex<float> cf4 {2.1,2.9};  // ouch! narrows
complex<float> cf5 {cd};       // ouch! narrows

I consider this yet another reason to be consistent in the use of the {} notation for initialization.

23.4.6.1. Templates and Constructors

To minimize the chances of confusion, I explicitly added a default copy constructor. Leaving it out would not change the meaning of the definition: complex would still get a default copy constructor. For technical reasons, a template constructor is never used to generate a copy constructor, so without the explicitly declared copy constructor, a default copy constructor would have been generated. Similarly, copy assignments, move constructors, and move assignments (§17.5.1, §17.6, §19.3.1) must be defined as non-template operators or the default versions will be generated.

23.4.6.2. Templates and virtual

A member template cannot be virtual. For example:

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class Shape {
     // ...
     template<typename T>
         virtual bool intersect(const T&) const =0;    // error: virtual template
};

This must be illegal. If it were allowed, the traditional virtual function table technique for implementing virtual functions (§3.2.3) could not be used. The linker would have to add a new entry to the virtual table for class Shape each time someone called intersect() with a new argument type. Complicating the implementation of the linker in this way was considered unacceptable. In particular, handling dynamic linking would require implementation techniques rather different from what is most commonly used.

23.4.6.3. Use of Nesting

In general, it is a good idea to keep information as local as possible. That way, a name is easier to find and less likely to interfere with anything else in a program. This line of thinking leads to types being defined as members. Doing so is often a good idea. However, for members of class templates we must consider if the parameterization is appropriate for a member type. Formally, a member of a template depends on all of a template’s arguments. That can have unfortunate side effects in cases where the behavior of the member does not in fact use every template argument. A famous example is a link type of a linked list. Consider:

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template<typename T, typename Allocator>
class List {
private:
     struct Link {
          T val;
          Link* succ;
          Link* prev;
     };
     // ...
};

Here, Link is an implementation detail of List. Thus, it seems a perfect example of a type best defined in the scope of List and even kept private. This has been a popular design and generally works very well. But surprisingly, it can imply performance cost compared to using a nonlocal Link type. Assume that no member of Link depends on the Allocator parameter, and that we need List<double,My_allocator> and List<double,Your_allocator>. Now List<double,My_allocator>::Link and List<double,Your_allocator>::Link are different types, so code using them cannot (without clever optimizers) be identical. That is, making Link a member when it uses only one of List’s two template parameters implies some code bloat. This leads us to consider a design where Link isn’t a member:

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template<typename T, typename Allocator>
class List;

template<typename T>
class Link {
     template<typename U, typename A>
         friend class List;
     T val;
     Link* succ;
     Link* prev;
};

template<typename T, typename Allocator>
class List {
     // ...
};

I made all members of Link private and granted List access. Except for making the name Link nonlocal, this preserves the design intent that Link is an implementation detail of List.

But what if a nested class is not considered an implementation detail? That is, what if we need an associated type that is meant for a variety of users? Consider:

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template<typename T, typename A>
class List {
public:
     class Iterator {
          Link<T>* current_position;
     public:
          // ... usual iterator operations ...
     };

     Iterator<T,A> begin();
     Iterator<T,A> end();
     // ...
};

Here, the member type List<T,A>::Iterator (obviously) does not use the second template argument A. However, because Iterator is a member and therefore formally depends on A (the compiler doesn’t know anything to the contrary), we can’t write a function to process Lists independently of how they were constructed using allocators:

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void fct(List<int>::Iterator b, List<int>::Iterator e) // error: List takes two arguments
{
     auto p = find(b,e,17);
     // ...
}

void user(List<int,My_allocator>& lm, List<int,Your_allocator>& ly)
{
     fct(lm.begin(),lm.end());
     fct(ly.begin(),ly.end());
}

Instead, we need to write a function template with a dependence on the allocator argument:

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void fct(List<int,My_allocator>::Iterator b, List<int,My_allocator>::Iterator e)
{

     auto p = find(b,e,17);
     // ...
}

However, that breaks our user():

void user(List<int,My_allocator>& lm, List<int,Your_allocator>& ly)
{
     fct(lm.begin(),lm.end());
     fct(ly.begin(),ly.end());     // error: fct takes List<int,My_allocator>::Iterators
}

We could make fct a template and generate separate specializations for each allocator. However, that would generate a new specialization for every use of Iterator, so this could lead to significant code bloat [Tsafrir,2009]. Again, we solve the problem by moving Link out of the class template:

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template<typename T>
struct Iterator {
     Link<T>* current_position;
};

template<typename T, typename A>
class List {
public:
     Iterator<T> begin();
     Iterator<T> end();
     // ...
};

This makes iterators for every List with the same first template argument interchangeable as far as their types are concerned. In this case, that was exactly what we wanted. Our user() now works as defined. Had fct() been defined to be a function template, there would have been only one copy (instantiation) of the definition of fct(). My rule of thumb is “Avoid nested types in templates unless they genuinely rely on every template parameter.” This is a special case of the general rule to avoid unnecessary dependencies in code.

23.4.7. Friends

As shown in §23.4.6.3, a template class can designate functions as friends. Consider the Matrix and Vector example from §19.4. Typically, both Matrix and Vector will be templates:

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template<typename T> class Matrix;

template<typename T>
class Vector {
     T v[4];
public:
     friend Vector operator*<>(const Matrix<T>&, const Vector&);
     // ...
};

template<typename T>
class Matrix {
     Vector<T> v[4];
public:
     friend Vector<T> operator*<>(const Matrix&, const Vector<T>&);
     // ...
};

The <> after the name of the friend function is needed to make clear that the friend is a template function. Without the <>, a non-template function would be assumed. The multiplication operator can then be defined to access data from Vector and Matrix directly:

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template<typename T>
Vector<T> operator*(const Matrix<T>& m, const Vector<T>& v)
{
     Vector<T> r;
     // ... use m.v[i] and v.v[i] for direct access to elements ...
     return r;
}

Friends do not affect the scope in which the template class is defined, nor do they affect the scope in which the template is used. Instead, friend functions and operators are found using a lookup based on their argument types (§14.2.4, §18.2.5, §iso.11.3). Like a member function, a friend function is instantiated only if it is used (§26.2.1).

Like other classes, a class template can designate other classes as friends. For example:

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class C;
using C2 = C;

template<typename T>
class My_class {
     friend C;             // OK: C is a class
     friend C2;            // OK: C2 is an alias for a class
     friend C3;            // error: no class C3 in scope
     friend class C4;      // OK: introduces a new class C4
};

Naturally, the interesting cases are those where the friend depends on a template argument. For example:

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template<typename T>
class my_other_class {
     friend T;                // my argument is my friend!
     friend My_class<T>;      // My_class with the corresponding argument is my friend
     friend class T;          // error: redundant "class"
};

As ever, friendship is neither inherited nor transitive (§19.4). For example, C has not become a friend of My_other_class<int> even though My_class<int> is a friend and C is a friend of My_class<int>.

We cannot directly make a template a friend of a class, but we can make a friend declaration a template. For example:

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template<typename T, typename A>
class List;

template<typename T>
class Link {
     template<typename U, typename A>
         friend class List;
     // ...
};

Unfortunately, there is no way of saying that Link<X> should only be a friend of List<X>.

Friend classes are designed to allow the representation of small clusters of closely related concepts. A complicated pattern of friendship is almost certainly a design error.

23.5. Function Templates

For many people, the first and most obvious use of templates is to define and use container classes such as vector (§31.4), list (§31.4.2), and map (§31.4.3). Soon after, the need for function templates to manipulate such containers arises. Sorting a vector is a simple example:

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template<typename T> void sort(vector<T>&);          // declaration

void f(vector<int>& vi, vector<string>& vs)
{
     sort(vi);  // sort(vector<int>&);
     sort(vs);  // sort(vector<string>&);
}

When a function template is called, the types of the function arguments determine which version of the template is used; that is, the template arguments are deduced from the function arguments (§23.5.2).

Naturally, the function template must be defined somewhere (§23.7):

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template<typename T>
void sort(vector<T>& v)                     // definition
     // Shell sort (Knuth, Vol. 3, pg. 84)
{
     const size_t n = v.size();

     for (int gap=n/2; 0<gap; gap/=2)
           for (int i=gap; i<n; i++)
                 for (int j=i–gap; 0<=j; j–=gap)
                       if (v[j+gap]<v[j]) {   // swap v[j] and v[j+gap]
                              T temp = v[j];
                              v[j] = v[j+gap];
                              v[j+gap] = temp;
                       }
}

Please compare this definition to the sort() defined in §12.5. This templatized version is cleaner and shorter because it can rely on more information about the type of the elements it sorts. Typically, it is also faster because it doesn’t rely on a pointer to function for the comparison. This implies that no indirect function calls are needed and that inlining a simple < is easy.

A further simplification is to use the standard-library template swap() (§35.5.2) to reduce the action to its natural form:

if (v[j+gap]<v[j])
       swap(v[j],v[j+gap]);

This does not introduce any new overhead. Better yet, the standard-library swap() uses move semantics, so we may see a speedup (§35.5.2).

In this example, operator < is used for comparison. However, not every type has a < operator. This limits the use of this version of sort(), but the limitation is easily avoided by adding an argument (see §25.2.3). For example:

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template<typename T, typename Compare = std::less<T>>
void sort(vector<T>& v)     // definition
     // Shell sort (Knuth, Vol. 3, pg. 84)
{
     Compare cmp;                      // make a default Compare object
     const size_t n = v.size();

     for (int gap=n/2; 0<gap; gap/=2)
           for (int i=gap; i<n; i++)
                 for (int j=i–gap; 0<=j; j–=gap)
                       if (cmp(v[j+gap],v[j]))
                            swap(v[j],v[j+gap]);
}

We can now sort using the default comparison operation (<) or supply our own:

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struct No_case {
     bool operator()(const string& a, const string& b) const;        // compare case insensitive
};

void f(vector<int>& vi, vector<string>& vs)
{
     sort(vi);                           // sort(vector<int>&)
     sort<int,std::greater<int>>(vi);    // sort(vector<int>&) using greater

     sort(vs);                           // sort(vector<string>&)
     sort<string,No_case>(vs);           // sort(vector<string>&) using No_case
}

Unfortunately, the rule that only trailing template arguments can be specified leads us to have to specify (rather than deduce) the element type when we specify the comparison operations.

The explicit specification of function template arguments is explained in §23.5.2.

23.5.1. Function Template Arguments

Function templates are essential for writing generic algorithms to be applied to a wide variety of container types (§3.4.2, §32.2). The ability to deduce template arguments for a call from the function arguments is crucial.

A compiler can deduce type and non-type arguments from a call, provided the function argument list uniquely identifies the set of template arguments. For example:

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template<typename T, int max>
struct Buffer {
     T buf[max];
public:
     // ...
};

template<typename T, int max>
T& lookup(Buffer<T,max>& b, const char* p);

Record& f(Buffer<string,128>& buf, const char* p)
{
     return lookup(buf,p); // use the lookup() where T is string and i is 128
}

Here, lookup()’s T is deduced to be string and max is deduced to be 128.

Note that class template parameters are never deduced. The reason is that the flexibility provided by several constructors for a class would make such deduction impossible in many cases and obscure in many more. Instead, specialization (§25.3) provides a mechanism for implicitly choosing between alternative definitions of a template. If we need to create an object of a deduced type, we can often do that by calling a function to do the deduction (and creation). For example, consider a simple variant of the standard library’s make_pair() (§34.2.4.1):

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template<typename T1, typename T2>
pair<T1,T2> make_pair(T1 a, T2 b)
{
     return {a,b};
}

auto x = make_pair(1,2);                     // x is a pair<int,int>
auto y = make_pair(string("New York"),7.7);  // y is a pair<string,double>

If a template argument cannot be deduced from the function arguments (§23.5.2), we must specify it explicitly. This is done in the same way that template arguments are explicitly specified for a template class (§25.2, §25.3). For example:

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template<typename T>
T* create();           // make a T and return a pointer to it

void f()
{
     vector<int> v;            // class, template argument int
     int* p = create<int>();   // function, template argument int
     int* q = create();        // error: can't deduce template argument
}

This use of explicit specification to provide a return type for a function template is very common. It allows us to define families of object creation functions (e.g., create()) and conversion functions (e.g., §27.2.2). The syntax for static_cast, dynamic_cast, etc. (§11.5.2, §22.2.1), matches the explicitly qualified function template syntax.

Default template arguments can be used to simplify explicit qualification in some cases (§25.2.5.1).

23.5.2. Function Template Argument Deduction

A compiler can deduce a type template argument, T or TT, and a non-type template argument, I, from a template function argument with a type composed of the following constructs (§iso.14.8.2.1):

Here, args_TI is a parameter list from which a T or an I can be determined by recursive application of these rules, and args is a parameter list that does not allow deduction. If not all parameters can be deduced in this way, a call is ambiguous. For example:

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template<typename T, typename U>
void f(const T*, U(*)(U));

int g(int);

void h(const char* p)
{
     f(p,g);       // T is char, U is int
     f(p,h);       // error: can't deduce U
}

Looking at the arguments of the first call of f(), we easily deduce the template arguments. Looking at the second call of f(), we see that h() doesn’t match the pattern U(*)(U) because h()’s argument and return types differ.

If a template parameter can be deduced from more than one function argument, the same type must be the result of each deduction. Otherwise, the call is an error. For example:

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template<typename T>
void f(T i, T* p);

void g(int i)
{
     f(i,&i);           // OK
     f(i,"Remember!");  // error, ambiguous: T is int or T is const char?
}

23.5.2.1. Reference Deduction

It can be useful to have different actions taken for lvalues and rvalues. Consider a class for holding an {integer,pointer} pair:

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template<typename T>
class Xref {
public:
     Xref(int i, T* p)      // store a pointer: Xref is the owner
           :index{i}, elem{p}, owner{true}
     {}

     Xref(int i, T& r)      // store a pointer to r, owned by someone else
           :index{i}, elem{&r}, owner{false}
     {}

     Xref(int i, T&& r)     // move r into Xref, Xref is the owner
           :index{i}, elem{new T{move(r)}}, owner{true}
     {}

     ~Xref()
     {
           if(owned) delete elem;
     }
     // ...
private:
     int index;
     T* elem;
     bool owned;
};

So:

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string x {"There and back again"};

Xref<string> r1 {7,"Here"};                 // r1 owns a copy of string{"Here"}
Xref<string> r2 {9,x};                      // r2 just refers to x
Xref<string> r3 {3,new string{"There"}};    // r3 owns the string{"There"}

Here, r1 picks Xref(int,string&&) because x is an rvalue. Similarly, r2 picks Xref(int,string&) because x is an lvalue.

Lvalues and rvalues are distinguished by template argument deduction: an lvalue of type X is deduced as an X& and an rvalue as X. This differs from the binding of values to non-template argument rvalue references (§12.2.1) but is especially useful for argument forwarding (§35.5.1). Consider writing a factory function that make Xrefs on the free store and returns unique_ptrs to them:

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template<typename T>
    T&& std::forward(typename remove_reference<T>::type& t) noexcept; // §35.5.1
template<typename T>
    T&& std::forward(typename remove_reference<T>::type&& t) noexcept;
template<typename TT, typename A>
unique_ptr<TT> make_unique(int i, A&& a)    // simple variant of make_shared (§34.3.2)
{
    return unique_ptr<TT>{new TT{i,forward<A>(a)}};
}

We want make_unique<T>(arg) to construct a T from an arg without making any spurious copies. To do that, it is essential that the lvalue/rvalue distinction is maintained. Consider:

auto p1 = make_unique<Xref<string>>(7,"Here");

"Here" is an rvalue, so forward(string&&) is called, passing along an rvalue, so that Xref(int,string&&) is called to move from the string holding "Here".

The more interesting (subtle) case is:

auto p2 = make_unique<Xref<string>>(9,x);

Here, x is an lvalue, so forward(string&) is called, passing along an lvalue: forward()’s T is deduced to string& so that the return value becomes string& &&, which means string& (§7.7.3). Thus, Xref(int,string&) is called for the lvalue x, so that x is copied.

Unfortunately, make_unique() is not part of the standard library, but it is widely supported nevertheless. Defining a make_unique() that can take arbitrary arguments is relatively easy using a variadic template for forwarding (§28.6.3).

23.5.3. Function Template Overloading

We can declare several function templates with the same name and even declare a combination of function templates and ordinary functions with the same name. When an overloaded function is called, overload resolution is necessary to find the right function or function template to invoke. For example:

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template<typename T>
     T sqrt(T);
template<typename T>
     complex<T> sqrt(complex<T>);
double sqrt(double);

void f(complex<double> z)
{
     sqrt(2);     // sqrt<int>(int)
     sqrt(2.0);   // sqrt(double)
     sqrt(z);     // sqrt<double>(complex<double>)
}

In the same way that a function template is a generalization of the notion of a function, the rules for resolution in the presence of function templates are generalizations of the function overload resolution rules. Basically, for each template we find the specialization that is best for the set of function arguments. Then, we apply the usual function overload resolution rules to these specializations and all ordinary functions (§iso.14.8.3):

[1] Find the set of function template specializations (§23.2.2) that will take part in overload resolution. Do this by considering each function template and deciding which template arguments, if any, would be used if no other function templates or functions of the same name were in scope. For the call sqrt(z), this makes sqrt<double>(complex<double>) and sqrt<complex<double>>(complex<double>) candidates. See also §23.5.3.2.

[2] If two function templates can be called and one is more specialized than the other (§25.3.3), consider only the most specialized template function in the following steps. For the call sqrt(z), this means that sqrt<double>(complex<double>) is preferred over sqrt<complex<double>>(complex<double>): any call that matches sqrt<T>(complex<T>) also matches sqrt<T>(T).

[3] Do overload resolution for this set of functions, plus any ordinary functions, as for ordinary functions (§12.3). If a function template’s argument has been determined by template argument deduction (§23.5.2), that argument cannot also have promotions, standard conversions, or user-defined conversions applied. For sqrt(2), sqrt<int>(int) is an exact match, so it is preferred over sqrt(double).

[4] If a function and a specialization are equally good matches, the function is preferred. Consequently, sqrt(double) is preferred over sqrt<double>(double) for sqrt(2.0).

[5] If no match is found, the call is an error. If we end up with two or more equally good matches, the call is ambiguous and is an error.

For example:

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template<typename T>
T max(T,T);

const int s = 7;

void k()
{
     max(1,2);       // max<int>(1,2)
     max('a','b');   // max<char>('a','b')
     max(2.7,4.9);   // max<double>(2.7,4.9)
     max(s,7);       // max<int>(int{s},7) (trivial conversion used)

     max('a',1);     // error: ambiguous: max<char,char>() or max<int,int>()?
     max(2.7,4);     // error: ambiguous: max<double,double>() or max<int,int>()?
}

The problem with the last two calls is that we don’t apply promotions and standard conversions until after template parameters have been uniquely determined. There is no rule telling the compiler to prefer one resolution over the other. In most cases, it is probably good that the language rules leave subtle decisions in the hands of the programmer. The alternative to surprising ambiguity errors is surprising results from unexpected resolutions. People’s “intuitions” about overload resolution differ dramatically, so it is impossible to design a perfectly intuitive set of overload resolution rules.

23.5.3.1. Ambiguity Resolution

We could resolve the two ambiguities by explicit qualification:

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void f()
{
     max<int>('a',1);          // max<int>(int('a'),1)
     max<double>(2.7,4);       // max<double>(2.7,double(4))
}

Alternatively, we could add suitable declarations:

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inline int max(int i, int j) { return max<int>(i,j); }
inline double max(int i, double d) { return max<double>(i,d); }
inline double max(double d, int i) { return max<double>(d,i); }
inline double max(double d1, double d2) { return max<double>(d1,d2); }

void g()
{
     max('a',1);      // max(int('a'),1)
     max(2.7,4);      // max(2.7,4)
}

For ordinary functions, ordinary overloading rules (§12.3) apply, and the use of inline ensures that no extra overhead is imposed.

The definition of max() is trivial, so we could have implemented the comparison directly rather than calling a specialization of max(). However, using an explicit specialization of the template is an easy way of defining such resolution functions and can help maintenance by avoiding almost identical code in several functions.

23.5.3.2. Argument Substitution Failure

When looking for a best match for a set of arguments for a function template, the compiler considers whether the argument can be used in the way required by the complete function template declaration (including the return type). For example:

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template<typename Iter>
typename Iter::value_type mean(Iter first, Iter last);

void f(vector<int>& v, int* p, int n)
{
     auto x = mean(v.begin(),v.end());   // OK
     auto y = mean(p,p+n);               // error
}

Here, the initialization of x succeeds because the arguments match and vector<int>::iterator has a member called value_type. The initialization of y fails because even though the arguments match, int* does not have a member called value_type, so we cannot say:

int*::value_type mean(int*,int*);     // int* does not have a member called value_type

However, what if there were another definition of mean()?

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template<typename Iter>
typename Iter::value_type mean(Iter first, Iter last);     // #1

template<typename T>
T mean(T*,T*);                                             // #2

void f(vector<int>& v, int* p, int n)
{
     auto x = mean(v.begin(),v.end());      // OK: call #1
     auto y = mean(p,p+n);                  // OK: call #2
}

This works: both initializations succeed. But why didn’t we get an error when trying to match mean(p,p+n) with the first template definition? The arguments match perfectly, but by substituting in the actual template argument (int*), we get the function declaration:

int*::value_type mean(int*,int*);   // int* does not have a member called value_type

That is garbage, of course: a pointer does not have a member value_type. Fortunately, considering this possible declaration is not by itself an error. There is a language rule (§iso.14.8.2) that says that such a substitution failure is not an error. It simply causes the template to be ignored; that is, the template does not contribute a specialization to the overload set. That done, mean(p,p+n) matches declaration #2, which is called.

Without the “substitution error is not a failure” rule, we would get compile-time errors even when error-free alternatives (such as #2) are available. More, this rule gives us a general tool for selecting among templates. Techniques based on this rule are described in §28.4. In particular, the standard library provides enable_if to simplify conditional definition of templates (§35.4.2).

The rule is known under the unpronounceable acronym SFINAE (Substitution Failure Is Not An Error). SFINAE is often used as a verb with the “F” pronounced as a “v”: “I SFINAEd away that constructor.” That sounds quite impressive, but I tend to avoid this jargon. “The constructor was eliminated by a substitution failure” is clearer for most people and does less violence to the English language.

So, if – in the process of generating a candidate function to resolve a function call – the compiler finds itself generating a template specialization that would be nonsensical, that candidate is not entered into the overloading set. A template specialization is considered nonsensical if it would lead to a type error. In this, we consider only a declaration; template function definitions and the definition of class members are not considered (or generated) unless they are actually used. For example:

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template<typename Iter>
Iter mean(Iter first, Iter last)                        // #1
{
     typename Iter::value_type = *first;
     // ...
}

template<typename T>
T* mean(T*,T*);                                          // #2

void f(vector<int>& v, int* p, int n)
{
     auto x = mean(v.begin(),v.end());       // OK: call #1
     auto y = mean(p,p+n);                   // error: ambiguous
}

The declaration of mean() #1 is fine for mean(p,p+n). The compiler does not start to instantiate the body of that mean() and eliminate it because of the type error.

Here, the result is an ambiguity error. Had mean() #2 not been present, declaration #1 would have been chosen and we would have suffered an instantiation-time error. Thus, a function may be chosen as the best match yet still fail to compile.

23.5.3.3. Overloading and Derivation

The overload resolution rules ensure that function templates interact properly with inheritance:

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template<typename T>
    class B { /* ... */ };
template<typename T>
    class D : public B<T> { /* ... */ };

template<typename T> void f(B<T>*);

void g(B<int>* pb, D<int>* pd)
{
     f(pb);         // f<int>(pb) of course
     f(pd);         // f<int>(static_cast<B<int>*>(pd));
                    // standard conversion D<int>* to B<int>* used
}

In this example, the function template f() accepts a B<T>* for any type T. We have an argument of type D<int>*, so the compiler easily deduces that by choosing T to be int, the call can be uniquely resolved to a call of f(B<int>*).

23.5.3.4. Overloading and Non-Deduced Parameters

A function argument that is not involved in the deduction of a template parameter is treated exactly as an argument of a non-template function. In particular, the usual conversion rules hold. Consider:

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template<typename T, typename C>
T get_nth(C& p, int n);   // get the nth element

This function presumably returns the value of the nth element of a container of type C. Because C has to be deduced from an actual argument of get_nth() in a call, conversions are not applicable to the first argument. However, the second argument is perfectly ordinary, so the full range of possible conversions is considered. For example:

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struct Index {
     operator int();
     // ...
};

void f(vector<int>& v, short s, Index i)
{
     int i1 = get_nth<int>(v,2); // exact match
     int i2 = get_nth<int>(v,s); // standard conversion: short to int
     int i3 = get_nth<int>(v,i); // user-defined conversion: Index to int
}

This notation is sometimes called explicit specialization (§23.5.1).

23.6. Template Aliases

We can define an alias for a type with the using syntax or with the typedef syntax (§6.5). The using syntax is more general in the important sense that it can be used to define an alias for a template with some of its arguments bound. Consider:

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template<typename T, typename Allocator = allocator<T>> vector;

using Cvec = vector<char>;                      // both arguments are bound

Cvec vc = {'a', 'b', 'c'};                      // vc is a vector<char,allocator<char>>

template<typename T>
using Vec = vector<T,My_alloc<T>>;              // vector using my allocator (2nd argument is bound)

Vec<int> fib = {0, 1, 1, 2, 3, 5, 8, 13};       // fib is a vector<int,My_alloc<int>>

In general, if we bind all arguments of a template, we get a type, but if we bind only some, we get a template. Note that what we get from using in an alias definition is always an alias. That is, when we use the alias, it is completely equivalent to a use of the original template. For example:

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vector<char,alloc<char>> vc2 = vc;             // vc2 and vc are of the same type
vector<int,My_alloc<int>> verbose = fib;       // verbose and fib are of the same type

The equivalence of the alias and the original template implies that if you specialize the template, you (correctly) get the specializations when you use the alias. For example:

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template<int>
struct int_exact_traits {   // idea: int_exact_traits<N>::type is a type with exactly N bits
     using type = int;
};

template<>
struct int_exact_traits<8> {
     using type = char;
};
template<>
struct int_exact_traits<16> {
     using type = short;
};

template<int N>
using int_exact = typename int_exact_traits<N>::type;   // define alias for convenient notation

int_exact<8> a = 7;  // int_exact<8> is an int with 8 bits

If specializations did not get used through the alias, we couldn’t claim that int_exact was simply an alias for int_exact_traits<N>::type; they would behave differently. On the other hand, you cannot define a specialization of an alias. If you had been able to, it would have been rather easy for a human reader to get confused about what was specialized, so no syntax is provided for specializing an alias.

23.7. Source Code Organization

There are three reasonably obvious ways of organizing code using templates:

[1] Include template definitions before their use in a translation unit.

[2] Include template declarations (only) before their use in a translation unit. Include definitions of templates later in the translation unit (potentially after their use).

[3] Include template declarations (only) before their use in a translation unit. Define the templates in some other translation unit.

For technical and historical reasons, option [3], the separate compilation of template definitions and their uses, is not offered. By far the most common approach is to include (usually #include) the definition of the templates you use in every translation unit in which you use them and rely on your implementation to optimize compile times and eliminate object code duplication. For example, I might provide a template out() in a header out.h:

// file out.h:

        #include<iostream>

        template<typename T>
        void out(const T& t)
        {
             std::cerr << t;
        }

We would #include this header wherever out() was needed. For example:

// file user1.cpp:

        #include "out.h"
        // use out()

and

// file user2.cpp:

        #include "out.h"
        // use out()

That is, the definition of out() and all declarations on which it depends are #included in several different compilation units. It is up to the compiler to generate code when needed (only) and to optimize the process of reading redundant definitions. This strategy treats template functions the same way as inline functions.

An obvious problem with this strategy is that users may accidentally come to depend on declarations included only for the benefit of the definition of out(). This danger can be limited by taking approach [2] “include template definitions later,” by using namespaces, by avoiding macros, and generally by reducing the amount of information included. The ideal is to minimize a template definition’s dependency on its environment.

To use the “include template definitions later” approach for our simple out() example, we first split out.h into two. The declarations go into a .h file:

// file outdecl.h:

        template<typename T>
        void out(const T& t);

The definitions go into out.cpp:

// file out.cpp:

        #include<iostream>

        template<typename T>
        void out(const T& t)
        {
             std::cerr << t;
        }

A user now #includes both:

// file user3.cpp:

        #include "out.h"
        // use out()
        #include "out.cpp"

This minimizes the chances of the implementation of the templates having undesirable effects on the user code. Unfortunately, it also increases the chances that something in the user code (say, a macro) will have an undesirable effect on the template definitions.

As ever, non-inline, non-template functions and static members (§16.2.12) must have a unique definition in some compilation unit. This implies that such members are best not used for templates that are otherwise included in many translation units. As shown with out(), the definition of a template function may be replicated in different translation units, so beware of contexts that might subtly change the meaning of a definition:

// file user1.cpp:

        #include "out.h"
        // use out()

and

// file user4.cpp:

        #define std MyLib
        #include "out.c"
        // use out()

This sneaky and error-prone use of a macro changes the definition of out so that user4.cpp’s definition differs from user1.cpp’s. This is an error, but it is an error that an implementation may not catch. This kind of error can be very hard to detect in large programs, so be careful to minimize context dependencies of templates and be very suspicious about macros (§12.6).

If you need more control over the context of instantiation, you can use explicit instantiation and extern templates (§26.2.2).

23.7.1. Linkage

The rules for linkage of templates are the rules for linkage of the generated classes and functions (§15.2, §15.2.3). This implies that if the layout of a class template or the definition of an inline function template changes, all code that uses that class or function must be recompiled.

For templates defined in header files and included “everywhere” this can imply a lot of recompilation because templates tend to include a lot of information in header files, more than non-template code using .cpp files. In particular, if dynamically linked libraries are used, care has to be taken that all uses of a template are consistently defined.

Sometimes, it is possible to minimize the exposure to changes in complicated template libraries by encapsulating their use in functions with non-template interfaces. For example, I might like to implement some computations using a general numerical library supporting a wide variety of types (e.g., Chapter 29, §40.4, §40.5, §40.6). However, I often know the type used for my calculations. For example, in a program I may consistently use doubles and vector<double>. In that case, I could define:

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double accum(const vector<double>& v)
{
    return accumulate(v.begin(),v.end(),0.0);
}

Given that, I can use the simple non-templated declaration of accum() in my code:

double accum(const vector<double>& v);

The dependence on std::accumulate has disappeared into a .cpp file that is not seen by the rest of my code. Also, I suffer the compilation-time overhead of a #include<numeric> only in that .cpp file.

Note that I took the opportunity to simplify the interface to accum() compared to std::accumulate(). The generality that is a key attribute of good template libraries can be seen as a source of complexity in a particular application.

I suspect that I would not use this technique for standard-library templates. Those are stable over years and known to the implementations. In particular, I did not bother to try to encapsulate vector<double>. However, for more complex, esoteric, or frequently changing template libraries, such encapsulation can be useful.

23.8. Advice

[1] Use templates to express algorithms that apply to many argument types; §23.1.

[2] Use templates to express containers; §23.2.

[3] Note that template<class T> and template<typename T> are synonymous; §23.2.

[4] When defining a template, first design and debug a non-template version; later generalize by adding parameters; §23.2.1.

[5] Templates are type-safe, but checking happens too late; §23.3.

[6] When designing a template, carefully consider the concepts (requirements) assumed for its template arguments; §23.3.

[7] If a class template should be copyable, give it a non-template copy constructor and a non-template copy assignment; §23.4.6.1.

[8] If a class template should be movable, give it a non-template move constructor and a non-template move assignment; §23.4.6.1.

[9] A virtual function member cannot be a template member function; §23.4.6.2.

[10] Define a type as a member of a template only if it depends on all the class template’s arguments; §23.4.6.3.

[11] Use function templates to deduce class template argument types; §23.5.1.

[12] Overload function templates to get the same semantics for a variety of argument types; §23.5.3.

[13] Use argument substitution failure to provide just the right set of functions for a program; §23.5.3.2.

[14] Use template aliases to simplify notation and hide implementation details; §23.6.

[15] There is no separate compilation of templates: #include template definitions in every translation unit that uses them; §23.7.

[16] Use ordinary functions as interfaces to code that cannot deal with templates; §23.7.1.

[17] Separately compile large templates and templates with nontrivial context dependencies; §23.7.

24. Generic Programming

Now is a good time to put your work on a firm theoretical basis.

– Sam Morgan

• Introduction

• Algorithms and Lifting

• Concepts

Discovering a Concept; Concepts and Constraints

• Making Concepts Concrete

Axioms; Multi-argument Concepts; Value Concepts; Constraints Checks; Template Definition Checking

• Advice

24.1. Introduction

What are templates for? In other words, what programming techniques are effective when you use templates? Templates offer:

• The ability to pass types (as well as values and templates) as arguments without loss of information. This implies excellent opportunities for inlining, of which current implementations take great advantage.

• Delayed type checking (done at instantiation time). This implies opportunities to weave together information from different contexts.

• The ability to pass constant values as arguments. This implies the ability to do compile-time computation.

In other words, templates provide a powerful mechanism for compile-time computation and type manipulation that can lead to very compact and efficient code. Remember that types (classes) can contain both code and values.

The first and most common use of templates is to support generic programming, that is, programming focused on the design, implementation, and use of general algorithms. Here, “general” means that an algorithm can be designed to accept a wide variety of types as long as they meet the algorithm’s requirements on its arguments. The template is C++’s main support for generic programming. Templates provide (compile-time) parametric polymorphism.

There are many definitions of “generic programming.” Thus, the term can be confusing. However, in the context of C++, “generic programming” implies an emphasis on the design of general algorithms implemented using templates.

Focusing more on generative techniques (seeing templates as type and function generators) and relying on type functions to express compile-time computation are called template metaprogramming, which is the subject of Chapter 28.

The type checking provided for templates checks the use of arguments in the template definition rather than against an explicit interface (in a template declaration). This provides a compile-time variant of what is often called duck typing (“If it walks like a duck and it quacks like a duck, it’s a duck”). Or – using more technical terminology – we operate on values, and the presence and meaning of an operation depend solely on its operand values. This differs from the alternative view that objects have types, which determine the presence and meaning of operations. Values “live” in objects. This is the way objects (e.g., variables) work in C++, and only values that meet an object’s requirements can be put into it. What is done at compile time using templates does not involve objects, only values. In particular, there are no variables at compile time. Thus, template programming resembles programming in dynamically-typed programming languages, but the run-time cost is zero, and errors that in a run-time typed language manifest themselves as exceptions become compile-time errors in C++.

A key aspect of generic programming, metaprogramming, and probably all uses of templates is the uniform handling of built-in types and user-defined types. For example, an accumulate() operation does not care whether the types of values it adds up are ints, complex<double>s, or Matrixes. What it cares about is that they can be added using the + operator. The use of a type as a template argument does not imply or require the use of a class hierarchy or any form of run-time self-identification of the type of an object. This is logically pleasing and essential for high-performance applications.

This section focuses on two aspects of generic programming:

• Lifting: generalizing an algorithm to allow the greatest (reasonable) range of argument types (§24.2), that is, to limit an algorithm’s (or a class’s) dependency on properties to what is essential

• Concepts: carefully and precisely specifying the requirements of an algorithm (or a class) on its arguments (§24.3)

24.2. Algorithms and Lifting

A function template is a generalization of an ordinary function in the sense that it can perform its actions on a variety of data types and use a variety of operations passed as arguments to implement those actions. An algorithm is a procedure or formula for solving a problem: a finite series of computation steps to produce a result. Thus, a function template is often called an algorithm.

How do we get from a function doing specific operations on specific data to an algorithm doing more general operations on a variety of data types? The most effective way of getting a good algorithm is to generalize from one – and preferably more – concrete example. Such generalization is called lifting: that is, lifting a general algorithm from specific functions. It is important to go from the concrete to the abstract while maintaining performance and keeping an eye on what is reasonable. Overly clever programmers can generalize to an absurd extent to try to cover every eventuality. Thus, trying to abstract from first principles in the absence of concrete examples typically leads to bloated, hard-to-use code.

I will illustrate the process of lifting by a concrete example. Consider:

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double add_all(double* array, int n)
    // one concrete algorithm on array of doubles
{
    double s {0};
    for (int i = 0; i<n; ++i)
          s = s + array[i];
    return s;
}

Obviously, this computes the sum of the doubles in the argument array. Also consider:

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struct Node {
     Node* next;
     int data;
};

int sum_elements(Node* first, Node* last)
     // another concrete algorithm on list of ints
{
     int s = 0;
     while (first!=last) {
           s += first–>data;
           first = first–>next;
     }
     return s;
}

This computes the sum of the ints in the singly-linked list implemented by the Nodes.

These two code fragments differ in detail and in style, but an experienced programmer will immediately say, “Well, this is just two implementations of the accumulate algorithm.” This is a popular algorithm. Like most popular algorithms, it has many names, including reduce, fold, sum, and aggregate. However, let us try to develop a general algorithm from the two concrete examples in stages, so as to get a feel for the process of lifting. First we try to abstract away the data types so that we don’t have to be specific about

• double vs. int, or

• array vs. linked list.

To do so, I write some pseudo code:

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// pseudo code:

T sum(data)
    // somehow parameterize by the value type and the container type
{
    T s = 0
    while (not at end) {
               s = s + current value
               get next data element
    }
    return s
}

To make this concrete, we need three operations to access the “container” data structure:

• Not at end

• Get current value

• Get next data element

For the actual data, we also need three operations:

• Initialize to zero

• Add

• Return the result

Obviously, this is rather imprecise, but we can turn it into code:

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// concrete STL-like code:

template<typename Iter, typename
Val sum(Iter first, Iter last)
{
     Val s = 0;
     while (first!=last) {
           s = s + *first;
           ++first;
     }
     return s;
}

Here, I took advantage of knowing the usual STL way of representing a sequence of values (§4.5). The sequence is represented as a pair of iterators supporting three operations:

• * for accessing the current value

• ++ for moving forward to the next element

• != for comparing iterators to check if we are at the end of a sequence

We now have an algorithm (a function template) that can be used for both arrays and linked lists and for both ints and doubles. The array example works immediately because double* is an example of an iterator:

double ad[] = {1,2,3,4};
double s = sum<double*>(ad,ad+4);

To use the handcrafted singly-linked list, we need to provide an iterator for it. Given a few operations, a Node* can be the iterator:

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struct Node { Node* next; int data; };

Node* operator++(Node* p) { return p–>next; }
int operator*(Node* p) { return p–>data; }
Node* end(lst) { return nullptr; }

void test(Node* lst)
{
     int s = sum<int*>(lst,end(lst));
}

I use the nullptr as the end iterator. I use an explicit template argument (here, <int>) to allow a caller to specify the type to use for the accumulator variable.

What we have so far is more general than a lot of real-world code. For example, sum() would work for lists of floating-point numbers (of all precisions), for arrays of integers (of all ranges), and for many other types, such as a vector<char>. Importantly, sum() is as efficient as the handcrafted functions we started from. We do not want to achieve generality at the cost of performance.

The experienced programmer will note that sum() can be generalized further. In particular, the use of an extra template argument is awkward, and we required the initial value 0. We can solve that by letting the caller supply an initial value and then deduce Val:

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template<typename Iter, typename Val>
Val accumulate(Iter first, Iter last, Val s)
{
     while (first!=last) {
           s = s + *first;
           ++first;
     }
     return s;
}

double ad[] = {1,2,3,4};
double s1 = accumulate(ad,ad+4,0.0);  // accumulate in a double
double s2 = accumulate(ad,ad+4,0);    // accumulate in an int

But why +? We sometimes want to multiply elements. In fact, there seem to be quite a few operations we might want to apply to the elements of a sequence. This leads to a further generalization:

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template<typename Iter, typename Val, typename Oper>
Val accumulate(Iter first, Iter last, Val s, Oper op)
{
     while (first!=last) {
           s = op(s,*first);
           ++first;
     }
     return s;
}

We now use the argument op to combine element values with the accumulator. For example:

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double ad[] = {1,2,3,4};
double s1 = accumulate(ad,ad+4,0.0,std::plus<double>);     // as before
double s2 = accumulate(ad,ad+4,1.0,std::multiply<double>);

The standard library provides common operations, such as plus and multiply, as function objects to be used as arguments. Here, we see the utility of having the caller supply the initial value: 0 and * don’t go well together for accumulation. The standard library offers a further generalization of accumulate() that allows a user to provide an alternative to = for combining the result of the “addition” and the accumulator (§40.6).

Lifting is a skill that requires knowledge of an application domain and some experience. The most important single guide for designing algorithms is to lift them from concrete examples without adding features (notation or run-time cost) that would impair their use. The standard-library algorithms are the results of lifting done with great attention to performance issues.

24.3. Concepts

What are a template’s requirements for its arguments? In other words, what does the template code assume about its argument types? Or conversely, what must a type provide to be acceptable as an argument to a template? The possibilities are infinite because we can build classes and templates with arbitrary properties, for example:

• Types that provide – but not +

• Types that can copy but not move values

• Types for which copy operations does not copy (§17.5.1.3)

• Types for which == compares equality and others for which compare() does that

• Types that define addition as a member function plus() and others that define it as a non-member function operator+()

In that direction lies chaos. If every class has a unique interface, it becomes difficult to write templates that can take many different types. Conversely, if each template’s requirements are unique, it becomes difficult to define types that can be used with many templates. We would have to remember and keep track of a multitude of interfaces; that’s feasible for a tiny program, but unmanageable for real-world libraries and programs. What we need to do is to identify a small number of concepts (sets of requirements) that can be used for many templates and many types as arguments. The ideal is a kind of “plug compatibility” as we know it from the physical world, with a small number of standard plug designs.

24.3.1. Discovering a Concept

As an example, consider the String class template from §23.2:

template<typename C>
class String {
     // ...
};

What is required of a type, X, for it to be used as an argument to String: String<X>? More generally, what does it take to be a character in such a character string class? An experienced designer will have a small number of likely answers to that question and start the design based on those. However, let us consider how we might answer it from first principles. We proceed through three stages of analysis:

[1] First, we look at our (initial) implementation and determine which properties (operations, functions, member types, etc.) it uses from its parameter types (and the meaning of those operations). The resulting list is the minimal requirements for that particular template implementation.

[2] Next, we look at plausible alternative template implementations and list their requirements on their template arguments. Doing so, we may decide that we should place more or stricter requirements on the template arguments to allow for alternative implementations. Alternatively, we might decide to prefer an implementation that makes fewer and/or simpler requirements.

[3] Finally, we look at the resulting list (or lists) of required properties and compare it to lists of requirements (concepts) that we have used for other templates. We try to find simple, preferably common, concepts that can express what would otherwise be many long lists of requirements. The aim here is to make our design benefit from general work on classification. The resulting concepts are easier to give meaningful names and easier to remember. They should also maximize the degree of interoperability of templates and types by limiting variations in concepts to what is essential.

The first two steps are – for fundamental reasons – very similar to the way we generalize (“lift”) concrete algorithms into generic algorithms (§24.2). The last step counteracts the temptation to provide each algorithm with a set of argument requirements that exactly match its implementation. Such requirement lists are overspecialized and not stable: each change to the implementation would imply changes to the requirements documented as part of the algorithm’s interface.

For String<C>, first consider the operations actually performed on the parameter C by the implementation of String (§19.3). That will be the minimal set of requirements for that implementation of String:

[1] Cs are copied by copy assignment and copy initialization.

[2] String compares Cs using == and !=.

[3] String makes arrays of Cs (that implies default construction of Cs).

[4] String takes the address of Cs.

[5] Cs are destroyed when a String is destroyed.

[6] String has >> and << operators that somehow must read and write Cs.

Requirements [4] and [5] are technical requirements that we usually assume for all data types, and I will not discuss types that fail to meet them; such types are almost all overly clever artifacts. The first requirement – that values can be copied – is not true for a few important types, such as std::unique_ptr, that represent real resources (§5.2.1, §34.3.1). However, it is true for almost all “ordinary types,” so we require it. The ability to invoke a copy operation goes together with the semantic requirement that a copy really is a copy of the original, that is, that – except for taking the address – the two copies behave identically. Therefore, the ability to copy usually (as for our String) goes together with the requirement to provide == with the usual semantics.

By requiring assignment, we imply that a const type cannot be used as a template argument. For example, String<const char> is not guaranteed to work. That’s fine in this case, as in most cases. Having assignment means that an algorithm can use temporary variables of its argument type, create containers of objects of an argument type, etc. It does not imply that we cannot use const to specify interfaces. For example:

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template<typename T>
bool operator==(const String<T>& s1, const String<T>& s2)
{
     if (s1.size()!=s2.size()) return false;
     for (auto i = 0; i!=s1.size(); ++i)
           if (s1[i]!=s2[i]) return false;
     return true;
}

For String<X> we require that objects of type X can be copied. Independently, through the consts in its argument types, operator==() promises not to write to the X elements.

Should we require a move for an element type C? After all, we provide move operations for String<C>. We could, but it’s not essential: what we do with a C can be handled by copying, and if some copy is implicitly turned into a move (e.g., when we returned a C), so much the better. In particular, potentially important examples, such as String<String<char>>, will work fine (correctly and efficiently) without adding move operations to the requirements.

So far, so good, but the last requirement (that we can read and write Cs using >> and <<) seems excessive. Do we really read and write every kind of string? Maybe it would be better to say that if we read and write a String<X>, then X must provide >> and <<? That is, instead of placing a requirement on C for the whole String, we require it (only) for Strings that we actually read and write.

This is an important and fundamental design choice: we can place a requirement on class template arguments (so that they apply to all class members) or just to template arguments on individual class function members. The latter is more flexible, but also more verbose (we have to express the requirement for each function that needs it) and harder for a programmer to remember.

Looking at the list of requirements so far, I note the absence of a couple of operations that are common for “ordinary characters” in “ordinary strings”:

[1] No ordering (e.g., <)

[2] No conversion to an integer value

After this initial analysis we can consider which “well-known concepts” (§24.3.2) our lists of requirements relate to. The central concept for “ordinary types” is regular. A regular type is a type that

• you can copy (using assignment or initialization) with the proper copy semantics (§17.5.1.3),

• you can default construct,

• doesn’t have problems with various minor technical requirements (such as taking the address of a variable),

• you can compare for equality (using == and !=).

That seems an excellent choice for our String template arguments. I considered leaving out the equality comparisons but decided that copying without equality is rarely useful. Typically, Regular is the safe bet, and thinking about the meaning of == can help avoid errors in the definition of copying. All the built-in types are regular.

But does it make sense to leave out ordering (<) for String? Consider how we use strings. The desired use of a template (such as String) should determine its requirements on its arguments. We do compare strings extensively, and in addition we use comparisons indirectly when we sort sequences of strings, we put strings into sets, etc. Also, the standard-library string does provide <. It is usually a good idea to look to the standard for inspiration. So, we require not just Regular for our String, but also ordering. That’s the concept Ordered.

Interestingly, there has been quite some debate on whether Regular should require < or not. It seems that most types related to numbers have a natural order. For example, characters are encoded in bit patterns that can be interpreted as integers, and any sequence of values can be lexicographically ordered. However, many types do not have a natural order (e.g., complex numbers and images) even though we could define one. Other types have several natural orderings, but no unique best ordering (e.g., records may be ordered by name or by address). Finally, some (reasonable) types simply don’t have an order. For example, consider:

enum class rsp { rock, scissors, paper };

The rock-scissors-and-paper game critically depends on

• scissors<rock,

• rock<paper, and

• paper<scissors.

However, our String is not supposed to take an arbitrary type as its character type; it is supposed to take a type that supports string operations (such as comparisons, sorting, and I/O), so I decided to require ordering.

Adding a default constructor and the == and < operator, to our requirements for String’s template argument allows us to provide several useful operations for String. In fact, the more we require of a template argument type, the easier the various tasks become for the template implementer and the more services the template can offer to its users. On the other hand, it is important not to load down a template with requirements that are only used rarely and by specific operations: each requirement places a burden on the implementer of argument types and limits the set of types that can be used as arguments. So, for String<X> we require:

• Ordered<X>

• >> and << for X (only) if we use String<X>’s >> and <<

• Convertibility to an integer (only) if we define and use a conversion operation from X

So far, we have expressed our requirement of a character type for String in terms of syntactic properties, such as X must provide copy operations, ==, and <. In addition, we must require that these operations have the right semantics; for example, a copy operation makes a copy, == (equality) compares for equality, and < (less than) provides ordering. Often, this semantics involves relations among the operations. For example, for the standard library, we have (§31.2.2.1):

• The result of a copy compares equal to anything the original compares equal to (a==b implies T{a}==T{b}) and the copy is independent of its source (§17.5.1.3).

• A less-than comparison (e.g., <) provides a strict weak order (§31.2.2.1).

The semantics are defined in English text or (better still) mathematics, but unfortunately we have no way of expressing semantic requirements in C++ itself (but see §24.4.1). For the standard library, you can find the semantic requirements written in formalized English in the ISO standard.

24.3.2. Concepts and Constraints

A concept is not an arbitrary collection of properties. Most lists of properties of a type (or a set of types) do not define a coherent and useful concept. To be useful as a concept, a list of requirements has to reflect the needs of a set of algorithms or a set of operations of a template class. In many fields of endeavor, people have designed or discovered concepts describing the fundamental concepts of the field (the technical use of the word “concept” in C++ was chosen with this common usage in mind). There seem to be surprisingly few concepts that make sense. For example, algebra builds on concepts such as monad, field, and ring, whereas the STL relies on concepts such as forward iterator, bidirectional iterator, and random-access iterator. Finding a new concept in a field is a major accomplishment; it is not something you should expect to do every year. Mostly, you find concepts by examining the foundational texts of a field of study or an application domain. The set of concepts used in this book are described in §24.4.4.

“Concepts” is a very general idea that does not inherently have anything to do with templates. Even K&R C [Kernighan,1978] had concepts in the sense that signed integral type is the language’s generalization of the idea of an integer in memory. Our requirements on template arguments are concepts (however expressed), so most interesting issues related to concepts come in the context of templates.

I see a concept as a carefully crafted entity that reflects fundamental properties of an application domain. Consequently, there should be only few concepts, and these can act as a guideline for the design of algorithms and types. The analogy is with physical plugs and sockets; we want the minimal number to simplify our lives and to keep design and construction costs down. This ideal can conflict with the ideal of minimal requirements for each individual generic algorithm (§24.2) and each individual parameterized class. Furthermore, the ideal can conflict with the ideal of providing absolutely minimal interfaces to classes (§16.2.3) and even with what some programmers regard as their right to write their code “exactly as they like.” However, we don’t get plug compatibility without effort and some form of standard.

I set the bar for being a concept very high: I require generality, some stability, usability across many algorithms, semantic consistency, and more. In fact, many simple constraints that we’d like for template arguments don’t qualify as concepts according to my criteria. I think that is unavoidable. In particular, we write many templates that do not reflect general algorithms or widely applicable types. Instead, they are implementation details, and their arguments only have to reflect the necessary details of a template intended for a single use in a single implementation of something. I call requirements for such template arguments constraints or (if you must) ad hoc concepts. One way to look at constraints is to consider them incomplete (partial) specifications of an interface. Often, a partial specification can be useful and much better than no specification.

As an example, consider a library for experimenting with balancing strategies for balanced binary trees. The tree takes a Balancer as a template argument:

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template<typename Node, typename Balance>
struct node_base { // base of balanced tree
     // ...
}

A balancer is simply a class that provides three operations on nodes. For example:

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struct Red_black_balance {
     // ...
     template<typename Node> static void add_fixup(Node* x);
     template<typename Node> static void touch(Node* x);
     template<typename Node> static void detach(Node* x);
};

Obviously, we’d like to say what’s required of node_base’s arguments, but a balancer is not meant to be a widely used and easily understood interface; it’s meant to be used only as a detail of a particular implementation of balanced trees. This idea of a balancer (I hesitate to use the word “concept”) is unlikely to be used elsewhere or even to survive a major rewrite of the balanced tree implementation unchanged. It would be hard to pin down the exact semantics of a balancer. For starters, the semantics of Balancer would critically depend on the semantics of Node. In those aspects, a Balancer differs from a proper concept, such as Random_access_iterator. We can, however, still use the minimal specification of a balancer, “provides those three functions on nodes,” as a constraint on arguments to a node_base.

Note the way “semantics” keep cropping up in the discussion of concepts. I find that “Can I write out a semiformal semantics?” to be the question that is most helpful when it comes to deciding whether something is a concept or simply an ad hoc collection of constraints on a type (or set of types). If I can write out a meaningful semantic specification, I have a concept. If not, what I have is a constraint that may be useful but shouldn’t be expected to be stable or widely useful.

24.4. Making Concepts Concrete

Unfortunately, C++ does not have specific language facilities for directly expressing concepts. However, handling “concepts” as a design notion only and presenting them informally as comments is not ideal. For starters, compilers do not understand comments, so requirements expressed only as comments must be checked by the programmer and cannot help the compiler provide good error messages. Experience shows that even though concepts cannot be represented perfectly without direct language support, we can approximate them using code that performs compile-time checks of template argument properties.

A concept is a predicate; that is, we think of a concept as a compile-time function that looks at a set of template arguments and returns true if they meet the concept’s requirements and false if they don’t. So, we implement a concept as a constexpr function. Here, I will use the term constraints check to refer to a call of a constexpr predicate that checks a concept for a set of types and values. In contrast to proper concepts, a constraints check does not deal with semantic issues; it simply checks assumptions about syntactic properties.

Consider our String; its character type argument is supposed to be Ordered:

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template<typename C>
class String {
     static_assert(Ordered<C>(),"String's character type is not ordered");
     // ...
};

When String<X> is instantiated for a type X, the static_assert will be executed by the compiler. If Ordered<X>() returns true, the compilation proceeds, generating exactly the code it would have done without the assert. Otherwise, the error message is produced.

At first glance, this looks rather reasonable for a workaround. I’d rather have said:

template<Ordered C>
class String {
     // ...
};

However, that is for the future, so let us see how to define the predicate Ordered<T>():

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template<typename T>
constexpr bool Ordered()
{
    return Regular<T>() && Totally_ordered<T>();
}

That is, a type is Ordered if it is both Regular and Totally_ordered. Let us “dig down” to see what that means:

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template<typename T>
constexpr bool Totally_ordered()
{
     return Equality_comparable<T>()   // has == and !=
           && Has_less<T>()&& Boolean<Less_result<T>>()
           && Has_greater<T>() && Boolean<Greater_result<T>>()
           && Has_less_equal<T>() && Boolean<Less_equal_result<T>>()
           && Has_greater_equal<T>() && Boolean<Greater_equal_result<T>>();
}

template<typename T>
constexpr bool Equality_comparable()
{
    return Has_equal<T>() && Boolean<Equal_result<T>>()
         && Has_not_equal<T>() && Boolean<Not_equal_result<T>>();
}

So, a type T is ordered if it is regular and provides the usual six comparison operations. The comparison operations have to deliver results that can be converted to bool. The comparison operators are also supposed to have their proper mathematical meaning. The C++ standard precisely specifies what that means (§31.2.2.1, §iso.25.4).

Has_equals is implemented using enable_if and the techniques described in §28.4.4.

I capitalize my constraints names (e.g., Regular) even though doing so violates my “house style” of capitalizing type and template names, but not functions. However, concepts are even more fundamental than types, so I feel a need to emphasize them. I also keep them in a separate namespace (Estd) in the hope that very similar names will eventually become part of the language or the standard library.

Digging a bit further into the set of useful concepts, we can define Regular:

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template<typename T>
constexpr bool Regular()
{
    return Semiregular<T>() && Equality_comparable<T>();
}

Equality_comparable gives us == and !=. Semiregular is the concept that express the notion of a type that doesn’t have unusual technical restrictions:

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template<typename T>
constexpr bool Semiregular()
{
    return Destructible<T>()
         && Default_constructible<T>()
         && Move_constructible<T>()
         && Move_assignable<T>()
         && Copy_constructible<T>()
         && Copy_assignable<T>();
}

A Semiregular can be both moved and copied. That describes most types, but there are examples of types that cannot be copied, such as unique_ptr. However, I don’t know of useful types that can be copied but not moved. Types that can neither be moved nor copied, such as type_info (§22.5), are very rare and tend to reflect system properties.

We can also use constraints checks for functions; for example:

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template<typename C>
ostream& operator<<(ostream& out, String<C>& s)
{
     static_assert(Streamable<C>(),"String's character not streamable");
     out << '"';
     for (int i=0; i!=s.size(); ++i) cout << s[i];
     out << '"';
}

The concept Streamable needed by String’s output operator << requires its argument C to provide the output operator <<:

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template<typename T>
constexpr bool Streamable()
{
    return Input_streamable<T>() && Output_streamable<T>();
}

That is, Streamable tests that we can use the standard stream I/O (§4.3, Chapter 38) for a type.

Checking concepts through constraints-check templates has obvious weaknesses:

• Constraints checks are placed in definitions, but they really belong in declarations. That is, a concept is part of the interface to an abstraction, but a constraints check can be used only in its implementation.

• The checking of constraints occurs as part of the instantiation of the constraints-check template. Therefore, the checking may occur later than we would like. In particular, we would have preferred for a constraints check to be guaranteed to be done by the compiler at the point of the first call, but that is impossible without language changes.

• We can forget to insert a constraints check (especially for a function template).

• The compiler does not check that a template implementation uses only the properties specified in its concepts. Thus, a template implementation may pass the constraints check, yet still fail to type check.

• We do not specify semantic properties in a way that a compiler can understand (e.g., we use comments).

Adding constraints checks makes the requirements on template arguments explicit, and if a constraints check is well designed, it leads to more comprehensible error messages. If we forget to insert constraints checks, we are back to the ordinary type checking of the code generated by template instantiation. That can be unfortunate, but it is not disastrous. These constraints checks are a technique for making checking of designs based on concepts more robust, rather than an integral part of the type system.

If we want to, we can place constraints checks almost anywhere. For example, to guarantee that a particular type is checked against a particular concept, we could place constraints checks in a namespace scope (e.g., the global scope). For example:

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static_assert(Ordered<std::string>,"std::string is not Ordered");    // will succeed
static_assert(Ordered<String<char>>,"String<char> is not Ordered");  // will fail

The first static_assert checks if the standard string is Ordered (it is, because it provides ==, !=, and <). The second checks if our String is Ordered (it is not, because I “forgot” to define <). Using such a global check will perform the constraints check independently of whether we actually use that particular specialization of a template in the program. Depending on our aims, that can be an advantage or a bother. Such a check forces type checking to be done at a specific point in the program; that is usually good for error isolation. Also, such checks can help unit testing. However, for programs using a number of libraries, explicit checks quickly become unmanageable.

Being Regular is an ideal for a type. We can copy objects of regular types, put them into vectors and arrays, compare them, etc. If a type is Ordered, we can also use its objects in sets, sort sequences of such objects, etc. So, we go back and improve our String to make it Ordered. In particular, we add < to provide a lexicographical ordering:

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template<typename C>
bool operator<(const String<C>& s1, const String<C>& s2)
{
     static_assert(Ordered<C>(),"String's character type not ordered");
     bool eq = true;
     for (int i=0; i!=s1.size() && i!=s2.size(); ++i) {
           if (s2[i]<s1[i]) return false;
           if (s1[i]<s2[i]) eq = false;         // not s1==s2
     }
     if (s2.size()<s1.size()) return false;     // s2 is shorter than s1
     if (s1.size()==s2.size() && eq) return false;   // s1==s2
     return true;
}

24.4.1. Axioms

As in mathematics, an axiom is something we can’t prove. It is something we assume to be true. In the context of requirements for template arguments, we use “axiom” in that sense to refer to semantic properties. We use an axiom to state what a class or an algorithm assumes about its set of inputs. An axiom, however expressed, represents an algorithm’s or class’s expectations of (assumptions about) its arguments. We cannot in general test to see whether an axiom holds for values of a type (that is one reason we refer to them as axioms). Furthermore, an axiom is only required to hold for the values actually used by an algorithm. For example, an algorithm can carefully avoid dereferencing null pointers or copying a floating-point NaN. If so, it could have axioms that require pointers to be dereferenceable and floating-point values to be copyable. Alternatively, axioms can be written with the general assumption that singular values (e.g., NaN and nullptr) violate some precondition, so that they need not be considered.

C++ does not (currently) have any way of expressing axioms, but as for concepts, we can make our idea of a concept a bit more concrete than a comment or some text in a design document.

Consider how we might express some of the key semantic requirements for a type to be regular:

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template<typename T>
bool Copy_equality(T x)                      // semantics of copy construction
{
     return T{x}==x;     // a copy compares equal to what it is a copy of
}

template<typename T>
bool Copy_assign_equality(T x, T& y)        // semantics of assignment
{
     return (y=x, y==x);  // the result of an assignment compares equal to the source of the assignment
}

In other words, copy operations make copies.

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template<typename T>
bool Move_effect(T x, T& y)                  // semantics of move
{
     return (x==y ? T{std::move(x)}==y) : true) && can_destroy(y);
}

template<typename T>
bool Move_assign_effect(T x, T& y, T& z)     // semantics of move assignment
{
     return (y==z ? (x=std::move(y), x==z)) : true) && can_destroy(y);
}

In other words, a move operation yields a value that compares equal to whatever the source of the move operation compared equal to, and the source of the move can be destroyed.

These axioms are represented as executable code. We might use them for testing, but most importantly, we have to think harder to express them than we would have to simply write a comment. The resulting axioms are more precisely stated than would have been the case in “ordinary English.” Basically, we can express such pseudo axioms using first-order predicate logic.

24.4.2. Multi-argument Concepts

When looking at a single-argument concept and applying it to a type, it looks very much as if we are doing conventional type checking and that the concept is the type of a type. That’s part of the story, but only a part. Often, we find that relationships among argument types are essential for correct specification and use. Consider the standard-library find() algorithm:

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template<typename Iter, typename Val>
Iter find(Iter b, Iter e, Val x);

The Iter template argument must be an input iterator, and we can (relatively) easily define a constraints-check template for that concept.

So far, so good, but find() depends critically on comparing x to elements of the sequence [b:e). We need to specify that comparison is required; that is, we need to state that Val and and the value type of the input iterator are equality comparable. That requires a two-argument version of Equality_comparable:

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template<typename A, typename B>
constexpr bool Equality_comparable(A a, B b)
{

    return Common<T, U>()
         && Totally_ordered<T>()
         && Totally_ordered<U>()
         && Totally_ordered<Common_type<T,U>>()
         && Has_less<T,U>() && Boolean<Less_result<T,U>>()
         && Has_less<U,T>() && Boolean<Less_result<U,T>>()
         && Has_greater<T,U>() && Boolean<Greater_result<T,U>>()
         && Has_greater<U,T>() && Boolean<Greater_result<U,T>>()
         && Has_less_equal<T,U>() && Boolean<Less_equal_result<T,U>>()
         && Has_less_equal<U,T>() && Boolean<Less_equal_result<U,T>>()
         && Has_greater_equal<T,U>() && Boolean<Greater_equal_result<T,U>>()
         && Has_greater_equal<U,T>() && Boolean<Greater_equal_result<U,T>>();
};

This is rather verbose for a simple concept. However, I wanted to be explicit about all of the operators and about the symmetry of their use rather than burying the complexity in a generalization.

Given that, we can define find():

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template<typename Iter, typename Val>
Iter find(Iter b, Iter e, Val x)
{
       static_assert(Input_iterator<Iter>(),"find() requires an input iterator");
       static_assert(Equality_comparable<Value_type<Iter>,Val>(),
                      "find()'s iterator and value arguments must match");

       while (b!=e) {
            if (*b==x) return b;
            ++b;
       }
       return b;
}

Multi-argument concepts are particularly common and useful when specifying generic algorithms. This is also the area where you find the greatest number of concepts and the greatest need to specify new concepts (as opposed to picking “standard ones” from a catalog of common concepts). The variations among well-defined types appear to be somewhat more limited than the variations among algorithms’ requirements on their arguments.

24.4.3. Value Concepts

Concepts can express arbitrary (syntactic) requirements on a set of template arguments. In particular, a template argument can be an integer value, so concepts can take integer arguments. For example, we can write a constraints check to test that a value template argument is small:

template<int N>
constexpr bool Small_size()
{
    return N<=8;
}

A more realistic example would be a concept for which the numeric argument was just one among others. For example:

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constexpr int stack_limit = 2048;

template<typename T,int N>
constexpr bool Stackable()   // T is regular and N elements of T can fit on a small stack
{
    return Regular<T>() && sizeof(T)*N<=stack_limit;
}

This implements a notion of “small enough to be stack allocated.” It might be used like this:

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template<typename T, int N>
struct Buffer {
     // ...
};

template<typename T, int N>
void fct()
{
     static_assert(Stackable<T,N>(),"fct() buffer won't fit on stack");
     Buffer<T,N> buf;
     // ...
}

Compared to the fundamental concepts for types, value concepts tend to be small and ad hoc.

24.4.4. Constraints Checks

The constraints checks used in this book can be found on the book’s support site. They are not part of a standard, and I hope that in the future they will be replaced by a proper language mechanism. However, they can be useful for thinking about template and type design and reflect the de facto concepts in the standard library. They should go in a separate namespace to avoid interfering with possible future language features and alternative implementations of the idea of concepts. I use namespace Estd, but that may be an alias (§14.4.2). Here are a few constraints checks that you might find useful:

• Input_iterator<X>: X is an iterator that we can use only once to traverse a sequence (forward using ++), reading each element once only.

• Output_iterator<X>: X is an iterator that we can use only once to traverse a sequence (forward using ++), writing each element once only.

• Forward_iterator<X>: X is an iterator that we can use to traverse a sequence (forward using ++). This is what a singly-linked list (e.g., forward_list) naturally supports.

• Bidirectional_iterator<X>: X is an iterator that we can move both forward (using ++) and backward (using ––). This is what a doubly-linked list (e.g., list) naturally supports.

• Random_access_iterator<X>: X is an iterator that we can use to traverse a sequence (forward and backward) and to randomly access elements using subscripting and positioning using += and –=. This is what an array naturally supports.

• Equality_comparable<X,Y>:An X can be compared with a Y using == and !=.

• Totally_ordered<X,Y>: X and Y are Equality_comparable and an X can be compared with a Y using <, <=, > and >=.

• Semiregular<X>: Xs can be copied, default constructed, allocated on the free store, and are free of minor annoying technical restrictions.

• Regular<X>: Xs are Semiregular and can be compared using equality. The standard-library containers require their elements to be regular.

• Ordered<X>: Xs are Regular and Totally_ordered. The standard-library associative containers require their elements to be ordered unless you explicitly provide a comparison operation.

• Assignable<X,Y>:A Y can be assigned to an X using =.

• Predicate<F,X>:An F can be called for an X yielding a bool.

• Streamable<X>:An X can be read and written using iostreams.

• Movable<X>: An X can be moved; that is, it has a move constructor and a move assignment. In addition, an X is addressable and destructible.

• Copyable<X>:An X is Movable and can also be copied.

• Convertible<X,Y>:An X can be implicitly converted to a Y.

• Common<X,Y>: An X and a Y can unambiguously be converted to a common type called Common_type<X,Y>. This is a formalization of the language rule for compatibility of operands to ?: (§11.1.3). For example, Common_type<Base*,Derived*> is Base* and Common_type<int,long> is long.

• Range<X>: An X that can be used by a range-for (§9.5.1), that is, X must provide members, x.begin() and x.end(), or nonmember equivalents, begin(x) and end(x), with the required semantics.

Obviously, these definitions are informal. In most cases, these concepts are based on standard-library type predicates (§35.4.1), and the ISO C++ standard provides formal definitions (e.g., §iso.17.6.3).

24.4.5. Template Definition Checking

A constraints-check template ensures that a type provides the properties required by the concept. If the implementation of a template in fact uses more properties than its concepts guarantee, we may get type errors. For example, the standard-library find() requires a pair of input iterators as arguments, but we might (incautiously) have defined it like this:

Click here to view code image

template<typename Iter, typename Val>
Iter find(Iter b, Iter e, Val x)
{
       static_assert(Input_iterator<Iter>(),"find(): Iter is not a Forward iterator");
       static_assert(Equality_comparable<Value_type<Iter>,Val>),
                      "find(): value type doesn't match iterator");

       while (b!=e) {
            if (*b==x) return b;
            b = b+1;             // note: not ++b
       }
              return b;
}

Now, b+1 is an error unless b is a random-access iterator (and not just a forward iterator as ensured by the constraints check). However, the constraints check does not help us detect that problem. For example:

Click here to view code image

void f(list<int>& lst, vector<string>& vs)
{
     auto p = find(lst.begin(),lst.end(),1209);        // error: list does not provide +
     auto q = find(vs.begin(),vs.end(),"Cambridge");   // OK: vector provides +
     // ...
}

The call of find() for the list will fail (because + is not defined for the forward iterator provided by list) and the call for the vector will succeed (because b+1 is fine for vector<string>::iterator).

Constraints checks primarily provide a service to the user of a template: the actual template arguments are checked against the template’s requirements. On the other hand, constraints checks do not help a template writer who would like to be sure that the implementation doesn’t use any properties beyond those specified in the concepts. Ideally, the type system would ensure that, but that requires language features that are still in the future. So, how do we test the implementation of a parameterized class or a generic algorithm?

Concepts provide a strong guideline: the implementation should use no property of an argument that isn’t specified by the concepts, so we should test the implementation with arguments that provide the properties specified by the implementation’s concepts, and only those. Such a type is sometimes called an archetype.

So, for the find() example, we look at Forward_iterator and Equality_comparable or at the standard’s definition of the forward-iterator and equal-comparable concepts (§iso.17.6.3.1, §iso.24.2.5). Then, we decide that we need an Iterator type that provides at least:

• A default constructor

• A copy constructor and a copy assignment

• Operators == and !=

• A prefix operator ++

• A type Value_type<Iterator>

• A prefix operator *

• The ability to assign the result of * to a Value_type<Iterator>

• The ability to assign a Value_type<Iterator> to the result of *

This is slightly simplified from the standard-library forward iterator, but sufficient for find(). Constructing that list by looking at the concepts is easy.

Given this list, we need to find or define a type that provides only the desired features. For a forward iterator, as needed by find(), the standard-library forward_list fits the bill perfectly. This is because “forward iterator” was defined to express the idea of something that allows us to iterate through a singly-linked list. It is not uncommon that a popular type is an archetype for a popular concept. If we decide to use an existing type, we have to be careful, though, not to pick a type that is more flexible than required. For example, the typical mistake when testing algorithms, such as find(), is to use a vector. However, the very generality and flexibility that make vector so popular make it unusable as an archetype for many simple algorithms.

If we can’t find an existing type that fits our needs, we must define one ourselves. That is done by going through the list of requirements and defining suitable members:

Click here to view code image

template<typename Val>
struct Forward {        // for checking find()
     Forward();
     Forward(const Forward&);
     Forward operator=(const Forward&);
     bool operator==(const Forward&);
     bool operator!=(const Forward&);
     void operator++();
     Val& operator*();  // simplified: does not handle a proxy for Val
};

template<typename Val>
using Value_type<Forward<Val>> = Val;      // simplified; see §28.2.4

void f()
{
     Forward<int> p = find(Forward<int>{},Forward<int>{},7);
}

At this level of testing, we need not check that these operations actually implement the right semantics. We just check that the template implementation does not rely on properties that it should not.

Here, I have simplified the testing by not introducing an archetype for the Val argument. Instead, I simply used int. Testing nontrivial conversions between an archetype for Val and an archetype for Iter would be significantly more work and most likely not particularly useful.

Writing a test harness that checks the implementation of find() against std::forward_list or X is not trivial, but it is not among the most difficult tasks facing a designer of generic algorithms. Using a relatively small and well-specified set of concepts makes the task manageable. The tests can and should be completely compile-time.

Note that this simple specification and checking strategy leads to find() requiring its iterator argument to have a Value_type type function (§28.2). That allows pointers to be used as iterators. For many template parameters it is important that built-in types can be used as well as user-defined types (§1.2.2, §25.2.1).

24.5. Advice

[1] A template can pass argument types without loss of information; §24.1.

[2] Templates provide a general mechanism for compile-time programming; §24.1.

[3] Templates provide compile-time “duck typing”; §24.1.

[4] Design generic algorithms by “lifting” from concrete examples; §24.2.

[5] Generalize algorithms by specifying template argument requirements in terms of concepts; §24.3.

[6] Do not give unconventional meaning to conventional notation; §24.3.

[7] Use concepts as a design tool; §24.3.

[8] Aim for “plug compatibility” among algorithms and argument type by using common and regular template argument requirements; §24.3.

[9] Discover a concept by minimizing an algorithm’s requirements on its template arguments and then generalizing for wider use; §24.3.1.

[10] A concept is not just a description of the needs of a particular implementation of an algorithm; §24.3.1.

[11] If possible, choose a concept from a list of well-known concepts; §24.3.1, §24.4.4.

[12] The default concept for a template argument is Regular; §24.3.1.

[13] Not all template argument types are Regular; §24.3.1.

[14] A concept requires a semantic aspect; it is not primarily a syntactic notion; §24.3.1, §24.3.2, §24.4.1.

[15] Make concepts concrete in code; §24.4.

[16] Express concepts as compile-time predicates (constexpr functions) and test them using static_assert() or enable_if<>; §24.4.

[17] Use axioms as a design tool; §24.4.1.

[18] Use axioms as a guide for testing; §24.4.1.

[19] Some concepts involve two or more template arguments; §24.4.2.

[20] Concepts are not just types of types; §24.4.2.

[21] Concepts can involve numeric values; §24.4.3.

[22] Use concepts as a guide for testing template definitions; §24.4.5.

25. Specialization

It ain’t what you don’t know that gets you into trouble.

It’s what you know for sure that just ain’t so.

– Mark Twain

• Introduction

• Template Parameters and Arguments

Types as Arguments; Values as Arguments; Operations as Arguments; Templates as Arguments; Default Template Arguments

• Specialization

Interface Specialization; The Primary Template; Order of Specialization; Function Template Specialization

• Advice

25.1. Introduction

Over the last two decades, templates have developed from a relatively simple idea to the backbone of most advanced C++ programming. In particular, templates are key to techniques for

• improving type safety (e.g., by eliminating the use of casts; §12.5);

• raising the general level of abstraction of programs (e.g., by using standard containers and algorithms; §4.4, §4.5, §7.4.3, Chapter 31, Chapter 32); and

• providing more flexible, type-safe, and efficient parameterization of types and algorithms (§25.2.3).

These techniques all critically rely on the ability of template code to use template arguments without overhead and in a type-safe manner. Most techniques also rely on the type deduction mechanisms offered by templates (sometimes called compile-time polymorphism; §27.2). These techniques are the backbone of C++ use in performance-critical areas, such as high-performance numerical computing and embedded systems programming. For mature examples, see the standard library (Part IV).

This chapter and the following two present simple examples of the advanced and/or specialized language features supporting techniques aimed at uncompromised flexibility and performance. Many of these techniques are primarily developed for and used by library implementers. Like most programmers, I prefer to forget about the more advanced techniques most of the time. Where I can, I keep my code simple and rely on libraries so that I can benefit from the use of advanced features in the hands of experts in a given application domain.

Templates are introduced in §3.4. This chapter is part of a sequence presenting templates and their uses:

• Chapter 23 gives a more detailed introduction to templates.

• Chapter 24 discusses generic programming, the most common use of templates.

• Chapter 25 (this chapter) shows how to specialize a template with a set of arguments.

• Chapter 26 focuses on template implementation issues related to name binding.

• Chapter 27 discusses the relation between templates and class hierarchies.

• Chapter 28 focuses on templates as a language for generating classes and functions.

• Chapter 29 presents a larger example of template-based programming techniques.

25.2. Template Parameters and Arguments

A template can take parameters:

• Type parameters of “type type”

• Value parameters of built-in types such as ints (§25.2.2) and pointers to functions (§25.2.3)

• Template parameters of “type template” (§25.2.4)

Type parameters are by far the most common, but value parameters are essential for many important techniques (§25.2.2, §28.3).

A template can take a fixed number of parameters or a variable number. The discussion of variadic templates is postponed until §28.6.

Note that it is common to use short names with initial uppercase letters as names of template type arguments, for example, T, C, Cont, and Ptr. This is acceptable because such names tend to be conventional and restricted to a relatively small scope (§6.3.3). However, when using ALL_CAPS, there is always a chance of clashing with macros (§12.6), so don’t use names that are long enough to clash with likely macro names.

25.2.1. Types as Arguments

A template argument is defined to be a type parameter by prefixing it with typename or class. The result of using either is completely equivalent. Every type (built-in or user-defined) is syntactically acceptable to a template declared to take a type parameter. For example:

Click here to view code image

template<typename T>
void f(T);

template<typename T>
class X {
     // ...
};
f(1);                     // T deduced to be int
f<double>(1);             // T is double
f<complex<double>>(1);    // T is complex<double>

X<double> x1;             // T is double
X<complex<double>> x2;    // T is complex<double>

A type argument is unconstrained; that is, there is nothing in the interface of a class that constrains it to be a certain kind of type or part of a class hierarchy. The validity of an argument type depends exclusively on its use in the templates, providing a form of duck typing (§24.1). You can implement general constraints as concepts (§24.3).

User-defined and built-in types are handled equivalently when used as template arguments. This is essential for allowing us to define templates that work identically for user-defined and builtin types. For example:

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vector<double> x1;             // vector of doubles
vector<complex<double>> x2;    // vector of complex<double>

In particular, there is no space or time overhead implied by using either compared to the other:

• Values of built-in types are not “boxed” into special container objects.

• Values of all types are retrieved directly from a vector without use of potentially expensive (e.g., virtual) “get() functions.”

• Values of user-defined types are not implicitly accessed through references.

To be used as a template argument, a type must be in scope and accessible. For example:

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class X {
     class M { /* ... */ };
     // ...
     void mf();
};

void f()
{
     struct S { /* ... */ };
     vector<S> vs;           // OK
     vector<X::M> vm;        // error: X::M is private
     // ...
}

void M::mf()
{
     vector<S> vs;     // error: no S in scope
     vector<M> vm;     // OK
     // ...
};

25.2.2. Values as Arguments

A template parameter that is not a type or a template is called a value parameter and an argument passed to it a value argument. For example, integer arguments come in handy for supplying sizes and limits:

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template<typename T, int max>
class Buffer {
     T v[max];
public:
     Buffer() { }
     // ...
};

Buffer<char,128> cbuf;
Buffer<int,5000> ibuf;
Buffer<Record,8> rbuf;

Simple and constrained containers such as Buffer can be important where run-time efficiency and compactness are paramount. They avoid the use of free store implied by the use of a more general string or vector while not suffering from the implicit conversions to a pointer like a built-in array (§7.4). The standard-library array (§34.2.1) implements this idea.

An argument for a template value parameter can be (§iso.14.3.2):

• An integral constant expression (§10.4)

• A pointer or a reference to an object or a function with external linkage (§15.2)

• A nonoverloaded pointer to member (§20.6)

• A null pointer (§7.2.2)

A pointer used as a template argument must be of the form &of, where of is the name of an object or a function, or of the form f, where f is the name of a function. A pointer to member must be of the form &X::of, where of is the name of a member. In particular, a string literal is not acceptable as a template argument:

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template<typename T, char* label>
class X {
     // ...
};

X<int,"BMW323Ci"> x1;     // error: string literal as template argument
char lx2[] = "BMW323Ci";
X<int,lx2> x2;            // OK: lx2 has external linkage

This restriction, like the one against floating-point template value arguments, exists to simplify implementation of separately compiled translation units. It is best to think of template value arguments as a mechanism for passing integers and pointers to functions. Resist the temptation to try something more clever. Unfortunately (for no fundamental reason), literal types (§10.4.3) cannot be used as template value parameters. The value template arguments are the mechanism for some more advanced compile-time computation techniques (Chapter 28).

An integer template argument must be a constant. For example:

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constexpr int max = 200;

void f(int i)
{
     Buffer<int,i> bx;      // error: constant expression expected
     Buffer<int,max> bm;    // OK: constant expression
     // ...
}

Conversely, a value template parameter is a constant within the template so that an attempt to change the value of a parameter is an error. For example:

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template<typename T, int max>
class Buffer {
     T v[max];
public:
     Buffer(int i) { max = i; }  // error: attempt to assign to template value argument
     // ...
};

A type template parameter can be used as a type later in a template parameter list. For example:

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template<typename T, T default_value>
class Vec {
     // ...
};

Vec<int,42> c1;
Vec<string,""> c2;

This becomes particularly useful when combined with a default template argument (§25.2.5); for example:

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template<typename T, T default_value = T{}>
class Vec {
     // ...
};

Vec<int,42> c1;
Vec<int> c11;                // default_value is int{}, that is, 0
Vec<string,"fortytwo"> c2;
Vec<string> c22;             // default_value is string{}; that is, ""

25.2.3. Operations as Arguments

Consider a slightly simplified version of the standard-library map (§31.4.3):

template<typename Key, Class V>
class map {
     // ...
};

How do we supply comparison criteria for Keys?

• We can’t hardwire a comparison criterion into the container because the container can’t (in general) impose its needs on the element types. For example, by default, the map uses < for comparison, but not all Keys have a < that we would want to use.

• We can’t hardwire an ordering criterion into the Key type because (in general) there are many different ways of ordering elements based on a key. For example, one of the most common Key types is string and strings can be ordered based on a variety of criteria (e.g., case sensitive and case insensitive).

Consequently, a sorting criterion is not built into the container type or into the element type. In principle, the notion of sorting criteria for a map could be represented as:

[1] A template value argument (e.g., a pointer to a comparison function)

[2] A template type argument to the map template determining the type of a comparison object

At first glance, the first solution (pass a comparison object of a specific type) seems simpler. For example:

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template<typename Key, typename V, bool(*cmp)(const Key&, const Key&)>
class map {
public:
     map();
     // ...
};

This map requires a user to supply the comparison as a function:

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bool insensitive(const string& x, const string& y)
{
     // compare case insensitive (e.g., "hello" equals "HellO")
}

map<string,int,insensitive> m;         // compare using insensitive()

However, this is not very flexible. In particular, the designer of map will have to decide whether to compare the (unknown) Key type using a pointer to function or a function object of some specific type. Also, because the argument types of the comparison operator must depend on the Key type, it can be hard to provide a default comparison criterion.

Consequently, the second alternative (pass the type of the comparison as a template type parameter) is the more common and the one used in the standard library. For example:

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template<typename Key, Class V, typename Compare = std::less<Key>>
class map {
public:
     map() { /* ... */ }                     // use the default comparison
     map(Compare c) :cmp{c} { /* ... */ }    // override the default
     // ...
     Compare cmp {};                         // default comparison
};

The most common case, comparing using less-than, is the default. If we want a different comparison criterion, we can supply it as a function object (§3.4.3):

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map<string,int> m1;                              // use the default comparison (less<string>)

map<string,int,std::greater<string>> m2;         // compare using greater<string>()

Function objects can carry state. For example:

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Complex_compare f3 {"French",3};                 // make a comparison object (§25.2.5)
map<string,int,Complex_compare> m3 {f3};         // compare using f3()

We can also use pointers to functions, including lambdas that can convert to a pointer to function (§11.4.5). For example:

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using Cmp = bool(*)(const string&,const string&);
map<string,int,Cmp> m4 {insensitive};            // compare using a pointer to function

map<string,int,Cmp> m4 {[](const string& a, const string b) { return a>b; } };

Passing the comparison operations as a function object has significant benefits compared to passing pointers to functions:

• A simple class member function defined in-class is trivial to inline, whereas inlining a call through a pointer to function requires exceptional attention from a compiler.

• A function object with no data members can be passed with no run-time cost.

• Several operations can be passed as a single object with no additional run-time cost.

The comparison criterion for a map is just an example. However, the technique used to pass it is general and very widely used to parameterize classes and functions with “policies.” Examples include actions for algorithms (§4.5.4, §32.4), allocators for containers (§31.4, §34.4), and deleters for unique_ptr (§34.3.1). We have the same design alternatives when we need to specify arguments for a function template, such as sort(), and the standard library chooses alternative [2] for those cases also (e.g., see §32.4).

If we had only one use of a comparison criterion in our program, it might make sense to use a lambda to express the function object version a bit more tersely:

map<string,int,Cmp> c3 {[](const string& x, const string& y) const { return x<y; }}; // error

Unfortunately, that doesn’t work because there is no conversion of a lambda to a function object type. We could name the lambda and then use that name:

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auto cmp = [](const string& x, const string& y) const { return x<y; }
map<string,int,decltype(cmp)> c4 {cmp};

I find naming operations useful from a design and maintenance point of view. Also, anything named and declared nonlocally might find other uses.

25.2.4. Templates as Arguments

Sometimes it is useful to pass templates – rather than classes or values – as template arguments. For example:

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template<typename T, template<typename>class C>
class Xrefd {
     C<T> mems;
     C<T*> refs;
     // ...
};

template<typename T>
     using My_vec = vector<T>;       // use default allocator

Xrefd<Entry,My_vec> x1;    // store cross references for Entrys in a vector

template<typename T>
class My_container {
     // ...
};

Xrefd<Record,My_container> x2; // store cross references for Records in a My_container

To declare a template as a template parameter, we must specify its required arguments. For example, we specify that Xrefd’s template parameter C is a template class that takes a single type argument. If we didn’t, we wouldn’t be able to use specializations of C. The point of using a template as a template parameter is usually that we want to instantiate it with a variety of argument types (such as T and T* in the previous example). That is, we want to express the member declarations of a template in terms of another template, but we want that other template to be a parameter so that it can be specified by users.

Only class templates can be template arguments.

The common case in which a template needs only a container or two is often better handled by passing the container types (§31.5.1). For example:

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template<typename C, typename C2>
class Xrefd2 {
     C mems;
     C2 refs;
     // ...
};

Xrefd2<vector<Entry>,set<Entry*>> x;

Here, the value types of C and C2 can be obtained by a simple type function (§28.2) for obtaining the type of elements of a container, for example, Value_type<C>. This is the technique used for the standard-library container adaptors, such as queue (§31.5.2).

25.2.5. Default Template Arguments

Explicitly specifying the comparison criterion for each use of map is tedious – especially as less<Key> is typically the best choice. We can specify less<Key> to be the default type for the Compare template argument, so that only uncommon comparison criteria have to be explicitly specified:

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template<typename Key, Class V, typename Compare = std::less<Key>>
class map {
public:
     explicit map(const Compare& comp ={});
     // ...
};

map<string,int> m1;               // will use less<string> for comparisons
map<string,int,less<string>> m2;  // same type as m1

struct No_case {
     // define operator()() to do case-insensitive string comparison
};

map<string,int,No_case> m3;       // m3 is of a different type from m1 and m2

Note how the default map constructor creates a default comparison object, Compare{}. That’s the common case. If we want a more elaborate construction, we must do so explicitly. For example:

map<string,int,Complex_compare> m {Complex_compare{"French",3}};

The semantic checking of a default argument for a template parameter is done only if that default argument is actually used. In particular, as long as we refrain from using the default template argument less<Key>, we can compare() values of a type X for which less<X> wouldn’t compile. This point is crucial in the design of the standard containers (e.g., std::map), which rely on a template argument to specify default values (§31.4).

Just as for default function arguments (§12.2.5), the default template arguments can be specified and supplied for trailing arguments only:

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void f1(int x = 0, int y);       // error: default argument not trailing
void f2(int x = 0, int y = 1);   // OK

f2(,2);    // syntax error
f2(2);     // call f(2,1);

template<typename T1 = int, typename T2>
class X1 {        // error: default argument not trailing
     // ...
};

template<typename T1 = int, typename T2 = double>
class X2 {    // OK
     // ...
};

X2<,float> v1; // syntax error
X2<float> v2;  // v2 is an X2<float,double>

Not allowing an “empty” argument to mean “use the default” was a deliberate tradeoff between flexibility and the opportunity for obscure errors.

The technique of supplying a policy through a template argument and then defaulting that argument to supply the most common policy is almost universal in the standard library (e.g., §32.4). Curiously enough, it is not used for basic_string (§23.2, Chapter 36) comparisons. Instead, the standard-library string relies on char_traits (§36.2.2). Similarly, the standard algorithms rely on iterator_traits (§33.1.3) and the standard-library containers rely on allocators (§34.4). The use of traits is presented in §28.2.4.

25.2.5.1. Default Function Template Arguments

Naturally, default template arguments can also be useful for function templates. For example:

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template<typename Target =string, typename Source =string>
Target to(Source arg)       // convert Source to Target
{
  stringstream interpreter;
  Target result;

  if (!(interpreter << arg)                // write arg into stream
      || !(interpreter >> result)          // read result from stream
      || !(interpreter >> std::ws).eof())  // stuff left in stream?
      throw runtime_error{"to<>() failed"};

  return result;
}

A function template argument needs to be explicitly mentioned only if it cannot be deduced or if there is no default, so we can write:

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auto x1 = to<string,double>(1.2);  // very explicit (and verbose)
auto x2 = to<string>(1.2);         // Source is deduced to double
auto x3 = to<>(1.2);               // Target is defaulted to string; Source is deduced to double
auto x4 = to(1.2);                 // the <> is redundant

If all function template arguments are defaulted, the <> can be left out (exactly as in function template specializations; §25.3.4.1).

This implementation of to() is a bit heavyweight for combinations of simple types, such as to<double>(int), but improved implementations can be supplied as specializations (§25.3). Note that to<char>(int) will not work because char and int do not share a string representation. For conversion among scalar numeric types, I tend to prefer narrow_cast<>() (§11.5).

25.3. Specialization

By default, a template gives a single definition to be used for every template argument (or combination of template arguments) that a user can think of. This doesn’t always make sense for someone writing a template. I might want to say, “If the template argument is a pointer, use this implementation; if it is not, use that implementation,” or “Give an error unless the template argument is a pointer derived from class My_base.” Many such design concerns can be addressed by providing alternative definitions of the template and having the compiler choose between them based on the template arguments provided where they are used. Such alternative definitions of a template are called user-defined specializations, or simply user specializations. Consider likely uses of a Vector:

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template<typename T>
class Vector { // general vector type
     T* v;
     int sz;
public:
     Vector();
     explicit Vector(int);

     T& elem(int i) { return v[i]; }
     T& operator[](int i);

     void swap(Vector&);
     // ...
};

Vector<int> vi;
Vector<Shape*> vps;
Vector<string> vs;
Vector<char*> vpc;
Vector<Node*> vpn;

In such code, most Vectors will be Vectors of some pointer type. There are several reasons for this, but the primary reason is that to preserve run-time polymorphic behavior, we must use pointers (§3.2.2, §20.3.2). That is, anyone who practices object-oriented programming and uses type-safe containers (such as the standard-library containers) will end up with a lot of containers of pointers.

The default behavior of most C++ implementations is to replicate the code for template functions. This is usually good for run-time performance, but unless care is taken, it leads to code bloat in critical cases such as the Vector example.

Fortunately, there is an obvious solution. Containers of pointers can share a single implementation. This can be expressed through specialization. First, we define a version (a specialization) of Vector for pointers to void:

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template<>
class Vector<void*>{       // complete specialization
     void** p;
     // ...
     void*& operator[](int i);
};

This specialization can then be used as the common implementation for all Vectors of pointers. Another use would be to implement unique_ptr<T> based on a single shared implementation class storing a void*.

The template<> prefix says that this is a specialization that can be specified without a template parameter. The template arguments for which the specialization is to be used are specified in <> brackets after the name. That is, the <void*> says that this definition is to be used as the implementation of every Vector for which T is void*.

The Vector<void*> is a complete specialization. That is, there is no template parameter to specify or deduce when we use the specialization; Vector<void*> is used for Vectors declared like this:

Vector<void*> vpv;

To define a specialization that is used for every Vector of pointers and only for Vectors of pointers, we can write:

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template<typename T>
class Vector<T*> : private Vector<void*>{  // partial specialization
public:
     using Base = Vector<void*>;

     Vector() {}
     explicit Vector(int i) : Base(i) {}

     T*& elem(int i) { return reinterpret_cast<T*&>(Base::elem(i)); }
     T*& operator[](int i) { return reinterpret_cast<T*&>(Base::operator[](i));}

     // ...
};

The specialization pattern <T*> after the name says that this specialization is to be used for every pointer type; that is, this definition is to be used for every Vector with a template argument that can be expressed as T*. For example:

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Vector<Shape*> vps;   // <T*> is <Shape*> so T is Shape
Vector<int**> vppi;   // <T*> is <int**> so T is int*

A specialization with a pattern containing a template parameter is called a partial specialization in contrast to complete specializations (as in the definition of vector<void*>), where “the pattern” is simply a specific type.

Note that when a partial specialization is used, a template parameter is deduced from the specialization pattern; the template parameter is not simply the actual template argument. In particular, for Vector<Shape*>, T is Shape and not Shape*.

Given this partial specialization of Vector, we have a shared implementation for all Vectors of pointers. The Vector<T*> class is simply an interface to Vector<void*> implemented exclusively through derivation and inline expansion.

It is important that this refinement of the implementation of Vector be achieved without affecting the interface presented to users. Specialization is a way of specifying alternative implementations for different uses of a common interface. Naturally, we could have given the general Vector and the Vector of pointers different names. However, when I tried that, many people who should have known better forgot to use the pointer classes and found their code much larger than expected. In this case, it is much better to hide the crucial implementation details behind a common interface.

This technique proved successful in curbing code bloat in real use. People who do not use a technique like this (in C++ or in other languages with similar facilities for type parameterization) have found that replicated code can cost megabytes of code space even in moderately sized programs. By eliminating the time needed to compile those additional versions of the Vector operations, this technique can also cut compile and link times dramatically. Using a single specialization to implement all lists of pointers is an example of the general technique of minimizing code bloat by maximizing the amount of shared code.

Some compilers are getting smart enough to perform this particular optimization without help from the programmer, but the technique is generally applicable and useful.

Variants of the technique of using a single run-time representation for values of a number of types and relying on the (static) type system to ensure that they are used only according to their declared type has been called type erasure. In the context of C++, it was first documented in the original template paper [Stroustrup,1988].

25.3.1. Interface Specialization

Sometimes, a specialization is not an algorithmic optimization, but a modification of an interface (or even a representation). For example, the standard library complex uses specializations to adjust the set of constructors and the argument types for important operations for important specializations (such as complex<float> and complex<double>). The general (primary) template (§25.3.1.1) looks like this:

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template<typename T>
class complex {
public:
     complex(const T& re = T{}, const T& im = T{});
     complex(const complex&);                 // copyconstructor
     template<typename X>
          complex(const complex<X>&);         // conversion from complex<X> to complex<T>

     complex& operator=(const complex&);
     complex<T>& operator=(const T&);
     complex<T>& operator+=(const T&);
     // ...
     template<typename X>
          complex<T>& operator=(const complex<X>&);
     template<typename X>
          complex<T>& operator+=(const complex<X>&);
     // ...
};

Note that the scalar assignment operators take reference arguments. That’s not efficient for floats, so complex<float> passes those by value:

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template<>
class complex<float> {
public:
     // ...
     complex<float>& operator= (float);
     complex<float>& operator+=(float);
     // ...
     complex<float>& operator=(const complex<float>&);
     // ...
};

For complex<double>, that same optimization applies. In addition, conversions from complex<float> and complex<long double> are provided (as described in §23.4.6):

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template<>
class complex<double> {
public:
     constexpr complex(double re = 0.0, double im = 0.0);
     constexpr complex(const complex<float>&);
     explicit constexpr complex(const complex<long double>&);
     // ...
};

Note that these specialized constructors are constexpr, making complex<double> a literal type. We could not do that for the general complex<T>. Also, this definition takes advantage of the knowledge that conversion from complex<float> to complex<double> is safe (it never narrows), so that we can have an implicit constructor from complex<float>. However, the constructor from complex<long double> is explicit to make narrowing less likely.

25.3.1.1. Implementation Specialization

Specialization can be used to provide alternative implementations of a class template for a specific set of template parameters. In that case, a specialization can even provide a representation that differs from that of the general template. For example:

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template<typename T, int N>
class Matrix;     // N-dimensional Matrix of Ts

template<typename T,0>
class Matrix {    // specialization for N==1
     T val;
     // ...
};

template<typename T,1>
class Matrix {    // specialization for N=1
     T* elem;
     int sz;   // number of elements
     // ...
};

template<typename T,2>
class Matrix {    // specialization for N=2
     T* elem;
     int dim1; // number of rows
     int dim2; // number of columns
     // ...
};

25.3.2. The Primary Template

When we have both a general definition of a template and specializations defining implementations for specific sets of template arguments, we refer to the most general template as the primary template. The primary template defines the interface for all specializations (§iso.14.5.5). That is, the primary template is the one used to determine if a use is valid and takes part in overload resolution. Only after a primary template has been chosen are specializations considered.

The primary template must be declared before any specialization. For example:

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template<typename T>
class List<T*>{
     // ...
};

template<typename T>
class List {         // error: primary template after specialization
     // ...
};

The critical information supplied by the primary template is the set of template parameters that the user must supply to use it or any of its specializations. If we have defined a constraints check for a template (§24.4), the primary template is where it belongs because concepts are something a user cares about and must understand to use the template. For example:

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template<typename T>
class List {
     static_assert(Regular<T>(),"List<T>: T must be Regular");
     // ...
};

For technical reasons (because the language doesn’t recognize constraints checks for what they are), a constraints check needs to be replicated in every specialization.

A declaration of the primary template is sufficient to allow the definition of a specialization:

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template<typename T>
class List;          // not a definition

template<typename T>
class List<T*>{
     // ...
};

If used, the primary template must be defined somewhere (§23.7). If the primary template is never instantiated, it need not be defined. This can be used to define a template for which only a fixed set of alternative arguments are accepted. If a user specializes a template, that specialization must be in scope for every use of the template with the type for which it was specialized. For example:

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template<typename T>
class List {
     // ...
};

List<int*> li;

template<typename T>
class List<T*>{      // error: specialization used before defined
     // ...
};

Here, List was specialized for int* after List<int*> had been used.

It is essential that every use of a template for a given set of template arguments be implemented by the same specialization. If not, the type system is broken, so that identical uses of a template in different places may yield different results and objects created in different parts of a program may not be compatible. Clearly that would be disastrous, so a programmer must take care that explicit specialization is consistent throughout a program. In principle, implementations are capable of detecting inconsistent specialization, but the standard does not require them to and some don’t.

All specializations of a template must be declared in the same namespace as the primary template. If used, a specialization that is explicitly declared (as opposed to generated from a more general template) must also be explicitly defined somewhere (§23.7). In other words, explicitly specializing a template implies that no (other) definition is generated for that specialization.

25.3.3. Order of Specialization

One specialization is more specialized than another if every argument list that matches its specialization pattern also matches the other, but not vice versa. For example:

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template<typename T>
     class Vector;           // general; the primary template
template<typename T>
     class Vector<T*>;       // specialized for any pointer
template<>
     class Vector<void*>;    // specialized for void*

Every type can be used as a template argument for the most general Vector, but only pointers can be used for Vector<T*> and only void*s can be used for Vector<void*>.

The most specialized version will be preferred over the others in declarations of objects, pointers, etc. (§25.3).

A specialization pattern can be specified in terms of types composed using the constructs allowed for template parameter deduction (§23.5.2).

25.3.4. Function Template Specialization

Specialization is also useful for template functions (§25.2.5.1). However, we can overload functions, so we see less specialization. Furthermore, C++ supports only complete specialization for functions (§iso.14.7), so we use overloading where we might have tried partial specialization.

25.3.4.1. Specialization and Overloading

Consider the Shell sort from §12.5 and §23.5. Those versions compare elements using < and swap elements using detailed code. A better definition would be:

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template<typename T>
bool less(T a, T b)
{
     return a<b;
}

template<typename T>
void sort(Vector<T>& v)
{
     const size_t n = v.size();

     for (int gap=n/2; 0<gap; gap/=2)
           for (int i=gap; i!=n; ++i)
                 for (int j=i–gap; 0<=j; j–=gap)
                       if (less(v[j+gap],v[j]))
                             swap(v[j],v[j+gap]);
}

This does not improve the algorithm itself, but it allows improvements to its implementation. We now have less and swap as named entities for which we can provide improved versions. Such names are often referred to as customization points.

As written, sort() will not sort a Vector<char; > correctly because < will compare the two char*s. That is, it will compare the addresses of the first char in each string. Instead, we would like it to compare the characters pointed to. A simple specialization of less() for const char* will take care of that:

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template<>
bool less<const char*>(const char* a, const char* b)
{
     return strcmp(a,b)<0;
}

As for classes (§25.3), the template<> prefix says that this is a specialization that can be specified without a template parameter. The <const char*> after the template function name means that this specialization is to be used in cases where the template argument is const char*. Because the template argument can be deduced from the function argument list, we need not specify it explicitly. So, we can simplify the definition of the specialization:

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template<>
bool less<>(const char* a, const char* b)
{
     return strcmp(a,b)<0;
}

Given the template<> prefix, the second empty <> is redundant, so we would typically simply write:

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template<>
bool less(const char* a, const char* b)
{
     return strcmp(a,b)<0;
}

I prefer this shorter form of declaration. We can go further still. With this last version the distinction between specialization and overloading has become razor thin and largely irrelevant, so we can simply write:

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bool less(const char* a, const char* b)
{
     return strcmp(a,b)<0;
}

Now that we have “specialized” less() to a version that is semantically correct, we can consider what we might do for swap(). The standard-library swap() is correct for our use and has already been optimized for every type that has efficient move operations. Therefore, when we used swap() instead of the three potentially expensive copy operations, we improved performance for a large number of argument types.

Specialization comes in handy when an irregularity of an argument type causes the general algorithm to give an undesired result (such as less() for C-style strings). These “irregular types” are often the built-in pointer and array types.

25.3.4.2. Specialization That Is Not Overloading

How does a specialization differ from overloading? From a technical point of view, they differ because individual functions take part in overloading whereas only the primary template takes part in specialization (§25.3.1.1). However, I can’t think of an example where that makes a practical difference.

There are a few uses of function specializations. For example, we can select among functions taking no arguments:

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template<typename T> T max_value();   // no definition

template<> constexpr int max_value<int>() { return INT_MAX; }
template<> constexpr char max_value<char>() { return CHAR_MAX; }
// ...

template<typename Iter>
Iter my_algo(Iter p)
{
      auto x = max_value<Value_type<Iter>>();   // works for types with specialized max_value()
      // ...
}

I used the type function Value_type<> to get the type of the object pointed to by an Iter (§24.4.2).

To get a roughly equivalent effect with overloading, we would have to pass a dummy (unused) argument. For example:

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int max2(int) { return INT_MAX; }
char max2(char) { return INT_MAX; }

template<typename Iter>
Iter my_algo2(Iter p)
{
      auto x = max2(Value_type<Iter>{});     // works for the types for which we overload max2()
      // ...
}

25.4. Advice

[1] Use templates to improve type safety; §25.1.

[2] Use templates to raise the level of abstraction of code; §25.1.

[3] Use templates to provide flexible and efficient parameterization of types and algorithms; §25.1.

[4] Remember that value template arguments must be compile-time constants; §25.2.2.

[5] Use function objects as type arguments to parameterize types and algorithms with “policies”; §25.2.3.

[6] Use default template arguments to provide simple notation for simple uses; §25.2.5.

[7] Specialize templates for irregular types (such as arrays); §25.3.

[8] Specialize templates to optimize for important cases; §25.3.

[9] Define the primary template before any specialization; §25.3.1.1.

[10] A specialization must be in scope for every use; §25.3.1.1.

26. Instantiation

For every complex problem, there is an answer that is clear, simple, and wrong.

– H. L. Mencken

• Introduction

• Template Instantiation

When Is Instantiation Needed?; Manual Control of Instantiation

• Name Binding

Dependent Names; Point-of-Definition Binding; Point-of-Instantiation Binding; Multiple Instantiation Points; Templates and Namespaces; Overaggressive ADL; Names from Base Classes

• Advice

26.1. Introduction

One of the great strengths of templates is that they are an extremely flexible mechanism for composition of code. To produce impressive code quality, a compiler combines code (information) from

• the template definition and its lexical environment,

• the template arguments and their lexical environment, and

• the environment of the template’s use.

The key to the resulting performance is that the compiler is able to look at code from those contexts simultaneously and weave it together in ways that use all information available. The problem with this is that code in a template definition isn’t as localized as we would prefer (all other things being equal). Sometimes, we can get confused about what a name used in a template definition refers to:

• Is it a local name?

• Is it a name associated with a template argument?

• Is it a name from a base class in a hierarchy?

• Is it a name from a named namespace?

• Is it a global name?

This chapter discusses such questions related to name binding and considers their implications for programming styles.

• Templates were introduced in §3.4.1 and §3.4.2.

• Chapter 23 gives a detailed introduction to templates and the use of template arguments.

• Chapter 24 introduces generic programming and the key notion of concepts.

• Chapter 25 presents details of class templates and function templates and introduces the notion of specialization.

• Chapter 27 discusses the relationship between templates and class hierarchies (supporting generic and object-oriented programming).

• Chapter 28 focuses on templates as a language for generating classes and functions.

• Chapter 29 presents a larger example of how the language facilities and programming techniques can be used in combination.

26.2. Template Instantiation

Given a template definition and a use of that template, it is the implementation’s job to generate correct code. From a class template and a set of template arguments, the compiler needs to generate the definition of a class and the definitions of those of its member functions that were used in the program (and only those; §26.2.1). From a template function and a set of template arguments, a function needs to be generated. This process is commonly called template instantiation.

The generated classes and functions are called specializations. When we need to distinguish between generated specializations and specializations explicitly written by the programmer (§25.3), we refer to generated specializations and explicit specializations, respectively. An explicit specialization is often referred to as a user-defined specialization, or simply a user specialization.

To use templates in nontrivial programs, a programmer must understand the basics of how names used in a template definition are bound to declarations and how source code can be organized (§23.7).

By default, the compiler generates classes and functions from the templates used in accordance with the name-binding rules (§26.3). That is, a programmer need not state explicitly which versions of which templates must be generated. This is important because it is not easy for a programmer to know exactly which versions of a template are needed. Often, templates that the programmer hasn’t even heard of are used in the implementation of libraries, and sometimes templates that the programmer does know of are used with unknown template argument types. For example, the standard-library map (§4.4.3, §31.4.3) is implemented in terms of a red-black tree template with data types and operations unknown to all but the most curious user. In general, the set of generated functions needed can be known only by recursive examination of the templates used in application code libraries. Computers are better suited than humans for doing such analysis.

On the other hand, it is sometimes important for a programmer to be able to state specifically where code should be generated from a template (§26.2.2). By doing so, the programmer gains detailed control over the context of the instantiation.

26.2.1. When Is Instantiation Needed?

It is necessary to generate a specialization of a class template only if the class’s definition is needed (§iso.14.7.1). In particular, to declare a pointer to some class, the actual definition of a class is not needed. For example:

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class X;
X* p;    // OK: no definition of X needed
X a;     // error: definition of X needed

When defining template classes, this distinction can be crucial. A template class is not instantiated unless its definition is actually needed. For example:

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template<typename T>
class Link {
     Link* suc;   // OK: no definition of Link needed (yet)
     // ...
};

Link<int>* pl;    // no instantiation of Link<int> needed (yet)

Link<int> lnk;    // now we need to instantiate Link<int>

A place where a template is used defines a point of instantiation (§26.3.3).

An implementation instantiates a template function only if that function has been used. By “used” we mean “called or had its address taken.” In particular, instantiation of a class template does not imply the instantiation of all of its member functions. This allows the programmer an important degree of flexibility when defining a template class. Consider:

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template<typename T>
class List {
     // ...
     void sort();
};

class Glob {
     // ... no comparison operators ...
};

void f(List<Glob>& lb, List<string>& ls)
{
     ls.sort();
     // ... use operations on lb, but not lb.sort() ...
}

Here, List<string>::sort() is instantiated, but List<Glob>::sort() isn’t. This both reduces the amount of code generated and saves us from having to redesign the program. Had List<Glob>::sort() been generated, we would have had to either add the operations needed by List::sort() to Glob, redefine sort() so that it wasn’t a member of List (the better design anyway), or use some other container for Globs.

26.2.2. Manual Control of Instantiation

The language does not require any explicit user action to achieve template instantiation. However, it does provide two mechanisms to help the user take control when needed. The need sometimes arises from a wish to

• optimize the compile-and-link process by eliminating redundant replicated instantiations, or

• know exactly which point of instantiation is used to eliminate surprises from complicated name-binding contexts.

An explicit instantiation request (often simply called an explicit instantiation) is a declaration of a specialization prefixed by the keyword template (not followed by <):

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template class vector<int>;                   // class
template int& vector<int>::operator[](int);   // member function
template int convert<int,double>(double);     // nonmember function

A template declaration starts with template<, whereas plain template starts an instantiation request. Note that template prefixes a complete declaration; just stating a name is not sufficient:

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template vector<int>::operator[];  // syntax error
template convert<int,double>;      // syntax error

As in template function calls, the template arguments that can be deduced from the function arguments can be omitted (§23.5.1). For example:

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template int convert<int,double>(double);   // OK (redundant)
template int convert<int>(double);          // OK

When a class template is explicitly instantiated, every member function is also instantiated.

The link-time and recompilation efficiency impact of instantiation requests can be significant. I have seen examples in which bundling most template instantiations into a single compilation unit cut the compile time from a number of hours to the equivalent number of minutes.

It is an error to have two definitions for the same specialization. It does not matter if such multiple specializations are user-defined (§25.3), implicitly generated (§23.2.2), or explicitly requested. However, a compiler is not required to diagnose multiple instantiations in separate compilation units. This allows a smart implementation to ignore redundant instantiations and thereby avoid problems related to composition of programs from libraries using explicit instantiation. However, implementations are not required to be smart. Users of “less smart” implementations must avoid multiple instantiations. The worst that will happen if they don’t is that their program won’t link; there will be no silent changes of meaning.

To complement explicit instantiation requests, the language provides explicit requests not to instantiate (usually called extern templates). The obvious use is to have one explicit instantiation for a specialization and use extern templates for its use in other translation units. This mirrors the classical use of one definition and many declarations (§15.2.3). For example:

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#include "MyVector.h"

extern template class MyVector<int>;   // suppresses implicit instantiation
                                       // explicitly instantiate elsewhere
void foo(MyVector<int>& v)
{
     // ... use the vector in here ...
}

The “elsewhere” might look something like this:

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#include "MyVector.h"

template class MyVector<int>;    // instantiate in this translation unit; use this point of instantiation

In addition to generating specializations for all members of a class, the explicit instantiation also determines a single point of instantiation so that other points of instantiation (§26.3.3) can be ignored. One use of this is to place the explicit instantiation in a shared library.

26.3. Name Binding

Define template functions to minimize dependencies on nonlocal information. The reason is that a template will be used to generate functions and classes based on unknown types and in unknown contexts. Every subtle context dependency is likely to surface as a problem for somebody – and that somebody is unlikely to want to know the implementation details of the template. The general rule of avoiding global names as much as possible should be taken especially seriously in template code. Thus, we try to make template definitions as self-contained as possible and to supply much of what would otherwise have been global context in the form of template arguments (e.g., traits; §28.2.4, §33.1.3). Use concepts to document dependencies on template arguments (§24.3).

However, it is not unusual that some nonlocal names must be used to achieve the most elegant formulation of a template. In particular, it is more common to write a set of cooperating template functions than to write just one self-contained function. Sometimes, such functions can be class members, but not always. Sometimes, nonlocal functions are the best choice. Typical examples of that are sort()’s calls to swap() and less() (§25.3.4). The standard-library algorithms are a large-scale example (Chapter 32). When something needs to be nonlocal, prefer a named namespace to the global scope. Doing so preserves some locality.

Operations with conventional names and semantics, such as +, *, [], and sort(), are another source of nonlocal name use in a template definition. Consider:

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bool tracing;

template<typename T>
T sum(std::vector<T>& v)
{
    T t {};
    if (tracing)
          cerr << "sum(" << &v << ")\n";
    for (int i = 0; i!=v.size(); i++)
          t = t + v[i];
    return t;
}
// ...

#include<quad.h>

void f(std::vector<Quad>& v)
{
     Quad c = sum(v);
}

The innocent-looking template function sum() depends on several names that are not explicitly specified in its definition, such as tracing, cerr, and the + operator. In this example, + is defined in <quad.h>:

Quad operator+(Quad,Quad);

Importantly, nothing related to Quad is in scope when sum() is defined, and the writer of sum() cannot be assumed to know about class Quad. In particular, the + may be defined later than sum() in the program text, and even later in time.

The process of finding the declaration for each name explicitly or implicitly used in a template is called name binding. The general problem with template name binding is that three contexts are involved in a template instantiation and they cannot be cleanly separated:

[1] The context of the template definition

[2] The context of the argument type declaration

[3] The context of the use of the template

When defining a function template, we want to assure that enough context is available for the template definition to make sense in terms of its actual arguments without picking up “accidental stuff” from the environment of a point of use. To help with this, the language separates names used in a template definition into two categories:

[1] Dependent names: names that depend on a template parameter. Such names are bound at a point of instantiation (§26.3.3). In the sum() example, the definition of + can be found in the instantiation context because it takes operands of the template argument type.

[2] Nondependent names: names that don’t depend on a template parameter. Such names are bound at the point of definition of the template (§26.3.2). In the sum() example, the template vector is defined in the standard header <vector>, and the Boolean tracing is in scope when the definition of sum() is encountered by the compiler.

To be considered, both dependent and independent names must either be in scope at their point of use or be found by argument-dependent lookup (ADL; §14.2.4).

The following subsections go into considerable technical detail about how dependent and non-dependent names in a template definition are bound for a specialization. For complete details, see §iso.14.6.

26.3.1. Dependent Names

The simplest definition of “N depends on a template parameter T” would be “N is a member of T.” Unfortunately, this doesn’t quite suffice; addition of Quads (§26.3) is a counter-example. Consequently, a function call is said to depend on a template argument if and only if one of these conditions holds:

[1] The type of the actual argument depends on a template parameter T according to the type deduction rules (§23.5.2), for example, f(T(1)), f(t), f(g(t)), and f(&t), assuming that t is a T.

[2] The function called has a parameter that depends on T according to the type deduction rules (§23.5.2), for example, f(T), f(list<T>&), and f(const T*).

Basically, the name of a called function is dependent if it is obviously dependent by looking at its arguments or at its formal parameters. For example:

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template<typename T>
T f(T a)
{
     return g(a);   // OK: a is a dependent name and therefore so is g
}

class Quad { /* ... */ };
void g(Quad);

int z = f(Quad{2});        // f's g is bound to g(Quad)

A call that by coincidence has an argument that matches an actual template parameter type is not dependent. For example:

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class Quad { /* ... */ };

template<typename T>
T ff(T a)
{
      return gg(Quad{1});    // error: no gg() in scope and gg(Quad{1}) doesn't depend on T
}

int gg(Quad);

int zz = ff(Quad{2});

Had gg(Quad{1}) been considered dependent, its meaning would have been most mysterious to a reader of the template definition. If a programmer wants gg(Quad) to be called, gg(Quad)’s declaration should be placed before the definition of ff() so that gg(Quad) is in scope when ff() is analyzed. This is exactly the same rule as for non-template function definitions (§26.3.2).

By default, a dependent name is assumed to name something that is not a type. So, to use a dependent name as a type, you have to say so, using the keyword typename. For example:

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template<typename Container>
void fct(Container& c)
{
     Container::value_type v1 = c[7]; // syntax error: value_type is assumed to be a non-type name
     typename Container::value_type v2 = c[9];  // OK: value_type assumed to name a type
     auto v3 = c[11];                           // OK: let the compiler figure it out
     // ...
}

We can avoid such awkward use of typename by introducing a type alias (§23.6). For example:

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template<typename T>
using Value_type<T> = typename T::value_type;

template<typename Container>
void fct2(Container& c)
{
     Value_type<Container> v1 = c[7]; // OK
     // ...
}

Naming a member template after a . (dot), –>, or :: requires similar use of the keyword template. For example:

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class Pool {   // some allocator
public:
     template<typename T> T* get();
     template<typename T> void release(T*);
     // ...
};

template<typename Alloc>
void f(Alloc& all)
{
     int* p1 = all.get<int>();              // syntax error: get is assumed to name a non-template
     int* p2 = all.template get<int>();     // OK: get() is assumed to be a template
     // ...
}

void user(Pool& pool){
{
     f(pool);
     // ...
}

Compared to the use of typename to explicitly state that a name is assumed to name a type, the use of template to explicitly state that a name is assumed to name a template is rare. Note the difference in the placement of the disambiguating keyword: typename appears before the qualified name and template immediately before the template name.

26.3.2. Point-of-Definition Binding

When the compiler sees a template definition, it determines which names are dependent (§26.3.1). If a name is dependent, looking for its declaration is postponed until instantiation time (§26.3.3).

Names that do not depend on a template argument are treated like names that are not in templates; they must be in scope (§6.3.4) at the point of definition. For example:

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int x;

template<typename T>
T f(T a)
{
     ++x;       // OK: x is in scope
     ++y;       // error: no y in scope, and y doesn't depend on T
     return a;  // OK: a is dependent
}

int y;

int z = f(2);

If a declaration is found, that declaration is used even if a “better” declaration might be found later. For example:

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void g(double);
void g2(double);

template<typename T>
int ff(T a)
{
       g2(2);    // call g2(double);
       g3(2);    // error: no g3() in scope
       g(2);     // call g(double); g(int) is not in scope
       // ...
}

void g(int);
void g3(int);

int x = ff(a);

Here, ff() will call g(double). The definition of g(int) comes too late to be considered – just as if ff() had not been a template or if g had named a variable.

26.3.3. Point-of-Instantiation Binding

The context used to determine the meaning of a dependent name (§26.3.1) is determined by the use of a template with a given set of arguments. This is called a point of instantiation for that specialization (§iso.14.6.4.1). Each use of a template for a given set of template arguments defines a point of instantiation. For a function template, that point is in the nearest global or namespace scope enclosing its use, just after the declaration that contains that use. For example:

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void g(int);

template<typename T>
void f(T a)
{
     g(a);    // g is bound at a point of instantiation
}
void h(int i)
{
     extern void g(double);
     f(i);
}
// point of declaration for f<int>

The point of instantiation for f<int>() is outside h(). This is essential to ensure that the g() called in f() is the global g(int) rather than the local g(double). An unqualified name used in a template definition can never be bound to a local name. Ignoring local names is essential to prevent a lot of nasty macro-like behavior.

To enable recursive calls, the point of declaration for a function template is after the declaration that instantiates it. For example:

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void g(int);

template<typename T>
void f(T a)
{
     g(a);           // g is bound at a point of instantiation
     if (i) h(a–1);  // h is bound at a point of instantiation
}

void h(int i)
{
     extern void g(double);
     f(i);
}
// point of declaration for f<int>

Here, having the point of instantiation after the definition of h() is necessary to allow the (indirectly recursive) call h(a–1).

For a template class or a class member, the point of instantiation is just before the declaration containing its use.

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template<typename T>
class Container {
     vector<T> v;    // elements
     // ...
public:
     void sort();    // sort elements
     // ...
};

// point of instantiation of Container<int>
void f()
{
     Container<int> c;    // point of use
     c.sort();
}

Had the point of instantiation been after f() the call c.sort() would have failed to find the definition of Container<int>.

Relying on template arguments to make dependencies explicit simplifies our thinking about the template code and even allows us to access local information. For example:

void fff()
{
     struct S { int a,b; };
     vector<S> vs;
     // ...
}

Here, S is a local name, but since we use it as an explicit argument, rather than trying to bury its name in the definition of vector, we have no potentially surprising subtleties.

So why don’t we completely avoid nonlocal names in template definitions? That would certainly solve the technical problem with name lookup, but – as for ordinary function and class definitions – we want to be able to use “other functions and types” freely in our code. Turning every dependency into an argument can lead to very messy code. For example:

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template<typename T>
void print_sorted(vector<T>& v)
{
     sort(v.begin(),v.end());
     for (const auto T& x : v)
           cout << x << '\n';
}

void use(vector<string>& vec)
{
     // ...
     print_sorted(vec);  // sort using std::sort, then print using std::cout
}

Here, we are using just two nonlocal names (sort and cout, both from the standard library). To eliminate those we would need to add parameters:

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template<typename T, typename S>
void print_sorted(vector<T>& v, S sort, ostream& os)
{
     sort(v.begin(),v.end());
     for (const auto T& x : v)
           os << x << '\n';
}

void fct(vector<string>& vec)
{
     // ...
     using Iter = decltype(vs.begin());  // vec's iterator type
     print_sorted(some_vec,std::sort<Iter>,std::cout);
}

In this trivial case, there is a lot to be said for removing the dependence on the global name cout. However, in general, as illustrated by sort(), adding parameters can make the code much more verbose without necessarily making it easier to understand.

Also, if the name-binding rules for templates were radically more restrictive than the rules for non-template code, writing template code would be a completely separate skill from writing non-template code. Templates and non-template code would no longer interoperate simply and freely.

26.3.4. Multiple Instantiation Points

A template specialization may be generated

• at any point of instantiation (§26.3.3),

• at any point subsequent to that in a translation unit,

• or in a translation unit specifically created for generating specializations.

This reflects three obvious strategies an implementation can use for generating specializations:

[1] Generate a specialization the first time a call is seen.

[2] At the end of a translation unit, generate all specializations needed for it.

[3] Once every translation unit of a program has been seen, generate all specializations needed for the program.

All three strategies have strengths and weaknesses, and combinations of these strategies are also possible.

So, a template used several times with the same set of template arguments has several points of instantiation. A program is illegal if it is possible to construct two different meanings by choosing different points of instantiation. That is, if the bindings of a dependent or a nondependent name can differ, the program is illegal. For example:

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void f(int);                           // here, I take care of ints

namespace N {
    class X {};
    char g(X,int);
}

template<typename T>
void ff(T t, double d)
{
      f(d);           // f is bound to f(int)
      return g(t,d);  // g might be bound to g(X,int)
}

auto x1 = ff(N::X{},1.1);         // ff<N::X,double>; may bind g to N::g(X,int), narrowing 1.1 to 1

Namespace N {                            // reopen N to take care of doubles
    double g(X,double);
}

auto x2 = ff(N::X,2.2);                  // ff<N::X,double>; binds g to N::g(X,double); the best match

For ff() we have two instantiation points. For the first call, we could generate the specialization at the initialization of x1 and get g(N::X,int) called. Alternatively, we could wait and generate the specialization at the end of the translation unit and get g(N::X,char) called. Consequently, the call ff(N::X{},1.1) is an error.

It is sloppy programming to call an overloaded function between two of its declarations. However, looking at a large program, a programmer would have no reason to suspect a problem. In this particular case, a compiler could catch the ambiguity. However, similar problems can occur in separate translation units, and then detection becomes much harder (for both compilers and programmers). An implementation is not obliged to catch problems of this kind.

To avoid surprising name bindings, try to limit context dependencies in templates.

26.3.5. Templates and Namespaces

When a function is called, its declaration can be found even if it is not in scope, provided it is declared in the same namespace as one of its arguments (§14.2.4). This is important for functions called in template definitions because it is the mechanism by which dependent functions are found during instantiation. The binding of dependent names is done (§iso.14.6.4.2) by looking at

[1] the names in scope at the point where the template is defined, plus

[2] the names in the namespace of an argument of a dependent call (§14.2.4).

For example:

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namespace N {
    class A { /* ... */ };
    char f(A);
}

char f(int);

template<typename T>
char g(T t)
{
     return f(t);          // choose f() depending on what T is
}

char f(double);

char c1 = g(N::A());       // causes N::f(N::A) to be called
char c2 = g(2);            // causes f(int) to be called
char c3 = g(2.1);          // causes f(int) to be called; f(double) not considered

Here, f(t) is clearly dependent, so we can’t bind f at the point of definition. To generate a specialization for g<N::A>(N::A), the implementation looks in namespace N for functions called f() and finds N::f(N::A).

The f(int) is found because it is in scope at the point of definition of the template. The f(double) is not found because it is not in scope at the point of definition of the template (§iso.14.6.4.1), and argument-dependent lookup (§14.2.4) does not find a global function that takes only arguments of built-in types. I find it easy to forget that.

26.3.6. Overaggressive ADL

Argument-dependent lookup (often referred to as ADL) is very useful to avoid verbosity (§14.2.4). For example:

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#include <iostream>

int main()
{
     std::cout << "Hello, world" << endl;// OK because of ADL
}

Without argument-dependent lookup, the endl manipulator would not be found. As it is, the compiler notices that the first argument to << is an ostream defined in std. Therefore, it looks for endl in std and finds it (in <iostream>).

However, ADL can be “too aggressive” when combined with unconstrained templates. Consider:

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#include<vector>
#include<algorithm>
// ...

namespace User {
    class Customer { /* ... */ };
    using Index = std::vector<Customer*>;

    void copy(const Index&, Index&, int deep);   // deep or shallow copy depending on the value of deep

    void algo(Index& x, Index& y)
    {
         // ...
         copy(x,y,false);// error
    }
}

It would be a good guess that the author of User meant for User::alg() to call User::copy(). However, that’s not what happens. The compiler notices that Index really is a vector defined in std and looks to see if a relevant function is available in std. In <algorithm>, it finds:

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template<typename In, typename Out>
Out copy(In,In,Out);

Obviously, this general template is a perfect match for copy(x,y,false). On the other hand, the copy() in User can be called only with a bool-to-int conversion. For this example, as for equivalent examples, the compiler’s resolution is a surprise to most programmers and a source of very obscure bugs. Using ADL to find fully general templates is arguably a language design error. After all, std::copy() requires a pair of iterators (not just two arguments of the same type, such as the two Indexes). The standard says so, but the code does not. Many such problems can be solved by the use of concepts (§24.3, §24.3.2). For example, had the compiler known that std::copy() required two iterators, a nonobscure error would have been the result.

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template<typename In, typename Out>
Out copy(In p1, In p2, Out q)
{
     static_assert(Input_iterator<In>(), "copy(): In is not an input iterator");
     static_assert(Output_iterator<Out>(), :copy(): Out is not an output iterator");
     static_assert(Assignable<Value_type<Out>,Value_type<In>>(), "copy(): value type mismatch");
     // ...
}

Better still, the compiler would have noticed that std::copy() wasn’t even a valid candidate for that call and User::copy() would have been invoked. For example (§28.4):

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template<typename In, typename Out,
         typename = enable_if(Input_iterator<In>()
                            && Output_iterator<Out>()
                            && Assignable<Value_type<Out>,Value_type<In>>())>
Out copy(In p1, In p2, Out q)
{
     // ...
}

Unfortunately, many such templates are in libraries that a user cannot modify (e.g., the standard library).

It is a good idea to avoid fully general (completely unconstrained) function templates in headers that also contain type definitions, but that’s hard to avoid. If you need one, protecting it with a constraints check is often worthwhile.

What can a user do if a library has trouble-causing unconstrained templates? Often, we know which namespace our function should come from, so we can be specific about that. For example:

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void User::algo(Index& x, Index& y)
{
     User::copy(x,y,false);   // OK
     // ...
     std::swap(*x[i],*x[j]);  // OK: only std::swap is considered
}

If we don’t want to be specific about which namespace to use, but want to make sure that a particular version of a function is considered by function overloading, we can use a using-declaration (§14.2.2). For example:

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template<typename Range, typename Op>
void apply(const Range& r, Op f)
{
     using std::begin;
     using std::end;
     for (auto& x : r)
           f(x);
}

Now, the standard begin() and end() are in the overload set used by the range-for to traverse the Range (unless Range has members begin() and end(); §9.5.1).

26.3.7. Names from Base Classes

When a class template has a base class, it can access names from that base. As for other names, there are two distinct possibilities:

• The base class depends on a template argument.

• The base class does not depend on a template argument.

The latter case is simple and treated just like base classes in classes that are not templates. For example:

void g(int);

struct B {
     void g(char);
     void h(char);
};

template<typename T>
class X : public B {
public:
     void h(int);
     void f()
     {
           g(2);     // call B::g(char)
           h(2);     // call X::h(int)
     }
     // ...
};

As ever, local names hide other names, so h(2) binds to X::h(int) and B::h(char) is never considered. Similarly, the call g(2) is bound to B::g(char) without any concern for functions declared outside X. That is, the global g() is never considered.

For base classes that depend on a template parameter, we have to be a bit more careful and explicit about what we want. Consider:

void g(int);

struct B {
     void g(char);
     void h(char);
};

template<typename T>
class X : public T {
public:
     void f()
     {
           g(2);     // call ::g(int)
     }
     // ...
};

void h(X<B> x)
{
     x.f();
}

Why doesn’t g(2) call B::g(char) (as in the previous example)? Because g(2) isn’t dependent on the template parameter T. It is therefore bound at the point of definition; names from the template argument T (which happens to be used as a base class) are not (yet) known and therefore not considered. If we want to have names from a dependent class considered, we must make the dependency clear. We have three ways of doing that:

• Qualify a name with a dependent type (e.g., T::g).

• Say that the name refers an object of this class (e.g., this–>g).

• Bring the name into scope with a using-declaration (e.g., using T::g).

For example:

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void g(int);
void g2(int);

struct B {
     using Type = int;
     void g(char);
     void g2(char)
};

template<typename T>
class X : public T {
public:
     typename T::Type m;   // OK
     Type m2;              // error (no Type in scope)

     using T::g2();        // bring T::g2() into scope

     void f()
     {
          this–>g(2);      // call T::g
          g(2);            // call ::g(int); surprise?
          g2(2);           // call T::g2
     }
     // ...
};

void h(X<B> x)
{
     x.f();
}

Only at the point of instantiation can we know if the argument used for the parameter T (here B) has the required names.

It is easy to forget to qualify names from a base, and the qualified code often looks a bit verbose and messy. However, the alternative would be that a name in a template class would sometimes bind to a base class member and sometimes to a global entity depending on the template argument. That is not ideal either, and the language rule supports the rule of thumb that a template definition should be as self-contained as possible (§26.3).

Qualifying access to dependent base members of a template can be a nuisance. However, explicit qualifications help maintainers, so the initial author shouldn’t grumble too much about the extra typing. A common occurrence of this problem is when a whole class hierarchy is templatized. For example:

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template<typename T>
class Matrix_base {    // memory for matrices, operations of all elements
     // ...
     int size() const { return sz; }
protected:
     int sz;   // number of elements
     T* elem;  // matrix elements
};

template<typename T, int N>
class Matrix : public Matrix_base<T> {  // N-dimensional matrix
     // ...
     T* data() // return pointer to element storage
     {
          return this–>elem;
     }
};

Here, the this–> qualification is required.

26.4. Advice

[1] Let the compiler/implementation generate specializations as needed; §26.2.1.

[2] Explicitly instantiate if you need exact control of the instantiation environment; §26.2.2.

[3] Explicitly instantiate if you optimize the time needed to generate specializations; §26.2.2.

[4] Avoid subtle context dependencies in a template definition; §26.3.

[5] Names must be in scope when used in a template definition or findable through argument-dependent lookup (ADL); §26.3, §26.3.5.

[6] Keep the binding context unchanged between instantiation points; §26.3.4.

[7] Avoid fully general templates that can be found by ADL; §26.3.6.

[8] Use concepts and/or static_assert to avoid using inappropriate templates; §26.3.6.

[9] Use using-declarations to limit the reach of ADL; §26.3.6.

[10] Qualify names from a template base class with –> or T:: as appropriate; §26.3.7.

27. Templates and Hierarchies

Euclid’s and Beethoven’s Fifth; knowing just one of them marks you as semi-educated.

– Stan Kelley-Bootle

• Introduction

• Parameterization and Hierarchy

Generated Types; Template Conversions

• Hierarchies of Class Templates

Templates as Interfaces

• Template Parameters as Base Classes

Composing Data Structures; Linearizing Class Hierarchies

• Advice

27.1. Introduction

Templates and derivation are mechanisms for building new types out of existing ones, for specifying interfaces, and generally for writing useful code that exploits various forms of commonality:

• A template class defines an interface. The template’s own implementation and those of its specializations can be accessed through that interface. The source code implementing the template (in the template definition) is identical for all parameter types. The implementations of different specializations can be very different, but they should all implement the semantics specified for the primary template. A specialization can add functionality to what the primary template offers.

• A base class defines an interface. The class’s own implementation and those of its derived classes can (using virtual functions) be accessed through that interface. The implementations of different derived classes can be very different, but they should all implement the semantics specified for the base class. A derived class can add functionality to what the base class offers.

From a design perspective, the two approaches are close enough to deserve a common name. Since both allow an algorithm to be expressed once and applied to a variety of types, people refer to both as polymorphic (from Greek “many shapes”). To distinguish them, what virtual functions provide is called run-time polymorphism, and what templates offer is called compile-time polymorphism or parametric polymorphism.

The rough duality of the generic and object-oriented approaches can be deceptive. Object-oriented programmers tend to focus on the design of hierarchies of classes (types) with an interface being an individual class (Chapter 21). Generic programmers tend to focus on the design of algorithms with the concepts for template arguments providing an interface that can accommodate many types (Chapter 24). The ideal for a programmer should be mastery of both techniques to the point where either can be used where most appropriate. In many cases, the optimal design contains elements of both. For example vector<Shape*> is a compile-time polymorphic (generic) container holding elements from a run-time polymorphic (object-oriented) hierarchy (§3.2.4).

Generally, good object-oriented programming requires more foresight than good generic programming because all types in a hierarchy must explicitly share an interface defined as a base class. A template will accept any type that meets its concept as an argument, even if there is no explicitly declared commonality among those types. For example accumulate() (§3.4.2, §24.2, §40.6.1) will accept vectors of ints and lists of complex<double> even though there are no declared relationship between the two element types and no declared relationship between the two sequence types.

27.2. Parameterization and Hierarchy

As shown in §4.4.1 and §27.2.2, combinations of templates and class hierarchies are the basis for many useful techniques. So:

• When do we choose to use a class template?

• When do we rely on a class hierarchy?

Consider these questions from a slightly simplified and abstract point of view:

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template<typename X>
class Ct {        // interface expressed in terms of the parameter
     X mem;
public:
     X f();
     int g();
     void h(X);
};

template<>
class Ct<A> {     // specialization (for A)
     A* mem;      // the representation can differ from that of the primary template
public:
     A f();
     int g();
     void h(A);
     void k(int);   // added functionality
};
     Ct<A> cta;     // specialization for A
     Ct<B> ctb;     // specialization for B

Given that, we can use f(), g(), and h() on the variables cta and ctb, using the implementations of Ct<A> and Ct<B>, respectively. I used an explicit specialization (§23.5.3.4) to show that implementations can vary from what the primary template offers and that it is possible to add functionality. The simpler case – without added functionality – is by far the more common.

The rough equivalent using a hierarchy is:

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class X {
     // ...
};

class Cx {                 // interface expressed in terms of types in scope
     X mem;
public:
     virtual X& f();
     virtual int g();
     virtual void h(X&);
};

Class DA : public Cx {     // derived class
public:
     X& f();
     int g();
     void h(X&);
};

Class DB : public Cx {    // derived class
     DB* p;               // representation can be more extensive than what the base provides
public:
     X& f();
     int g();
     void h(X&);
     void k(int);         // added functionality
};

Cx& cxa {*new DA}; // cxa is an interface to a DA
Cx& cxb {*new DB}; // cxb is an interface to a DB

Given that, we can use f(), g(), and h() on the variables cxa and cxb, using the implementations of DA and DB, respectively. I use references in the hierarchical version to reflect that we must manipulate derived class objects through pointers or references to preserve run-time polymorphic behavior.

In either case, we manipulate objects that share a common set of operations. From this simplified and abstract point of view we can observe:

• If the types in the interface to the generated or derived classes need to differ, templates have an advantage. To gain access to differing interfaces for derived classes through a base, we must use some form of explicit casting (§22.2).

• If the implementations of generated or derived classes differ only through a parameter or differ only in a few special cases, templates have an advantage. Irregular implementations can be expressed through derived classes or specializations.

• If the actual types of objects used cannot be known at compile time, a class hierarchy is essential.

• If a hierarchical relationship is required between generated or derived types, hierarchies have an advantage. The base class provides a common interface. Conversions among template specializations must be explicitly defined by the programmer (§27.2.2).

• If explicit use of free store (§11.2) is undesirable, templates have an advantage.

• If run-time efficiency is at such a premium that inlining of operations is essential, templates should be used (because effective use of hierarchy requires the use of pointers or references, which inhibit inlining).

Keeping base classes minimal and type-safe can be a struggle. Expressing the interface in terms of existing types that cannot vary for derived classes can be a struggle. Often the result is a compromise that either overconstrains the base class interface (e.g., we pick a class X with a “rich interface” which must be implemented by all derived classes and “for all time”) or underconstrains (e.g., we use void* or a minimal Object*).

The combination of templates and class hierarchies provides design choices and flexibility beyond what either can offer by itself. For example, a pointer to a base class can be used as a template argument to provide run-time polymorphism (§3.2.4), and a template parameter can be used to specify a base class interface to provide type safety (§26.3.7, §27.3.1).

It is not possible to have a virtual function template (§23.4.6.2).

27.2.1. Generated Types

A class template is usefully understood as a specification of how particular types are to be created. In other words, the template implementation is a mechanism that generates types when needed based on a specification. Consequently, a class template is sometimes called a type generator.

As far as the C++ language rules are concerned, there is no relationship between two classes generated from a single class template. For example:

class Shape {
     // ...
};

class Circle : public Shape {
{
     // ...
};

Given these declarations, people sometimes think that there must be an inheritance relationship between set<Circle> and set<Shape> or at least between set<Circle*> and set<Shape*>. This is a serious logical error based on a flawed argument: “A Circle is a Shape, so a set of Circles is also a set of Shapes; therefore, I should be able to use a set of Circles as a set of Shapes.” The “therefore” part of this argument doesn’t hold. The reason is that a set of Circles guarantees that the members of the set are Circles; a set of Shapes does not provide that guarantee. For example:

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class Triangle : public Shape {
     // ...
};

void f(set<Shape*>& s)
{
     // ...
     s.insert(new Triangle{p1,p2,p3});
}

void g(set<Circle*>& s)
{
     f(s); // error, type mismatch: s is a set<Circle*>, not a set<Shape*>
}

This won’t compile because there is no built-in conversion from set<Circle*>& to set<Shape*>&. Nor should there be. The guarantee that the members of a set<Circle*> are Circles allows us to safely and efficiently apply Circle-specific operations, such as determining the radius, to members of the set. If we allowed a set<Circle*> to be treated as a set<Shape*>, we could no longer maintain that guarantee. For example, f() inserts a Triangle* into its set<Shape*> argument. If the set<Shape*> could have been a set<Circle*>, the fundamental guarantee that a set<Circle*> contains Circle*s only would have been violated.

Logically, we could treat an immutable set<Circle*> as an immutable set<Shape*> because the problem of inserting an inappropriate element into the set cannot occur when we cannot change the set. That is, we could provide a conversion from const set<const Circle*> to const set<const Shape*>. The language doesn’t do so by default, but the designer of set could.

The combination of an array and a base class is particularly nasty because a built-in array does not offer the type safety provided by containers. For example:

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void maul(Shape* p, int n)         // Danger!
{
     for (int i=0; i!=n; ++i)
           p[i].draw();            // looks innocent; it is not
}

void user()
{
     Circle image[10];             // an image is composed of 10 Circles
     // ...
     maul(image,10);               // "maul" 10 Circles
     // ...
}

How can we call maul() with image? First, image’s type is converted (decays) from Circle[] to Circle*. Next, Circle* is converted to Shape*. The implicit conversion of an array name to a pointer to the array’s first element is fundamental to C-style programming. Similarly, implicit conversion of a pointer to a derived class to a pointer to its base class is fundamental to object-oriented programming. In combination, they offer the opportunity of disaster.

In the example above, assume that a Shape is an abstract class with size 4 and that Circle adds a center and a radius. Then sizeof(Circle)>sizeof(Shape) and when we look at the layout of image we find something like this:

When maul() tries to invoke a virtual function on p[1], there is no virtual function pointer where it is expected and the call hopefully fails instantly.

Note that no explicit cast was needed to get this disaster:

• Prefer containers over built-in arrays.

• Consider interfaces such as void f(T* p, int count) highly suspect; when T can be a base class and count is an element count, trouble awaits.

• Consider . (dot) suspect when applied to something that is supposed to be run-time polymorphic unless it is obviously applied to a reference.

27.2.2. Template Conversions

There cannot be any default relationship between classes generated from the same template (§27.2.1). However, for some templates we would like to express such a relationship. For example, when we define a pointer template, we would like to reflect inheritance relationships among the objects pointed to. Member templates (§23.4.6) allow us to specify many such relationships where desired. Consider:

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template<typename T>
class Ptr {   // pointer to T
     T* p;
public:
     Ptr(T*);
     Ptr(const Ptr&);                      // copy constructor
     template<typename T2>
           explicit operator Ptr<T2>();    // convert Ptr<T> to Ptr<T2>
     // ...
};

We would like to define the conversion operators to provide the inheritance relationships we are accustomed to for built-in pointers for these user-defined Ptrs. For example:

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void f(Ptr<Circle> pc)
{
     Ptr<Shape> ps {pc};      // should work
     Ptr<Circle> pc2 {ps};    // should give error
}

We want to allow the first initialization if and only if Shape really is a direct or indirect public base class of Circle. In general, we need to define the conversion operator so that the Ptr<T> to Ptr<T2> conversion is accepted if and only if a T* can be assigned to a T2*. That can be done like this:

template<typename T>
    template<typename T2>
        Ptr<T>::operator Ptr<T2>()
        {
            return Ptr<T2>{p};
        }

The return-statement will compile if and only if p (which is a T*) can be an argument to the Ptr<T2>(T2*) constructor. Therefore, if T* can be implicitly converted into a T2*, the Ptr<T> to Ptr<T2> conversion will work. For example, we can now write:

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void f(Ptr<Circle> pc)
{
     Ptr<Shape> ps {pc};     // OK: can convert Circle* to Shape*
     Ptr<Circle> pc2 {ps};   // error: cannot convert Shape* to Circle*
}

Be careful to define logically meaningful conversions only. If in doubt, use a named conversion function, rather than a conversion operator. A named conversion function offers fewer opportunities for ambiguities.

The template parameter lists of a template and one of its template members cannot be combined. For example:

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template<typename T, typename T2>   // error
Ptr<T>::operator Ptr<T2>()
{
     return Ptr<T2>(p);
}

An alternative solution to this problem uses type traits and enable_if() (§28.4).

27.3. Hierarchies of Class Templates

Using object-oriented techniques, a base class is often used to provide a common interface to a set of derived classes. A template can be used to parameterize such an interface, and when that is done it is tempting to parameterize the whole hierarchy of derived classes with the same template parameters. For example, we could parameterize the classical shape example (§3.2.4) with types used to provide an abstraction of the target output “device”:

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template<typename Color_scheme, typename Canvas>     // questionable example
class Shape {
     // ...
};

template<typename Color_scheme, typename Canvas>
class Circle : public Shape {
     // ...
};
template<typename Color_scheme, typename Canvas>
class Triangle : public Shape {
     // ...
};

void user()
{
     auto p = new Triangle<RGB,Bitmapped>{{0,0},{0,60},{30,sqr t(60*60–30 *30)}};
     // ...
}

Something along this line is often the first idea (after seeing something like vector<T>) that a programmer used to object-oriented programming considers. However, caution is recommended when mixing object-oriented and generic techniques.

As written, this parameterized shape hierarchy is too verbose for real use. That could be addressed using default template arguments (§25.2.5). However, the verbosity is not the main problem. If only one combination of Color_scheme and Canvas is used in a program, the amount of code generated is almost exactly the same as would have been generated for the unparameterized equivalent. The “almost” comes because the compiler will suppress code generation for the definitions of unused non-virtual member functions of a class template. However, if N combinations of Color_scheme and Canvas are used in a program, the code for every virtual function will be replicated N times. Because a graphics hierarchy is likely to have many derived classes, many member functions, and many complicated functions, the result is likely to be massive code bloat. In particular, the compiler cannot know whether a virtual function is used or not, so it must generate code for all such functions and for all functions called by such functions. Parameterizing a huge class hierarchy with many virtual member functions is typically a poor idea.

For this shape example, the Color_scheme and Canvas parameters are unlikely to affect the interface much: most member functions will not have them as part of their function type. These parameters are an “implementation detail” that escaped into the interface – with likely serious performance implications. It is not really the whole hierarchy that needs those parameters; it is a few configuration functions and (most likely) a few lower-level drawing/rendering functions. It is generally not a good idea to “overparameterize” (§23.4.6.3): try to avoid parameters that affect only a few members. If only a few member functions are affected by a parameter, try to make those function templates with that parameter. For example:

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class Shape {
     template<typename Color_scheme, typename Canvas>
         void configure(const Color_scheme&, const Canvas&);
     // ...
};

How to share the configuration information among different classes and different objects is a separate issue. Clearly, we cannot simply store a Color_scheme and Canvas in the Shape without parameterizing Shape itself with Color_scheme and Canvas. One solution would be for configure() to “translate” the information in Color_scheme and Canvas into a standard set of configuration parameters (e.g., a set of integers). Another solution is to give a Shape a Configuration* member, where Configuration is a base class providing a general interface to configuration information.

27.3.1. Templates as Interfaces

A template class can be used to provide a flexible and type-safe interface to a common implementation. The vector from §25.3 is a good example of this:

template<typename T>
class Vector<T*>
     : private Vector<void*>
{
     // ...
};

In general, this technique can be used to provide type-safe interfaces and for localizing casts to implementations, rather than forcing users to write them.

27.4. Template Parameters as Base Classes

In classical object-oriented programming using class hierarchies, we place information that can be different for different classes in derived classes and access it through virtual functions in a base class (§3.2.4, §21.2.1). That way, we can write common code without worrying about variations in the implementations. However, this technique does not allow us to vary the types used in the interface (§27.2). Also, those virtual function calls can be expensive compared to a simple operation from an inlined function. To compensate, we might pass the specialized information and operations to the base class as template arguments. In fact, a template argument can be used as a base class.

The general problem addressed by the following two subsections is “How can we combine separately specified information into a single compact object with a well-specified interface?” This is a fundamental question and the solutions are of general importance.

27.4.1. Composing Data Structures

Consider writing a balanced binary tree library. Since we are providing a library to be used by many different users, we can’t build the type of the user’s (application’s) data into our tree nodes. We have many alternatives:

• We could put the user’s data in a derived class and access it using virtual functions. But the virtual function calls (or equivalently, run-time resolved and checked solutions) are relatively expensive, and our interface to the user’s data is not expressed in terms of the user’s type, so we still need to use casts to access it.

• We could put a void* in our nodes and let the user use that to refer to data allocated outside our nodes. But that could double the number of allocations, add many (potentially expensive) pointer dereferences, and add the space overhead of a pointer in each node. We would also need to use a cast to access our user data using its correct type. That cast can’t be type checked.

• We could put a Data* into our nodes, where Data is a “universal base class” for our data structures. That would solve the type-checking problem, but that combines the cost and inconvenience of the previous two approaches.

There are more alternatives, but consider:

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template<typename N>
struct Node_base {     // doesn't know about Val (the user data)
     N* left_child;
     N* right_child;

     Node_base();

     void add_left(N* p)
     {
          if (left_child==nullptr)
                left_child = p;
          else
                // ...
     }
     // ...
};

template<typename Val>
struct Node : Node_base<Node<Val>> {     // use derived class as part of its own base
     Val v;
     Node(Val vv);
     // ...
};

Here, we pass the derived class Node<Val> as a template argument to its own base (Node_base). That allows Node_base to use Node<Val> in its interfaces without even knowing its real name!

Note that the layout of a Node is compact. For example, a Node<double> will look roughly equivalent to this:

struct Node_base_double {
     double val;
     Node_base_double* left_child;
     Node_base_double* right_child;
};

Unfortunately, with this design, a user has to be aware of Node_base’s operations and the structure of the resulting tree. For example:

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using My_node = Node<double>;

void user(const vector<double>& v)
{
     My_node root;
     int i = 0;

     for (auto x : v) {
           auto p = new My_node{x};
           if (i++%2)                // choose where to insert
                 root.add_left(p);
           else
                 root.add_right(p);
     }
}

However, it is not easy for a user to keep the structure of a tree reasonable. Typically, we would like to let the tree take care of that by implementing a tree-balancing algorithm. However, to balance a tree so that you can search it efficiently, the balancer needs to know the user’s values.

How do we add a balancer to our design? We could hardwire the balancing strategy into Node_base and let Node_base “peek” at the user data. For example, a balanced tree implementation, such as the standard-library map, (by default) requires that a value type provides a less-than operation. That way, the Node_base operations can simply use <:

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template<typename N>
struct Node_base {
     static_assert(Totally_ordered<N>(), "Node_base: N must have a <");

     N* left_child;
     N* right_child;
     Balancing_info bal;

     Node_base();

     void insert(N& n)
     {
           if (n<left_child)
                 // ... do something ...
           else
                 // ... do something else ...
     }
     // ...
};

This works nicely. In fact, the more information about nodes we build into the Node_base, the simpler the implementation becomes. In particular, we could parameterize the Node_base with a value type rather than a node type (as is done for std::map), and we would have the tree in a single compact package. However, doing so doesn’t address the fundamental question we are trying to address here: how to combine information from several separately specified sources. Writing everything in one place dodges that problem.

So let us assume that the user will want to manipulate Nodes (e.g., move a node from one tree to another), so that we can’t simply store user data into an anonymous node. Let us further assume that we would like to be able to use a variety of balancing algorithms, so that we need to make the balancer an argument. These assumptions force us to face the fundamental question. The simplest solution is to let Node combine the value type with a balancer type. However, Node doesn’t need to use the balancer, so it just passes it on to Node_base:

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template<typename Val, typename Balance>
struct Search_node : public Node_base<Search_node<Val, Balance>, Balance>
{
     Val val;     // user data
     search_node(Val v): val(v) {}
};

Balance is mentioned twice here because it is part of the node type and because Node_base needs to make an object of type Balance:

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template<typename N, typename Balance>
struct Node_base : Balance {
     N* left_child;
     N* right_child;

     Node_base();

     void insert(N& n)
     {
          if (this–>compare(n,left_child))     // use compare() from Balance
                // ... do something ...
          else
                // ... do something else ...
     }
     // ...
};

I could have used Balance to define a member, rather than using it as a base. However, some important balancers require no per-node data, so by making Balance a base, I benefit from the empty-base optimization. The language guarantees that if a base class has no non-static data members, no memory will be allocated for it in an object of derived class (§iso.1.8). Also, this design is with minor stylistic differences that of a real binary tree framework [Austern,2003]. We might use these classes like this:

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struct Red_black_balance {
     // data and operations needed to implement red-black trees
};

template<typename T>
using Rbnode = Search_node<T,Red_black_balance>;  // type alias for red-black trees

Rbnode<double> my_root;      // a red-black tree of doubles

using My_node = Rb_node<double>;

void user(const vector<double>& v)
{
     for (auto x : v)
           root.insert(*new My_node{x});
}

The layout of a node is compact, and we can easily inline all performance-critical functions. What we achieved by the slightly elaborate set of definitions was type safety and ease of composition. This elaboration delivers a performance advantage compared to every approach that introduces a void* into the data structure or function interfaces. Such a use of void* disables valuable type-based optimization techniques. Choosing a low-level (C-style) programming technique in the key parts of a balanced binary tree implementation implies a significant run-time cost.

We passed the balancer as a separate template argument:

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template<typename N, typename Balance>
struct Node_base : Balance {
         // ...
};

template<typename Val, typename Balance>
struct Search_node
     : public Node_base<Search_node<Val, Balance>, Balance>
{
     // ...
};

Some find this clear, explicit, and general; others find it verbose and confusing. The alternative is to make the balancer an implicit argument in the form of an associated type (a member type of Search_node):

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template<typename N>
struct Node_base : N::balance_type {   // use N's balance_type
         // ...
};

template<typename Val, typename Balance>
struct Search_node
     : public Node_base<Search_node<Val,Balance>>
{
     using balance_type = Balance;
     // ...
};

This technique is heavily used in the standard library to minimize explicit template arguments.

The technique of deriving from a base class is very old. It was mentioned in the ARM (1989) and is sometimes referred to as the Barton-Nackman trick after an early use in mathematical software [Barton,1994]. Jim Coplien called it the curiously recurring template pattern (CRTP) [Coplien,1995].

27.4.2. Linearizing Class Hierarchies

The Search_node example from §27.4.1 uses its template to compress its representation and to avoid using void*. The techniques are general and very useful. In particular, many programs that deal with trees rely on it for type safety and performance. For example, the “Internal Program Representation” (IPR) [DosReis,2011] is a general and systematic representation of C++ code as typed abstract syntax trees. It uses template parameters as base classes extensively, both as an implementation aid (implementation inheritance) and to provide abstract interfaces in the classical object-oriented way (interface inheritance). The design addresses a difficult set of criteria, including compactness of nodes (there can be many millions of nodes), optimized memory management, access speed (don’t introduce unnecessary indirections or nodes), type safety, polymorphic interfaces, and generality.

The users see a hierarchy of abstract classes providing perfect encapsulation and clean functional interfaces representing the semantics of a program. For example, a variable is a declaration, which is a statement, which is an expression, which is a node:

Var –> Decl –> Stmt –> Expr –> Node

Clearly, some generalization has been done in the design of the IPR because in ISO C++ statements cannot be used as expressions.

In addition, there is a parallel hierarchy of concrete classes providing compact and efficient implementations of the classes in the interface hierarchy:

impl::Var –> impl::Decl –> impl::Stmt –> impl::Expr –> impl::Node

In all, there are about 80 leaf classes (such as Var, If_stmt, and Multiply) and about 20 generalizations (such as Decl, Unary, and impl::Stmt).

The first attempt of a design was a classical multiple-inheritance “diamond” hierarchy (using solid arrows to represent interface inheritance and dotted arrows for implementation inheritance):

That worked but led to excessive memory overhead: the nodes were too large because of data needed to navigate the virtual bases. In addition, programs were seriously slowed down by the many indirections to access the many virtual bases in each object (§21.3.5).

The solution was to linearize the dual hierarchy so that no virtual bases were used:

For the full set of classes the chain of derivation becomes:

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impl::Var –>
     impl::Decl<impl::Var> –>
          impl::Stmt<impl::Var> –>
               impl::Expr<impl::Var> –>
                    impl::Node<impl::Var> –>
                         ipr::Var –>
                              ipr::Decl –>
                                   ipr::Stmt –>
                                        ipr::Expr–>
                                             ipr::Node

This is represented as a compact object with no internal “management data” except the single vptr (§3.2.3, §20.3.2).

I will show how that is done. The interface hierarchy, defined in namespace ipr is described first. Starting from the bottom, a Node holds data used to optimize traversal and Node type identification (the code_category) and to ease storage of IPR graphs in files (the node_id). These are fairly typical “implementation details” hidden from the users. What a user will know is that every node in an IPR graph has a unique base of type Node and that this can be used to implement operations using the visitor pattern [Gamma,1994] (§22.3):

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struct ipr::Node {
     const int node_id;
     const Category_code category;

     virtual void accept(Visitor&) const = 0;   // hook for visitor classes
protected:
     Node(Category_code);
};

Node is meant to be used as a base class only, so its constructor is protected. It also has a pure virtual function, so it cannot be instantiated except as a base class.

An expression (Expr) is a Node that has a type:

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struct ipr::Expr : Node {
     virtual const Type& type() const = 0;
protected:
     Expr(Category_code c) : Node(c) { }
};

Obviously, this is quite a generalization of C++ because it implies that even statements and types have types: it is an aim of the IPR to represent all of C++ without implementing all of C++’s irregularities and limitations.

A statement (Stmt) is an Expr that has a source file location and can be annotated with various information:

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struct ipr::Stmt : Expr {
     virtual const Unit_location& unit_location() const = 0;     // line in file
     virtual const Source_location& source_location() const = 0; // file

     virtual const Sequence<Annotation>& annotation() const = 0;
protected:
     Stmt(Category_code c) : Expr(c) { }
};

A declaration (Decl) is a Stmt that introduces a name:

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struct ipr::Decl : Stmt {
     enum Specifier { /* storage class, virtual, access control, etc. */ };

     virtual Specifier specifiers() const = 0;
     virtual const Linkage& lang_linkage() const = 0;

     virtual const Name& name() const = 0;

     virtual const Region& home_region() const = 0;
     virtual const Region& lexical_region() const = 0;

     virtual bool has_initializer() const = 0;
     virtual const Expr& initializer() const = 0;

     // ...
protected:
     Decl(Category_code c) : Stmt(c) { }
};

As you might expect, Decl is one of the central notions when it comes to representing C++ code. This is where you find scope information, storage classes, access specifiers, initializers, etc.

Finally, we can define a class to represent a variable (Var) as a leaf class (most derived class) of our interface hierarchy:

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struct ipr::Var : Category<var_cat, Decl> {
};

Basically, Category is a notational aid with the effect of deriving Var from Decl and giving the Category_code used to optimize Node type identification:

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template<Category_code Cat, typename T = Expr>
struct Category : T {
protected:
     Category() : T(Cat) { }
};

Every data member is a Var. That includes global, namespace, local, and class static variables and constants.

Compared to representations you find in compilers, this interface is tiny. Except for some data for optimizations in Node, this is just a set of classes with pure virtual functions. Note that it is a single hierarchy with no virtual base classes. It is a straightforward object-oriented design. However, implementing this simply, efficiently, and maintainably is not easy, and IPR’s solution is certainly not what an experienced object-oriented designer would first think of.

For each IPR interface class (in ipr), there is a corresponding implementation class (in impl). For example:

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template<typename T>
struct impl::Node : T {
     using Interface = T; // make the template argument type available to users
     void accept(ipr::Visitor& v) const override { v.visit(*this); }
};

The “trick” is to establish the correspondence between the ipr nodes and the impl nodes. In particular, the impl nodes must provide the necessary data members and override the abstract virtual functions in the ipr nodes. For impl::Node, we can see that if T is an ipr::Node or any class derived from ipr::Node, then the accept() function is properly overridden.

Now, we can proceed to provide implementation classes for the rest of the ipr interface classes:

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template<typename Interface>
struct impl::Expr : impl::Node<Interface> {
     const ipr::Type* constraint;       // constraint is the type of the expression

     Expr() : constraint(0) { }

     const ipr::Type& type() const override { return *util::check(constraint); }
};

If the Interface argument is an ipr::Expr or any class derived from ipr::Expr, then impl::Expr is an implementation for ipr::Expr. We can make sure of that. Since ipr::Expr is derived from ipr::Node, this implies that impl::Node gets the ipr::Node base class that it needs.

In other words, we have managed to provide implementations for two (different) interface classes. We can proceed in this manner:

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template<typename S>
struct impl::Stmt : S {
     ipr::Unit_location unit_locus;        // logical position in translation unit
     ipr::Source_location src_locus;              // source file, line, and column
     ref_sequence<ipr::Annotation> notes;

     const ipr::Unit_location& unit_location() const override { return unit_locus; }
     const ipr::Source_location& source_location() const override { return src_locus; }
     const ipr::Sequence<ipr::Annotation>& annotation() const override { return notes; }
};

That is, impl:Stmt provides the three data items needed to implement ipr::Stmt’s interface and overrides ipr::Stmt’s three virtual functions to do so.

Basically, all impl classes follow Stmt’s pattern:

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template<typename D>
struct impl::Decl : Stmt<Node<D> > {
     basic_decl_data<D> decl_data;
     ipr::Named_map* pat;
     val_sequence<ipr::Substitution> args;

     Decl() : decl_data(0), pat(0) { }

     const ipr::Sequence<ipr::Substitution>& substitutions() const { return args; }
     const ipr::Named_map& generating_map() const override { return *util::check(pat); }
     const ipr::Linkage& lang_linkage() const override;
     const ipr::Region& home_region() const override;
};

Finally, we can define the leaf class impl::Var:

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struct Var : impl::Decl<ipr::Var> {
     const ipr::Expr* init;
     const ipr::Region* lexreg;

     Var();

     bool has_initializer() const override;
     const ipr::Expr& initializer() const override;
     const ipr::Region& lexical_region() const override;
};

Note that Var is not a template; it is a user-level abstraction in our application. The implementation of Var is an example of generic programming, but its use is classical object-oriented programming.

The combination of inheritance and parameterization is powerful. This expressive power can lead to confusion for beginners and occasionally even for experienced programmers when faced with a new application area. However, the benefits of the combination are concrete: type safety, performance, and minimal source code size. The extensibility offered by class hierarchies and virtual functions is not compromised.

27.5. Advice

[1] When having to express a general idea in code, consider whether to represent it as a template or as a class hierachy; §27.1.

[2] A template usually provides common code for a variety of arguments; §27.1.

[3] An abstract class can completely hide implementation details from users; §27.1.

[4] Irregular implementations are usually best represented as derived classes; §27.2.

[5] If explicit use of free store is undesirable, templates have an advantage over class hierarchies; §27.2.

[6] Templates have an advantage over abstract classes where inlining is important; §27.2.

[7] Template interfaces are easily expressed in terms of template argument types; §27.2.

[8] If run-time resolution is needed, class hierarchies are necessary; §27.2.

[9] The combination of templates and class hierarchies is often superior to either without the other; §27.2.

[10] Think of templates as type generators (and function generators); §27.2.1.

[11] There is no default relation between two classes generated from the same template; §27.2.1.

[12] Do not mix class hierarchies and arrays; §27.2.1.

[13] Do not naively templatize large class hierarchies; §27.3.

[14] A template can be used to provide a type-safe interface to a single (weakly typed) implementation; §27.3.1.

[15] Templates can be used to compose type-safe and compact data structures; §27.4.1.

[16] Templates can be used to linearize a class hierarchy (minimizing space and access time); §27.4.2.

28. Metaprogramming

Trips to fairly unknown regions should be made twice; once to make mistakes and once to correct them.

– John Steinbeck

• Introduction

• Type Functions

Type Aliases; Type Predicates; Selecting a Function; Traits

• Control Structures

Selection; Iteration and Recursion; When to Use Metaprogramming

• Conditional Definition: Enable_if

Use of Enable_if; Implementing Enable_if; Enable_if and Concepts; More Enable_if Examples

• A Compile-Time List: Tuple

A Simple Output Function; Element Access; make_tuple

• Variadic Templates

A Type-Safe printf(); Technical Details; Forwarding; The Standard-Library tuple

• SI Units Example

Units; Quantitys; Unit Literals; Utility Functions

• Advice

28.1. Introduction

Programming that manipulates program entities, such as classes and functions, is commonly called metaprogramming. I find it useful to think of templates as generators: they are used to make classes and functions. This leads to the notion of template programming as an exercise in writing programs that compute at compile time and generate programs. Variations of this idea have been called two-level programming, multilevel programming, generative programming, and – more commonly – template metaprogramming.

There are two main reasons for using metaprogramming techniques:

• Improved type safety: We can compute the exact types needed for a data structure or algorithm so that we don’t need to directly manipulate low-level data structures (e.g., we can eliminate many uses of explicit type conversion).

• Improved run-time performance: We can compute values at compile time and select functions to be called at run time. That way, we don’t need to do those computations at run time (e.g., we can resolve many examples of polymorphic behavior to direct function calls). In particular, by taking advantage of the type system, we can dramatically improve the opportunities for inlining. Also, by using compact data structures (possibly generated; §27.4.2, §28.5), we make better use of memory with positive effects on both the amount of data we can handle and the execution speed.

Templates were designed to be very general and able to generate optimal code [Stroustrup,1994]. They provide arithmetic, selection, and recursion. In fact, they constitute a complete compile-time functional programming language [Veldhuizen,2003]. That is, templates and their template instantiation mechanism are Turing complete. One demonstration of this was that Eisenecker and Czarnecki wrote a Lisp interpreter in only a few pages using templates [Czarnecki,2000]. The C++ compile-time mechanisms provide a pure functional programming language: You can create values of various types, but there are no variables, assignments, increment operators, etc. The Turing completeness implies the possibility of infinite compilations, but that’s easily taken care of by translation limits (§iso.B). For example, an infinite recursion will be caught by running out of some compile-time resource, such as the number of recursive constexpr calls, the number of nested classes, or the number of recursively nested template instantiations.

Where should we draw the line between generic programming and template metaprogramming? The extreme positions are:

• It is all template metaprogramming: after all, any use of compile-time parameterization implies instantiation that generates “ordinary code.”

• It is all generic programming: after all, we are just defining and using generic types and algorithms.

Both of these positions are useless because they basically define generic programming and template metaprogramming as synonyms. I think there is a useful distinction to be made. A distinction helps us decide between alternative approaches to problems and to focus on what is important for a given problem. When I write a generic type or algorithm, I don’t feel that I am writing a compile-time program. I am not using my programming skills for the compile-time part of my program. Instead, I am focusing on defining requirements on arguments (§24.3). Generic programming is primarily a design philosophy – a programming paradigm, if you must (§1.2.1).

In contrast, metaprogramming is programming. The emphasis is on computation, often involving selection and some form of iteration. Metaprogramming is primarily a set of implementation techniques. I can think of four levels of implementation complexity:

[1] No computation (just pass type and value arguments)

[2] Simple computation (on types or values) not using compile-time tests or iteration, for example, && of Booleans (§24.4) or addition of units (§28.7.1)

[3] Computation using explicit compile-time tests, for example, a compile-time if (§28.3).

[4] Computation using compile-time iteration (in the form of recursion; §28.3.2).

The ordering indicates the level of complexity, with implications for the difficulty of the task, the difficulty of debugging, and the likelihood of error.

So, metaprogramming is a combination of “meta” and programming: a metaprogram is a compile-time computation yielding types or functions to be used at run time. Note that I don’t say “template metaprogramming” because the computation may be done using constexpr functions. Note also that you can rely on other people’s metaprogramming without actually doing metaprogramming yourself: calling a constexpr function hiding a metaprogram (§28.2.2) or extracting the type from a template type function (§28.2.4) is not in itself metaprogramming; it just uses a metaprogram.

Generic programming usually falls into the first, “no computation” category, but it is quite possible to support generic programming using metaprogramming techniques. When doing so, we have to be careful that our interface specifications are precisely defined and correctly implemented. Once we use (meta)programming as part of an interface, the possibility of programming errors creeps in. Without programming, the meaning is directly defined by the language rules.

Generic programming focuses on interface specification, whereas metaprogramming is programming, usually with types as the values.

Overenthusiastic use of metaprogramming can lead to debugging problems and excessive compile times that render some uses unrealistic. As ever, we have to apply common sense. There are many simple uses of metaprogramming that lead to better code (better type safety, lower memory footprint, and lower run time) without exceptional compile-time overhead. Many standard-library components, such as function (§33.5.3), thread (§5.3.1, §42.2.2), and tuple (§34.2.4.2), are examples of relatively simple application of metaprogramming techniques.

This chapter explores the basic metaprogramming techniques and presents the basic building blocks of metaprograms. Chapter 29 offers a more extensive example.

28.2. Type Functions

A type function is a function that either takes at least one type argument or produces at least one type as a result. For example, sizeof(T) is a built-in type function that given a type argument T returns the size of an object (measured in chars; §6.2.8).

Type functions don’t have to look like conventional functions. In fact, most don’t. For example, the standard library’s is_polymorphic<T> takes its argument as a template argument and returns its result as a member called value:

if (is_polymorphic<int>::value) cout << "Big surprise!";

The value member of is_polymorphic is either true or false. Similarly, the standard-library convention is that a type function that returns a type does so by a member called type. For example:

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enum class Axis : char { x, y, z };
enum flags { off, x=1, y=x<<1, z=x<<2, t=x<<3 };

typename std::underlying_type<Axis>::type x;   // x is a char
typename std::underlying_type<Axis>::type y;   // y is probably an int (§8.4.2)

A type function can take more than one argument and return several result values. For example:

template<typename T, int N>
struct Array_type {
     using type = T;
     static const int dim = N;
     // ...
};

This Array_type is not a standard-library function or even a particularly useful function. I just used it as an excuse to show how to write a simple multi-argument, multi-return-value type function. It can be used like this:

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using Array = Array_type<int,3>;

Array::type x;                 // x is an int
constexpr int s = Array::dim;  // s is 3

Type functions are compile-time functions. That is, they can only take arguments (types and values) that are known at compile time and produce results (types and values) that can be used at compile time.

Most type functions take at least one type argument, but there are useful ones that don’t. For example, here is a type function that returns an integer type of the appropriate number of bytes:

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template<int N>
struct Integer {
     using Error = void;
     using type = Select<N,Error,signed char,short,Error,int,Error,Error,Error,long>;
};

typename Integer<4>::type i4 = 8;  // 4-byte integer
typename Integer<1>::type i1 = 9;  // 1-byte integer

Select is defined and explained in §28.3.1.3. It is of course possible to write templates that take values only and produce values only. I don’t consider those type functions. Also, constexpr functions (§12.1.6) are usually a better way of expressing compile-time computations on values. I can compute a square root at compile time using templates, but why would I want to when I can express the algorithm more cleanly using constexpr functions (§2.2.3, §10.4, §28.3.2)?

So, C++ type functions are mostly templates. They can perform very general computations using types and values. They are the backbone of metaprogramming. For example, we might want to allocate an object on the stack provided that it is small and on the free store otherwise:

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constexpr int on_stack_max = sizeof(std::string); // max size of object we want on the stack

template<typename T>
struct Obj_holder {
     using type = typename std::conditional<(sizeof(T)<=on_stack_max),
                                            Scoped<T>,         // first alternative
                                            On_heap<T>         // second alternative
                                       >::type;
};

The standard-library template conditional is a compile-time selector between two alternatives. If its first argument evaluates to true, the result (presented as the member type) is the second argument; otherwise, the result is the third argument. §28.3.1.1 shows how conditional is implemented. In this case, Obj_holder<X>’s type is defined to be Scoped<X> if an object of X is small and On_heap<X> if it is large. Obj_holder can be used like this:

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void f()
{
     typename Obj_holder<double>::type v1;                   // the double goes on the stack
     typename Obj_holder<array<double,200>>::type v2;        // the array goes on the free store
     // ...
     *v1 = 7.7;    // Scoped provides pointer-like access (* and [])
     v2[77] = 9.9; // On_heap provides pointer-like access (* and [])
     // ...
}

The Obj_holder example is not hypothetical. For example, the C++ standard contains the following comment in its definition of the function type (§33.5.3) for holding function-like entities: “Implementations are encouraged to avoid the use of dynamically allocated memory for small callable objects, for example, where f’s target is an object holding only a pointer or reference to an object and a member function pointer” (§iso.20.8.11.2.1). It would be hard to follow that advice without something like Obj_holder.

How are Scoped and On_heap implemented? Their implementations are trivial and do not involve any metaprogramming, but here they are:

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template<typename T>
struct On_heap {
     On_heap() :p(new T) {}    // allocate
     ~On_heap() { delete p; }  // deallocate

     T& operator*() { return *p; }
     T* operator–>() { return p; }

     On_heap(const On_heap&) = delete;        // prevent copying
     On_heap operator=(const On_heap&) = delete;
private:
     T* p;    // pointer to object on the free store
};

template<typename T>
struct Scoped {
     T& operator*() { return x; }
     T* operator–>() { return &x; }

     Scoped(const Scoped&) = delete;          // prevent copying
     Scoped operator=(const Scoped&) = delete;
private:
     T x;     // the object
};

On_heap and Scoped provide good examples of how generic programming and template metaprogramming require us to devise uniform interfaces to different implementations of a general idea (here, the idea of allocation of an object).

Both On_heap and Scoped can be used as members as well as local variables. On_heap always places its object on the free store, whereas Scoped contains its object.

§28.6 shows how we can implement versions of On_heap and Scoped for types that take constructor arguments.

28.2.1. Type Aliases

Note how the implementation details of Obj_holder (as for Int) shine through when we use typename and ::type to extract the member type. This is a consequence of the way the language is specified and used, this is the way template metaprogramming code has been written for the last 15 years, and this is the way it appears in the C++11 standard. I consider it insufferable. It reminds me of the bad old days in C, where every occurrence of a user-defined type had to be prefixed with the struct keyword. By introducing a template alias (§23.6), we can hide the ::type implementation details and make a type function look much more like a function returning a type (or like a type). For example:

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template<typename T>
using Holder = typename Obj_holder<T>::type;

void f2()
{
     Holder<double> v1;
         // the double goes on the stack
     Holder<array<double,200>> v2;       // the array goes on the free store
     // ...
     *v1 = 7.7;     // Scoped provides pointer-like access (* and [])
     v2[77] = 9.9;  // On_heap provides pointer-like access (* and [])
     // ...
}

Except when explaining an implementation or what the standard specifically offers, I use such type aliases systematically. When the standard provides a type function (called something like “type property predicate” or “composite type category predicate”), such as conditional, I define a corresponding type alias (§35.4.1):

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template<typename C, typename T, typename F>
using Conditional = typename std::conditional<C,T,F>::type;

Please note that these aliases are unfortunately not part of the standard.

28.2.1.1. When Not to Use an Alias

There is one case in which it is significant to use ::type directly, rather than an alias. If only one of the alternatives is supposed to be a valid type, we should not use an alias. Consider first a simple analogy:

if (p) {
       p–>f(7);
       // ...
}

It is important that we don’t enter the block if p is the nullptr. We are using the test to see if p is valid. Similarly, we might want to test to see if a type is valid. For example:

conditional<
  is_integral<T>::value,
  make_unsigned<T>,
  Error<T>
>::type

Here, we test if T is an integral type (using the std::is_integral type predicate) and make the unsigned variant of that type if it is (using the std::make_unsigned type function). If that succeeds, we have an unsigned type; otherwise, we will have to deal with the Error indicator.

Had we written Make_unsigned<T> meaning

typename make_unsigned<T>::type

and tried to use it for a nonintegral type, say std::string, we would have tried to make a nonexistent type (make_unsigned<std::string>::type). The result would have been a compile-time error.

In the rare cases where we can’t use aliases consistently to hide ::type, we can fall back on the more explicit, implementation-oriented ::type style. Alternatively, we can introduce a Delay type function to delay evaluation of a type function until its use:

Conditional<
  is_integral<T>::value,
  Delay<Make_unsigned,T>,
  Error<T>
>

The implementation of a perfect Delay function is nontrivial, but for many uses this will do:

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template<template<typename...> class F, typename... Args>
using Delay = F<Args...>;

This uses a template template argument (§25.2.4) and variadic templates (§28.6).

Independently of which solution we choose to avoid the undesired instantiation, this is the kind of expert territory that I enter only with some trepidation.

28.2.2. Type Predicates

A predicate is a function that returns a Boolean value. If you want to write functions that take arguments that are types, it seems obvious that you’ll like to ask questions about the arguments’ types. For example: Is this a signed type? Is this type polymorphic (i.e., does it have at least one virtual function)? Is this type derived from that type?

The answers to many such questions are known to the compiler and exposed to the programmer through a set of standard-library type predicates (§35.4.1). For example:

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template<typename T>
void copy(T* p, const T* q, int n)
{
     if (std::is_pod<T>::value)
           memcpy(p,q,n);             // use optimized memory copy
     else
         for (int i=0; i!=n; ++i)
               p[i] = q[i];           // copy individual values
}

Here, we try to optimize the copy by using the (supposedly optimal) standard-library function memcpy() when we can treat the objects as “plain old data” (POD; §8.2.6). If not, we copy the objects one by one (potentially) using their copy constructor. We determine whether the template argument type is a POD by the standard-library type predicate is_pod. The result is presented by the member value. This standard-library convention is similar to the way type functions present their result as a member type.

The std::is_pod predicate is one of the many provided by the standard library (§35.4.1). Since the rules for being a POD are tricky, is_pod is most likely a compiler intrinsic rather than implemented in the library as C++ code.

Like the ::type convention, the value ::value causes verbosity and is a departure from conventional notation that lets implementation details shine through: a function returning a bool should be called using ():

template<typename T>
void copy(T* p, const T* q, int n)
{
     if (is_pod<T>())
     // ...
}

Fortunately, the standard supports that for all standard-library type predicates. Unfortunately, for language-technical reasons, this resolution is not available in the context of a template argument. For example:

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template<typename T>
void do_something()
{
     Conditional<is_pod<T>(),On_heap<T>,Scoped<Y>) x;  // error: is_pod<T>() is a type
     // ..
}

In particular, is_pod<T> is interpreted as the type of a function taking no argument and returning an is_pod<T> (§iso.14.3[2]).

My solution is to add functions to provide the conventional notation in all contexts:

template<typename T>
constexpr bool Is_pod()
{
    return std::is_pod<T>::value;
}

I capitalize the names of these type functions to avoid confusion with the standard-library versions. In addition, I keep them in a separate namespace (Estd).

We can define our own type predicates. For example:

template<typename T>
constexpr bool Is_big()
{
    return 100<sizeof(T);
}

We could use this (rather crude) notion of “big” like this:

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template<typename T>
using Obj_holder = Conditional<(Is_big<T>()), Scoped<T>, On_heap<T>>;

It is rarely necessary to define predicates that directly reflect basic properties of types because the standard library provides many of those. Examples are is_integral, is_pointer, is_empty, is_polymorphic, and is_move_assignable (§35.4.1). When we have to define such predicates, we have rather powerful techniques available. For example, we can define a type function to determine whether a class has a member of a given name and of an appropriate type (§28.4.4).

Naturally, type predicates with more than one argument can also be useful. In particular, this is how we represent relations between two types, such as is_same, is_base_of, and is_convertible. These are also from the standard library.

I use Is_* constexpr functions to support the usual () calling syntax for all of these is_ *functions.

28.2.3. Selecting a Function

A function object is an object of some type, so the techniques for selecting types and values can be used to select a function. For example:

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struct X { // write X
     void operator()(int x) { cout <<"X&" << x << "!"; }
     // ...
};

struct Y { // write Y
     void operator()(int y) { cout <<"Y" << y << "!"; }
     // ...
};

void f()
{
     Conditional<(sizeof(int)>4),X,Y>{}(7);   // make an X or a Y and call it

     using Z = Conditional<(Is_polymorphic<X>()),X,Y>;
     Z zz;     // make an X or a Y
     zz(7);    // call an X or a Y
}

As shown, a selected function object type can be used immediately or “remembered” for later use.

Classes with member functions computing some value are the most general and flexible mechanism for computation in template metaprogramming.

Conditional is a mechanism for compile-time programming. In particular, this means that the condition must be a constant expression. Note the parentheses around sizeof(int)>4; without those, we would have gotten a syntax error because the compiler would have interpreted the > as the end of the template argument list. For that reason (and others), I prefer to use < (less than) rather than > (greater than). Also, I sometimes use parentheses around conditions for readability.

28.2.4. Traits

The standard library relies heavily on traits. A trait is used to associate properties with a type. For example, the properties of an iterator are defined by its iterator_traits (§33.1.3):

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template<typename Iterator>
struct iterator_traits {
     using difference_type = typename Iterator::difference_type;
     using value_type = typename Iterator::value_type;
     using pointer = typename Iterator::pointer;
     using reference = typename Iterator::reference;
     using iterator_category = typename Iterator::iterator_category;
};

You can see a trait as a type function with many results or as a bundle of type functions.

The standard library provides allocator_traits (§34.4.2), char_traits (§36.2.2), iterator_traits (§33.1.3), regex_traits (§37.5), pointer_traits (§34.4.3). In addition, it provides time_traits (§35.2.4) and type_traits (§35.4.1), which confusingly are simple type functions.

Given iterator_traits for a pointer, we can talk about the value_type and the difference_type of a pointer even though pointers don’t have members:

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template<typename Iter>
Iter search(Iter p, Iter q, typename iterator_traits<Iter>::value_type val)
{
      typename iterator_traits<Iter>::difference_type m = q–p;
      // ...
}

This is a most useful and powerful technique, but:

• It is verbose.

• It often bundles otherwise weakly related type functions.

• It exposes implementation details to users.

Also, people sometimes throw in type aliases “just in case,” leading to unneccesary complexity. Consequently, I prefer to use simple type functions:

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template<typename T>
    using Value_type = typename std::iterator_trait<T>::value_type;

template<typename T>
    using Difference_type = typename std::iterator_trait<T>::difference_type;

template<typename T>
    using Iterator_category= typename std::iterator_trait<T>::iterator_category;

The example cleans up nicely:

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template<typename Iter>
Iter search(Iter p, iter q, Value_type<Iter> val)
{
      Difference_type<Iter> m = q–p;
      // ...
}

I suspect that traits are currently overused. Consider how to write the previous example without any mention of traits or other type functions:

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template<typename Iter, typename Val>
Iter search(Iter p, iter q, Val val)
{
      auto x = *p;                                // if we don't need to name *p's type
      auto m = q–p;                               // if we don't need to name q-p's type

      using value_type = decltype(*p);            // if we want to name *p's type
      using difference_type = decltype(q–p);      // if we want to name q-p's type

     // ...
}

Of course, decltype() is a type function, so all I did was to eliminate user-defined and standard-library type functions. Also, auto and decltype are new in C++11, so older code could not have been written this way.

We need a trait (or equivalent, such as decltype()) to associate a type with another type, such as a value_type with a T*. For that, a trait (or an equivalent) is indispensable for non-intrusively adding type names needed for generic programming or metaprogramming. When a trait is used simply to provide a name for something that already has a perfectly good name, such as pointer for value_type* and reference for value_type&, the utility is less clear and the potential for confusion greater. Don’t blindly define traits for everything “just in case.”

28.3. Control Structures

To do general computation at compile time, we need selection and recursion.

28.3.1. Selection

In addition to what is trivially done using ordinary constant expressions (§10.4), I use:

• Conditional: a way of choosing between two types (an alias for std::conditional)

• Select: a way of choosing among several types (defined in §28.3.1.3)

These type functions return types. If you want to choose among values, ?: is sufficient; Conditional and Select are for selecting types. They are not simply compile-time equivalents to if and switch even though they can appear to be when they are used to choose among function objects (§3.4.3, §19.2.2).

28.3.1.1. Selecting between Two Types

It is surprisingly simple to implement Conditional, as used in §28.2. The conditional template is part of the standard library (in <type_traits>), so we don’t have to implement it, but it illustrates an important technique:

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template<bool C, typename T, typename F>  // general template
struct conditional {
     using type = T;
};

template<typename T, typename F>         // specialization for false
struct conditional<false,T,F> {
     using type = F;
};

The primary template (§25.3.1.1) simply defines its type to be T (the first template parameter after the condition). If the condition is not true, the specialization for false is chosen and type is defined to be F. For example:

typename conditional<(std::is_polymorphic<T>::value),X,Y>::type z;

Obviously, the syntax leaves a bit to be desired (§28.2.2), but the underlying logic is beautiful.

Specialization is used to separate the general case from one or more specialized ones (§25.3). In this example, the primary template takes care of exactly half of the functionality, but that fraction can vary from nothing (every nonerroneous case is handled by a specialization; §25.3.1.1) to all but a single terminating case (§28.5). This form of selection is completely compile-time and doesn’t cost a byte or a cycle at run time.

To improve the syntax, I introduce a type alias:

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template<bool B, typename T, typename F>
using Conditional = typename std::conditional<B,T,F>::type;

Given that, we can write:

Conditional<(Is_polymorphic<T>()),X,Y> z;

I consider that a significant improvement.

28.3.1.2. Compile Time vs. Run Time

Looking at something like

Conditional<(std::is_polymorphic<T>::value),X,Y> z;

for the first time, it is not uncommon for people to think, “Why don’t we just write a normal if?” Consider having to choose between two alternatives, Square and Cube:

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struct Square {
     constexpr int operator()(int i) { return i*i; }
};

struct Cube {
     constexpr int operator()(int i) { return i*i*i; }
};

We might try the familiar if-statement:

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if (My_cond<T>())
      using Type = Square;   // error: declaration as if-statement branch
else
      using Type = Cube;     // error: declaration as if-statement branch

Type x;  // error: Type is not in scope

A declaration cannot be the only statement of a branch of an if-statement (§6.3.4, §9.4.1), so this will not work even though My_cond<T>() is computed at compile time. Thus, an ordinary if-statement is useful for ordinary expressions, but not for type selection.

Let us try an example that doesn’t involve defining a variable:

Conditional<My_cond<T>(),Square,Cube>{}(99); // invoke Square{}(99) or Cube{}(99)

That is, select a type, construct a default object of that type, and call it. That works. Using “conventional control structures,” this would become:

((My_cond<T>())?Square:Cube){}(99);

This example doesn’t work because Square{}(99) and Cube{}(99) do not yield types, rather than values of types that are compatible in a conditional expression (§11.1.3). We could try

(My_cond<T>()?Square{}:Cube{})(99);   // error: incompatible arguments for ?:

Unfortunately, this version still suffers from the problem that Square{} and Cube{} are not of compatible types acceptable as alternatives in a ?: expression. The restriction to compatible types is often unacceptable in metaprogramming because we need to choose between types that are not explicitly related.

Finally, this works:

My_cond<T>()?Square{}(99):Cube{}(99);

Furthermore, it is not significantly more readable than

Conditional<My_cond<T>(),Square,Cube>{}(99);

28.3.1.3. Selecting among Several Types

Selecting among N alternatives is very similar to choosing between two. Here is a type function returning its Nth argument type:

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class Nil {};

template<int I, typename T1 =Nil, typename T2 =Nil, typename T3 =Nil, typename T4 =Nil>
struct select;

template<int I, typename T1 =Nil, typename T2 =Nil, typename T3 =Nil, typename T4 =Nil>
using Select = typename select<I,T1,T2,T3,T4>::type;

// Specializations for 0-3:

template<typename T1, typename T2, typename T3, typename T4>
struct select<0,T1,T2,T3,T4> { using type = T1; }; // specialize for N==0

template<typename T1, typename T2, typename T3, typename T4>
struct select<1,T1,T2,T3,T4> { using type = T2; }; // specialize for N==1

template<typename T1, typename T2, typename T3, typename T4>
struct select<2,T1,T2,T3,T4> { using type = T3; }; // specialize for N==2

template<typename T1, typename T2, typename T3, typename T4>
struct select<3,T1,T2,T3,T4> { using type = T4; }; // specialize for N==3

The general version of select should never be used, so I didn’t define it. I chose zero-based numbering to match the rest of C++. This technique is perfectly general: such specializations can present any aspect of the template arguments. We don’t really want to pick a maximum number of alternatives (here, four), but that problem can be addressed using variadic templates (§28.6). The result of picking a nonexisting alternative is to use the primary (general) template. For example:

Select<5,int,double,char> x;

In this case, that would lead to an immediate compile-time error as the general Select isn’t defined.

A realistic use would be to select the type for a function returning the Nth element of a tuple:

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template<int N, typename T1, typename T2, typename T3, typename T4>
Select<N,T1,T2,T3,T4> get(Tuple<T1,T2,T3,T4>& t);   // see §28.5.2

auto x = get<2>(t); // assume that t is a Tuple

Here, the type of x will be whatever T3 is for the Tuple called t. Indexing into tuples is zero-based.

Using variadic templates (§28.6), we can provide a far simpler and more general select:

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template<unsigned N, typename... Cases>   // general case; never instantiated
struct select;

template<unsigned N, typename T, typename... Cases>
struct select<N,T,Cases...> :select<N–1,Cases...> {
};

template<typename T, typename... Cases>   // final case: N==0
struct select<0,T,Cases...> {
   using type = T;
};

template<unsigned N, typename... Cases>
using Select = typename select<N,Cases...>::type;

28.3.2. Iteration and Recursion

The basic techniques for calculating a value at compile time can be illustrated by a factorial function template:

template<int N>
constexpr int fac()
{
    return N*fac<N–1>();
}}

template<>
constexpr int fac<1>()
{
    return 1;
}

constexpr int x5 = fac<5>();

The factorial is implemented using recursion, rather than using a loop. Since we don’t have variables at compile time (§10.4), that makes sense. In general, if we want to iterate over a set of values at compile time, we use recursion.

Note the absence of a condition: there is no N==1 or N<2 test. Instead, the recursion is terminated when the call of fac() selects the specialization for N==1. In template metaprogramming (as in functional programming), the idiomatic way of working your way through a sequence of values is to recurse until you reach a terminating specialization.

In this case, we could also do the computation in the more conventional way:

constexpr int fac(int i)
{
    return (i<2)?1:fac(i–1);
}

constexpr int x6 = fac(6);

I find this clearer than the function template expression of the idea, but tastes vary and there are algorithms that are best expressed by separating the terminating case from the general case. The non-template version is marginally easier for a compiler to handle. The run-time performance will, of course, be identical.

The constexpr version can be used for both compile-time and run-time evaluation. The template (metaprogramming) version is for compile-time use only.

28.3.2.1. Recursion Using Classes

Iteration involving more complicated state or more elaborate parameterization can be handled using classes. For example, the factorial program becomes:

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template<int N>
struct Fac {
     static const int value = N*Fac<N–1>::value;
};

template<>
struct Fac<1> {
     static const int value = 1;
};

constexpr int x7 = Fac<7>::value;

For a more realistic example, see §28.5.2.

28.3.3. When to Use Metaprogramming

Using the control structures described here, you can compute absolutely everything at compile time (translation limits permitting). The question remains: Why would you want to? We should use these techniques if and when they yield cleaner, better-performing, and easier-to-maintain code than alternative techniques. The most obvious constraint on metaprogramming is that code depending on complicated uses of templates can be hard to read and very hard to debug. Nontrivial uses of templates can also impact compile times. If you have a hard time understanding what is going on in code requiring complicated patterns of instantiation, so might the compiler. Worse still, so may the programmer who gets to maintain your code.

Template metaprogramming attracts clever people:

• Partly, that’s because metaprogramming allows us to express things that simply can’t be done at the same level of type safety and run-time performance. When the improvements are significant and the code maintainable, these are good – sometimes even compelling – reasons.

• Partly, that’s because metaprogramming allows us to show off our cleverness. Obviously, that is to be avoided.

How would you know that you have gone too far with metaprogramming? One warning sign that I use is an urge to use macros (§12.6) to hide “details” that have become too ugly to deal with directly. Consider:

#define IF(c,x,y) typename std::conditional<(c),x,y>::type

Is this going too far? It allows us to write

IF(cond,Cube,Square) z;

rather than

typename std::conditional<(cond),Cube,Square>::type z;

I have biased the question by using the very short name IF and the long form std::conditional.

Similarly, a more complex condition would almost equalize the number of characters used. The fundamental difference is that I have to write typename and ::type to use the standard’s terminology. That exposes the template implementation technique. I would like to hide that, and the macro does. However, if many people need to collaborate and programs get large, a bit of verbosity is preferable to a divergence of notations.

Another serious argument against the IF macro is that its name is misleading: conditional is not a “drop-in replacement” for a conventional if. That ::type represents a significant difference: conditional selects between types; it does not directly alter control flow. Sometimes it is used to select a function and thus represent a branch in a computation; sometimes it is not. The IF macro hides an essential aspect of its function. Similar objections can be leveled at many other “sensible” macros: they are named for some programmer’s particular idea of their use, rather than reflecting fundamental functionality.

In this case, the problems of verbosity, of the implementation details leaking out, and of poor naming are easily handled by a type alias (Conditional; §28.2.1). In general, look hard for ways to clean up the syntax presented to users without inventing a private language. Prefer systematic techniques, such as specialization and the use of aliases, to macro hackery. Prefer constexpr functions to templates for compile-time computation, and hide template metaprogramming implementation details in constexpr functions whenever feasible (§28.2.2).

Alternatively, we can look at the fundamental complexity of what we are trying to do:

[1] Does it require explicit tests?

[2] Does it require recursion?

[3] Can we write concepts (§24.3) for our template arguments?

If the answer to question [1] or [2] is “yes” or the answer to question [3] is “no,” we should consider whether there may be maintenance problems. Maybe some form of encapsulation is possible? Remember that complexities of a template implementation become visible to users (“leak out”) whenever an instantiation fails. Also, many programmers do look into header files where every detail of a metaprogram is immediately exposed.

28.4. Conditional Definition: Enable_if

When we write a template, we sometimes want to provide an operation for some template arguments, but not for others. For example:

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template<typename T>
class Smart_pointer {
     // ...
     T& operator*();     // return reference to whole object
     T* operator–>();    // select a member (for classes only)
     // ...
}

If T is a class, we should provide operator–>(), but if T is a built-in type, we simply cannot do so (with the usual semantics). Therefore, we want a language mechanism for saying, “If this type has this property, define the following.” We might try the obvious:

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template<typename T>
class Smart_pointer {
     // ...
     T& operator*();                      // return reference to whole object
     if (Is_class<T>()) T* operator–>();  // syntax error
     // ...
}

However, that does not work. C++ does not provide an if that can select among definitions based on a general condition. But, as with Conditional and Select (§28.3.1), there is a way. We can write a somewhat curious type function to make the definition of operator–>() conditional. The standard library (in <type_traits>) provides enable_if for that. The Smart_pointer example becomes:

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template<typename T>
class Smart_pointer {
     // ...
     T& operator*();                             // return reference to whole object
     Enable_if<Is_class<T>(),T>* operator–>();   // select a member (for classes only)
     // ...
}

As usual, I have used type aliases and constexpr functions to simplify the notation:

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template<bool B, typename T>
using Enable_if = typename std::enable_if<B,T>::type;

template<typename T> bool Is_class()
{
    return std::is_class<T>::value;
}

If Enable_if’s condition evaluates to true, its result is its second argument (here, T). If Enable_if’s condition evaluates to false, the whole function declaration of which it is part is completely ignored. In this case, if T is a class, we get a definition of operator–>() returning a T*, and if it is not, we don’t declare anything.

Given the definition of Smart_pointer using Enable_if, we get:

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void f(Smart_pointer<double> p, Smart_pointer<complex<double>> q)
{
    auto d0 = *p;            // OK
    auto c0 = *q;            // OK
    auto d1 = q–>real();     // OK
    auto d2 = p–>real();     // error: p doesn't point to a class object
    // ...
}

You may consider Smart_pointer and operator–>() exotic, but providing (defining) operations conditionally is very common. The standard library provides many examples of conditional definition, such as Alloc::size_type (§34.4.2) and pair being movable if both of their elements are (§34.2.4.1). The language itself defines –> only for pointers to class objects (§8.2).

In this case, the elaboration of the declaration of operator–>() with Enable_if simply changes the kind of error we get from examples, such as p–>real():

• If we unconditionally declare operator–>(), we get a “–> used on a non-class pointer” error at instantiation time for the definition of Smart_pointer<double>::operator–>().

• If we conditionally declare operator–>() using Enable_if, if we use –> on a smart_ptr<double>, we get a “Smart_ptr<double>::operator–>() not defined” error at the point of use of Smart_ptr<double>::operator–>().

In either case, we do not get an error unless we use –> on a smart_ptr<T> where T is not a class.

We have moved the error detection and reporting from the implementation of smart_pointer<T>::operator–>() to its declaration. Depending on the compiler and especially on how deep in a nest of template instantiations the error happens, this can make a significant difference. In general, it is preferable to specify templates precisely so as to detect errors early rather than relying on bad instantiations being caught. In this sense, we can see Enable_if as a variant of the idea of a concept (§24.3): it allows a more precise specification of the requirements of a template.

28.4.1. Use of Enable_if

For many uses, the functionality of enable_if is pretty ideal. However, the notation we have to use is often awkward. Consider:

Enable_if<Is_class<T>(),T> *operator–>();

The implementation shows through rather dramatically. However, what is actually expressed is pretty close to the minimal ideal:

declare_if (Is_class<T>()) T* operator–>();   // not C++

However, C++ does not have a declare_if construct for selecting declarations.

Using Enable_if to decorate the return type places it up front where you can see it and where it logically belongs, because it affects the whole declaration (not just the return type). However, some declarations do not have a return type. Consider two of vector’s constructors:

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template<typename T>
class vector<T> {
public:
     vector(size_t n, const T& val); // n elements of type T with value val

     template<typename Iter>
         vector(Iter b, Iter e); // initialize from [b:e)
     // ...
};

This looks innocent enough, but the constructor taking a number of elements wrecks its usual havoc. Consider:

vector<int> v(10,20);

Is that 10 elements with the value 20 or an attempt to initialize from [10:20]? The standard requires the former, but the code above would naively pick the latter because an int-to-size_t conversion is required for the first constructor whereas the pair of ints is a perfect match for the template constructor. The problem is that I “forgot” to tell the compiler that the Iter type should be an iterator. However, that can be done:

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template<typename T>
class vector<T> {
public:
     vector(size_t n, const T& val);   // n elements of type T with value val

     template<typename Iter, typename =Enable_if<Input_iterator<Iter>(),Iter>>
         vector(Iter b, Iter e);      // initialize from [b:e)
     // ...
};

That (unused) default template argument will be instantiated because we certainly can’t deduce that unused template parameter. This implies that the declaration of vector(Iter,Iter) will fail unless Iter is an Input_iterator (§24.4.4).

I introduced the Enable_if as a default template argument because that is the most general solution. It can be used for templates without arguments and/or without return types. However, in this case, we could alternatively apply it to the constructor argument type:

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template<typename T>
class vector<T> {
public:
     vector(size_t n, const T& val);     // n elements of type T with value val

     template<typename Iter>
         vector(Enable_if<Input_iterator<Iter>(),Iter>> b, Iter e);       // initialize from [b:e)
     // ...
};

The Enable_if techniques work for template functions (including member functions of class templates and specializations) only. The implementation and use of Enable_if rely on a detail in the rules for overloading function templates (§23.5.3.2). Consequently, it cannot be used to control declarations of classes, variables, or non-template functions. For example:

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Enable_if<(version2_2_3<config),M_struct>* make_default() // error: not a template
{
     return new Mystruct{};
}

template<typename T>
void f(const T& x)
{
     Enable_if<(20<sizeof<T>),T> tmp = x;            // error: tmp is not a function
     Enable_if<!(20<sizeof<T>),T&> tmp = *new T{x};  // error: tmp is not a function
     // ...
}

For tmp, using Holder (§28.2) would almost certainly be cleaner anyway: if you had managed to construct that free-store object, how would you delete it?

28.4.2. Implementing Enable_if

The implementation of Enable_if is almost trivial:

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template<bool B, typename T = void>
struct std::enable_if {
     typedef T type;
};

template<typename T>
struct std::enable_if<false, T> {};     // no ::type if B==false

template<bool B, typename T = void>
using Enable_if = typename std::enable_if<B,T>::type;

Note that we can leave out the type argument and get void by default.

For a language-technical explanation of how these simple declarations become useful as a fundamental construct see §23.5.3.2.

28.4.3. Enable_if and Concepts

We can use Enable_if for a wide variety of predicates, including many tests of type properties (§28.3.1.1). Concepts are among the most general and useful predicates we have. Ideally, we would like to overload based on concepts, but lacking language support for concepts, the best we can do is to use Enable_if to select based on constraints. For example:

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template<typename T>
Enable_if<Ordered<T>()> fct(T* ,T* );    // optimized implementation

template<typename T>
Enable_if<!Ordered<T>()> fct(T*,T*);     // nonoptimized implementation

Note that Enable_if defaults to void, so fct() is a void function. I’m not sure that using that default increases readability, but we can use fct() like this:

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void f(vector<int>& vi, vector<complex<int>>& vc)
{
     if (vi.size()==0 || vc.size()==0) throw runtime_error("bad fct arg");
     fct(&vi.front(),&vi.back());            // call optimized
     fct(&vc.front(),&vc.back());            // call nonoptimized
}

These calls are resolved as described because we can use < for an int but not for a complex<int>. Enable_if resolves to void if we don’t provide a type argument.

28.4.4. More Enable_if Examples

When using Enable_if, sooner or later we want to ask if a class has a member with a specific name and an appropriate type. For many of the standard operations, such as constructors and assignments, the standard library provides a type property predicate, such as is_copy_assignable and is_default_constructible (§35.4.1). However, we can build our own predicates. Consider the question “Can we call f(x) if x is of type X?” Defining has_f to answer that question gives an opportunity to demonstrate some of the techniques used and some of the scaffolding/boilerplate code provided internally in many template metaprogramming libraries (including parts of the standard library). First, define the usual class plus specialization to represent an alternative:

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struct substitution_failure { }; // represent a failure to declare something

template<typename T>
struct substitution_succeeded : std::true_type
{ };

template<>
struct substitution_succeeded<substitution_failure> : std::false_type
{ };

Here, substitution_failure is used to represent a substitution failure (§23.5.3.2). We derive from std::true_type unless the argument type is substitution_failure. Obviously, std::true_type and std::false_type are types that represent the values true and false, respectively:

std::true_type::value == true
std::false_type::value == false

We use substitution_succeeded to define the type functions we really want. For example, we might be looking for a function f that we can call as f(x). For that, we can define has_f:

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template<typename T>
struct has_f
   : substitution_succeeded<typename get_f_result<T>::type>
{};

So, if get_f_result<T> yields a proper type (presumably the return type of a call of f), has_f::value is true_type::value, which is true. If get_f_result<T> doesn’t compile, it returns substitution_failure and has_f::value is false.

So far, so good, but how do we get get_f_result<T> to be substitution_failure if somehow f(x) doesn’t compile for a value x of type X? The definition that achieves that looks innocent enough:

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template<typename T>
struct get_f_result {
private:
     template<typename X>
         static auto check(X const& x) –> decltype(f(x));   // can call f(x)
     static substitution_failure check(...);                // cannot call f(x)
public:
     using type = decltype(check(std::declval<T>()));
};

We simply declare a function check so that check(x) has the same return type as f(x). Obviously, that won’t compile unless we can call f(x). So, that declaration of check fails if we can’t call f(x). In that case, because substitution failure is not an error (SFINAE; §23.5.3.2), we get the second definition of check(), which has substitution_failure as its return type. And, yes, this elaborate piece of trickery fails if our function f was declared to return a substitution_failure.

Note that decltype() does not evaluate its operand.

We managed to turn what looked like a type error into the value false. It would have been simpler if the language had provided a primitive (built-in) operation for doing that conversion; for example:

is_valid());   // can f(x) be compiled?

However, a language cannot provide everything as a language primitive. Given the scaffolding code, we just have to provide conventional syntax:

template<typename T>
constexpr bool Has_f()
{
    return has_f<T>::value;
}

Now, we can write:

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template<typename T>
class X {
     // ...
     Enable_if<Has_f<T>()> use_f(const T&)
     {
          // ...
          f(t);
          // ...
     }
     // ...
};

X<T> has a member use_f() if and only if f(t) can be called for a T value t.

Note that we cannot simply write:

if (Has_f<decltype(t)>()) f(t);

The call f(t) will be type checked (and fail type checking) even if Has_f<decltype(t)>() returns false.

Given the technique used to define Has_f, we can define Has_foo for any operation or member foo we can think of. The scaffolding is 14 lines of code for each foo. This can get repetitive but is not difficult.

This implies that Enable_if<> allows us to choose among overloaded templates based on just about any logical criteria for argument types. For example, we can define a Has_not_equals() type function to check if != is available and use it like this:

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template<typename Iter, typename Val>
Enable_if<Has_not_equals<Iter>(),Iter> find(Iter first, Iter last, Val v)
{
     while (first!=last && !(*first==v))
           ++first;
     return first;
}

template<typename Iter, typename Val>
Enable_if<!Has_not_equals<Iter>(),Iter> find(Iter first, Iter last, Val v)
{
     while (!(first==last) && !(*first==v))
           ++first;
     return first;
}

Such ad hoc overloading easily gets messy and unmanageable. For example, try adding versions that use != for the value comparison (that is, *first!=v, rather than !(*first==v)), when possible. Consequently, I recommend relying on the more structured standard overloading rules (§12.3.1) and specialization rules (§25.3) when there is a choice. For example:

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template<typename T>
auto operator!=(const T& a, const T& b) –> decltype(!(a==b))
{
     return !(a==b);
}

The rules ensure that if a specific != has already been defined for a type T (as a template or as a non-template function), this definition will not be instantiated. I use decltype() partly to show how in general to derive the return type from a previously defined operator, and partly to handle the rare cases where != returns something different from bool.

Similarly, we can conditionally define >, <=, >=, etc., given a <.

28.5. A Compile-Time List: Tuple

Here, I’ll demonstrate the basic template metaprogramming techniques in a single simple, but realistic, example. I will define a Tuple with an associated access operation and an output operation. Tuples defined like this have been used industrially for more than a decade. The more elegant and more general std::tuple is presented in §28.6.4 and §34.2.4.2.

The idea is to allow code like this:

Tuple<double, int, char> x {1.1, 42, 'a'};
cout << x << "\n";
cout << get<1>(x) << "\n";

The resulting output is:

{ 1.1, 42, 'a'};
42

The definition of Tuple is fundamentally simple:

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template<typename T1=Nil, typename T2=Nil, typename T3=Nil, typename T4=Nil>
struct Tuple : Tuple<T2, T3, T4> { // layout: {T2,T3,T4} before T1
     T1 x;

     using Base = Tuple<T2, T3, T4>;
     Base* base() { return static_cast<Base*>(this); }
     const Base* base() const { return static_cast<const Base*>(this); }

     Tuple(const T1& t1, const T2& t2, const T3& t3, const T4& t4) :Base{t2,t3,t4}, x{t1} { }
};

So, a Tuple of four elements (often referred to as a 4-tuple) is a Tuple of three elements (a 3-tuple) followed by a fourth element.

We construct a Tuple of four elements with a constructor that takes four values (potentially of four different types). It uses its last three elements (its tail) to initialize its base 3-tuple and the first (its head) to initialize its member x.

Manipulation of the tail of a Tuple – that is of the base class of the Tuple – is important and common in the implementation of the Tuple. Consequently, I provided an alias Base and a pair of member functions base() to simplify manipulation of the base/tail.

Obviously, this definition handles only tuples that really have four elements. Furthermore, it leaves much of the work to the 3-tuple. Tuples with fewer than four elements are defined as specializations:

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template<>
struct Tuple<> { Tuple() {} };           // 0-tuple

template<typename T1>
struct Tuple<T1> : Tuple<> {             // 1-tuple
     T1 x;

     using Base = Tuple<>;
     Base *base() { return static_cast<Base*>(this); }
     const Base *base() const { return static_cast<const Base*>(this); }

     Tuple(const T1& t1) :Base{}, x{t1} { }
};

template<typename T1, typename T2>
struct Tuple<T1, T2> : Tuple<T2> {      // 2-tuple, layout: T2 before T1
     T1 x;

     using Base = Tuple<T2>;
     Base* base() { return static_cast<Base*>(this); }
     const Base* base() const { return static_cast<const Base*>(this); }

     Tuple(const T1& t1, const T2& t2) :Base{t2}, x{t1} { }
};

template<typename T1, typename T2, typename T3>
struct Tuple<T1, T2, T3> : Tuple<T2, T3> {     // 3-tuple, layout: {T2,T3} before T1
     T1 x;
     using Base = Tuple<T2, T3>;
     Base* base() { return static_cast<Base*>(this); }
     const Base* base() const { return static_cast<const Base* >(this); }

     Tuple(const T1& t1, const T2& t2, const T3& t3) :Base{t2, t3}, x{t1} { }
};

These declarations are rather repetitive and follow the simple pattern of the first Tuple (the 4-tuple). That definition of a 4-tuple, Tuple, is the primary template and provides the interface to Tuples of all sizes (0, 1, 2, 3, and 4). That is why I had to provide those Nil default template arguments. In fact, they will never be used. Specialization will choose one of the simpler Tuples rather than use Nil.

The way I defined Tuple as a “stack” of derived classes is fairly conventional (e.g., std::tuple is defined similarly; §28.5). It has the curious effect that the first element of a Tuple will (given the usual implementation techniques) get the highest address and that the last element will have the same address as the whole Tuple. For example:

tuple<double,string,int,char>{3.14,string{"Bob"},127,'c'}

can be graphically represented like this:

This opens some interesting optimization possibilities. Consider:

class FO { /* function object with no data members */ };

typedef Tuple<int* , int *> T0;
typedef Tuple<int* ,FO> T1;
typedef Tuple<int* , FO, FO> T2;

On my implementation, I got sizeof(T0)==8, sizeof(T1)==4, and sizeof(T2)==4 as the compiler optimizes away the empty base classes. This is called the empty-base optimization and is guaranteed by the language (§27.4.1).

28.5.1. A Simple Output Function

The definition of Tuple has a nice regular, recursive structure that we can use to define a function for displaying the list of elements. For example:

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template<typename T1, typename T2, typename T3, typename T4>
void print_elements(ostream& os, const Tuple<T1,T2,T3,T4>& t)
{
     os << t.x << ", ";            // t's x
     print_elements(os,*t.base());
}

template<typename T1, typename T2, typename T3>
void print_elements(ostream& os, const Tuple<T1,T2,T3>& t)
{
     os << t.x << ", ";
     print_elements(os,*t.base());
}

template<typename T1, typename T2>
void print_elements(ostream& os, const Tuple<T1,T2>& t)
{
     os << t.x << ", ";
     print_elements(os,*t.base());
}

template<typename T1>
void print_elements(ostream& os, const Tuple<T1>& t)
{
     os << t.x;
}

template<>
void print_elements(ostream& os, const Tuple<>& t)
{
     os << " ";
}

The similarity of the print_elements() for the 4-tuple, 3-tuple, and 2-tuple hints at a better solution (§28.6.4), but for now I’ll just use these print_elements() to define a << for Tuples:

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template<typename T1, typename T2, typename T3, typename T4>
ostream& operator<<(ostream& os, const Tuple<T1,T2,T3,T4>& t)
{
     os << "{ ";
     print_elements(os,t);
     os << " }";
     return os;
}

We can now write:

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Tuple<double, int, char> x {1.1, 42, 'a'};
cout << x << "\n";

cout << Tuple<double,int,int,int>{1.2,3,5,7} << "\n";
cout << Tuple<double,int,int>{1.2,3,5} << "\n";
cout << Tuple<double,int>{1.2,3} << "\n";
cout << Tuple<double>{1.2} << "\n";
cout << Tuple<>{} << "\n";

Unsurprisingly, the output is:

{ 1.1 42, a }
{ 1.2,3,5,7 }
{ 1.2,3,5 }
{ 1.2,3 }
{ 1.2 }
{ }

28.5.2. Element Access

As defined, Tuple has a variable number of elements of potentially differing types. We would like to access those elements efficiently and without the possibility of type system violations (i.e., without using casts). We can imagine a variety of schemes, such as naming the elements, numbering the elements, and accessing elements by recursing though the elements until we reach a desired element. The last alternative is what we will use to implement the most common access strategy: index the elements. In particular, I want to implement a way to subscript a tuple. Unfortunately, I am unable to implement an appropriate operator[], so I use a function template get():

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Tuple<double, int, char> x {1.1, 42, 'a'};

cout << "{ "
     << get<0>(x) << ", "
     << get<1>(x) << ", "
     << get<2>(x) << " }\n";  // write { 1.1, 42, a }

auto xx = get<0>(x); // xx is a double

The idea is to index the elements, starting from 0, in such a way that the element selection is done at compile time and we preserve all type information.

The get() function constructs an object of type getNth<T,int>. The job of getNth<X,N> is to return a reference to the Nth element, which is assumed to have type X. Given such a helper, we can define get():

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template<int N, typename T1, typename T2, typename T3, typename T4>
Select<N, T1, T2, T3, T4>& get(Tuple<T1, T2, T3, T4>& t)
{
     return getNth<Select<N, T1, T2, T3, T4>,N>::get(t);
}

The definition of getNth is a variant of the usual recursion from N down to the specialization for 0:

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template<typename Ret, int N>
struct getNth {         // getNth() remembers the type (Ret) of the Nth element
     template<typename T>
     static Ret& get(T& t)     // get the value element N from t's Base
     {
          return getNth<Ret,N–1>::get(*t.base());
     }
};
template<typename Ret>
struct getNth<Ret,0> {
     template<typename T>
     static Ret& get(T& t)
     {
          return t.x;
     }
};

Basically, getNth is a special-purpose for-loop, implemented by recursing N–1 times. The member functions are static because we don’t really want any objects of class getNth. That class is only used as a place to hold Ret and N in a way that allows the compiler to use them.

This is quite a bit of scaffolding to index into a Tuple, but at least the resulting code is type-safe and efficient. By “efficient,” I mean that given a reasonably good compiler (as is common), there is no run-time overhead for accessing a Tuple member.

Why must we write get<2>(x) rather than just x[2]? We could try:

template<typename T>
constexpr auto operator[](T t,int N)
{
     return get<N>(t);
}

Unfortunately, this does not work:

• operator[]() must be a member, but we could handle that by defining it within Tuple.

• Inside operator[](), the argument N is not known to be a constant expression.

• I “forgot” that only lambdas can deduce their result type from their return-statement (§11.4.4), but that could be handled by adding a –>decltype(get<N>(t)).

To get that, we need some language lawyering and for now, we have to make do with get<2>(x).

28.5.2.1. const Tuples

As defined, get() works for non-const Tuple elements and can be used on the left-hand side of assignments. For example:

Tuple<double, int, char> x {1.1, 42, 'a'};

get<2>(x) = 'b';    // OK

However, it can’t be used for consts:

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const Tuple<double, int, char> xx {1.1, 42, 'a'};

get<2>(xx) = 'b';        // error: xx is const
char cc = get<2>(xx);    // error: xx is const (surprise?)

The problem is that get() takes its argument by non-const reference. But xx is a const, so it is not an acceptable argument.

Naturally, we also want to be able to have const Tuples. For example:

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const Tuple<double, int, char> xx {1.1, 422, 'a'};
char cc = get<2>(xx);               // OK: reading from const
cout << "xx: " << xx << "\n";
get<2>(xx) = 'x';                   // error: xx is const

To handle const Tuples, we have to add const versions of get() and getNth’s get(). For example:

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template<typename Ret, int N>
struct getNth {        // getNth() remembers the type (Ret) of the Nth element
     template<typename T>
     static Ret& get(T& t)   // get the value element N from t's Base
     {
            return getNth<Ret,N–1>::get(*t.base());
     }

     template<typename T>
     static const Ret& get(const T& t)      // get the value element N from t's Base
     {
            return getNth<Ret,N–1>::get(*t.base());
     }
};

template<typename Ret>
struct getNth<Ret,0> {
     template<typename T> static Ret& get(T& t) { return t.x; }
     template<typename T> static const Ret& get(const T& t) { return t.x; }
};

template<int N, typename T1, typename T2, typename T3, typename T4>
Select<N, T1, T2, T3, T4>& get(Tuple<T1, T2, T3, T4>& t)
{
     return getNth<Select<N, T1, T2, T3, T4>,N>::get(t);
}

template<int N, typename T1, typename T2, typename T3>
const Select<N, T1, T2, T3>& get(const Tuple<T1, T2, T3>& t)
{
     return getNth<Select<N, T1, T2, T3>,N>::get(t);
}

Now, we can handle both const and non-const arguments.

28.5.3. make_tuple

A class template cannot deduce its template arguments, but a function template can deduce them from its function arguments. This implies that we can make a Tuple type implicit in code by having a function construct it for us:

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template<typename T1, typename T2, typename T3, typename T4>
Tuple<T1, T2, T3, T4> make_tuple(const T1& t1, const T2& t2, const T3& t3, const T4& t4)
{
     return Tuple<T1, T2, T3, T4>{t1, t2, t3,t4};
}

// ... and the other four make_Tuples ...

Given make_tuple(), we can write:

auto xxx = make_Tuple(1.2,3,'x',1223);
cout << "xxx: " << xxx << "\n";

Other useful functions, such as head() and tail(), are easily implemented. The standard-library tuple provides a few such utility functions (§28.6.4).

28.6. Variadic Templates

Having to deal with an unknown number of elements is a common problem. For example, an error-reporting function may take between zero and ten arguments, a matrix may have between one and ten dimensions, and a tuple can have zero to ten elements. Note that in the first and the last example, the elements may not necessarily be of the same type. In most cases, we would prefer not to deal with each case separately. Ideally, a single piece of code should handle the cases for one element, two elements, three elements, etc. Also, I pulled the number ten out of a hat: ideally, there should be no fixed upper limit on the number of elements.

Over the years, many solutions have been found. For example, default arguments (§12.2.5) can be used to allow a single function to accept a variable number of arguments, and function overloading (§12.3) can be used to provide a function for each number of arguments. Passing a single list of elements (§11.3) can be an alternative to having a variable number of arguments as long as the elements are all of the same type. However, to elegantly handle the case of an unknown number of arguments of unknown (and possibly differing) types, some additional language support is needed. That language feature is called a variadic template.

28.6.1. A Type-Safe printf()

Consider the archetypical example of a function needing an unknown number of arguments of a variety of types: printf(). As provided by the C and C++ standard libraries, printf() is flexible and performs nicely (§43.3). However, it is not extensible to user-defined types and not type-safe, and it is a popular target for hackers.

The first argument to printf() is a C-style string interpreted as a “format string.” Additional arguments are used as required by the format string. Format specifiers, such as %g for floating-point and %s for zero-terminated arrays of characters, control the interpretation of the additional arguments. For example:

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printf("The value of %s is %g\n","x",3.14);
string name = "target";
printf("The value of %s is %P\n",name,Point{34,200});

printf("The value of %s is %g\n",7);

The first call of printf() works as intended, but the second call has two problems: the format specification %s refers to C-style strings, and printf() will not interpret the std::string argument correctly. Furthermore, there is no %P format and in general no direct way of printing values of user-defined types, such as Point. In the third call of printf(), I provided an int as the argument for %s and I “forgot” to provide an argument for %g. In general, a compiler is not able to compare the number and types of arguments required by the format string with the number and types of arguments provided by the programmer. The output of that last call (if any) would not be pretty.

Using variadic templates, we can implement an extensible and type-safe variant of printf(). As is common for compile-time programming, the implementation has two parts:

[1] Handle the case where there is just one argument (the format string).

[2] Handle the case where there is at least one “additional” argument that, suitably formatted, needs to output at an appropriate point indicated by the format string.

The simplest case is the one with only one argument, the format string:

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void printf(const char* s)
{
     if (s==nullptr) return;

     while (*s) {
          if (*s=='%' && *++s!='%') // make sure no more arguments are expected
                                    // %% represents plain % in a format string
                throw runtime_error("invalid format: missing arguments");
          std::cout << *s++;
     }
}

That prints out the format string. If a format specifier is found, this printf() throws an exception because there is no argument to be formatted. A format specifier is defined to be a % not followed by another % (%% is printf()’s notation for a % that does not start a type specifier). Note that *++s does not overflow even if a % is the last character in a string. In that case, *++s refers to the terminating zero.

That done, we must handle printf() with more arguments. Here is where a template, and in particular a variadic template, comes into play:

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template<typename T, typename... Args>      // variadic template argument list: one or more arguments
void printf(const char* s, T value, Args... args)    // function argument list: two or more arguments

{
     while (s &&* s) {
          if (*s=='%' &&*++s!='%') {           // a format specifier (ignore which one it is)
                std::cout << value;            // use first non-format argument
                return printf(++s, args...);   // do a recursive call with the tail of the argument list
          }
          std::cout << *s++;
     }
     throw std::runtime_error("extra arguments provided to printf");
}

This printf() finds and prints the first non-format argument, “peels off” that argument, and then calls itself recursively. When there are no more non-format arguments, it calls the first (simpler) printf(). Ordinary characters (i.e., not % formal specifiers) are simply printed.

The overloading of << replaces the use of the (possibly erroneous) “hint” in the format specifier. If an argument has a type for which << is defined, that argument is printed; otherwise, that call does not type check and the program will never run. A formatting character after a % is not used. I can imagine type-safe uses for such characters, but the purpose of this example is not to design the perfect printf() but to explain variadic templates.

The Args... defines what is called a parameter pack. A parameter pack is a sequence of (type/value) pairs from which you can “peel off” arguments starting with the first. When printf() is called with two or more arguments

void printf(const char *s, T value, Args... args);

is chosen, with the first argument as s, the second as value, and the rest (if any) bundled into the parameter pack args for later use. In the call printf(++s,args...) the parameter pack args is expanded so that the first element of args is selected as value and args is one element shorter than in the previous call. This carries on until args is empty, so that we call:

void printf(const char*);

If we really wanted to, we could check printf() format directives, such as %s. For example:

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template<typename T, typename... Args>       // variadic template argument list: one or more arguments
void printf(const char* s, T value, Args... args)  // function argument list: two or more arguments
{
     while (s && *s) {
          if (*s=='%') {  // a format specifier or %%
                switch (*++s) {
                case '%':     // not format specifier
                      break;
                case 's':
                      if (!Is_C_style_string<T>() && !Is_string<T>())
                             throw runtime_error("Bad printf() format");
                      break;
                case 'd':
                      if (!Is_integral<T>()) throw runtime_error("Bad printf() format");
                      break;
                case 'g':
                      if (!Is_floating_point<T>()) throw runtime_error("Bad printf() format");
                      break;
                }
                std::cout << value;              // use first non-format argument
                return printf(++s, args...);     // do a recursive call with the tail of the argument list
          }
          std::cout <<*s++;

     }
     throw std::runtime_error("extra arguments provided to printf");
}

The standard library provides std::is_integral and std::is_floating_point, but you’d have to craft Is_C_style_string yourself.

28.6.2. Technical Details

If you are familiar with functional programming, you should find the printf() example (§28.6) an unusual notation for a pretty standard technique. If not, here are minimal technical examples that might help. First, we can declare and use a simple variadic template function:

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template<typename... Types>
void f(Types... args);   // variadic template function

That is, f() is a function that can be called with an arbitrary number of arguments of arbitrary types:

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f();                  // OK: args contains no arguments
f(1);                 // OK: args contains one argument: int
f(2, 1.0);            // OK: args contains two arguments: int and double
f(2, 1.0, "Hello");   // OK: args contains three arguments: int, double, and const char*

A variadic template is defined with the ... notation:

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template<typename... Types>
void f(Types... args);  // variadic template function

The typename... in the declaration of Types specifies that Types is a template parameter pack. The ... in the type of args specifies that args is a function parameter pack. The type of each args function argument is the corresponding Types template argument. We can use class... with the same meaning as typename.... The ellipsis (...) is a separate lexical token, so you can place whitespace before or after it. That ellipsis can appear in many different places in the grammar, but it always means “zero or more occurrences of something”). Think of a parameter pack as a sequence of values for which the compiler has remembered the types. For example, we could graphically represent a parameter pack for {'c',127,string{"Bob"},3.14}:

This is typically called a tuple. The memory layout is not specified by the C++ standard. For example, it might be the reverse of what is shown here (last element at the lowest memory address; §28.5). However, it is a dense, not a linked, representation. To get to a value, we need to start from the beginning and work our way through to what we want. The implementation of Tuple demonstrates that technique (§28.5). We can find the type of the first element and access it using that, then we can (recursively) proceed to the next argument. If we want to, we can give the appearance of indexed access using something like get<N> for Tuple (and for std::tuple; §28.6.4), but unfortunately there is no direct language support for that.

If you have a parameter pack, you can expand it into its sequence of elements by placing a ... after it. For example:

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template<typename T, typename... Args>
void printf(const char* s, T value, Args... args)
{
     // ...
     return printf(++s, args...);    // do a recursive call with the elements of args as arguments
     // ...
}

Expansion of a parameter pack into its elements is not restricted to function calls. For example:

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template<typename... Bases>
class X : public Bases... {
public:
     X(const Bases&... b) : Bases(b)... { }
};

X<> x0;
X<Bx> x1(1);
X<Bx,By> x2(2,3);
X<Bx,By,Bz> x3(2,3,4);

Here, Bases... says that X has zero or more bases. When it comes to initializing an X, the constructor requires zero or more values of types specified in the Bases variadic template argument. One by one those values are passed to the corresponding base initializer.

We can use the ellipsis to mean “zero or more elements of something” in most places where a list of elements is required (§iso.14.5.3), such as in:

• A template argument list

• A function argument list

• An initializer list

• A base specifier list

• A base or member initializer list

• A sizeof... expression

A sizeof... expression is used to obtain the number of elements in a parameter pack. For example, we can define a constructor for a tuple given a pair provided the number of tuple elements is two:

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template<typename... Types>
class tuple {
     // ...
     template<typename T, typename U, typename = Enable_if<sizeof...(Types)==2>
         tuple(const pair<T,U>>&);
};

28.6.3. Forwarding

One of the major uses of variadic templates is forwarding from one function to another. Consider how to write a function that takes as arguments something to be called and a possibly empty list of arguments to give to the “something” as arguments:

template<typename F, typename... T>
void call(F&& f, T&&... t)
{
     f(forward<T>(t)...);
}

That is pretty simple and not a hypothetical example. The standard-library thread has constructors using this technique (§5.3.1, §42.2.2). I use pass-by-rvalue-reference of a deduced template argument type to be able to correctly distinguish between rvalues and lvalues (§23.5.2.1) and std::forward() to take advantage of that (§35.5.1). The ... in T&&... is read as “accept zero or more && arguments, each of the type of the corresponding T.” The ... in forward<T>(t)... is read “forward the zero or more arguments from t.”

I used a template argument for the type of the “something” to be called, so that call() can accept functions, pointers to functions, function objects, and lambdas.

We can test call():

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void g0()
{
     cout << "g0()\n";
}

template<typename T>
void g1(const T& t)
{
     cout << "g1(): " << t << '\n';
}

void g1d(double t)
{
     cout << "g1d(): " << t << '\n'; }

template<typename T, typename T2>
void g2(const T& t, T2&& t2)
{
     cout << "g2(): " << t << ' ' << t2 << '\n';
}

void test()
{
     call(g0);
     call(g1);                           // error: too few arguments
     call(g1<int>,1);
     call(g1<const char*>,"hello");
     call(g1<double>,1.2);
     call(g1d,1.2);
     call(g1d,"No way!");                // error: wrong argument type for g1d()
     call(g1d,1.2,"I can't count");      // error: too many arguments for g1d()
     call(g2<double,string>,1,"world!");

     int i = 99;                         // testing with lvalues
     const char* p = "Trying";
     call(g2<double,string>,i,p);

     call([](){ cout <<"l1()\n"; });
     call([](int i){ cout <<"l0(): " << i << "\n";},17);
     call([i](){ cout <<"l1(): " << i << "\n"; });
}

I have to be specific about which specialization of a template function to pass because call() cannot deduce which one to use from the types of the other arguments.

28.6.4. The Standard-Library tuple

The simple Tuple in §28.5 has an obvious weakness: it can handle at most four elements. This section presents the definition of the standard-library tuple (from <tuple>; §34.2.4.2) and explains the techniques used to implement it. The key difference between std::tuple and our simple Tuple is that the former uses variadic templates to remove the limitation on the number of elements. Here are the key definitions:

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template<typename Head, typename... Tail>
class tuple<Head, Tail...>
     : private tuple<Tail...> {  // here is the recursion
/*
     Basically, a tuple stores its head (first (type,value) pairs)
     and derives from the tuple of its tail (the rest of the (type/value) pairs).
     Note that the type is encoded in the type, not stored as data
*/
     typedef tuple<Tail...> inherited;
public:
     constexpr tuple() { } // default: the empty tuple

     // Construct tuple from separate arguments:
     tuple(Add_const_reference<Head> v, Add_const_reference<Tail>... vtail)
          : m_head(v), inherited(vtail...) { }

     // Construct tuple from another tuple:
     template<typename... VValues>
     tuple(const tuple<VValues...>& other)
          : m_head(other.head()), inherited(other.tail()) { }
     template<typename... VValues>
     tuple& operator=(const tuple<VValues...>& other) // assignment
     {
          m_head = other.head();
          tail() = other.tail();
          return *this;
     }
     // ...

protected:
     Head m_head;
private:
     Add_reference<Head> head() { return m_head; }
     Add_const_reference<const Head> head() const { return m_head; }

     inherited& tail() { return *this; }
     const inherited& tail() const { return *this; }
};

There is no guarantee that std::tuple is implemented as hinted here. In fact, several popular implementations derive from a helper class (also a variadic class template), so as to get the element layout in memory to be the same as a struct with the same member types.

The “add reference” type functions add a reference to a type if it isn’t a reference already. They are used to avoid copying (§35.4.1).

Curiously, std::tuple does not provide head() and tail() functions, so I made them private. In fact, tuple does not provide any member functions for accessing an element. If you want to access an element of a tuple, you must (directly or indirectly) call a function that splits it into a value and .... If I want head() and tail() for the standard-library tuple, I can write them:

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template<typename Head, typename... Tail>
Head head(tuple<Head,Tail...>& t)
{
     return std::get<0>(t);   // get first element of t (§34.2.4.2)
}

template<typename Head, typename... Tail>
tuple<T&...> tail(tuple<Head, Tail...>& t)
{
   return /* details */;
}

The “details” of the definition of tail() are ugly and complicated. If the designers of tuple had meant for us to use tail() on a tuple, they would have provided it as a member.

Given tuple, we can make tuples and copy and manipulate them:

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tuple<string,vector,double> tt("hello",{1,2,3,4},1.2);
string h = head(tt.head);                            // "hello"
tuple<vector<int>,double> t2 = tail(tt.tail);        // {{1,2,3,4},1.2};

It can get tedious to mention all of those types. Instead, we can deduce them from argument types, for example, using the standard-library make_tuple():

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template<typename... Types>
tuple<Types...> make_tuple(Types&&... t)    // simplified (§iso.20.4.2.4)
{
     return tuple<Types...>(t...);
}
string s = "Hello";
vector<int> v = {1,22,3,4,5};
auto x = make_tuple(s,v,1.2);

The standard-library tuple has many more members than listed in the implementation above (hence the // ...). In addition, the standard provides several helper functions. For example, get() is provided for element access (like get() from §28.5.2), so we can write:

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auto t = make_tuple("Hello tuple", 43, 3.15);
double d = get<2>(t);         // d becomes 3.15

So std::get() provides compile-time zero-based subscripting of std::tuples.

Every member of std::tuple is useful to someone and most are useful to many, but none adds to our understanding of variadic templates, so I do not go into details. There are constructors and assignments from the same type (copy and move), from other tuple types (copy and move), and from pairs (copy and move). The operations taking a std::pair argument use sizeof... (§28.6.2) to ensure that their target tuples have exactly two elements. There are (nine) constructors and assignments taking allocators (§34.4) and a swap() (§35.5.2).

Unfortunately, the standard library does not offer << or >> for tuple. Worse, writing a << for std::tuple is amazingly complicated because there is no simple and general way of iterating through the elements of a standard-library tuple. First we need a helper; it is a struct with two print() functions. One print() recurses through a list printing elements, and the other stops the recursion when there is no more elements to print:

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template<size_t N> // print element N and following elements
struct print_tuple {
     template<typename... T>
     typename enable_if<(N<sizeof...(T))>::type
     print(ostream& os, const tuple<T...>& t) const     // nonempty tuple
     {
          os << ", " << get<N>(t);      // print an element
          print_tuple<N+1>()(os,t);     // print the rest of the elements
     }

     template<typename... T>
     typename enable_if<!(N<sizeof...(T))>::type                // empty tuple
     print(ostream&, const tuple<T...>&) const
     {
     }
};

The pattern is that of a recursive function with a terminating overload (like printf() from §28.6.1).

However, note how it wastefully lets get<N>() count from 0 to N.

We can now write a << for tuple:

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std::ostream& operator << (ostream& os, const tuple<>&)  // the empty tuple
{
  return os << "{}";
}

template<typename T0, typename... T>
ostream& operator<<(ostream& os, const tuple<T0, T...>& t) // a nonempty tuple
{
  os << '{' << std::get<0>(t); // print first element
  print_tuple<1>::print(os,t); // print the rest of the elements
  return os << '}';
}

We can now print a tuple:

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void user()
{
     cout << make_tuple() << '\n';
     cout << make_tuple("One meatball!") << '\n';
     cout << make_tuple(1,1.2,"Tail!") << '\n';
}

28.7. SI Units Example

Using constexpr and templates, we can compute just about anything at compile time. Providing input for such computations can be tricky, but we can always #include data into the program text. However, I prefer simpler examples that in my opinion stand a better chance when it comes to maintenance. Here, I will show an example that provides a reasonable tradeoff between implementation complexity and utility. The compilation overhead is minimal and there is no run-time overhead. The example is to provide a small library for computations using units, such as meters, kilograms, and seconds. These MKS units are a subset of the international standard (SI) units used universally in science. The example is chosen to show how the simplest metaprogramming techniques can be used in combination with other language features and techniques.

We want to attach units to our values, so as to avoid meaningless computations. For example:

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auto distance = 10_m;       // 10 meters
auto time = 20_s;           // 20 seconds
auto speed = distance/time; // .5 m/s (meters per second)

if (speed == 20)            // error: 20 is dimensionless
// ...
if (speed == distance)      // error: can't compare m to m/s
// ...
if (speed == 10_m/20_s)     // OK: the units match
// ...
Quantity<MpS2> acceleration = distance/square(time); // MpS2 means m/(s*s)

cout << "speed==" << speed << " acceleration==" << acceleration << "\n";

Units provide a type system for physical values. As shown, we can use auto to hide types when we want to (§2.2.2), user-defined literals to introduce typed values (§19.2.6), and a type Quantity for use when we want to be explicit about Units. A Quantity is a numeric value with a Unit.

28.7.1. Units

First, I will define Unit:

template<int M, int K, int S>
struct Unit {
     enum { m=M, kg=K, s=S };
};

A Unit has components representing the three units of measurement that we are interested in:

• Meters for length

• Kilograms for mass

• Seconds for time

Note that the unit values are encoded in the type. A Unit is meant for compile-time use.

We can provide more conventional notation for the most common units:

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using M = Unit<1,0,0>;      // meters
using Kg = Unit<0,1,0>;     // kilograms
using S = Unit<0,0,1>;      // seconds
using MpS = Unit<1,0,–1>;   // meters per second (m/s)
using MpS2 = Unit<1,0,–2>;  // meters per square second (m/(s*s))

Negative unit values indicate division by a quantity with that unit. This three-value representation of a unit is very flexible. We can represent the proper unit of any computation involving distance, mass, and time. I doubt we will find much use for Quantity<123,–15,1024>, that is, 123 distances multiplied, divided by 15 masses multiplied, and then multiplied by 1024 time measurements multiplied – but it is nice to know that the system is general. Unit<0,0,0> indicates a dimensionless entity, a value without a unit.

When we multiply two quantities, their units are added. Thus, addition of Units is useful:

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template<typename U1, typename U2>
struct Uplus {
     using type = Unit<U1::m+U2::m, U1::kg+U2::kg, U1::s+U2::s>;
};

template<typename U1, U2>
using Unit_plus = typename Uplus<U1,U2>::type;

Similarly, when we divide two quantities, their units are subtracted:

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template<typename U1, typename U2>
struct Uminus {
     using type = Unit<U1::m–U2::m, U1::kg–U2::kg, U1::s–U2::s>;
};

template<typename U1, U2>
using Unit_minus = typename Uminus<U1,U2>::type;

Unit_plus and Unit_minus are simple type functions (§28.2) on Units.

28.7.2. Quantitys

A Quantity is a value with an associated Unit:

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template<typename U>
struct Quantity {
     double val;
     explicit Quantity(double d) : val{d} {}
};

A further refinement would have made the type used to represent the value a template parameter, possibly defaulted to double. We can define Quantitys with a variety of units:

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Quantity<M> x {10.5};   // x is 10.5 meters
Quantity<S> y {2};      // y is 2 seconds

I made the Quantity constructor explicit to make it less likely to get implicit conversions from dimensionless entities, such as plain C++ floating-point literals:

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Quantity<MpS> s = 7;   // error: attempt to convert an int to meters/second

Quantity<M> comp(Quantity<M>);
// ...
Quantity<M> n = comp(7);     // error: comp() requires a distance

Now we can start thinking about computations. What do we do to physical measurements? I’m not going to review a whole physics textbook, but certainly we need addition, subtraction, multiplication, and division. You can only add and subtract values with the same units:

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template<typename U>
Quantity<U> operator+(Quantity<U> x, Quantity<U> y) // same dimension
{
     return Quantity<U>{x.val+y.val};
}

template<typename U>
Quantity<U> operator–(Quantity<U> x, Quantity<U> y) // same dimension
{
     return Quantity<U>{x.val–y.val};
}

Quantity’s constructor is explicit, so we have to convert the resulting double value back to Quantity.

Multiplication Quantitys require addition of their Units. Similarly, division of Quantitys subtraction of their Units. For example:

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template<typename U1, typename U2>
Quantity<Unit_plus<U1,U2>> operator *(Quantity<U1> x, Quantity<U2> y)
{
     return Quantity<Unit_plus<U1,U2>>{x.val *y.val};
}

template<typename U1, typename U2>
Quantity<Unit_minus<U1,U2>> operator/(Quantity<U1> x, Quantity<U2> y)
{
     return Quantity<Unit_minus<U1,U2>>{x.val/y.val};
}

Given these arithmetic operations, we can express most computations. However, we find that real-world computations contain a fair number of scaling operations, that is, multiplications and divisions by dimensionless values. We could use Quantity<Unit<0,0,0>> but that gets tedious:

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Quantity<MpS> speed {10};
auto double_speed = Quantity<Unit<0,0,0>>{2} *speed;

To eliminate that verbosity, we can either provide an implicit conversion from double to Quantity<Unit<0,0,0>> or add a couple of variants to the arithmetic operations. I chose the latter:

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template<typename U>
Quantity<U> operator *(Quantity<U> x, double y)
{
    return Quantity<U>{x.val *y};
}

template<typename U>
Quantity<U> operator *(double x, Quantity<U> y)
{
    return Quantity<U>{x *y.val};
}

We can now write:

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Quantity<MpS> speed {10};
auto double_speed = 2*speed;

The main reason I do not define an implicit conversion from double to Quantity<Unit<0,0,0>> is that we do not want that conversion for addition or subtraction:

Quantity<MpS> speed {10};
auto increased_speed = 2.3+speed;     // error: can't add a dimensionless scalar to a speed

It is nice to have the detailed requirement for the code precisely dictated by the application domain.

28.7.3. Unit Literals

Thanks to the type aliases for the most common units, we can now write:

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auto distance = Quantity<M>{10}; // 10 meters
auto time = Quantity<S>{20};     // 20 seconds
auto speed = distance/time;      // .5 m/s (meters per second)

That’s not bad, but it is still verbose compared to code that conventionally simply leaves the units in the heads of the programmers:

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auto distance = 10.0;        // 10 meters
double time = 20;            // 20 seconds
auto speed = distance/time;  // .5 m/s (meters per second)

We needed the .0 or the explicit double to ensure that the type is double (and get the correct result for the division).

The code generated for the two examples should be identical, and we can do better still notationally. We can introduce user-defined literals (UDLs; §19.2.6) for the Quantity types:

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constexpr Quantity<M> operator"" _m(double d) { return Quantity<M>{d}; }
constexpr Quantity<Kg> operator"" _kg(double d) { return Quantity<Kg>{d}; }
constexpr Quantity<S> operator"" _s(double d) { return Quantity<S>{d}; }

That gives us the literals from our original example:

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auto distance = 10_m;       // 10 meters
auto time = 20_s;           // 20 seconds
auto speed = distance/time; // .5 m/s (meters per second)

if (speed == 20)            // error: 20 is dimensionless
// ...
if (speed == distance)      // error: can't compare m to m/s
// ...
if (speed == 10_m/20_s)     // OK: the units match

I defined * and / for combinations of Quantitys and dimensionless values, so we can scale the units using multiplication or division. However, we could also provide more of the conventional units as user-defined literals:

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constexpr Quantity<M> operator"" _km(double d) { return 1000*d; }
constexpr Quantity<Kg> operator"" _g(double d) { return d/1000; }
constexpr Quantity<Kg> operator"" _mg(double d) { return d/10000000; }       // milligram
constexpr Quantity<S> operator"" _ms(double d) { return d/1000; }            // milliseconds
constexpr Quantity<S> operator"" _us(double d) { return d/1000; }            // microseconds
constexpr Quantity<S> operator"" _ns(double d) { return d/1000000000; }      // nanoseconds
// ...

Obviously, this could really get out of control through overuse of nonstandard suffixes (e.g., us is suspect even though it is widely used because u looks a bit like a Greek µ).

I could have provided the various magnitudes as more types (as is done for std::ratio; §35.3) but thought it simpler to keep the Unit types simple and focused on doing their primary task well.

I use underscores in my units _s and _m so as not to get in the way of the standard library providing the shorter and nicer s and m suffixes.

28.7.4. Utility Functions

To finish the job (as defined by the initial example), we need the utility function square(), the equality operator, and the output operator. Defining square() is trivial:

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template<typename U>
Quantity<Unit_plus<U,U>> square(Quantity<U> x)
{
    return Quantity<Unit_plus<U,U>>(x.val*x.val);
}

That basically shows how to write arbitrary computational functions. I could have constructed the Unit right there in the return value definition, but using the existing type function was easier. Alternatively, we could easily have defined a type function Unit_double.

The == looks more or less like all ==s. It is defined for values of the same Units only:

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template<typename U>
bool operator==(Quantity<U> x, Quantity<U> y)
{
     return x.val==y.val;
}

template<typename U>
bool operator!=(Quantity<U> x, Quantity<U> y)
{
     return x.val!=y.val;
}

Note that I pass Quantitys by value. At run time, they are represented as doubles.

The output functions just do conventional character manipulation:

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string suffix(int u, const char* x)  // helper function
{
     string suf;
     if (u) {
            suf += x;
            if (1<u) suf += '0'+u;

            if (u<0) {
                  suf += '–';
                  suf += '0'–u;
            }
     }
     return suf;
}
template<typename U>
ostream& operator<<(ostream& os, Quantity<U> v)
{
     return os << v.val << suffix(U::m,"m") << suffix(U::kg,"kg") << suffix(U::s,"s");
}

Finally, we can write:

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auto distance = 10_m;       // 10 meters
auto time = 20_s;           // 20 seconds
auto speed = distance/time; // .5 m/s (meters per second)

if (speed == 20)            // error: 20 is dimensionless
// ...
if (speed == distance)      // error: can't compare m to m/s
// ...
if (speed == 10_m/20_s)     // OK: the units match
// ...

Quantity<MpS2> acceleration = distance/square(time); // MpS2 means m/(s*s)

cout << "speed==" << speed << " acceleration==" << acceleration << "\n";

Such code will, given a reasonable compiler, generate exactly the same code as would have been generated using doubles directly. However, it is “type checked” (at compile time) according to the rules for physical units. It is an example of how we can add a whole new set of application-specific types with their own checking rules to a C++ program.

28.8. Advice

[1] Use metaprogramming to improve type safety; §28.1.

[2] Use metaprogramming to improve performance by moving computation to compile time; §28.1.

[3] Avoid using metaprogramming to an extent where it significantly slows down compilation; §28.1.

[4] Think in terms of compile-time evaluation and type functions; §28.2.

[5] Use template aliases as the interfaces to type functions returning types; §28.2.1.

[6] Use constexpr functions as the interfaces to type functions returning (non-type) values; §28.2.2.

[7] Use traits to nonintrusively associate properties with types; §28.2.4.

[8] Use Conditional to choose between two types; §28.3.1.1.

[9] Use Select to choose among several alternative types; §28.3.1.3.

[10] Use recursion to express compile-time iteration; §28.3.2.

[11] Use metaprogramming for tasks that cannot be done well at run time; §28.3.3.

[12] Use Enable_if to selectively declare function templates; §28.4.

[13] Concepts are among the most useful predicates to use with Enable_if; §28.4.3.

[14] Use variadic templates when you need a function that takes a variable number of arguments of a variety of types; §28.6.

[15] Don’t use variadic templates for homogeneous argument lists (prefer initializer lists for that); §28.6.

[16] Use variadic templates and std::move() where forwarding is needed; §28.6.3.

[17] Use simple metaprogramming to implement efficient and elegant unit systems (for fine-grained type checking); §28.7.

[18] Use user-defined literals to simplify the use of units; §28.7.

29. A Matrix Design

Never express yourself more clearly than you are able to think.

– Niels Bohr

• Introduction

Basic Matrix Uses; Matrix Requirements

• A Matrix Template

Construction and Assignment; Subscripting and Slicing

• Matrix Arithmetic Operations

Scalar Operations; Addition; Multiplication

• Matrix Implementation

slice; Matrix Slices; Matrix_ref; Matrix List Initialization; Matrix Access; Zero-Dimensional Matrix

• Solving Linear Equations

Classical Gaussian Elimination; Pivoting; Testing; Advice

29.1. Introduction

A language feature in isolation is boring and useless. This chapter demonstrates how features can be used in combination to address a challenging design task: a general N-dimensional matrix.

I have never seen a perfect matrix class. In fact, given the wide variety of uses of matrices, it is doubtful whether one could exist. Here, I present the programming and design techniques needed to write a simple N-dimensional dense matrix. If nothing else, this Matrix is far easier to use, and just as compact and fast, as anything a programmer would have time to write using vectors or builtin arrays directly. The design and programming techniques used for Matrix are widely applicable.

29.1.1. Basic Matrix Uses

Matrix<T,N> is an N-dimensional matrix of some value type T. It can be used like this:

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Matrix<double,0> m0{1};         // zero dimensions: a scalar
Matrix<double,1> m1{1,2,3,4};   // one dimension: a vector (4 elements)
Matrix<double,2> m2{            // two dimensions (4*3 elements)
     {00,01,02,03},    //row 0
     {10,11,12,13},    //row 1
     {20,21,22,23}     //row 2
};
Matrix<double,3> m3(4,7,9);    // three dimensions (4*7*9 elements), all 0-initialized
Matrix<complex<double>,17> m17;// 17 dimensions (no elements so far)

The element type must be something we can store. We do not require every property that we have for a floating-point number from every element type. For example:

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Matrix<double,2> md;         // OK
Matrix<string,2> ms;         // OK: just don't try arithmetic operations

Matrix<Matrix<int,2>,2> mm { // 3-by-2 matrix of 2-by-2 matrices
                             // a matrix is a plausible "number"
     { // row 0
            {{1, 2}, {3, 4}}, // col 0
            {{4, 5}, {6, 7}}, // col 1
     },
     { // row 1
            {{8, 9}, {0, 1}}, // col 0
            {{2, 3}, {4, 5}}, // col 1
     },
     { // row 2
            {{1, 2}, {3, 4}}, // col 0
            {{4, 5}, {6, 7}}, // col 1
     }
};

Matrix arithmetic doesn’t have exactly the same mathematical properties as integer or floating-point arithmetic (e.g., matrix multiplication is not commutative), so we must be careful how we use such a matrix.

As for vector, we use () to specify sizes and {} to specify element values (§17.3.2.1, §17.3.4.1). The number rows must match the specified number of dimensions and the number of elements in each dimension (each column) must match. For example:

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Matrix<char,2> mc1(2,3,4);    // error: too many dimension sizes
Matrix<char,2> mc2 {
     {'1','2','3'}            // error: initializer missing for second dimension
};
Matrix<char,2> mc2 {
     {'1','2','3'},
     {'4','5'}                // error: element missing for third column
};

Matrix<T,N> has its number of dimensions (its order()) specified as a template argument (here, N). Each dimension has a number of elements (its extent()) deduced from the initializer list or specified as a Matrix constructor argument using the () notation. The total number of elements is referred to as its size(). For example:

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Matrix<double,1> m1(100);       // one dimension: a vector (100 elements)
Matrix<double,2> m2(50,6000);   // two dimensions: 50*6000 elements

auto d1 = m1.order();           // 1
auto d2 = m2.order();           // 2

auto e1 = m1.extent(0);         // 100
auto e1 = m1.extent(1);         // error: m1 is one-dimensional

auto e2 = m2.extent(0);         // 50
auto e2 = m2.extent(1);         // 6000

auto s1 = m1.size();            // 100
auto s2 = m2.size();            // 50*6000

We can access Matrix elements by several forms of subscripting. For example:

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Matrix<double,2> m {             // two dimensions (4*3 elements)
     {00,01,02,03}, // row 0
     {10,11,12,13}, // row 1
     {20,21,22,23}  // row 2
};

double d1 = m(1,2);              // d==12
double d2 = m[1][2];             // d==12
Matrix<double,1> m1 = m[1];      // row 1: {10,11,12,13}
double d3 = m1[2];               // d==12

We can define an output function for use in debugging like this:

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template<typename M>
     Enable_if<Matrix_type<M>(),ostream&>
operator<<(ostream& os, const M& m)
{
    os << '{';
    for (size_t i = 0; i!=rows(m); ++i){
          os << m[i];
          if (i+1!=rows(m)) os << ',';
    }
    return os << '}';
}

Here, Matrix_type is a concept (§24.3). Enable_if is an alias for enable_if’s type (§28.4), so this operator<<() returns an ostream&.

Given that, cout<<m prints: {{0,1,2,3},{10,11,12,13},{20,21,22,23}}.

29.1.2. Matrix Requirements

Before proceeding with an implementation, consider what properties we might like to have:

• N dimensions, where N is a parameter that can vary from 0 to many, without specialized code for every dimension.

• N-dimensional storage is useful in general, so the element type can be anything we can store (like a vector element).

• The mathematical operations should apply to any type that can reasonably be described as a number, including a Matrix.

• Fortran-style subscripting using one index per dimension, for example, m(1,2,3) for a 3-D Matrix, yielding an element.

• C-style subscripting, for example, m[7], yielding a row (a row is an N–1-D sub-Matrix of an N-D Matrix).

• Subscripting should be potentially fast and potentially range checked.

• Move assignment and move constructor to ensure efficient passing of Matrix results and to eliminate expensive temporaries.

• Some mathematical matrix operations, such as + and *=.

• A way to read, write, and pass around references to submatrices, Matrix_refs, for use for both reading and writing elements.

• The absence of resource leaks in the form of the basic guarantee (§13.2).

• Fused critical operations, for example, m*v+v2 as a single function call.

This is a relatively long and ambitious list, but it does not add up to “everything for everybody.” For example, I did not list:

• Many more mathematical matrix operations

• Specialized matrices (e.g., diagonal and triangular matrices)

• Sparse Matrix support

• Support for parallel execution of Matrix operations

However valuable those properties are, they go beyond what is needed to present basic programming techniques.

To provide this, I use a combination of several language features and programming techniques:

• Classes (of course)

• Parameterization with numbers and types

• Move constructors and assignments (to minimize copying)

• RAII (relying on constructors and destructors)

• Variadic templates (for specifying extents and for indexing)

• Initializer lists

• Operator overloading (to get conventional notation)

• Function objects (to carry information about subscripting)

• Some simple template metaprogramming (e.g., for checking initializer lists and for distinguishing reading and writing for Matrix_refs)

• Implementation inheritance for minimizing code replication.

Obviously, a Matrix like this could be a built-in type (as it is in many languages), but the point here is exactly that in C++ it is not built in. Instead, facilities are provided for users to make their own.

29.2. A Matrix Template

To give an overview, here is the declaration of Matrix with its most interesting operations:

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template<typename T, size_t N>
class Matrix {
public:
     static constexpr size_t order = N;
     using value_type = T;
     using iterator = typename std::vector<T>::iterator;
     using const_iterator = typename std::vector<T>::const_iterator;

     Matrix() = default;
     Matrix(Matrix&&) = default;                                   // move
     Matrix& operator=(Matrix&&) = default;
     Matrix(Matrix const&) = default;                              // copy
     Matrix& operator=(Matrix const&) = default;
     ~Matrix() = default;

     template<typename U>
         Matrix(const Matrix_ref<U,N>&);                           // construct from Matrix_ref
     template<typename U>
         Matrix& operator=(const Matrix_ref<U,N>&);                // assign from Matrix_ref

     template<typename...Exts>                                     // specify the extents
         explicit Matrix(Exts... exts);

     Matrix(Matrix_initializer<T,N>);                              // initialize from list
     Matrix& operator=(Matrix_initializer<T,N>);                   // assign from list

     template<typename U>
         Matrix(initializer_list<U>) =delete;                      // don't use {} except for elements
     template<typename U>
         Matrix& operator=(initializer_list<U>) = delete;

     static constexpr size_t order() { return N; }                 // number of dimensions
     size_t extent(size_t n) const { return desc.extents[n]; }     // #elements in the nth dimension
     size_t size() const { return elems.size(); }                  // total number of elements
     const Matrix_slice<N>& descriptor() const { return desc; }    // the slice defining subscripting

     T* data() { return elems.data(); }                            // "flat" element access
     const T* data() const { return elems.data(); }

     // ...

private:
     Matrix_slice<N> desc;         // slice defining extents in the N dimensions
     vector<T> elems;              // the elements
};

Using a vector<T> to hold the elements relieves us from concerns of memory management and exception safety. A Matrix_slice holds the sizes necessary to access the elements as an N-dimensional matrix (§29.4.2). Think of it as a gslice (§40.5.6) specialized for our Matrix.

A Matrix_ref (§29.4.3) behaves just like a Matrix except that it refers to a Matrix, typically a sub-Matrix such as a row or a column, rather than owning its own elements. Think of it as a reference to a sub-Matrix.

A Matrix_initializer<T,N> is a suitably nested initializer list for a Matrix<T,N> (§29.4.4).

29.2.1. Construction and Assignment

The default copy and move operations have just the right semantics: memberwise copy or move of the desc (slice descriptor defining subscripting) and the elements. Note that for management of the storage for elements, Matrix gets all the benefits from vector. Similarly, the default constructor and destructor have just the right semantics.

The constructor that takes extents (numbers of elements in dimensions) is a fairly trivial example of a variadic template (§28.6):

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template<typename T, size_t N>
    template<typename ... Exts>
    Matrix<T,N>::Matrix(Exts... exts)
         :desc{exts...},     // copy extents
          elems(desc.size)   // allocate desc.size elements and default initialize them
    {}

The constructor that takes an initializer list requires a bit of work:

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template<typename T, size_t N>
Matrix<T, N>::Matrix(Matrix_initializer<T,N> init)
{
     Matrix_impl::derive_extents(init,desc.extents);    // deduce extents from initializer list (§29.4.4)
     elems.reserve(desc.size);                          // make room for slices
     Matrix_impl::insert_flat(init,elems);              // initialize from initializer list (§29.4.4)
     assert(elems.size() == desc.size);
}

The Matrix_initializer is a suitably nested initializer_list (§29.4.4). The extents are deduced by the Matrix_slice constructor, checked, and stored in desc. Then, the elements are stored in elems by insert_flat() from the Matrix_impl namespace.

To ensure that {} initialization is only used for lists of elements, I =deleted the simple initializer_list constructor. This is to enforce the use of () initialization for extents. For example:

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enum class Piece { none, cross, naught };

Matrix<Piece,2> board1 {
     {Piece::none, Piece::none, Piece::none},
     {Piece::none, Piece::none, Piece::none},
     {Piece::none, Piece::none, Piece::cross}
};
Matrix<Piece,2> board2(3,3);  // OK
Matrix<Piece,2> board3 {3,3}; // error: constructor from initializer_list<int> deleted

Without that =delete, that last definition would have been accepted.

Finally, we have to be able to construct from a Matrix_ref, that is, from a reference to a Matrix or a part of a Matrix (a submatrix):

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template<typename T, size_t N>
    template<typename U>
    Matrix<T,N>::Matrix(const Matrix_ref<U,N>& x)
         :desc{x.desc}, elems{x.begin(),x.end()} // copy desc and elements
    {
         static_assert(Convertible<U,T>(),"Matrix constructor: incompatible element types");
    }

The use of a template allows us to construct from a Matrix with a compatible element type.

As usual, the assignments resemble the constructors. For example:

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template<typename T, size_t N>
    template<typename U>
    Matrix<T,N>& Matrix<T,N>::operator=(const Matrix_ref<U,N>& x)
    {
         static_assert(Convertible<U,T>(),"Matrix =: incompatible element types");

         desc = x.desc;
         elems.assign(x.begin(),x.end());
         return *this;
    }

That is, we copy the members of Matrix.

29.2.2. Subscripting and Slicing

A Matrix can be accessed through subscripting (to elements or rows), through rows and columns, or through slices (parts of rows or columns).

These are all member functions:

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template<typename T, size_t N>
class Matrix {
public:
     // ...

     template<typename ... Args>                               // m(i,j,k) subscripting with integers
         Enable_if<Matrix_impl::Requesting_element<Args...>(), T&>
         operator()(Args... args);
     template<typename ... Args>
         Enable_if<Matrix_impl::Requesting_element<Args...>(), const T&>
         operator()(Args... args) const;
     template<typename ... Args>                               // m(s1,s2,s3) subscripting with slices
         Enable_if<Matrix_impl::Requesting_slice<Args...>(), Matrix_ref<T, N>>
         operator()(const Args&... args);
     template<typename ... Args>
         Enable_if<Matrix_impl::Requesting_slice<Args...>(), Matrix_ref<const T,N>>
         operator()(const Args&... args) const;

     Matrix_ref<T,N–1> operator[](size_t i) { return row(i); } // m[i] row access
     Matrix_ref<const T,N–1> operator[](size_t i) const { return row(i); }

     Matrix_ref<T,N–1> row(size_t n);                          // row access
     Matrix_ref<const T,N–1> row(size_t n) const;

     Matrix_ref<T,N–1> col(size_t n);                          // column access
     Matrix_ref<const T,N–1> col(size_t n) const;

     // ...
};

C-style subscripting is done by m[i] selecting and returning the ith row:

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template<typename T, size_t N>
Matrix_ref<T,N–1> Matrix<T,N>::operator[](size_t n)
{
   return row(n);  // §29.4.5
}

Think of a Matrix_ref (§29.4.3) as a reference to a sub-Matrix.

Matrix_ref<T,0> is specialized so that it refers to a single element (§29.4.6).

Fortran-style subscripting is done by listing an index for each dimension, for example, m(i,j,k), yielding a scalar:

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Matrix<int,2> m2 {
     {01,02,03},
     {11,12,13}
};

m(1,2) = 99;         // overwrite the element in row 1 column 2; that is 13
auto d1 = m(1);      // error: too few subscripts
auto d2 = m(1,2,3);  // error: too many subscripts

In addition to subscripting with integers, we can subscript with slices. A slice describes a subset of the elements of a dimension (§40.5.4). In particular, slice{i,n} refers to elements [i:i+n) of the dimension to which it applies. For example:

Matrix<int> m2 {
     {01,02,03},
     {11,12,13},
     {21,22,23}
};

auto m22 = m(slice{1,2},slice{0,3});

Now m22 is a Matrix<int,2> with the value

{
    {11,12,13},
    {21,22,23}
}

The first (row) subscript slice{1,2} selects the last two rows, and the second (column) subscript slice{0,3} selects all elements in the columns.

The return type for a () with slice subscripts is a Matrix_ref, so we can use it as the target of an assignment. For example:

m(slice{1,2},slice{0,3}) = {
     {111,112,113},
     {121,122,123}
}

Now m has the value

{
     {01,02,03},
     {111,112,113},
     {121,122,123}
}

Selecting all elements from a point onward is so common that there is a shorthand: slice{i} means slice{i,max} where max is larger than the largest subscript in the dimension. So, we can simplify m(slice{1,2},slice{0,3}) to the equivalent m(slice{1,2},slice{0}).

The other simple common case is to select all elements of a single row or column, so a plain integer subscript i among a set of slice subscripts is interpreted as slice{i,1}. For example:

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Matrix<int> m3 {
     {01,02,03},
     {11,12,13},
     {21,22,23}
};

auto m31 = m(slice{1,2},1);       // m31 becomes {{12},{22}}
auto m32 = m(slice{1,2},0);       // m33 becomes {{11},{21}}
auto x = m(1,2);                  // x == 13

The notion of slicing subscripts is supported in essentially all languages used for numeric programming, so hopefully it is not too unfamiliar.

The implementations of row(), column(), and operator()() are presented in §29.4.5. The implementations of const versions of these functions are basically the same as those of their non-const versions. The key difference is that const versions return results with const elements.

29.3. Matrix Arithmetic Operations

So, we can create Matrixes, copy them, access their elements and rows. However, what we often want is to have mathematical operations that save us from expressing our algorithms in terms of accesses to individual elements (scalars). For example:

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Matrix<int,2> mi {{1,2,3}, {4,5,6 }};       // 2-by-3
Matrix<int,2> m2 {mi};                      // copy
mi*=2;                                      // scale: {{2,4,6},{8,10,12}}
Matrix<int,2> m3 = mi+m2;                   // add: {{3,6,9},{12,15,18}}
Matrix<int,2> m4 {{1,2}, {3,4}, {5,6}};     // 3-by-2
Matrix<int,1> v = mi*m4;                    // multiply: {{18,24,30},{38,52,66},{58,80,102}}

The mathematical operations are defined like this:

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template<typename T, size_t N>
class Matrix {
    // ...

    template<typename F>
        Matrix& apply(F f);                 // f(x) for every element x

    template<typename M, typename F>
        Matrix& apply(const M& m, F f);     // f(x,mx) for corresponding elements

    Matrix& operator=(const T& value);      // assignment with scalar

    Matrix& operator+=(const T& value);     // scalar addition
    Matrix& operator-=(const T& value);     // scalar subtraction
    Matrix& operator*=(const T& value);     // scalar multiplication
    Matrix& operator/=(const T& value);     // scalar division
    Matrix& operator%=(const T& value);     // scalar modulo

    template<typename M>                    // matrix addition
        Matrix& operator+=(const M& x);
    template<typename M>                    // matrix subtraction
        Matrix& operator-=(const M& x);

    // ...
};

// Binary +, -, * are provided as nonmember functions

29.3.1. Scalar Operations

A scalar arithmetic operation simply applies its operation and right-hand operand to each element. For example:

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template<typename T, size_t N>
Matrix<T,N>& Matrix<T,N>::operator+=(const T& val)
{
     return apply([&](T& a) { a+=val; } ); // using a lambda (§11.4)
}

This apply() applies a function (or a function object) to each element of its Matrix:

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template<typename T, size_t N>
    template<typename F>
    Matrix<T,N>& Matrix<T,N>::apply(F f)
    {
         for (auto& x : elems) f(x);    // this loop uses stride iterators
         return *this;
    }

As usual, returning *this enables chaining. For example:

m.apply(abs).apply(sqrt);    // m[i] = sqrt(abs(m[i])) for all i

As usual (§3.2.1.1, §18.3), we can define the “plain operators,” such as +, outside the class using the assignment operators, such as +=. For example:

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template<typename T, size_t N>
Matrix<T,N> operator+(const Matrix<T,N>& m, const T& val)
{
     Matrix<T,N> res = m;
     res+=val;
     return res;
}

Without the move constructor, this return type would be a bad performance bug.

29.3.2. Addition

Addition of two Matrixes is very similar to the scalar versions:

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template<typename T, size_t N>
    template<typename M>
    Enable_if<Matrix_type<M>(),Matrix<T,N>&> Matrix<T,N>::operator+=(const M& m)
    {
         static_assert(m.order()==N,"+=: mismatched Matrix dimensions");
         assert(same_extents(desc,m.descriptor()));      // make sure sizes match

         return apply(m, [](T& a,Value_type<M>&b) { a+=b; });
    }

Matrix::apply(m,f) is the two-argument version of Matrix::apply(f). It applies its f to its two Matrixes (m and *this):

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template<typename T, size_t N>
    template<typename M, typename F>
    Enable_if<Matrix_type<M>(),Matrix<T,N>&> Matrix<T,N>::apply(M& m, F f)
    {
        assert(same_extents(desc,m.descriptor()));            // make sure sizes match
        for (auto i = begin(), j = m.begin(); i!=end();++i,++j)
              f(*i,*j);
        return *this;
    }

Now operator+() is easily defined:

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template<typename T, size_t N>
Matrix<T,N> operator+(const Matrix<T,N>& a, const Matrix<T,N>& b)
{
     Matrix<T,N> res = a;
     res+=b;
     return res;
}

This defines + for two Matrixes of the same type yielding a result of that type. We could generalize:

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template<typename T, typename T2, size_t N,
    typename RT = Matrix<Common_type<Value_type<T>,Value_type<T2>>,N>
Matrix<RT,N> operator+(const Matrix<T,N>& a, const Matrix<T2,N>& b)
{
     Matrix<RT,N> res = a;
     res+=b;
     return res;
}

If, as is common, T and T2 are the same type, Common_type is that type. The Common_type type function is derived from std::common_type (§35.4.2). For built-in types it, like ?:, gives a type that best preserves values of arithmetic operations. If Common_type is not defined for a pair of types we want to use in combination, we can define it. For example:

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template<>
struct common_type<Quad,long double> {
     using type = Quad;
};

Now Common_type<Quad,long double> is Quad.

We also need operations involving Matrix_refs (§29.4.3). For example:

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template<typename T, size_t N>
Matrix<T,N> operator+(const Matrix_ref<T,N>& x, const T& n)
{
     Matrix<T,N>
     res = x; res+=n;
     return res;
}

Such operations look exactly like their Matrix equivalents. There is no difference between Matrix and Matrix_ref element access: the difference between Matrix and Matrix_ref is in the initialization and ownership of elements.

Subtraction, multiplication, etc., by scalars and the handling of Matrix_refs are just repetition of the techniques used for addition.

29.3.3. Multiplication

Matrix multiplication is not as simple as addition: the product of an N-by-M matrix and a M-by-P matrix is an N-by-P matrix. For M==1 we get that the product of two vectors is a matrix, and from P==1 we get that the product of a matrix and a vector is a vector. We can generalize matrix multiplication into higher dimensions, but to do that we have to introduce tensors [Kolecki,2002], and I don’t want to divert this discussion of programming techniques and how to use language features into a physics and engineering math lesson. So, I’ll stick to one and two dimensions.

Treating one Matrix<T,1> as an N-by-1 matrix and another as a 1-by-M matrix, we get:

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template<typename T>
Matrix<T,2> operator*(const Matrix<T,1>& u, const Matrix<T,1>& v)
{
     const size_t n = u.extent(0);
     const size_t m = v.extent(0);
     Matrix<T,2> res(n,m);                 // an n-by-m matrix
     for (size_t i = 0; i!=n; ++i)
           for (size_t j = 0; j!=m; ++j)
                 res(i,j) = u[i]*v[j];
     return res;
}

This is the simplest case: matrix element res(i,j) is u[i]*v[j]. I have not tried to generalize to handle the cases where the element types of the vectors are different. If necessary, the techniques discussed for addition can be used.

Note that I’m writing to each element of res twice: once to initialize to T{} and once to assign u[i]*v[j]. This roughly doubles the cost of the multiplication. If that bothers you, write a multiplication without that overhead and see if the difference matters in your program.

Next, we can multiply an N-by-M matrix with a vector seen as an M-by-1 matrix. The result is an N-by-1 matrix:

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template<typename T>
Matrix<T,1> operator*(const Matrix<T,2>& m, const Matrix<T,1>& v)
{
     assert(m.extent(1)==v.extent(0));

     const size_t n = m.extent(0);
     Matrix<T,1> res(n);
     for (size_t i = 0; i!=n; ++i)
           for (size_t j = 0; j!=n; ++j)
                 res(i) += m(i,j)*v(j);
     return res;
}

Note that the declaration of res initializes its elements to T{}, which is zero for numeric types, so that the += starts out from zero.

The N-by-M matrix times M-by-P matrix is handled similarly:

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template<typename T>
Matrix<T,2> operator*(const Matrix<T,2>& m1, const Matrix<T,2>& m2)
{
     const size_t n = m1.extent(0);
     const size_t m = m1.extent(1);
     assert(m==m2.extent(0));      // columns must match rows

     const size_t p = m2.extent(1);
     Matrix<T,2> res(n,p);
     for (size_t i = 0; i!=n; ++i)
           for (size_t j = 0; j!=m; ++j)
                 for (size_t k = 0; k!=p; ++k)
                       res(i,j) = m1(i,k)*m2(k,j);
    return res;
}

There are numerous ways of optimizing this important operation.

That innermost loop could be more elegantly expressed as:

res(i,j) = dot_product(m1[i],m2.column(j))

Here, dot_product() is simply an interface to the standard-library inner_product() (§40.6.2):

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template<typename T>
T dot_product(const Matrix_ref<T,1>& a, const Matrix_ref<T,1>& b)
{
     return inner_product(a.begin(),a.end(),b.begin(),0.0);
}

29.4. Matrix Implementation

So far, I have delayed the presentation of the most complicated (and for some programmers the most interesting) “mechanical” parts of the Matrix implementation. For example: What is a Matrix_ref? What is a Matrix_slice? How do you initialize a Matrix from a nest of initializer_lists and make sure the dimensions are reasonable? How do we ensure that we don’t instantiate a Matrix with an unsuitable element type?

The easiest way to present this code is to place all of Matrix in a header file. In that case, add inline the definition of every nonmember function.

The definitions of functions that are not members of Matrix, Matrix_ref, Matrix_slice, or part of the general interface are placed in namespace Matrix_impl.

29.4.1. slice()

A simple slice as used for slice subscripting describes a mapping from an integer (subscript) to an element location (index) in terms of three values:

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struct slice {
     slice() :start(-1), length(-1), stride(1) { }
     explicit slice(size_t s) :start(s), length(-1), stride(1) { }
     slice(size_t s, size_t l, size_t n = 1) :start(s), length(l), stride(n) { }

     size_t operator()(size_t i) const { return start+i*stride; }

     static slice all;

     size_t start;        // first index
     size_t length;       // number of indices included (can be used for range checking)
     size_t stride;       // distance between elements in sequence
};

There is a standard-library version of slice; see §40.5.4 for a more thorough discussion. This version provides notational convenience (e.g., the default values provided by the constructors).

29.4.2. Matrix Slices

A Matrix_slice is the part of the Matrix implementation that maps a set of subscripts to the location of an element. It uses the idea of generalized slices (§40.5.6):

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template<size_t N>
struct Matrix_slice {
     Matrix_slice() = default;                              // an empty matrix: no elements

     Matrix_slice(size_t s, initializer_list<size_t> exts); // extents
     Matrix_slice(size_t s, initializer_list<size_t> exts, initializer_list<size_t> strs);// extents and strides

     template<typename...Dims>                              // N extents
         Matrix_slice(Dims... dims);

     template<typename... Dims,
              typename = Enable_if<All(Convertible<Dims,size_t>()...)>>
         size_t operator()(Dims... dims) const;             // calculate index from a set of subscripts

     size_t size;                  // total number of elements
     size_t start;                 // starting offset
     array<size_t,N> extents;      // number of elements in each dimension
     array<size_t,N> strides;      // offsets between elements in each dimension
};

In other words, a Matrix_slice describes what is considered rows and columns in a region of memory. In the usual C/C++ row-major layout of a matrix, the elements of rows are contiguous, and the elements of a column are separated by a fixed number of elements (a stride). A Matrix_slice is a function object, and its operator()() does a stride calculation (§40.5.6):

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template<size_t N>
    template<typename... Dims>
    size_t Matrix_slice<N>::operator()(Dims... dims) const
    {

        static_assert(sizeof...(Dims) == N, "");

        size_t args[N] { size_t(dims)... };    // Copy arguments into an array

        return inner_product(args,args+N,strides.begin(),size_t(0));
    }

Subscripting must be efficient. This is a simplified algorithm that needs to be optimized. If nothing else, specialization can be used to eliminate the simplifying copy of subscripts out of the variadic template’s parameter pack. For example:

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template<>
struct Matrix_slice<1> {

    // ...

    size_t operator()(size_t i) const
    {
         return i;
    }
}

template<>
struct Matrix_slice<2> {

    // ...

    size_t operator()(size_t i, size_t j) const
    {
         return i*stides[0]+j;
    }
}

The Matrix_slice is fundamental for defining the shape of a Matrix (its extents) and for implementing N-dimensional subscripting. However, it is also useful for defining submatrices.

29.4.3. Matrix_ref

A Matrix_ref is basically a clone of the Matrix class used to represent sub-Matrixes. However, a Matrix_ref does not own its elements. It is constructed from a Matrix_slice and a pointer to elements:

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template<typename T, size_t N>
class Matrix_ref {
public:
     Matrix_ref(const Matrix_slice<N>& s, T* p) :desc{s}, ptr{p} {}
     // ... mostly like Matrix ...
private:
     Matrix_slice<N> desc;   // the shape of the matrix
     T* ptr;                 // the first element in the matrix
};

A Matrix_ref simply points to the elements of “its” Matrix. Obviously, a Matrix_ref should not outlive its Matrix. For example:

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Matrix_ref<double,1> user()
{
     Matrix<double,2> m = {{1,2}, {3,4}, {5,6}};
     return m.row(1);
}

auto mr = user();   // trouble

The great similarity between Matrix and Matrix_ref leads to duplication. If that becomes a bother, we can derive both from a common base:

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template<typename T, size_t N>
class Matrix_base {
     // ... common stuff ...
};

template<typename T, size_t N>
class Matrix : public Matrix_base<T,N> {
     // ... special to Matrix ...
private:
     Matrix_slice<N> desc;     // the shape of the matrix
     vector<T> elements;
};

template<typename T, size_t N>
class Matrix_ref : public Matrix_base<T,N> {
     // ... special to Matrix_ref ...
private:
     Matrix_slice<N> desc;    // the shape of the matrix
     T* ptr;
};

29.4.4. Matrix List Initialization

The Matrix constructor that constructs from an initializer_list takes as its argument type the alias Matrix_initializer:

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template<typename T, size_t N>
using Matrix_initializer = typename Matrix_impl::Matrix_init<T, N>::type;

Matrix_init describes the structure of a nested initializer_list.

Matrix_init<T,N> simply has Matrix_init<T,N–1> as its member type:

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template<typename T, size_t N>
struct Matrix_init {
     using type = initializer_list<typename Matrix_init<T,N–1>::type>;
};

The N==1 is special. That is where we get to the (most deeply nested) initializer_list<T>:

template<typename T>
struct Matrix_init<T,1> {
     using type = initializer_list<T>;
};

To avoid surprises, we define N=0 to be an error:

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template<typename T>
struct Matrix_init<T,0>;  // undefined on purpose

We can now complete the Matrix constructor that takes a Matrix_initializer:

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template<typename T, size_t N>
Matrix<T, N>::Matrix(Matrix_initializer<T,N> init)
{
     Matrix_impl::derive_extents(init,desc.extents);   // deduce extents from initializer list (§29.4.4)
     elems.reserve(desc.size);                         // make room for slices
     Matrix_impl::insert_flat(init,elems);             // initialize from initializer list (§29.4.4)
     assert(elems.size() == desc.size);
}

To do so, we need two operations that recurse down a tree of initializer_lists for a Matrix<T,N>:

• derive_extents() determines the shape of the Matrix:

• Checks that the tree really is N deep

• Checks that each row (sub-initialize_list) has the same number of elements

• Sets the extent of each row

• insert_flat() copies the elements of the tree of initializer_list<T>s into the elems of a Matrix.

The derived_extents() called from a Matrix constructor to initialize its desc looks like this:

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template<size_t N, typename List>
array<size_t, N> derive_extents(const List& list)
{
     array<size_t,N> a;
     auto f = a.begin();
     add_extents<N>(f,list);  // put extents from list into f[]
     return a;
}

You give it an initializer_list and it returns an array of extents.

The recursion is done from N to the final 1 where the initializer_list is an initializer_list<T>.

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template<size_t N, typename I, typename List>
Enable_if<(N>1),void> add_extents(I& first, const List& list)
{
     assert(check_non_jagged(list));
     *first = list.size();
     add_extents<N-1>(++first,*list.begin());
}

template<size_t N, typename I, typename List>
Enable_if<(N==1),void> add_extents(I& first, const List& list)
{
     *first++ = list.size();    // we reached the deepest nesting
}

The check_non_jagged() function checks that all rows have the same number of elements:

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template<typename List>
bool check_non_jagged(const List& list)
{
     auto i = list.begin();
     for (auto j = i+1; j!=list.end(); ++j)
           if (i->size()!=j->size())
                 return false;
     return true;
}

We need insert_flat() to take a possibly nested initializer list and present its elements to Matrix<T> as a vector<T>. It takes the initializer_list given to a Matrix as the Matrix_initializer and provides the elements as the target:

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template<typename T, typename Vec>
void insert_flat(initializer_list<T> list, Vec& vec)
{
     add_list(list.begin(),list.end(),vec);
}

Unfortunately, we can’t rely on the elements being allocated contiguously in memory, so we need to build the vector through a set of recursive calls. If we have a list of initializer_lists, we recurse through each:

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template<typename T, typename Vec> // nested initializer_lists
void add_list(const initializer_list<T>* first, const initializer_list<T>* last, Vec& vec)
{
     for (;first!=last;++first)
           add_list(first->begin(),first->end(),vec);
}

When we reach a list with non-initializer_list elements, we insert those elements into our vector:

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template<typename T, typename Vec>
void add_list(const T *first, const T *last, Vec& vec)
{
     vec.insert(vec.end(),first,last);
}

I use vec.insert(vec.end(),first,last) because there is no push_back() that takes a sequence argument.

29.4.5. Matrix Access

A Matrix provides access by row, column, slice (§29.4.1), and element (§29.4.3). A row() or column() operation returns a Matrix_ref<T,N–1>, the () subscript operation with integers returns a T&, and the () subscript operation with slices returns a Matrix<T,N>.

The row of a Matrix<T,N> is a Matrix_ref<T,N–1> as long as 1<N:

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template<typename T, size_t N>
Matrix_ref<T,N-1> Matrix<T,N>::row(size_t n)
{
     assert(n<rows());
     Matrix_slice<N-1> row;
     Matrix_impl::slice_dim<0>(n,desc,row);
     return {row,data()};
}

We need specializations for N==1 and N==0:

template<typename T>
T& Matrix<T,1>::row(size_t i)
{
     return &elems[i];
}

template<typename T>
T& Matrix<T,0>::row(size_t n) = delete;

Selecting a column() is essentially the same as selecting a row(). The difference is simply in the construction of the Matrix_slice:

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template<typename T, size_t N>
Matrix_ref<T,N-1> Matrix<T,N>::column(size_t n)
{
     assert(n<cols());
     Matrix_slice<N-1> col;
     Matrix_impl::slice_dim<1>(n,desc,col);
     return {col,data()};
}

The const versions are equivalent.

Requesting_element() and Requesting_slice() are concepts for a set of integers used for subscripting with a set of integers and subscripting by a slice, respectively (§29.4.5). They check that a sequence of access-function arguments are of suitable types for use as subscripts.

Subscripting with integers is defined like this:

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template<typename T, size_t N>        // subscripting with integers
     template<typename... Args>
     Enable_if<Matrix_impl::Requesting_element<Args...>(),T&>
     Matrix<T,N>::operator()(Args... args)
     {
          assert(Matrix_impl::check_bounds(desc, args...));
          return *(data() + desc(args...));
}

The check_bounds() predicate checks that the number of subscripts equals the number of dimensions and that the subscripts are within bounds:

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template<size_t N, typename... Dims>
bool check_bounds(const Matrix_slice<N>& slice, Dims... dims)
{
     size_t indexes[N] {size_t(dims)...};
     return equal(indexes, indexes+N, slice.extents, less<size_t> {});
}

The actual location of the element in the Matrix is calculated by invoking the Matrix’s Matrix_slice’s generalized slice calculation presented as a function object: desc(args...). Add that to the start of the data (data()) and we have our location:

return *(data() + desc(args...));

This leaves the most mysterious part of the declaration for last. The specification of operator()()’s return type looks like this:

Enable_if<Matrix_impl::Requesting_element<Args...>(),T&>

So the return type is T& provided that

Matrix_impl::Requesting_element<Args...>()

is true (§28.4). This predicate simply checks that every subscript can be converted to the required size_t by using a concept version of the standard-library predicate is_convertible (§35.4.1):

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template<typename ... Args>
constexpr bool Requesting_element()
{
     return All(Convertible<Args,size_t>()...);
}

All() simply applies its predicate to every element of a variadic template:

constexpr bool All() { return true; }

template<typename ... Args>
constexpr bool All(bool b, Args... args)
{
     return b && All(args...);
}

The reason for using a predicate (Requesting_element) and the Enable_if() “hidden” within Request is to choose between the element and the slice subscript operators. The predicate used by the slice subscript operator looks like this:

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template<typename... Args>
constexpr bool Requesting_slice()
{
     return All((Convertible<Argssize_t>() || Same<Args,slice>())...)
                && Some(Same<Args,slice>()...);
}

That is, if there is at least one slice argument and if all arguments are either convertible to slice or size_t, we have something that can be used to describe a Matrix<T,N>:

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template<typename T, size_t N>   // subscripting with slices
    template<typename... Args>
        Enable_if<Matrix_impl::Requesting_slice<Args...>(), Matrix_ref<T,N>>
    Matrix<T,N>::operator()(const Args&... args)
    {
         matrix_slice<N> d;
         d.start = matrix_impl::do_slice(desc,d,args...);
         return {d,data()};
    }

The slices represented as extents and strides in a Matrix_slice and used for slice subscripting are computed like this:

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template<size_t N, typename T, typename... Args>
size_t do_slice(const Matrix_slice<N>& os, Matrix_slice<N>& ns, const T& s, const Args&... args)
{
     size_t m = do_slice_dim<sizeof...(Args)+1>(os,ns,s);
     size_t n = do_slice(os,ns,args...);
     return m+n;
}

As usual, the recursion is terminated by a simple function:

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template<size_t N>
size_t do_slice(const Matrix_slice<N>& os, Matrix_slice<N>& ns)
{
     return 0;
}

The do_slice_dim() is a tricky bit of computation (to get the slice values right) but illustrates no new programming techniques.

29.4.6. Zero-Dimensional Matrix

The Matrix code contains a lot of occurrences of N–1 where N is the number of dimensions. Thus, N==0 could easily become a nasty special case (for the programming as well as for the mathematics). Here, we solve the problem by defining a specialization:

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template<typename T>
class Matrix<T,0> {
public:
     static constexpr size_t order = 0;
     using value_type = T;

     Matrix(const T& x) : elem(x) { }
     Matrix& operator=(const T& value) { elem = value; return *this; }

     T& operator()() { return elem; }
     const T& operator()() const { return elem; }

     operator T&() { return elem; }
     operator const T&() { return elem; }
private:
     T elem;
};

Matrix<T,0> is not really a matrix. It stores a single element of type T and can only be converted to a reference to that type.

29.5. Solving Linear Equations

The code for a numerical computation makes sense if you understand the problem being solved and the math used to express the solution and tends to appear to be utter nonsense if you don’t. The example used here should be rather trivial if you have learned basic linear algebra; if not, just see it as an example of transcribing a textbook solution into code with minimal rewording.

The example here is chosen to demonstrate a reasonably realistic and important use of Matrixes. We will solve a set (any set) of linear equations of this form:

a1,1 x₁ + ... + a1,n xn = b₁

...

an,1 x₁ + ... + an,n xn = bn

Here, the xs designate the n unknowns; as and bs are given constants. For simplicity, we assume that the unknowns and the constants are floating-point values. The goal is to find values for the unknowns that simultaneously satisfy the n equations. These equations can compactly be expressed in terms of a matrix and two vectors:

Ax =b

Here, A is the square n-by-n matrix defined by the coefficients:

The vectors x and b are the vectors of unknowns and constants, respectively:

This system may have zero, one, or an infinite number of solutions, depending on the coefficients of the matrix A and the vector b. There are various methods for solving linear systems. We use a classic scheme, called Gaussian elimination [Freeman,1992], [Stewart,1998], [Wood,1999]. First, we transform A and b so that A is an upper-triangular matrix. By “upper-triangular,” we mean all the coefficients below the diagonal of A are zero. In other words, the system looks like this:

This is easily done. A zero for position a(i,j) is obtained by multiplying the equation for row i by a constant so that a(i,j) equals another element in column j, say a(k,j). That done, we just subtract the two equations, and a(i,j)==0 and the other values in row i change appropriately.

If we can get all the diagonal coefficients to be nonzero, then the system has a unique solution, which can be found by “back substitution.” The last equation is easily solved:

an,n xn = bn

Obviously, x[n] is b[n]/a(n,n). That done, eliminate row n from the system and proceed to find the value of x[n–1], and so on, until the value for x[1] is computed. For each n, we divide by a(n,n) so the diagonal values must be nonzero. If that does not hold, the back substitution method fails, meaning that the system has zero or an infinite number of solutions.

29.5.1. Classical Gaussian Elimination

Now let us look at the C++ code to express this. First, we’ll simplify our notation by conventionally naming the two Matrix types that we are going to use:

using Mat2d = Matrix<double,2>;
using Vec = Matrix<double,1>;

Next, we will express our desired computation:

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Vec classical_gaussian_elimination(Mat2d A, Vec b)
{
     classical_elimination(A, b);
     return back_substitution(A, b);
}

That is, we make copies of our inputs A and b (using call-by-value), call a function to solve the system, and then calculate the result to return by back substitution. The point is that our breakdown of the problem and our notation for the solution are right out of the textbook. To complete our solution, we have to implement classical_elimination() and back_substitution(). Again, the solution is in the textbook:

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void classical_elimination(Mat2d& A, Vec& b)
{
     const size_t n = A.dim1();

     // traverse from 1st column to the next-to-last, filling zeros into all elements under the diagonal:
     for (size_t j = 0; j!=n-1; ++j) {
           const double pivot = A(j, j);
           if (pivot==0) throw Elim_failure(j);
           // fill zeros into each element under the diagonal of the ith row:
           for (size_t i = j+1; i!=n; ++i) {
                 const double mult = A(i,j) / pivot;
                 A[i](slice(j)) = scale_and_add(A[j](slice(j)), -mult,A[i](slice(j)));
                 b(i) -= mult*b(j); // make the corresponding change to b
           }
     }
}

The pivot is the element that lies on the diagonal of the row we are currently dealing with. It must be nonzero because we need to divide by it; if it is zero, we give up by throwing an exception:

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Vec back_substitution(const Mat2d& A, const Vec& b)
{
     const size_t n = A.dim1();
     Vec x(n);

     for (size_t i = n-1; i>=0; --i) {
           double s = b(i)-dot_product(A[i](slice(i+1)),x(slice(i+1)));
           if (double m = A(i,i))
                 x(i) = s/m;
           else
                 throw Back_subst_failure(i);
     }
     return x;
}

29.5.2. Pivoting

We can avoid the divide-by-zero problem and also achieve a more robust solution by sorting the rows to get zeros and small values away from the diagonal. By “more robust” we mean less sensitive to rounding errors. However, the values change as we go along placing zeros under the diagonal, so we have to also reorder to get small values away from the diagonal (that is, we can’t just reorder the matrix and then use the classical algorithm):

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void elim_with_partial_pivot(Mat2d& A, Vec& b)
{
     const size_t n = A.dim1();

     for (size_t j = 0; j!=n; ++j) {
           size_t pivot_row = j;
     // look for a suitable pivot:
            for (size_t k = j+1; k!=n; ++k)
                  if (abs(A(k,j)) > abs(A(pivot_row,j)))
                        pivot_row = k;

            // swap the rows if we found a better pivot:
            if (pivot_row!=j) {
                   A.swap_rows(j,pivot_row);
                   std::swap(b(j),b(pivot_row));
            }

            // elimination:
            for (size_t i = j+1; i!=n; ++i) {
                  const double pivot = A(j,j);
                  if (pivot==0) error("can't solve: pivot==0");
                  const double mult = A(i,j)/pivot;
                  A[i].slice(j) = scale_and_add(A[j].slice(j), –mult, A[i].slice(j));
                  b(i) –= mult*b(j);
            }
      }
}

We use swap_rows() and scale_and_multiply() to make the code more conventional and to save us from writing an explicit loop.

29.5.3. Testing

Obviously, we have to test our code. Fortunately, there is a simple way to do that:

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void solve_random_system(size_t n)
{
     Mat2d A = random_matrix(n); // generate random Mat2d
     Vec b = random_vector(n);   // generate random Vec

     cout << "A = " << A << endl;
     cout << "b = " << b << endl;

     try {
          Vec x = classical_gaussian_elimination(A, b);
          cout << "classical elim solution is x = " << x << endl;
               Vec v = A * x;
          cout << " A * x = "<<v<< endl;
     }
     catch(const exception& e) {
          cerr << e.what() << endl;
     }
}

We can get to the catch-clause in three ways:

• A bug in the code (but, being optimists, we don’t think there are any)

• An input that trips up classical_elimination() (using elim_with_partial_pivot() would minimize the chances of that)

• Rounding errors

However, our test is not as realistic as we’d like because genuinely random matrices are unlikely to cause problems for classical_elimination().

To verify our solution, we print out A*x, which had better equal b (or close enough for our purpose, given rounding errors). The likelihood of rounding errors is the reason we didn’t just do:

if (A*x!=b) error("substitution failed");

Because floating-point numbers are just approximations to real numbers, we have to accept approximately correct answers. In general, using == and != on the result of a floating-point computation is best avoided: floating-point is inherently an approximation. Had I felt the need for a machine check, I would have defined an equal() function with a notion of which error ranges to consider acceptable and then written:

if (equal(A*x,b)) error("substitution failed");

The random_matrix() and random_vector() are simple uses of random numbers and are left as simple exercises for the reader.

29.5.4. Fused Operations

In addition to providing efficient primitive operations, a general matrix class must handle three related problems to satisfy performance-conscious users:

[1] The number of temporaries must be minimized.

[2] Copying of matrices must be minimized.

[3] Multiple loops over the same data in composite operations must be minimized.

Consider U=M*V+W, where U, V, and W are vectors (Matrix<T,1>) and M is a Matrix<T,2>. A naive implementation introduces temporary vectors for M*V and M*V+W and copies the results of M*V and M*V+W. A smart implementation calls a function mul_add_and_assign(&U,&M,&V,&W) that introduces no temporaries, copies no vectors, and touches each element of the matrices the minimum number of times.

The move constructor helps: the temporary used for M*V is used for (M*V)+W. If we had written

Matrix<double,1> U=M*V+W;

we would have eliminated all element copies: the elements allocated in the local variable in M*V are the ones ending up in U.

That leaves the problem of merging the loops: loop fusion. This degree of optimization is rarely necessary for more than a few kinds of expressions, so a simple solution to efficiency problems is to provide functions such as mul_add_and_assign() and let the user call those where it matters. However, it is possible to design a Matrix so that such optimizations are applied automatically for expressions of the right form. That is, we can treat U=M*V+W as a use of a single operator with four operands. The basic technique was demonstrated for ostream manipulators (§38.4.5.2). In general, it can be used to make a combination of n binary operators act like an (n+1)-ary operator. Handling U=M*V+W requires the introduction of two auxiliary classes. However, the technique can result in impressive speedups (say, 30 times) on some systems by enabling more powerful optimization techniques. First, for simplicity, let us restrict ourselves to two-dimensional matrices of double-precision floating-point numbers:

using Mat2d = Matrix<double,2>;
using Vec = Matrix<double,1>;

We define the result of multiplying a Mat2d by a Vec:

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struct MVmul {
     const Mat2d& m;
     const Vec& v;

     MVmul(const Mat2d& mm, const Vec &vv) :m{mm}, v{vv} { }

     operator Vec();// evaluate and return result
};

inline MVmul operator*(const Mat2d& mm, const Vec& vv)
{
     return MVmul(mm,vv);
}

This “multiplication” should replace the one from §29.3 and does nothing except store references to its operands; the evaluation of M*V is deferred. The object produced by * is closely related to what is called a closure in many technical communities. Similarly, we can deal with what happens if we add a Vec:

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struct MVmulVadd {
     const Mat2d& m;
     const Vec& v;
     const Vec& v2;

     MVmulVadd(const MVmul& mv, const Vec& vv) :m(mv.m), v(mv.v), v2(vv) { }

     operator Vec();// evaluate and return result
};

inline MVmulVadd operator+(const MVmul& mv, const Vec& vv)
{
     return MVmulVadd(mv,vv);
}

This defers the evaluation of M*V+W. We now have to ensure that it all gets evaluated using a good algorithm when it is assigned to a Vec:

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template<>
class Matrix<double,1> {     // specialization (just for this example)
     // ...

public:
     Matrix(const MVmulVadd& m)                   // initialize by result of m
     {
          // allocate elements, etc.
          mul_add_and_assign(this,&m.m,&m.v,&m.v2);
     }

     Matrix& operator=(const MVmulVadd& m)        // assign the result of m to *this
     {
         mul_add_and_assign(this,&m.m,&m.v,&m.v2);
         return *this;
     }
     // ...
};

Now U=M*V+W is automatically expanded to

U.operator=(MVmulVadd(MVmul(M,V),W))

which because of inlining resolves to the desired simple call

mul_add_and_assign(&U,&M,&V,&W)

Clearly, this eliminates the copying and the temporaries. In addition, we might write mul_add_and_assign() in an optimized fashion. However, if we just wrote it in a fairly simple and unoptimized fashion, it would still be in a form that offered great opportunities to an optimizer.

The importance of this technique is that most really time-critical vector and matrix computations are done using a few relatively simple syntactic forms. Typically, there is no real gain in optimizing expressions of half a dozen operators. For that we typically want to write a function anyway.

This technique is based on the idea of using compile-time analysis and closure objects to transfer evaluation of a subexpression into an object representing a composite operation. It can be applied to a variety of problems with the common attribute that several pieces of information need to be gathered into one function before evaluation can take place. I refer to the objects generated to defer evaluation as composition closure objects, or simply compositors.

If this composition technique is used to delay execution of all operations, it is referred to as expression templates [Vandevoorde,2002] [Veldhuizen,1995]. Expression templates systematically use function objects to represent expressions as abstract syntax trees (ASTs).

29.6. Advice

[1] List basic use cases; §29.1.1.

[2] Always provide input and output operations to simplify simple testing (e.g., unit testing); §29.1.1.

[3] Carefully list the properties a program, class, or library ideally should have; §29.1.2.

[4] List the properties of a program, class, or library that are considered beyond the scope of the project; §29.1.2.

[5] When designing a container template, carefully consider the requirements on the element type; §29.1.2.

[6] Consider how the design might accommodate run-time checking (e.g., for debugging); §29.1.2.

[7] If possible, design a class to mimic existing professional notation and semantics; §29.1.2.

[8] Make sure that the design does not leak resources (e.g., have a unique owner for each resource and use RAII); §29.2.

[9] Consider how a class can be constructed and copied; §29.1.1.

[10] Provide complete, flexible, efficient, and semantically meaningful access to elements; §29.2.2, §29.3.

[11] Place implementation details in their own _impl namespace; §29.4.

[12] Provide common operations that do not require direct access to the representation as helper functions; §29.3.2, §29.3.3.

[13] For fast access, keep data compact and use accessor objects to provide necessary nontrivial access operations; §29.4.1,§29.4.2, §29.4.3.

[14] The structure of data can often be expressed as nested initializer lists; §29.4.4.

[15] When dealing with numbers, aways consider “end cases,” such as zero and “many”; §29.4.6.

[16] In addition to unit testing and testing that the code meets its requirements, test the design through examples of real use; §29.5.

[17] Consider how the design might accommodate unusually stringent performance requirements; §29.5.4

Part IV: The Standard Library

This part describes the C++ standard library. The aim is to provide an understanding of how to use the library, to demonstrate generally useful design and programming techniques, and to show how to extend the library in the ways in which it was intended to be extended.

Chapters

30 Standard-Library Overview

31 STL Containers

32 STL Algorithms

33 STL Iterators

34 Memory and Resources

35 Utilities

36 Strings

37 Regular Expressions

38 I/O Streams

39 Locales

40 Numerics

41 Concurrency

42 Threads and Tasks

43 The C Standard Library

44 Compatibility

“... I am just now beginning to discover the difficulty of expressing one’s ideas on paper. As long as it consists solely of description it is pretty easy; but where reasoning comes into play, to make a proper connection, a clearness & a moderate fluency, is to me, as I have said, a difficulty of which I had no idea ...”

– Charles Darwin

30. Standard-Library Overview

Many secrets of art and nature are thought by the unlearned to be magical.

– Roger Bacon

• Introduction

Standard-Library Facilities; Design Constraints; Description Style

• Headers

• Language Support

initializer_list Support; Range-for Support

• Error Handling

Exceptions; Assertions; system_error

• Advice

30.1. Introduction

The standard library is the set of components specified by the ISO C++ standard and shipped with identical behavior (modulo performance) by every C++ implementation. For portability and long-term maintainability, I strongly recommend using the standard library whenever feasible. Maybe you can design and implement a better alternative for your application, but:

• How easy will it be for some future maintainer to learn that alternative design?

• How likely is the alternative to be available on a yet unknown platform ten years from now?

• How likely is the alternative to be useful for future applications?

• How likely is it that your alternative will be interoperable with code written using the standard library?

• How likely is it that you can spend as much effort optimizing and testing your alternative as was done for the standard library?

And, of course, if you use an alternative, you (or your organization) will be responsible for the maintenance and evolution of the alternative “forever.” In general: try not to reinvent the wheel.

The standard library is rather large: its specification in the ISO C++ standard is 785 dense pages. And that is without describing the ISO C standard library, which is a part of the C++ standard library (another 139 pages). To compare, the C++ language specification is 398 pages. Here, I summarize, relying heavily on tables, and give a few examples. Details can be found elsewhere, including online copies of the standard, complete online documentation of implementations, and (if you like to read code) open source implementations. Rely on the references to the standard for complete details.

The standard-library chapters are not intended to be read in their order of presentation. Each chapter and typically each major subsection can be read in isolation. Rely on cross-references and the index if you encounter something unknown.

30.1.1. Standard-Library Facilities

What ought to be in the standard C++ library? One ideal is for a programmer to be able to find every interesting, significant, and reasonably general class, function, template, etc., in a library. However, the question here is not “What ought to be in some library?” but “What ought to be in the standard library?” “Everything!” is a reasonable first approximation to an answer to the former question but not to the latter. A standard library is something that every implementer must supply so that every programmer can rely on it.

The C++ standard library provides:

• Support for language features, such as memory management (§11.2), the range-for statement (§9.5.1), and run-time type information (§22.2)

• Information about implementation-defined aspects of the language, such as the largest finite float value (§40.2)

• Primitive operations that cannot be easily or efficiently implemented in the language itself, such as is_polymorphic, is_scalar, and is_nothrow_constructible (§35.4.1)

• Facilities for low-level (“lock-free”) concurrent programming (§41.3)

• Support for thread-based concurrency (§5.3, §42.2)

• Minimal support for task-based concurrency, such as future and async() (§42.4)

• Functions that most programmers cannot easily implement optimally and portably, such as uninitialized_fill() (§32.5) and memmove() (§43.5)

• Minimal support for (optional) reclamation of unused memory (garbage collection), such as declare_reachable() (§34.5)

• Nonprimitive foundational facilities that a programmer can rely on for portability, such as lists (§31.4), maps (§31.4.3), sort() (§32.6), and I/O streams (Chapter 38)

• Frameworks for extending the facilities it provides, such as conventions and support facilities that allow a user to provide I/O of a user-defined type in the style of I/O for built-in types (Chapter 38) and the STL (Chapter 31)

A few facilities are provided by the standard library simply because it is conventional and useful to do so. Examples are the standard mathematical functions, such as sqrt() (§40.3), random number generators (§40.7), complex arithmetic (§40.4), and regular expressions (Chapter 37).

The standard library aims to be the common foundation for other libraries. In particular, combinations of its facilities allow the standard library to play three supporting roles:

• A foundation for portability

• A set of compact and efficient components that can be used as the foundation for performance-sensitive libraries and applications

• A set of components enabling intra-library communications

The design of the library is primarily determined by these three roles. These roles are closely related. For example, portability is commonly an important design criterion for a specialized library, and common container types such as lists and maps are essential for convenient communication between separately developed libraries.

The last role is especially important from a design perspective because it helps limit the scope of the standard library and places constraints on its facilities. For example, string and list facilities are provided in the standard library. If they were not, separately developed libraries could communicate only by using built-in types. However, advanced linear algebra and graphics facilities are not provided. Such facilities are obviously widely useful, but they are rarely directly involved in communication between separately developed libraries.

Unless a facility is somehow needed to support these roles, it can be left to some library outside the standard. For good and bad, leaving something out of the standard library opens the opportunity for different libraries to offer competing realizations of an idea. Once a library proves itself widely useful in a variety of computing environments and application domains, it becomes a candidate for the standard library. The regular expression library (Chapter 37) is an example of this.

A reduced standard library is available for freestanding implementations, that is, implementations running with minimal or no operating system support (§6.1.1).

30.1.2. Design Constraints

The roles of a standard library impose several constraints on its design. The facilities offered by the C++ standard library are designed to be:

• Valuable and affordable to essentially every student and professional programmer, including the builders of other libraries.

• Used directly or indirectly by every programmer for everything within the library’s scope.

• Efficient enough to provide genuine alternatives to hand-coded functions, classes, and templates in the implementation of further libraries.

• Either policy free or with an option to supply policies as arguments.

• Primitive in the mathematical sense. That is, a component that serves two weakly related roles will almost certainly suffer overhead compared to individual components designed to perform only a single role.

• Convenient, efficient, and reasonably safe for common uses.

• Complete in what they do. The standard library may leave major functions to other libraries, but if it takes on a task, it must provide enough functionality so that individual users or implementers need not replace it to get the basic job done.

• Easy to use with built-in types and operations.

• Type safe by default, and therefore in principle checkable at run time.

• Supportive of commonly accepted programming styles.

• Extensible to deal with user-defined types in ways similar to the way built-in types and standard-library types are handled.

For example, building the comparison criteria into a sort function is unacceptable because the same data can be sorted according to different criteria. This is why the C standard-library qsort() takes a comparison function as an argument rather than relying on something fixed, say, the < operator (§12.5). On the other hand, the overhead imposed by a function call for each comparison compromises qsort() as a building block for further library building. For almost every data type, it is easy to do a comparison without imposing the overhead of a function call.

Is that overhead serious? In most cases, probably not. However, the function call overhead can dominate the execution time for some algorithms and cause users to seek alternatives. The technique described in §25.2.3 of supplying comparison criteria through a template argument solves that problem for sort() and many other standard-library algorithms. The sort example illustrates the tension between efficiency and generality. It is also an example of how such tensions can be resolved. A standard library is not merely required to perform its tasks. It must also perform them so efficiently that users are not tempted to supply their own alternatives to what the standard offers. Otherwise, implementers of more advanced features are forced to bypass the standard library in order to remain competitive. This would add a burden to the library developer and seriously complicate the lives of users wanting to stay platform-independent or to use several separately developed libraries.

The requirements of “primitiveness” and “convenience of common uses” can conflict. The former requirement precludes exclusively optimizing the standard library for common cases. However, components serving common, but nonprimitive, needs can be included in the standard library in addition to the primitive facilities, rather than as replacements. The cult of orthogonality must not prevent us from making life convenient for the novice and the casual user. Nor should it cause us to leave the default behavior of a component obscure or dangerous.

30.1.3. Description Style

A full description of even a simple standard-library operation, such as a constructor or an algorithm, can take pages. Consequently, I use an extremely abbreviated style of presentation. Sets of related operations are typically presented in tables:

I try to be mnemonic when choosing identifiers, so b and e will be iterators specifying a range, p a pointer or an iterator, and x some value, all depending on context. In this notation, only the commentary distinguishes no result from a Boolean result, so you can confuse those if you try hard enough. For an operation returning a Boolean, the explanation usually ends with a question mark. Where an algorithm follows the usual pattern of returning the end of an input sequence to indicate “failure,” “not found,” etc. (§4.5.1, §33.1.1), I do not mention that explicitly.

Usually, such an abbreviated description is accompanied with a reference to the ISO C++ standard, some further explanation, and examples.

30.2. Headers

The facilities of the standard library are defined in the std namespace and presented as a set of headers. The headers identify the major parts of the library. Thus, listing them gives an overview of the library.

The rest of this subsection is a list of headers grouped by function, accompanied by brief explanations and annotated by references to where they are discussed. The grouping is chosen to match the organization of the standard.

A standard header with a name starting with the letter c is equivalent to a header in the C standard library. For every header <X.h> defining part of the C standard library in the global namespace and also in namespace std, there is a header <cX> defining the same names. Ideally, the names from a <cX> header do not pollute the global namespace (§15.2.4), but unfortunately (due to complexities of maintaining multilanguage, multi-operating-system environments) most do.

The associative containers multimap and multiset can be found in <map> and <set>, respectively. The priority_queue (§31.5.3) is declared in <queue>.

Iterators provide the mechanism to make standard algorithms generic (§3.4.2, §33.1.4).

A typical general algorithm can be applied to any sequence (§3.4.2, §32.2) of any type of element. The C standard library functions bsearch() and qsort() apply to built-in arrays with elements of types without user-defined copy constructors and destructors only (§12.5).

Assertions using exceptions are described in §13.4.

The <cstring> header declares the strlen(), strcpy(), etc., family of functions. The <cstdlib> declares atof() and atoi() which convert C-style strings to numeric values.

Manipulators are objects used to manipulate the state of a stream (§38.4.5.2).

A locale localizes differences such as the output format for dates, the symbol used to represent currency, and string collation criteria that vary among different natural languages and cultures.

The <cstddef> header defines the type of values returned by sizeof(), size_t, the type of the result of pointer subtraction and of array subscripts, ptrdiff_t (§10.3.1), and the infamous NULL macro (§7.2.2).

C-style stack unwinding (using setjmp and longjmp from <csetjmp>) is incompatible with the use of destructors and with exception handling (Chapter 13, §30.4) and is best avoided. C-style stack unwinding and signals are not discussed in this book.

For historical reasons, abs() and div() are found in <cstdlib> rather than in <cmath> with the rest of the mathematical functions (§40.3).

C provides standard-library facilities of varying relevance to C++ programmers. The C++ standard library provides access to all such facilities:

The <cstdbool> header will not define macros bool, true, or false. The <cstdalign> header will not define a macro alignas. The .h equivalents to <cstdbool>, <ccomplex>, <calign>, and <ctgmath> approximate C++ facilities for C. Avoid them if you can.

The <cfenv> header provides types (such as fenv_t and fexcept_t), floating-point status flags, and control modes describing an implementation’s floating-point environment.

A user or a library implementer is not allowed to add or subtract declarations from the standard headers. Nor is it acceptable to try to change the contents of a header by defining macros to change the meaning of declarations in a header (§15.2.3). Any program or implementation that plays such games does not conform to the standard, and programs that rely on such tricks are not portable. Even if they work today, the next release of any part of an implementation may break them. Avoid such trickery.

For a standard-library facility to be used, its header must be included. Writing out the relevant declarations yourself is not a standards-conforming alternative. The reason is that some implementations optimize compilation based on standard header inclusion, and others provide optimized implementations of standard-library facilities triggered by the headers. In general, implementers use standard headers in ways programmers cannot predict and shouldn’t have to know about.

A programmer can, however, specialize utility templates, such as swap() (§35.5.2), for non-standard-library, user-defined types.

30.3. Language Support

A small but essential part of the standard library is language support, that is, facilities that must be present for a program to run because language features depend on them.

30.3.1. initializer_list Support

A {}-list is converted into an object of type std::initializer_list<X> according to the rules described in §11.3. In <initializer_list>, we find initializer_list:

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template<typename T>
class initializer_list { // §iso.18.9
public:
     using value_type = T;
     using reference = const T&;       // note const: initializer_list elements are immutable
     using const_reference = const T&;
     using size_type = size_t;
     using iterator = const T*;
     using const_iterator = const T*;

     initializer_list() noexcept;

     size_t size() const noexcept;     // number of elements
     const T* begin() const noexcept;  // first element
     const T* end() const noexcept;    // one-past-last element
};

template<typename T>
     const T* begin(initializer_list<T> lst) noexcept { return lst.begin(); }
template<typename T>
     const T* end(initializer_list<T> lst) noexcept { return lst.end(); }

Unfortunately, initializer_list does not offer a subscript operator. If you want to use [] rather than *, subscript a pointer:

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void f(initializer_list<int> lst)
{
     for(int i=0; i<lst.size(); ++i)
           cout << lst[i] << '\n';   // error

     const int* p = lst.begin();
     for(int i=0; i<lst.size(); ++i)
           cout << p[i] << '\n';     // OK
}

Naturally, an initializer_list can also be used by a range-for. For example:

void f2(initializer_list<int> lst)
{
     for (auto x : lst)
           cout << x << '\n';
}

30.3.2. Range-for Support

A range-for statement is mapped to a for-statement using an iterator as described in §9.5.1.

In <iterator>, the standard library provides std::begin() and std::end() functions for built-in arrays and for every type that provides member begin() and end(); see §33.3.

All standard-library containers (e.g., vector and unordered_map) and strings support iteration using range-for; container adaptors (such as stack and priority_queue) do not. The container headers, such as <vector>, include<initializer_list>, so the user rarely has to do so directly.

30.4. Error Handling

The standard library consists of components developed over a period of almost 40 years. Thus, their style and approaches to error handling are not consistent:

• C-style libraries consist of functions, many of which set errno to indicate that an error happened; see §13.1.2 and §40.3.

• Many algorithms operating on a sequence of elements return an iterator to the one-past-the-last element to indicate “not found” or “failure”; see §33.1.1.

• The I/O streams library relies on a state in each stream to reflect errors and may (if the user requests it) throw exceptions to indicate errors; see §38.3.

• Some standard-library components, such as vector, string, and bitset, throw exceptions to indicate errors.

The standard library is designed so that all facilities obey “the basic guarantee” (§13.2); that is, even if an exception is thrown, no resource (such as memory) is leaked and no invariant for a standard-library class is broken.

30.4.1. Exceptions

Some standard-library facilities report errors by throwing exceptions:

These exceptions may be encountered in any code that directly or indirectly uses these facilities. In addition, any operation that manipulates an object that may throw an exception must be assumed to throw (that exception) unless care has been taken to avoid that. For example, a packaged_task will throw an exception if the function it is required to execute throws.

Unless you know that no facility is used in a way that could throw an exception, it is a good idea to always catch one of the root classes of the standard-library exception hierarchy (such as exception) as well as any exception (...) somewhere (§13.5.2.3), for example, in main().

30.4.1.1. The Standard exception Hierarchy

Do not throw built-in types, such as int and C-style strings. Instead, throw objects of types specifically defined to be used as exceptions.

This hierarchy of standard exception classes provides a classification of exceptions:

This hierarchy attempts to provide a framework for exceptions beyond the ones defined by the standard library. Logic errors are errors that in principle could be caught either before the program starts executing or by tests of arguments to functions and constructors. Run-time errors are all other errors. The system_error is described in §30.4.3.3.

The standard-library exception hierarchy is rooted in class exception:

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class exception {
public:
     exception();
     exception(const exception&);
     exception& operator=(const exception&);
     virtual ~exception();
     virtual const char* what() const;
};

The what() function can be used to obtain a string that is supposed to indicate something about the error that caused the exception.

A programmer can define an exception by deriving from a standard-library exception like this:

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struct My_error : runtime_error {
     My_error(int x) :runtime_error{"My_error"}, interesting_value{x} { }
     int interesting_value;
};

Not all exceptions are part of the standard-library exception hierarchy. However, all exceptions thrown by the standard library are from the exception hierarchy.

Unless you know that no facility is used in a way that could throw an exception, it is a good idea to somewhere catch all exceptions. For example:

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int main()
try {
     // ...
}
catch (My_error& me) {          // a My_error happened
     // we can use me.interesting_value and me.what()
}
catch (runtime_error& re) {     // a runtine_error happened
     // we can use re.what()
}
catch (exception& e) {          // some standard-library exception happened
     // we can use e.what()
}
catch (...) {                   // Some unmentioned exception happened
     // we can do local cleanup
}

As for function arguments, we use references to avoid slicing (§17.5.1.4).

30.4.1.2. Exception Propagation

In <exception>, the standard library provides facilities for making propagation of exceptions accessible to programmers:

An exception_ptr can point to any exception, not just exceptions from the exception hierarchy. Think of exception_ptr as a smart pointer (like shared_ptr) that keeps its exception alive for as long as an exception_ptr points to it. That way, we can pass an exception_pointer to an exception out of a function that caught it and re-throw elsewhere. In particular, an exception_ptr can be used to implement a re-throw of an exception in a different thread from the one in which the exception was caught. This is what promise and future (§42.4) rely on. Use of rethrow_exception() on an exception_ptr (from different threads) does not introduce a data race.

The make_exception_ptr() could be implemented as:

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template<typename E>
exception_ptr make_exception_ptr(E e) noexcept;
try {
     throw e;
}
catch(...) {
     return current_exception();
}

A nested_exception is class that stores an exception_ptr obtained from a call of current_exception():

The intended use of nested_exception is as a base class for a class used by an exception handler to pass some information about the local context of an error together with a exception_ptr to the exception that caused it to be called. For example:

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struct My_error : runtime_error {
     My_error(const string&);
     // ...
};

void my_code()
{
     try {
          // ...
     }
     catch (...) {
          My_error err {"something went wrong in my_code()"};
          // ...
          throw_with_nested(err);
     }
}

Now My_error information is passed along (rethrown) together with a nested_exception holding an exception_ptr to the exception caught.

Further up the call chain, we might want to look at the nested exception:

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void user()
{
     try {
          my_code();
     }
     catch(My_error& err) {

     // ... clear up My_error problems ...

          try {
              rethrow_if_nested(err);   // re-throw the nested exception, if any
          }
          catch (Some_error& err2) {
               // ... clear up Some_error problems ...
          }
     }
}

This assumes that we know that some_error might be nested with My_error.

An exception cannot propagate out of a noexcept function (§13.5.1.1).

30.4.1.3. terminate()

In <exception>, the standard library provides facilities for dealing with unexpected exceptions:

Avoid using these functions, except very occasionally set_terminate() and terminate(). A call of terminate() terminates a program by calling a terminate handler set by a call of set_terminate(). The – almost always correct – default is to immediately terminate the program. For fundamental operating system reasons, it is implementation-defined whether destructors for local objects are invoked when terminate() is called. If terminate() is invoked as the result of a noexcept violation, the system is allowed (important) optimizations that imply that the stack may even be partially unwound (§iso.15.5.1).

It is sometimes claimed that uncaught_exception() can be useful for writing destructors that behave differently depending on whether a function is exited normally or by an exception. However, uncaught_exception() is also true during stack unwinding (§13.5.1) after the initial exception has been caught. I consider uncaught_exception() too subtle for practical use.

30.4.2. Assertions

The standard provides:

For example:

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template<typename T>
void draw_all(vector<T*>& v)
{
     static_assert(Is_base_of<Shape,T>(),"non-Shape type for draw_all()");

     for (auto p : v) {
          assert(p!=nullptr);
          // ...
     }
}

The assert() is a macro found in <cassert>. The error message produced by assert() is implementation-defined but should contain the source file name (__FILE__), and the source line number (__LINE__) containing the assert().

Asserts are (as they should be) used more frequently in production code than in small illustrative textbook examples.

The name of the function (__func__) may also be included in the message. It can be a serious mistake to assume that the assert() is evaluated when it is not. For example, given a usual compiler setup, assert(p!=nullptr) will catch an error during debugging, but not in the final shipped product.

For a way to manage assertions, see §13.4.

30.4.3. system_error

In <system_error>, the standard library provides a framework for reporting errors from the operating system and lower-level system components. For example, we may write a function to check a file name and then open a file like this:

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ostream& open_file(const string& path)
{
     auto dn = split_into_directory_and_name(path);          // split into {path,name}

     error_code err {does_directory_exist(dn.first)};        // ask "the system" about the path
     if (err) { // err!=0 means error

          // ... see if anything can be done ...

          if (cannot_handle_err)
                throw system_error(err);
     }

     // ...
     return ofstream{path};
}

Assuming that “the system” doesn’t know about C++ exceptions, we have no choice about whether to deal with error codes or not; the only questions are “where?” and “how?” In <system_error>, the standard library provides facilities for classifying error codes, for mapping system-specific error codes into more portable ones, and for mapping error codes into exceptions:

30.4.3.1. Error Codes

When an error “bubbles up” from a lower level as an error code, we must handle the error it represents or turn it into an exception. But first we must classify it: different systems use different error codes for the same problem, and different systems simply have different kinds of errors.

For a type representing the simple idea of an error code, error_code provides a lot of members. It is basically as simple map from an integer to a pointer to an error_category:

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class error_code {
public:
     // representation: {value,category} of type {int,const error_category*}
};

An error_category is an interface to an object of a class derived from error_category. Therefore, an error_category is passed by reference and stored as a pointer. Each separate error_category is represented by a unique object.

Consider again the open_file() example:

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ostream& open_file(const string& path)
{
     auto dn = split_into_directory_and_name(path);          // split into {path,name}

     if (error_code err {does_directory_exist(dn.first)}) {  // ask "the system" about the path
          if (err==errc::permission_denied) {
                // ...
          }
          else if (err==errc::not_a_directory) {
                // ...
          }
          throw system_error(err); // can't do anything locally
     }

     // ...
     return ofstream{path};
}

The errc error codes are described in §30.4.3.6. Note that I used an if-then-else chain rather than the more obvious switch-statement. The reason is that == is defined in terms of equivalence, taking both the error category() and the error value() into account.

The operations on error_codes are system-specific. In some cases, error_codes can be mapped into error_conditions (§30.4.3.4) using the mechanisms described in §30.4.3.5. An error_condition is extracted from an error_code using default_error_condition(). An error_condition typically contains less information than an error_code, so it is usually a good idea to keep the error_code available and only extract its error_condition when needed.

Manipulating error_codes does not change the value of errno (§13.1.2, §40.3). The standard library leaves the error states provided by other libraries unchanged.

30.4.3.2. Error Categories

An error_category represents a classification of errors. Specific errors are represented by a class derived from class error_category:

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class error_category {
public:
     // ... interface to specific categories derived from error_category ...
};

Because error_category is designed to be used as a base class, no copy or move operations are provided. Access an error_category through pointers or references.

There are four named standard-library categories:

These categories are necessary because a simple integer error code can have different meanings in different contexts (categorys). For example, 1 means “operation not permitted” (EPERM) in POSIX, is a generic code (state) for all errors as an iostream error, and means “future already retrieved” (future_already_retrieved) as a future error.

30.4.3.3. Exception system_error

A system_error is used to report errors that ultimately originate in the parts of the standard library that deal with the operating system. It passes along an error_code and optionally an error-message string:

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class system_error : public runtime_error {
public:
     // ...
};

Code catching a system_error has its error_code available. For example:

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try {
     // something
}
catch (system_error& err) {
     cout << "caught system_error " << err.what() <<'\n';     // error message

     auto ec = err.code();
     cout << "category: " << ec.category().what() <<'\n';
     cout << "value: " << ec.value() <<'\n';
     cout << "message: " << ec.message() <<'\n';
}

Naturally, system_errors can be used by code that is not part of the standard library. A system-specific error_code is passed, rather than a potentially portable error_condition (§30.4.3.4). To get an error_condition from an error_code use default_error_condition() (§30.4.3.1).

30.4.3.4. Potentially Portable Error Conditions

Potentially portable error codes (error_conditions) are represented almost identically to the system-specific error_codes:

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class error_condition {   // potentially portable (§iso.19.5.3)
public:
     // like error_code but
     // no output operator (<<) and
     // no default_error_condition()
};

The general idea is that each system has a set of specific (“native”) codes that are mapped into the potentially portable ones for the convenience of programmers of programs (often libraries) that need to work on multiple platforms.

30.4.3.5. Mapping Error Codes

Making an error_category with a set of error_codes and at least one error_condition starts with defining an enumeration with the desired error_code values. For example:

enum class future_errc {
    broken_promise = 1,
    future_already_retrieved,
    promise_already_satisfied,
    no_state
};

The meaning of these values is completely category-specific. The integer values of these enumerators are implementation-defined.

The future error category is part of the standard, so you can find it in your standard library. The details are likely to differ from what I describe.

Next, we need to define a suitable category for our error codes:

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class future_cat : error_category {     // to be returned from future_category()
public:
     const char* name() const noexcept override { return "future"; }

     string message(int ec) const override;
};

const error_category& future_category() noexcept
{
     static future_cat obj;
     return &obj;
}

The mapping from integer values to error message() strings is a bit tedious. We have to invent a set of messages that are likely to be meaningful to a programmer. Here, I’m not trying to be clever:

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string future_error::message(int ec) const
{
     switch (ec) {
     default:                                return "bad future_error code";
     future_errc::broken_promise:            return "future_error: broken promise";
     future_errc::future_already_retrieved:  return "future_error: future already retrieved";
     future_errc::promise_already_satisfied: return "future_error: promise already satisfied";
     future_errc::no_state:                  return "future_error: no state";
     }
}

We can now make an error_code out of a future_errc:

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error_code make_error_code(future_errc e) noexcept
{
     return error_code{int(e),future_category()};
}

For the error_code constructor and assignment that take a single error value, it is required that the argument be of the appropriate type for the error_category. For example, an argument intended to become the value() of an error_code of future_category() must be a future_errc. In particular, we can’t just use any int. For example:

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error_code ec1 {7};                             // error
error_code ec2 {future_errc::no_state};         // OK

ec1 = 9;                                        // error
ec2 = future_errc::promise_already_satisfied;   // OK
ec2 = errc::broken_pipe;                        // error: wrong error category

To help the implementer of error_code, we specialize the trait is_error_code_enum for our enumeration:

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template<>
struct is_error_code_enum<future_errc> : public true_type { };

The standard already provides the general template:

template<typename>
struct is_error_code_enum : public false_type { };

This states that anything we don’t deem an error code value isn’t. For error_condition to work for our category, we must repeat what we did for error_code. For example:

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error_condition make_error_condition(future_errc e) noexcept;

template<>
struct is_error_condition_enum<future_errc> : public true_type { };

For a more interesting design, we could use a separate enum for the error_condition and have make_error_condition() implement a mapping from future_errc to that.

30.4.3.6. errc Error Codes

Standard error_codes for the system_category() are defined by enum class errc with values equivalent to the POSIX-derived contents of <cerrno>:

These codes are valid for the "system" category: system_category(). For systems supporting POSIX-like facilities, they are also valid for the "generic" category: generic_category().

The POSIX macros are integers whereas the errc enumerators are of type errc. For example:

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void problem(errc e)
{
     if (e==EPIPE) {                // error: no conversion of errc to int
          // ...
     }

     if (e==broken_pipe) {          // error: broken_pipe not in scope
          // ...
     }

     if (e==errc::broken_pipe) {    // OK
          // ...
     }
}

30.4.3.7. future_errc Error Codes

Standard error_codes for the future_category() are defined by enum class future_errc:

These codes are valid for the "future" category: future_category().

30.4.3.8. io_errc Error Codes

Standard error_codes for the iostream_category() are defined by enum class io_errc:

This code is valid for the "iostream" category: iostream_category().

30.5. Advice

[1] Use standard-library facilities to maintain portability; §30.1, §30.1.1.

[2] Use standard-library facilities to minimize maintenance costs; §30.1.

[3] Use standard-library facilities as a base for more extensive and more specialized libraries; §30.1.1.

[4] Use standard-library facilities as a model for flexible, widely usable software; §30.1.1.

[5] The standard-library facilities are defined in namespace std and found in standard-library headers; §30.2.

[6] A C standard-library header X.h is presented as a C++ standard-library header in <cX>; §30.2.

[7] Do not try to use a standard-library facility without #includeing its header; §30.2.

[8] To use a range-for on a built-in array, #include<iterator>; §30.3.2.

[9] Prefer exception-based error handling over return-code-based error handling; §30.4.

[10] Always catch exception& (for standard-library and language support exceptions) and ... (for unexpected exceptions); §30.4.1.

[11] The standard-library exception hierarchy can be (but does not have to be) used for a user’s own exceptions; §30.4.1.1.

[12] Call terminate() in case of serious trouble; §30.4.1.3.

[13] Use static_assert() and assert() extensively; §30.4.2.

[14] Do not assume that assert() is always evaluated; §30.4.2.

[15] If you can’t use exceptions, consider <system_error>; §30.4.3.

31. STL Containers

It was new. It was singular. It was simple. It must succeed!

– H. Nelson

• Introduction

• Container Overview

Container Representation; Element Requirements

• Operations Overview

Member Types; Constructors, Destructor, and Assignments; Size and Capacity; Iterators; Element Access; Stack Operations; List Operations; Other Operations

• Containers

vector; Lists; Associative Containers

• Container Adaptors

stack; queue; priority_queue

• Advice

31.1. Introduction

The STL consists of the iterator, container, algorithm, and function object parts of the standard library. The rest of the STL is presented in Chapter 32 and Chapter 33.

31.2. Container Overview

A container holds a sequence of objects. This section summarizes the types of containers and briefly outlines their properties. Operations on containers are summarized in §31.3.

Containers can be categorized like this:

• Sequence containers provide access to (half-open) sequences of elements.

• Associative containers provide associative lookup based on a key.

In addition, the standard library provides types of objects that hold elements while not offering all of the facilities of sequence containers or associative containers:

• Container adaptors provide specialized access to underlying containers.

• Almost containers are sequences of elements that provide most, but not all, of the facilities of a container.

The STL containers (the sequence and associative containers) are all resource handles with copy and move operations (§3.3.1). All operations on containers provide the basic guarantee (§13.2) to ensure that they interact properly with exception-based error handling.

The A template argument is the allocator that the container uses to acquire and release memory (§13.6.1, §34.4). For example:

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template<typename T, typename A = allocator<T>>
class vector {
    // ...
};

A is defaulted to std::allocator<T> (§34.4.1) which uses operator new() and operator delete() when it needs to acquire or release memory for its elements.

These containers are defined in <vector>, <list>, and <deque>. The sequence containers are contiguously allocated (e.g., vector) or linked lists (e.g., forward_list) of elements of their value_type (T in the notation used above). A deque (pronounced “deck”) is a mixture of linked-list and contiguous allocation.

Unless you have a solid reason not to, use a vector. Note that vector provides operations for inserting and erasing (removing) elements, allowing a vector to grow and shrink as needed. For sequences of small elements, a vector can be an excellent representation for a data structure requiring list operations.

When inserting and erasing elements of a vector, elements may be moved. In contrast, elements of a list or an associative container do not move when new elements are inserted or other elements are erased.

A forward_list (a singly-linked list) is basically a list optimized for empty and very short lists. An empty forward_list takes up only one word. There are surprisingly many uses for lists where most are empty (and the rest are very short).

These containers are usually implemented as balanced binary trees (usually red-black trees).

The default ordering criterion for a key, K, is std::less<K> (§33.4).

As for sequence containers, the A template argument is the allocator that the container uses to acquire and release memory (§13.6.1, §34.4). The A template argument is defaulted to std::allocator<std::pair<const K,T>> (§31.4.3) for maps and std::allocator<K> for sets.

These containers are implemented as hash tables with linked overflow. The default hash function type, H, for a type K is std::hash<K> (§31.4.3.2). The default for the equality function type, E, for a type K is std::equal_to<K> (§33.4); the equality function is used to decide whether two objects with the same hash code are equal.

The associative containers are linked structures (trees) with nodes of their value_type (in the notation used above, pair<const K,V> for maps and K for sets). The sequence of a set, map, or multimap is ordered by its key value (K). An unordered container need not have an ordering relation for its elements (e.g., <) and uses a hash function instead (§31.2.2.1). The sequence of an unordered container does not have a guaranteed order. A multimap differs from a map in that a key value may occur many times.

Container adaptors are containers providing specialized interfaces to other containers:

The default for a priority_queue’s priority function, Cmp, is std::less<T>. The default for the container type, C,is std::deque<T> for queue and std::vector<T> for stack and priority_queue. See §31.5.

Some data types provide much of what is required of a standard container, but not all. We sometimes refer to those as “almost containers.” The most interesting of those are:

For basic_string, A is the allocator (§34.4) and Tr is the character traits (§36.2.2).

Prefer a container, such as vector, string, or array, over an array when you have a choice. The implicit array-to-pointer conversion and the need to remember the size for a built-in array are major sources of errors (e.g., see §27.2.1).

Prefer the standard strings to other strings and to C-style strings. The pointer semantics of C-style strings imply an awkward notation and extra work for the programmer, and they are a major source of errors (such as memory leaks) (§36.3.1).

31.2.1. Container Representation

The standard doesn’t prescribe a particular representation for a standard container. Instead, the standard specifies the container interfaces and some complexity requirements. Implementers will choose appropriate and often cleverly optimized implementations to meet the general requirements and common uses. In addition to what is needed to manipulate elements, such a “handle” will hold an allocator (§34.4).

For a vector, the element data structure is most likely an array:

The vector will hold a pointer to an array of elements, the number of elements, and the capacity (the number of allocated, currently unused slots) or equivalent (§13.6).

A list is most likely represented by a sequence of links pointing to the elements and the number of elements:

A forward_list is most likely represented by a sequence of links pointing to the elements:

A map is most likely implemented as a (balanced) tree of nodes pointing to (key,value) pairs:

An unordered_map is most likely implemented as a hash table:

A string might be implemented as outlined in §19.3 and §23.2; that is, for short strings the characters are stored in the string handle itself, and for longer strings the elements are stored contiguously on the free-store (like vector elements). Like vector, a string can grow into “free space” allocated to avoid repeated reallocations:

Like a built-in array (§7.3), an array is simply a sequence of elements, with no handle:

This implies that a local array does not use any free store (unless it is allocated there) and that an array member of a class does not imply any free store operations.

31.2.2. Element Requirements

To be an element of a container, an object must be of a type that allows the container implementation to copy or move it, and to swap elements. If a container copies an element using a copy constructor or copy assignment, the result of the copy must be an equivalent object. This roughly means that any test for equality that you can devise on the value of the objects must deem the copy equal to the original. In other words, copying an element must work much like an ordinary copy of an int. Similarly, a move constructor and a move assignment must have the conventional definitions and move semantics (§17.5.1). In addition, it must be possible to swap() elements with the usual semantics. If a type has copy or move, the standard-library swap() will work.

The details of the element requirements are scattered over the standard and quite hard to read (§iso.23.2.3, §iso.23.2.1, §iso.17.6.3.2), but basically a container can hold elements of a type that has conventional copy or move operations. Many basic algorithms, such as copy(), find(), and sort() will work as long as the requirements for being a container element are met as well as the algorithm’s specific requirements (such as elements being ordered; §31.2.2.1).

Some violations of the rules for standard containers can be detected by a compiler, but others cannot and might then cause unexpected behavior. For example, an assignment operation that throws an exception might leave a partially copied element behind. That would be bad design (§13.6.1) and would violate the rules of the standard by not providing the basic guarantee (§13.2). An element in an invalid state could cause serious trouble later.

When copying objects is not reasonable, an alternative is to put pointers to objects into containers instead of the objects themselves. The most obvious example is polymorphic types (§3.2.2, §20.3.2). For example, we use vector<unique_ptr<Shape>> or vector<Shape*> rather than vector<Shape> to preserve polymorphic behavior.

31.2.2.1. Comparisons

Associative containers require that their elements can be ordered. So do many operations that can be applied to containers (e.g., sort() and merge()). By default, the < operator is used to define the order. If < is not suitable, the programmer must provide an alternative (§31.4.3, §33.4). The ordering criterion must define a strict weak ordering. Informally, this means that both less-than and equality (if defined) must be transitive. That is, for an ordering criterion cmp (think of it as “less than”) we require:

[1] Irreflexivity: cmp(x,x) is false.

[2] Antisymmetry: cmp(x,y) implies !cmp(y,x).

[3] Transitivity: If cmp(x,y) and cmp(y,z), then cmp(x,z).

[4] Transitivity of equivalence: Define equiv(x,y) to be !(cmp(x,y)||cmp(y,x)). If equiv(x,y) and equiv(y,z), then equiv(x,z).

The last rule is the one that allows us to define equality (x==y) as !(cmp(x,y)||cmp(y,x)) if we need ==.

Standard-library operations that require a comparison come in two versions. For example:

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template<typename Ran>
    void sort(Ran first, Ran last);          // use < for comparison
template<typename Ran, typename Cmp>
    void sort(Ran first, Ran last, Cmp cmp); // use cmp

The first version uses < and the second uses a user-supplied comparison cmp. For example, we might decide to sort fruit using a comparison that isn’t case sensitive. We do that by defining a function object (§3.4.3, §19.2.2) that does the comparison when invoked for a pair of strings:

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class Nocase {      // case-insensitive string compare
public:
     bool operator()(const string&, const string&) const;
};

bool Nocase::operator()(const string& x, const string& y) const
    // return true if x is lexicographically less than y, not taking case into account
{
    auto p = x.begin();
    auto q = y.begin();

    while (p!=x.end() && q!=y.end() && toupper(*p)==toupper(*q)) {
         ++p;
         ++q;
    }
    if (p == x.end()) return q != y.end();
    if (q == y.end()) return false;
    return toupper(*p) < toupper(*q);
}

We can call sort() using that comparison criterion. Consider:

fruit:
      apple pear Apple Pear lemon

Sorting using sort(fruit.begin(),fruit.end(),Nocase()) would yield something like

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fruit:
      Apple apple lemon Pear pear

Assuming a character set in which uppercase letters precede lowercase letters, plain sort(fruit.begin(),fruit.end()) would give:

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fruit:
      Apple Pear apple lemon pear

Beware that < on C-style strings (i.e., const char*s) compares pointer values (§7.4). Thus, associative containers will not work as most people would expect them to if C-style strings are used as keys. To make them work properly, a less-than operation that compares based on lexicographical order must be used. For example:

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struct Cstring_less {
     bool operator()(const char* p, const char* q) const { return strcmp(p,q)<0; }
};

map<char*,int,Cstring_less> m;          // map that uses strcmp() to compare const char* keys

31.2.2.2. Other Relational Operators

By default, containers and algorithms use < when they need to do a less-than comparison. When the default isn’t right, a programmer can supply a comparison criterion. However, no mechanism is provided for also passing an equality test. Instead, when a programmer supplies a comparison cmp, equality is tested using two comparisons. For example:

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if (x == y)                   // not done where the user supplied a comparison

if (!cmp(x,y) && !cmp(y,x))   // done where the user supplied a comparison cmp

This saves the user from having to provide an equality operation for every type used as the value type for an associative container or by an algorithm using a comparison. It may look expensive, but the library doesn’t check for equality very often, in about 50% of the cases only a single call of cmp() is needed, and often the compiler can optimize away the double check.

Using an equivalence relationship defined by less-than (by default <) rather than equality (by default ==) also has practical uses. For example, associative containers (§31.4.3) compare keys using an equivalence test !(cmp(x,y)||cmp(y,x)). This implies that equivalent keys need not be equal. For example, a multimap (§31.4.3) that uses case-insensitive comparison as its comparison criterion will consider the strings Last, last, lAst, laSt, and lasT equivalent, even though == for strings deems them different. This allows us to ignore differences we consider insignificant when sorting.

If equals (by default ==) always gives the same result as the equivalence test !(cmp(x,y)||cmp(y,x)) (by default cmp() is <), we say that we have a total order.

Given < and ==, we can easily construct the rest of the usual comparisons. The standard library defines them in the namespace std::rel_ops and presents them in <utility> (§35.5.3).

31.3. Operations Overview

The operations and types provided by the standard containers can be summarized like this:

An arrow indicates that a set of operations is provided for a container; it is not an inheritance operation. A question mark (?) indicates a simplification: I have included operations that are provided for only some of the containers. In particular:

• A multi* associative container or a set does not provide [] or at().

• A forward_list does not provide insert(), erase(), or emplace(); instead, it provides the *_after operations.

• A forward_list does not provide back(), push_back(), pop_back(), or emplace_back().

• A forward_list does not provide reverse_iterator, const_reverse_iterator, rbegin(), rend(), crbegin(), crend(), or size().

• A unordered_* associative container does not provide <, <=, >, or >=.

The [] and at() operations are replicated simply to reduce the number of arrows.

The bucket interface is described in §31.4.3.2.

Where meaningful, an access operation exists in two versions: one for const and one for non-const objects.

The standard-library operations have complexity guarantees:

“Front” operations refer to insertion and deletion before the first element. Similarly, “Back” operations refer to insertion and deletion after the last element, and “List” operations refer to insertion and deletion not necessarily at the ends of a container.

In the Iterators column, “Ran” means “random-access iterator,” “For” means “forward iterator,” and “Bi” means “bidirectional iterator” (§33.1.4).

Other entries are measures of the efficiency of the operations. A const entry means the operation takes an amount of time that does not depend on the number of elements in the container; another conventional notation for constant time is O(1). O(n) means the operation takes time proportional to the number of elements involved. A + suffix indicates that occasionally a significant extra cost is incurred. For example, inserting an element into a list has a fixed cost (so it is listed as const), whereas the same operation on a vector involves moving the elements following the insertion point (so it is listed as O(n)). Occasionally, all elements of a vector must be relocated (so I added a +). The “big O” notation is conventional. I added the + for the benefit of programmers who care about predictability in addition to average performance. A conventional term for O(n)+ is amortized linear time.

Naturally, if a constant is large, it can dwarf a small cost proportional to the number of elements. However, for large data structures const tends to mean “cheap,” O(n) to mean “expensive,” and O(log(n)) to mean “fairly cheap.” For even moderately large values of n, O(log(n)), where log is the binary logarithm, is far closer to constant time than to O(n). For example:

People who care about cost must take a closer look. In particular, they must understand what elements are counted to get the n. However, the message is clear: don’t mess with quadratic algorithms for larger values of n.

The measures of complexity and cost are upper bounds. The measures exist to give users some guidance as to what they can expect from implementations. Naturally, implementers will try to do better in important cases.

Note that the “Big O” complexity measures are asymptotic; that is, it could require a lot of elements before complexity differences matter. Other factors, such as the cost of an individual operation on an element, may dominate. For example, traversing a vector and a list both have complexity O(n). However, given modern machine architectures, getting to the next element through a link (in a list) can be very much more expensive than getting to the next element of a vector (where the elements are contiguous). Similarly, a linear algorithm may take significantly more or significantly less than ten times as long for ten times as many elements because of the details of memory and processor architecture. Don’t just trust your intuition about cost and your complexity measures; measure. Fortunately, the container interfaces are so similar that comparisons are easy to code.

The size() operation is constant time for all operations. Note that forward_list does not have size(), so if you want to know the number of elements, you must count them yourself (at the cost of O(n)). A forward_list is optimized for space and does not store its size or a pointer to its last element.

The string estimates are for longer strings. The “short string optimization” (§19.3.3) makes all operations of short strings (e.g., less than 14 characters) constant time.

The entries for stack and queue reflect the cost for the default implementation using a deque as the underlying container (§31.5.1, §31.5.2).

31.3.1. Member Types

A container defines a set of member types:

Every container and “almost container” provides most of these member types. However, they don’t provide types that are not meaningful. For example, array does not have an allocator_type and vector does not have a key_type.

31.3.2. Constructors, Destructor, and Assignments

Containers provide a variety of constructors and assignment operations. For a container called C (e.g., vector<double> or map<string,int>) we have:

Additional constructors for associative containers are described in §31.4.3.

Note that an assignment does not copy or move allocators. A target container gets a new set of elements but retains its old container, which it uses to allocate space for the new elements (if any). Allocators are described in §34.4.

Remember that a constructor or an element copy may throw an exception to indicate that it cannot perform its tasks.

The potential ambiguities for initializers are discussed in §11.3.3 and §17.3.4.1. For example:

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void use()
{
     vector<int> vi {1,3,5,7,9};    // vector initialized by five ints
     vector<string> vs(7);          // vector initialized by seven empty strings

     vector<int> vi2;
     vi2 = {2,4,6,8};               // assign sequence of four ints to vi2
     vi2.assign(&vi[1],&vi[4]);     // assign the sequence 3,5,7 to vi2

     vector<string> vs2;
     vs2 = {"The Eagle", "The Bird and Baby"};           // assign two strings to vs2
     vs2.assign("The Bear", "The Bull and Vet");         // run-time error
}

The error in the assignment to vs2 is that a pair of pointers are passed (not an initializer_list) and the two pointers do not point into the same array. Use () for size initializers and {} for every other kind of iterator.

Containers are often large, so we almost always pass them by reference. However, because they are resource handles (§31.2.1), we can return them (implicitly using move) efficiently. Similarly, we can move them as arguments when we don’t want aliasing. For example:

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void task(vector<int>&& v);

vector<int> user(vector<int>& large)
{
    vector<int> res;
    // ...
    task(move(large));  // transfer ownership of data to task()
    // ...
    return res;
}

31.3.3. Size and Capacity

The size is the number of elements in the container; the capacity is the number of elements that a container can hold before allocating more memory:

When changing the size or the capacity, the elements may be moved to new storage locations. That implies that iterators (and pointers and references) to elements may become invalid (i.e., point to the old element locations). For an example, see §31.4.1.1.

An iterator to an element of an associative container (e.g., a map) is only invalidated if the element to which it points is removed from the container (erase()d; §31.3.7). To contrast, an iterator to an element of a sequence container (e.g., a vector) is invalidated if the elements are relocated (e.g., by a resize(), reserve(), or push_back()) or if the element to which it points is moved within the container (e.g., by an erase() or insert() of an element with a lower index).

It is tempting to assume that reserve() improves performance, but the standard growth strategies for vector (§31.4.1.1) are so effective that performance is rarely a good reason to use reserve(). Instead, see reserve() as a way of increasing the predictability of performance and for avoiding invalidation of iterators.

31.3.4. Iterators

A container can be viewed as a sequence either in the order defined by the containers iterator or in the reverse order. For an associative container, the order is based on the containers comparison criterion (by default <):

The most common form of iteration over elements is to traverse a container from its beginning to its end. The simplest way of doing that is by a range-for (§9.5.1) which implicitly uses begin() and end(). For example:

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for (auto& x : v)          // implicit use of v.begin() and v.end()
      cout << x << '\n';

When we need to know the position of an element in a container or if we need to refer to more than one element at a time, we use iterators directly. In such cases, auto is useful to minimize source code size and eliminate opportunities for typos. For example, assuming a random-access iterator:

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for (auto p = v.begin(); p!=end(); ++p) {
      if (p!=v.begin() && *(p–1)==*p)
            cout << "duplicate " << *p << '\n';
}

When we don’t need to modify elements, cbegin() and cend() are appropriate. That is, I should have written:

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for (auto p = v.cbegin(); p!=cend(); ++p) {          // use const iterators
      if (p!=v.cbegin() && *(p–1)==*p)
            cout << "duplicate " << *p << '\n';
}

For most containers and most implementations, using begin() and end() repeatedly is not a performance problem, so I did not bother to complicate the code like this:

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auto beg = v.cbegin();
auto end = v.cend();

for (auto p = beg; p!=end; ++p) {
      if (p!=beg && *(p–1)==*p)
            cout << "duplicate " << *p << '\n';
}

31.3.5. Element Access

Some elements can be accessed directly:

Some implementations – especially debug versions – always do range checking, but you cannot portably rely on that for correctness or on the absence of checking for performance. Where such issues are important, examine your implementations.

The associative containers map and unordered_map have [] and at() that take arguments of the key type, rather than positions (§31.4.3).

31.3.6. Stack Operations

The standard vector, deque, and list (but not forward_list or the associative containers) provide efficient operations at the end (back) of their sequence of elements:

A c.push_back(x) moves or copies x into c, increasing c’s size by one. If we run out of memory or x’s copy constructor throws an exception, c.push_back(x) fails. A failed push_back() has no effect on the container: the strong guarantee is offered (§13.2).

Note that pop_back() does not return a value. Had it done so, a copy constructor throwing an exception could seriously complicate the implementation.

In addition, list and deque provide the equivalent operations on the start (front) of their sequences (§31.4.2). So does forward_list.

The push_back() is a perennial favorite for growing a container without preallocation or chance of overflow, but emplace_back() can be used similarly. For example:

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vector<complex<double>> vc;
for (double re,im; cin>>re>>im; )   // read two doubles
      vc.emplace_back(re,im);       // add complex<double>{re,im} at the end

31.3.7. List Operations

Containers provide list operations:

For insert() functions, the result, q, points to the last element inserted. For erase() functions, q points to the element that followed the last element erased.

For containers with contiguous allocation, such as vector and deque, inserting and erasing an element can cause elements to be moved. An iterator pointing to a moved element becomes invalid. An element is moved if its position is after the insertion/deletion point or if all elements are moved because the new size exceeds the previous capacity. For example:

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vector<int> v {4,3,5,1};
auto p = v.begin()+2;        // points to v[2], that is, the 5
v.push_back(6);              // p becomes invalid; v == {4,3,5,1,6}
p = v.begin()+2;             // points to v[2], that is, the 5
auto p2 = v.begin()+4;       // p2 points to v[4], that is, the 6
v.erase(v.begin()+3);        // v == {4,3,5,6}; p is still valid; p2 is invalid

Any operation that adds an element to a vector may cause every element to be reallocated (§13.6.4).

The emplace() operation is used when it is notationally awkward or potentially inefficient to first create an object and then copy (or move) it into a container. For example:

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void user(list<pair<string,double>>& lst)
{

     auto p = lst.begin();
     while (p!=lst.end()&& p–>first!="Denmark")              // find an insertion point
           /* do nothing */ ;
     p=lst.emplace(p,"England",7.5);                         // nice and terse
     p=lst.insert(p,make_pair("France",9.8));                // helper function
     p=lst.insert(p,pair<string,double>>{"Greece",3.14});    // verbose
}

The forward_list does not provide operations, such as insert(), that operate before an element identified by an iterator. Such an operation could not be implemented because there is no general way of finding the previous element in a forward_list given only an iterator. Instead, forward_iterator provides operations, such as insert_after(), that operate after an element identified by an iterator. Similarly, unordered containers use emplace_hint() to provide a hint rather than “plain” emplace().

31.3.8. Other Operations

Containers can be compared and swapped:

When comparing containers with an operator (e.g., <=), the elements are compared using the equivalent element operator generated from == or < (e.g., a>b is done using !(b<a)).

The swap() operations exchange both elements and allocators.

31.4. Containers

This section goes into more detail about:

• vector, the default container (§31.4.1)

• The linked lists: list and forward_list (§31.4.2)

• The associative containers, such as map and unordered_map (§31.4.3)

31.4.1. vector

The STL vector is the default container. Use it unless you have a good reason not to. If your suggested alternative is a list or a built-in array, think twice.

§31.3 describes the operations on vector and implicitly contrasts them with what is provided for other containers. However, given the importance of vector, this section takes a second look with more emphasis on how the operations are provided.

The vector’s template argument and member types are defined like this:

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template<typename T, typename Allocator = allocator<T>>
class vector {
public:
     using reference = value_type&;
     using const_reference = const value_type&;
     using iterator = /* implementation-defined */;
     using const_iterator = /* implementation-defined */;
     using size_type = /* implementation-defined */;
     using difference_type = /* implementation-defined */;
     using value_type = T;
     using allocator_type = Allocator;
     using pointer = typename allocator_traits<Allocator>::pointer;
     using const_pointer = typename allocator_traits<Allocator>::const_pointer;
     using reverse_iterator = std::reverse_iterator<iterator>;
     using const_reverse_iterator = std::reverse_iterator<const_iterator>;

     // ...
};

31.4.1.1. vector and Growth

Consider the layout of a vector object (as described in §13.6):

The use of both a size (number of elements) and a capacity (the number of available slots for elements without reallocation) makes growth through push_back() reasonably efficient: there is not an allocation operation each time we add an element, but only every time we exceed capacity (§13.6). The standard does not specify by how much capacity is increased when it is exceeded, but adding half the size is common. I used to be careful about using reserve() when I was reading into a vector. I was surprised to find that for essentially all of my uses, calling reserve() did not measurably affect performance. The default growth strategy worked just as well as my estimates, so I stopped trying to improve performance using reserve(). Instead, I use it to increase predictability of reallocation delays and to prevent invalidation of pointers and iterators.

The notion of capacity allows for iterators into a vector to be valid unless a reallocation actually happens. Consider reading letters into a buffer and keeping track of word boundaries:

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vector<char> chars;           // input "buffer" for characters
constexpr int max = 20000;
chars.reserve(max);
vector<char*> words;          // pointers to start of words

bool in_word = false;
for (char c; cin.get(c)) {
      if (isalpha(c)) {
             if (!in_word) {          // found beginning of word
                    in_word = true;
                    chars.push_back(0);   // end of previous word
                    chars.push_back(c);
                    words.push_back(&chars.back());
             }
             else
                    chars.push_back(c);
      }
      else
             in_word = false;
}
if (in_word)
      chars.push_back(0);      // terminate last word

if (max<chars.size()) {  // oops: chars grew beyond capacity; the words are invalid
      // ...
}
chars.shrink_to_fit();   // release any surplus capacity

Had I not used reserve() here, the pointers in words would have been invalidated if chars.push_back() caused a relocation. By “invalidated,” I mean that any use of those pointers would be undefined behavior. They may – or may not – point to an element, but almost certainly not to the elements they pointed to before the relocation.

The ability to grow a vector using push_back() and related operations implies that low-level C-style use of malloc() and realloc() (§43.5) is as unnecessary as it is tedious and error-prone.

31.4.1.2. vector and Nesting

A vector (and similar contiguously allocated data structures) has three major advantages compared to other data structures:

• The elements of a vector are compactly stored: there is no per-element memory overhead. The amount of memory consumed by a vec of type vector<X> is roughly size of (vector<X>)+vec.size()*size of (X). The size of (vector<X>) is about 12 bytes, which is insignificant for larger vectors.

• Traversal of a vector is very fast. To get to the next element, the code does not have to indirect through a pointer, and modern machines are optimized for consecutive access through a vector-like structure. This makes linear scans of vector elements, as in find() and copy(), close to optimal.

• vector supports simple and efficient random access. This is what makes many algorithms on vectors, such as sort() and binary_search(), efficient.

It is easy to underestimate these benefits. For example, a doubly-linked list, such as list, usually incurs a four-words-per-element memory overhead (two links plus a free-store allocation header), and traversing it can easily be an order of magnitude more expensive than traversing a vector containing equivalent data. The effect can be so spectacular and surprising that I suggest you test it yourself [Stroustrup,2012a].

The benefits of compactness and efficiency of access can be unintentionally compromised. Consider how to represent a two-dimensional matrix. There are two obvious alternatives:

• A vector of vectors: vector<vector<double>> accessed by C-style double subscripting: m[i][j]

• A specific matrix type, Matrix<2,double> (Chapter 29), that stores elements contiguously (e.g., in a vector<double>) and computes locations in that vector from a pair of indices: m(i,j)

The memory layout for a 3-by-4 vector<vector<double>> looks like this:

The memory layout for Matrix<2,double> looks like this:

To construct the vector<vector<double>>, we need four constructor calls with four free-store allocation operations. To access an element, we need to do a double indirection.

To construct the Matrix<2,double>, we need one constructor call with one free-store allocation. To access an element, we need a single indirection.

Once we reach an element of a row, we don’t need a further indirection to access its successor, so access to the vector<vector<double>> is not always twice as costly as access to Matrix<2,double>. However, for algorithms that require high performance, the allocation, deallocation, and access costs implied by the linked structure of vector<vector<double>> could be a problem.

The vector<vector<double>> solution implies the possiblity of the row having different sizes. There are cases where that is an advantage, but more often it is simply an opportunity for errors and a burden for testing.

The problems and overhead get worse when we need higher dimensions: compare the number of added indirections and allocations for a vector<vector<vector<double>>> and a Matrix<3,double>.

In summary, I note that the importance of compactness of data structures is often underestimated or compromised. The advantages are logical as well as performance related. Combine this with a tendency to overuse pointers and new and we have a widespread problem. For example, consider the development complexities, run-time costs, memory costs, and opportunities for errors in an implementation of a two-dimensional structure when the rows are implemented as independent objects on the free store: vector<vector<double>*>.

31.4.1.3. vector and Arrays

A vector is a resource handle. This is what allows it to be resized and enables efficient move semantics. However, that occasionally puts it at a disadvantage compared to data structures (such as built-in arrays and array) that do not rely on storing elements separately from a handle. Keeping a sequence of elements on the stack or in another object can give a performance advantage, just as it can be a disadvantage.

A vector deals with properly initialized objects. This is what allows us to use them simply and rely on proper destruction of elements. However, that occasionally puts it at a disadvantage compared to data structures (such as built-in arrays and array) that allow uninitialized elements.

As an example, we need not initialize array elements before reading into them:

void read()
{
     array<int,MAX]> a;
     for (auto& x : a)
           cin.get(&x);
}

For vector, we might use emplace_back() to achieve a similar effect (without having to specify a MAX).

31.4.1.4. vector and string

A vector<char> is a resizable, contiguous sequence of chars, and so is a string. So how do we choose between the two?

A vector is a general mechanism for storing values. It makes no assumptions about the relationships among the values stored in it. To a vector<char>, the string Hello, World! is just a sequence of 13 elements of type char. Sorting them into !,HWdellloor (preceded by a space) makes sense. To contrast, a string is intended to hold character sequences. The relationships among the characters are assumed to be important. So, for example, we rarely sort the characters in a string because that destroys meaning. Some string operations reflect that (e.g., c_str(), >>, and find() “know” that C-style strings are zero-terminated). The implementations of string reflect assumptions about the way we use strings. For example, the short-string optimization (§19.3.3) would be a pure pessimization if it wasn’t for the fact that we use many short strings, so that minimizing free-store use becomes worthwhile.

Should there be a “short-vector optimization”? I suspect not, but it would require a massive empirical study to be sure.

31.4.2. Lists

The STL provides two linked-list types:

• list: a doubly-linked list

• forward_list: a singly-linked list

A list is a sequence optimized for insertion and deletion of elements. When you insert into a list or delete an element from a list, the locations of other elements of the list are not affected. In particular, iterators referring to other elements are not affected.

Compared to vector, subscripting could be painfully slow, so subscripting is not provided for lists. If necessary, use advance() and similar operations to navigate lists (§33.1.4). A list can be traversed using iterators: list provides bidirectional iterators (§33.1.2) and forward_list provides forward iterators (hence the name of that type of list).

By default, list elements are individually allocated in memory and include predecessor and successor pointers (§11.2.2). Compared to a vector, a list uses more memory per element (usually at least four words more per element), and traversals (iteration) are significantly slower because they involve indirection through pointers rather than simple consecutive access.

A forward_list is a singly-linked list. Think of it as a data structure optimized for empty or very short lists that you typically traverse starting from the beginning. For compactness, forward_list doesn’t even provide a size(); an empty forward_list takes up just one word of memory. If you need to know the number of elements of a forward_list, just count them. If there are enough elements to make counting them expensive, maybe you should use a different container.

With the exception of subscripting, capacity management, and size() for forward_list, the STL lists provide the member types and operations offered by vector (§31.4). In addition, list and forward_list provide specific list member functions:

As opposed to the general remove() and unique() algorithms (§32.5), the member algorithms really do affect the size of a list. For example:

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void use()
{
     list<int> lst {2,3,2,3,5};
     lst.remove(3);                   // lst is now {2,2,5}
     lst.unique();                    // lst is now {2,5}
     cout << lst.size() << '\n';      // writes 2
}

The merge() algorithm is stable; that is, equivalent elements keep their relative order.

A splice() operation does not copy element values and does not invalidate iterators to elements. For example:

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list<int> lst1 {1,2,3};
list<int> lst2 {5,6,7};

auto p = lst1.begin();
++p;                     // p points to 2

auto q = lst2.begin();
++q;                     // q points to 6

lst1.splice(p,lst2);     // lst1 is now {1,5,6,7,2,3}; lst2 is now {}
                         // p still points to 2 and q still points to 6

A forward_list cannot access the element before one pointed to by an iterator (it does not have a predecessor link), so its emplace(), insert(), erase(), and splice() operations operate on the position after an iterator:

These list operations are all stable; that is, they preserve the relative order of elements that have equivalent values.

31.4.3. Associative Containers

Associative containers provide lookup based on keys. They come in two variants:

• Ordered associative containers do lookup based on an ordering criterion, by default < (less than). They are implemented as balanced binary trees, usually red-black trees.

• Unordered associative containers do lookup based on a hash function. They are implemented as hash tables with linked overflow.

Both come as

• maps: sequences of {key,value} pairs

• sets: maps without values (or you could say that the key is also the value)

Finally, maps and sets, whether ordered or unordered, come in two variants:

• “Plain” sets or maps with a unique entry for each key

• “Multi” sets or maps for which multiple entries can exist for each key

The name of an associate container indicates its place in this 3-dimensional space: {set|map, plain|unordered, plain|multi}. “Plain” is never spelled out, so the associative containers are:

Their template arguments are described in §31.4.

Internally, a map and an unordered_map are very different. See §31.2.1 for graphical representations. In particular, map uses its comparison criterion (typically <) on a key to search through a balanced tree (an O(log(n)) operation), whereas unordered_map applies a hash function on a key to find a slot in a hash table (an O(1) operation for a good hash function).

31.4.3.1. Ordered Associative Containers

Here are the template arguments and member types for map:

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template<typename Key,
    typename T,
    typename Compare = less<Key>,
    typename Allocator = allocator<pair<const Key, T>>>
class map {
public:
    using key_type = Key;
    using mapped_type = T;
    using value_type = pair<const Key, T>;
    using key_compare = Compare;
    using allocator_type = Allocator;
    using reference = value_type&;
    using const_reference = const value_type&;
    using iterator = /* implementation-defined */ ;
    using const_iterator = /* implementation-defined */ ;
    using size_type = /* implementation-defined */ ;
    using difference_type = /* implementation-defined */ ;
    using pointer = typename allocator_traits<Allocator>::pointer;
    using const_pointer = typename allocator_traits<Allocator>::const_pointer;
    using reverse_iterator = std::reverse_iterator<iterator>;
    using const_reverse_iterator = std::reverse_iterator<const_iterator>;

    class value_compare { /* operator()(k1,k2) does a key_compare()(k1,k2) */ };
    // ...
};

In addition to the constructors mentioned in §31.3.2, the associative containers have constructors allowing a programmer to supply a comparator:

For example:

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map<string,pair<Coordinate,Coordinate>> locations
    {
         {"Copenhagen",{"55:40N","12:34E"}},
         {"Rome",{"41:54N","12:30E"}},
         {"New York",{"40:40N","73:56W"}
    };

The associative containers offer a variety of insertion and lookup operations:

Operations specific to unordered containers are presented in §31.4.3.5.

If a key, k, is not found by a subscript operation, m[k], a default value is inserted. For example:

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map<string,string> dictionary;

dictionary["sea"]="large body of water";    // insert or assign to element

cout << dictionary["seal"];                 // read value

If seal is not in the dictionary, nothing is printed: the empty string was entered as the value for seal and returned as the result of the lookup.

If that is not the desired behavior, we can use find() and insert() directly:

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auto q = dictionary.find("seal");        // lookup; don't insert

if (q==dictionary.end()) {
      cout << "entry not found";
      dictionary.insert(make_pair("seal","eats fish"));
}
else
      cout q–>second;

In fact, [] is little more than a convenient notation for insert(). The result of m[k] is equivalent to the result of (*(m.insert(make_pair(k,V{})).first)).second, where V is the mapped type.

The insert(make_pair()) notation is rather verbose. Instead, we could use emplace():

dictionary.emplace("sea cow","extinct");

Depending on the quality of the optimizer, this may also be more efficient.

If you try to insert a value into a map and there already is an element with its key, the map is unchanged. If you want to have more than one value for a single key, use a multimap.

The first iterator of the pair (§34.2.4.1) returned by equal_range() is lower_bound() and the second upper_bound(). You can print the value of all elements with the key "apple" in a multimap<string,int> like this:

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multimap<string,int> mm {{"apple",2}, { "pear",2}, {"apple",7}, {"orange",2}, {"apple",9}};

const string k {"apple"};
auto pp = mm.equal_range(k);
if (pp.first==pp.second)
      cout << "no element with value '" << k << "'\n";
else {
      cout << "elements with value '" << k << "':\n";
      for (auto p=pp.first; p!=pp.second; ++p)
            cout << p–>second << ' ';
}

This prints 2 7 9.

I could equivalently have written:

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auto pp = make_pair(m.lower_bound(),m.upper_bound());
// ...

However, that would imply an extra traversal of the map. The equal_range(), lower_bound(), and upper_bound() are also provided for sorted sequences (§32.6).

I tend to think of a set as a map with no separate value_type. For a set, the value_type is also the key_type. Consider:

struct Record {
     string label;
     int value;
};

To have a set<Record>, we need to provide a comparison function. For example:

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bool operator<(const Record& a, const Record& b)
{
     return a.label<b.label;
}

Given that, we can write:

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set<Record> mr {{"duck",10}, {"pork",12}};

void read_test()
{
     for (auto& r : mr) {
          cout << '{' << r.label << ':' << r.value << '}';
     }
     cout << endl;
}

The key of an element in an associative container is immutable (§iso.23.2.4). Therefore, we cannot change the values of a set. We cannot even change a member of an element that takes no part in the comparison. For example:

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void modify_test()
{
     for (auto& r : mr)
          ++r.value;     // error: set elements are immutable
}

If you need to modify an element, use a map. Don’t try to modify a key: if you were to succeed, the underlying mechanism for finding elements would break.

31.4.3.2. Unordered Associative Containers

The unordered associative containers (unordered_map, unordered_set, unordered_multimap, unordered_multiset) are hash tables. For simple uses, there are few differences from (ordered) containers because the associative containers share most operations (§31.4.3.1). For example:

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unordered_map<string,int> score1 {
    {"andy", 7}, {"al",9}, {"bill",–3}, {"barbara",12}
};

map<string,int> score2 {
    {"andy", 7}, {"al",9}, {"bill",–3}, {"barbara",12}
};

template<typename X, typename Y>
ostream& operator<<(ostream& os, pair<X,Y>& p)
{
    return os << '{' << p.first << ',' << p.second << '}';
}
void user()
{
    cout <<"unordered: ";
    for (const auto& x : score1)
          cout << x << ", ";

    cout << "\nordered: ";
    for (const auto& x : score2)
          cout << x << ", ";
}

The visible difference is that iteration through a map is ordered and for an unordered_map it is not:

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unordered: {andy,7}, {al,9}, {bill,–3}, {barbara,12},
ordered: {al,9}, {andy, 7}, {barbara,12}, {bill,–3},

Iteration over an unordered_map depends on the order of insertion, the hash function, and the load factor. In particular, there is no guarantee that elements are printed in the order of their insertion.

31.4.3.3. Constructing unordered_maps

The unordered_map has a lot of template arguments and member type aliases to match:

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template<typename Key,
         typename T,
         typename Hash = hash<Key>,
         typename Pred = std::equal_to<Key>,
         typename Allocator = std::allocator<std::pair<const Key, T>>>
class unordered_map {
public:
     using key_type = Key;
     using value_type = std::pair<const Key, T>;
     using mapped_type = T;
     using hasher = Hash;
     using key_equal = Pred;
     using allocator_type = Allocator;
     using pointer = typename allocator_traits<Allocator>::pointer;
     using const_pointer= typename allocator_traits<Allocator>::const_pointer;
     using reference = value_type&;
     using const_reference = const value_type&
     using size_type = /* implementation-defined */;
     using difference_type = /* implementation-defined */;
     using iterator = /* implementation-defined */;
     using const_iterator = /* implementation-defined */;
     using local_iterator = /* implementation-defined */;
     using const_local_iterator = /* implementation-defined */;

     // ...
};

By default, an unordered_map<X> uses hash<X> for hashing and equal_to<X> to compare keys.

The default equal_to<X> (§33.4) simply compares X values using ==.

The general (primary) template hash doesn’t have a definition. It is up to users of a type X to define hash<X> if needed. For common types, such as string, standard hash specializations are provided, so the user need not provide them:

A hash function (e.g., a specialization of hash for a type T or a pointer to function) must be callable with an argument of type T and return a size_t (§iso.17.6.3.4). Two calls of a hash function for the same value must give the same result, and ideally such results are uniformly distributed over the set of size_t values so as to minimize the chances that h(x)==h(y) if x!=y.

There is a potentially bewildering set of combinations of template argument types, constructors, and defaults for an unordered container. Fortunately, there is a pattern:

Here, n is an element count for an otherwise empty unordered_map.

Here, we get the initial elements from a sequence [b:e). The number of elements will be then number of elements in [b:e), distance(b,e).

Here, we get the initial elements from a sequence from a {}-delimited initializer list of elements. The number of elements in the unordered_map will be the number of elements in the initializer list.

Finally, unordered_map has copy and move constructors, and also equivalent constructors that supply allocators:

Be careful when constructing an unordered_map with one or two arguments. There are many possible combinations of types, and mistakes can lead to strange error messages. For example:

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map<string,int> m {My_comparator};             // OK
unordered_map<string,int> um {My_hasher};      // error

A single constructor argument must be another unordered_map (for a copy or move constructor), a bucket count, or an allocator. Try something like:

unordered_map<string,int> um {100,My_hasher};  // OK

31.4.3.4. Hash and Equality Functions

Naturally, a user can define a hash function. In fact, there are several ways to do that. Different techniques serve different needs. Here, I present several versions, starting with the most explicit and ending with the simplest. Consider a simple Record type:

struct Record {
     string name;
     int val;
};

I can define Record hash and equality operations like this:

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struct Nocase_hash {
     int d = 1;    // shift code d number of bits in each iteration
     size_t operator()(const Record& r) const
     {
          size_t h = 0;
          for (auto x : r.name) {
                h <<= d;
                h ^= toupper(x);
          }

          return h;
     }
};

struct Nocase_equal {
     bool operator()(const Record& r,const Record& r2) const
     {
          if (r.name.size()!=r2.name.size()) return false;
          for (int i = 0; i<r.name.size(); ++i)
                if (toupper(r.name[i])!=toupper(r2.name[i]))
                      return false;
          return true;
     }
};

Given that, I can define and use an unordered_set of Records:

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unordered_set<Record,Nocase_hash,Nocase_equal> m {
    { {"andy", 7}, {"al",9}, {"bill",–3}, {"barbara",12} },
    Nocase_hash{2},
    Nocase_equal{}
};

for (auto r : m)
      cout << "{" << r.name << ',' << r.val << "}\n";

If, as is most common, I wanted to use the default values for my hash and equality functions, I could do that by simply not mentioning them as constructor arguments. By default, the unordered_set uses the default versions:

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unordered_set<Record,Nocase_hash,Nocase_equal> m {
    {"andy", 7}, {"al",9}, {"bill",–3}, {"barbara",12}
    // use Nocase_hash{} and Nocase_equal{}
};

Often, the easiest way of writing a hash function is to use the standard-library hash functions provided as specializations of hash (§31.4.3.2). For example:

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size_t hf(const Record& r) { return hash<string>()(r.name)^hash<int>()(r.val); };

bool eq (const Record& r, const Record& r2) { return r.name==r2.name && r.val==r2.val; };

Combining hash values using exclusive OR (^) preserves their distributions over the set of values of type size_t (§3.4.5, §10.3.1).

Given this hash function and equality function, we can define an unordered_set:

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unordered_set<Record,decltype(&hf),decltype(&eq)> m {
    { {"andy", 7}, {"al",9}, {"bill",–3}, {"barbara",12} },
    hf,
    eq
};

for (auto r : m)
      cout << "{" << r.name << ',' << r.val << "}\n";
}

I used decltype to avoid having to explicitly repeat the types of hf and eq.

If we don’t have an initializer list handy, we can give an initial size instead:

unordered_set<Record,decltype(&hf),decltype(&eq)> m {10,hf,eq};

That also makes it a bit easier to focus on the hash and equality operations.

If we wanted to avoid separating the definitions of hf and eq from their point of use, we could try lambdas:

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unordered_set<Record,                                  // value type
        function<size_t(const Record&)>,               // hash type
        function<bool(const Record&,const Record&)>    // equal type
    > m { 10,
     [](const Record& r) { return hash<string>{}(r.name)^hash<int>{}(r.val); },
     [](const Record& r, const Record& r2) { return r.name==r2.name && r.val==r2.val; }
    };

The point about using (named or unnamed) lambdas instead of functions is that they can be defined locally in a function, next to their use.

However, here, function may incur overhead that I would prefer to avoid if the unordered_set was heavily used. Also, I consider that version messy and prefer to name the lambdas:

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auto hf = [](const Record& r) { return hash<string>()(r.name)^hash<int>()(r.val); };
auto eq = [](const Record& r, const Record& r2) { return r.name==r2.name && r.val==r2.val; };

unordered_set<Record,decltype(hf),decltype(eq)> m {10,hf,eq};

Finally, we may prefer to define the meaning of hash and equality once for all unordered containers of Record by specializing the standard-library hash and equal_to templates used by unordered_map:

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namespace std {
   template<>
   struct hash<Record>{
        size_t operator()(const Record &r) const
        {
             return hash<string>{}(r.name)^hash<int>{}(r.val);
        }
   };
   template<>
   struct equal_to<Record> {
        bool operator()(const Record& r, const Record& r2) const
        {
             return r.name==r2.name && r.val==r2.val;
        }
   };
}
unordered_set<Record> m1;
unordered_set<Record> m2;

The default hash and hashes obtained from it by using exclusive-or are often pretty good. Don’t rush to use homemade hash functions without experimentation.

31.4.3.5. Load and Buckets

Significant parts of the implementation of an unordered container are made visible to the programmer. Keys with the same hash value are said to be “in the same bucket” (see §31.2.1). A programmer can examine and set the size of the hash table (known as “the number of buckets”):

The load factor of an unordered associative container is simply the fraction of the capacity that has been used. For example, if the capacity() is 100 elements and the size() is 30, the load_factor() is 0.3.

Note that setting the max_load_factor, calling rehash(), or calling reserve() can be very expensive operations (worst case O(n*n)) because they can – and in realistic scenarios typically do – cause rehashing of all elements. These functions are used to ensure that rehashing takes place at relatively convenient times in a program’s execution. For example:

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unordered_set<Record,[](const Record& r) { return hash(r.name); }> people;
// ...
constexpr int expected = 1000000;    // expected maximum number of elements
people.max_load_factor(0.7);         // at most 70% full
people.reserve(expected);            // about 1,430,000 buckets

You need to experiment to find a suitable load factor for a given set of elements and a particular hash function, but 70% (0.7) is often a good choice.

Use of an n for which c.max_bucket_count()<=n as an index into a bucket is undefined (and probably disastrous).

One use for the bucket interface is to allow experimentation with hash functions: a poor hash function will lead to large bucket_count()s for some key values. That is, it will lead to many keys being mapped to the same hash value.

31.5. Container Adaptors

A container adaptor provides a different (typically restricted) interface to a container. Container adaptors are intended to be used only through their specialized interfaces. In particular, the STL container adaptors do not offer direct access to their underlying container. They do not offer iterators or subscripting.

The techniques used to create a container adaptor from a container are generally useful for nonintrusively adapting the interface of a class to the needs of its users.

31.5.1. stack

The stack container adaptor is defined in <stack>. It can be described by a partial implementation:

Click here to view code image

template<typename T, typename C = deque<T>>
class stack {     // §iso.23.6.5.2
public:
     using value_type = typename C::value_type;
     using reference = typename C::reference;
     using const_reference = typename C::const_reference;
     using size_type = typename C::size_type;
     using container_type = C;
public:
     explicit stack(const C&); // copy from container
     explicit stack(C&& = C{});     // move from container

     // default copy, move, assignment, destructor

     template<typename A>
         explicit stack(const A& a);             // default container, allocator a
     template<typename A>
         stack(const C& c, const A& a);          // elements from c, allocator a
     template<typename A>
         stack(C&&, const A&);
     template<typename A>
         stack(const stack&, const A&);
     template<typename A>
         stack(stack&&, const A&);

     bool empty() const { return c.empty(); }
     size_type size() const { return c.size(); }
     reference top() { return c.back(); }
     const_reference top() const { return c.back(); }
     void push(const value_type& x) { c.push_back(x); }
     void push(value_type&& x) { c.push_back(std::move(x)); }
     void pop() { c.pop_back(); }     // pop the last element

     template<typename ... Args>
     void emplace(Args&&... args)
     {
          c.emplace_back(std::forward<Args>(args)...);
     }

     void swap(stack& s) noexcept(noexcept(swap(c, s.c)))
     {
          using std::swap;  // be sure to use the standard swap()
          swap(c,s.c);
     }
protected:
     C c;
};

That is, a stack is an interface to a container of the type passed to it as a template argument. A stack eliminates the non-stack operations on its container from the interface, and provides the conventional names: top(), push(), and pop().

In addition, stack provides the usual comparison operators (==, <, etc.) and a nonmember swap().

By default, a stack makes a deque to hold its elements, but any sequence that provides back(), push_back(), and pop_back() can be used. For example:

Click here to view code image

stack<char> s1;                // uses a deque<char> to store elements
stack<int,vector<int>> s2;     // uses a vector<int> to store elements

Often, vector is faster than deque and uses less memory.

Elements are added to a stack using push_back() on the underlying container. Consequently, a stack cannot “overflow” as long as there is memory available on the machine for the container to acquire. On the other hand, a stack can underflow:

Click here to view code image

void f()
{
     stack<int> s;
     s.push(2);
     if (s.empty()) {         // underflow is preventable
           // don't pop
     }
     else {                   // but not impossible
          s.pop();     // fine: s.size() becomes 0
          s.pop();     // undefined effect, probably bad
     }
}

We do not pop() an element to use it. Instead, the top() is accessed and then pop()ed when it is no longer needed. This is not too inconvenient, can be more efficient when a pop() is not necessary, and greatly simplifies the implementation of exception guarantees. For example:

Click here to view code image

void f(stack<char>& s)
{
     if (s.top()=='c') s.pop();   // optionally remove optional initial 'c'
     // ...
}

By default, a stack relies on the allocator from its underlying container. If that’s not enough, there are a handful of constructors for supplying another.

31.5.2. queue

Defined in <queue>, a queue is an interface to a container that allows the insertion of elements at the back() and the extraction of elements at the front():

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template<typename T, typename C = deque<T> >
class queue {     //§iso.23.6.3.1
     // ... like stack ...
     void pop() { c.pop_front(); }   // pop the first element
};

Queues seem to pop up somewhere in every system. One might define a server for a simple message-based system like this:

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void server(queue<Message>& q, mutex& m)
{
     while (!q.empty()) {
          Message mess;
          {   lock_guard<mutex> lck(m);   // lock while extracting message
              if (q.empty()) return;            // somebody else got the message
              mess = q.front();
              q.pop();
          }
          // serve request
     }
}

31.5.3. priority_queue

A priority_queue is a queue in which each element is given a priority that controls the order in which the elements get to be the top(). The declaration of priority_queue is much like the declaration of queue with additions to deal with a comparison object and a couple of constructors initializing from a sequence:

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template<typename T, typename C = vector<T>, typename Cmp = less<typename C::value_type>>
class priority_queue {     // §iso.23.6.4
protected:
     C c;
     Cmp comp;
public:
     priority_queue(const Cmp& x, const C&);
     explicit priority_queue(const Cmp& x = Cmp{}, C&& = C{});
     template<typename In>
         priority_queue(In b, In e, const Cmp& x, const C& c);   // insert [b:e) into c
     // ...
};

The declaration of priority_queue is found in <queue>.

By default, the priority_queue simply compares elements using the < operator, and top() returns the largest element:

Click here to view code image

struct Message {
     int priority;
     bool operator<(const Message& x) const { return priority < x.priority; }
     // ...
};

void server(priority_queue<Message>& q, mutex& m)
{
     while (!q.empty()) {
          Message mess;
          {   lock_guard<mutex> lck(m);   // hold lock while extracting message
              if (q.empty()) return;      // somebody else got the message
              mess = q.top();
              q.pop();
          }
          // serve highest priority request
     }
}

This differs from the queue version (§31.5.2) in that Messages with higher priority will get served first. The order in which elements with equal priority come to the head of the queue is not defined. Two elements are considered of equal priority if neither has higher priority than the other (§31.2.2.1).

Keeping elements in order isn’t free, but it needn’t be expensive either. One useful way of implementing a priority_queue is to use a tree structure to keep track of the relative positions of elements. This gives an O(log(n)) cost of both push() and pop(). A priority_queue is almost certainly implemented using a heap (§32.6.4).

31.6. Advice

[1] An STL container defines a sequence; §31.2.

[2] Use vector as your default container; §31.2, §31.4.

[3] Insertion operators, such as insert() and push_back() are often more efficient on a vector than on a list; §31.2, §31.4.1.1.

[4] Use forward_list for sequences that are usually empty; §31.2, §31.4.2.

[5] When it comes to performance, don’t trust your intuition: measure; §31.3.

[6] Don’t blindly trust asymptotic complexity measures; some sequences are short and the cost of individual operations can vary dramatically; §31.3.

[7] STL containers are resource handles; §31.2.1.

[8] A map is usually implemented as a red-black tree; §31.2.1, §31.4.3.

[9] An unordered_map is a hash table; §31.2.1, §31.4.3.2.

[10] To be an element type for a STL container, a type must provide copy or move operations; §31.2.2.

[11] Use containers of pointers or smart pointers when you need to preserve polymorphic behavior; §31.2.2.

[12] Comparison operations should implement a strict weak order; §31.2.2.1.

[13] Pass a container by reference and return a container by value; §31.3.2.

[14] For a container, use the ()-initializer syntax for sizes and the {}-initializer syntax for lists of elements; §31.3.2.

[15] For simple traversals of a container, use a range-for loop or a begin/end pair of iterators; §31.3.4.

[16] Use const iterators where you don’t need to modify the elements of a container; §31.3.4.

[17] Use auto to avoid verbosity and typos when you use iterators; §31.3.4.

[18] Use reserve() to avoid invalidating pointers and iterators to elements; §31.3.3, §31.4.1.

[19] Don’t assume performance benefits from reserve() without measurement; §31.3.3.

[20] Use push_back() or resize() on a container rather than realloc() on an array; §31.3.3, §31.4.1.1.

[21] Don’t use iterators into a resized vector or deque; §31.3.3.

[22] When necessary, use reserve() to make performance predictable; §31.3.3.

[23] Do not assume that [] range checks; §31.2.2.

[24] Use at() when you need guaranteed range checks; §31.2.2.

[25] Use emplace() for notational convenience; §31.3.7.

[26] Prefer compact and contiguous data structures; §31.4.1.2.

[27] Use emplace() to avoid having to pre-initialize elements; §31.4.1.3.

[28] A list is relatively expensive to traverse; §31.4.2.

[29] A list usually has a four-word-per-element memory overhead; §31.4.2.

[30] The sequence of an ordered container is defined by its comparison object (by default <); §31.4.3.1.

[31] The sequence of an unordered container (a hashed container) is not predictably ordered; §31.4.3.2.

[32] Use unordered containers if you need fast lookup for large amounts of data; §31.3.

[33] Use unordered containers for element types with no natural order (e.g., no reasonable <); §31.4.3.

[34] Use ordered associative containers (e.g., map and set) if you need to iterate over their elements in order; §31.4.3.2.

[35] Experiment to check that you have an acceptable hash function; §31.4.3.4.

[36] Hash function obtained by combining standard hash functions for elements using exclusive or are often good; §31.4.3.4.

[37] 0.7 is often a reasonable load factor; §31.4.3.5.

[38] You can provide alternative interfaces for containers; §31.5.

[39] The STL adaptors do not offer direct access to their underlying containers; §31.5.

32. STL Algorithms

Form is liberating.

– Engineer’s proverb

• Introduction

• Algorithms

Sequences; Policy Arguments; Complexity

• Nonmodifying Sequence Algorithms

for_each(); Sequence Predicates; count(); find(); equal() and mismatch(); search()

• Modifying Sequence Algorithms

copy(); unique(); remove() and replace(); rotate(), random_shuffle(), and partition(); Permutations; fill(); swap()

• Sorting and Searching

Binary Search; merge(); Set Algorithms; Heaps; lexcographical_compare()

• Min and Max

• Advice

32.1. Introduction

This chapter presents the STL algorithms. The STL consists of the iterator, container, algorithm, and function object parts of the standard library. The rest of the STL is presented in Chapter 31 and Chapter 33.

32.2. Algorithms

There are about 80 standard algorithms defined in <algorithm>. They operate on sequences defined by a pair of iterators (for inputs) or a single iterator (for outputs). When copying, comparing, etc., two sequences, the first is represented by a pair of iterators, [b:e), but the second by just a single iterator, b2, which is considered the start of a sequence holding sufficient elements for the algorithm, for example, as many elements as the first sequence: [b2:b2+(e–b)). Some algorithms, such as sort(), require random-access iterators, whereas many, such as find(), only read their elements in order so that they can make do with a forward iterator. Many algorithms follow the usual convention of returning the end of a sequence to represent “not found” (§4.5). I don’t mention that for each algorithm.

Algorithms, both the standard-library algorithms and the users’ own ones, are important:

• Each names a specific operation, documents an interface, and specifies semantics.

• Each can be widely used and known by many programmers.

For correctness, maintainability, and performance, these can be immense advantages compared to “random code” with less well-specified functions and dependencies. If you find yourself writing a piece of code with several loops, local variables that don’t seem to relate to each other, or complicated control structures, consider if the code could be simplified by making a part into a function/algorithm with a descriptive name, a well-defined purpose, a well-defined interface, and well-defined dependencies.

Numerical algorithms in the style of the STL algorithms are presented in §40.6.

32.2.1. Sequences

The ideal for a standard-library algorithm is to provide the most general and flexible interface to something that can be implemented optimally. The iterator-based interfaces are a good, but not perfect, approximation to that ideal (§33.1.1). For example, an iterator-based interface does not directly represent the notion of a sequence, leading to the possibility of confusion and difficulties in detecting some range errors:

Click here to view code image

void user(vector<int>& v1, vector<int>& v2)
{
     copy(v1.begin(),v1.end(),v2.begin());   // may overflow v2
     sort(v1.begin(),v2.end());                   // oops!
}

Many such problems can be alleviated by providing container versions of the standard-library algorithms. For example:

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template<typename Cont>
void sort(Cont& c)
{
     static_assert(Range<Cont>(), "sort(): Cont argument not a Range");
     static_assert(Sortable<Iterator<Cont>>(), "sort(): Cont argument not Sortable");

     std::sort(begin(c),end(c));
}

template<typename Cont1, typename Cont2>
void copy(const Cont1& source, Cont2& target)
{
     static_assert(Range<Cont1>(), "copy(): Cont1 argument not a Range");
     static_assert(Range<Cont2>(), "copy(): Cont2 argument not a Range");
     if (target.size()<source.size()) throw out_of_range{"copy target too small"};

     std::copy(source.begin(),source.end(),target.begin());
}

This would simplify the definition of user(), make the second error impossible to express, and catch the first at run time:

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void user(vector<int>& v1, vector<int>& v2)
{
     copy(v1,v2);  // overflows will be caught
     sort(v1);
}

However, the container versions are also less general than the versions that use iterators directly. In particular, you cannot use the container sort() to sort half a container, and you cannot use the container copy() to write to an output stream.

A complementary approach is to define a “range” or “sequence” abstraction that allows us to define sequences when needed. I use the concept Range to denote anything with begin() and end() iterators (§24.4.4). That is, there is no Range class holding data – exactly as there is no Iterator class or Container class in the STL. So, in the “container sort()” and “container copy()” examples, I called the template argument Cont (for “container”), but they will accept any sequence with a begin() and an end() that meets the rest of the requirements for the algorithm.

The standard-library containers mostly return iterators. In particular, they do not return containers of results (except in a few rare examples, a pair). One reason for that is that when the STL was designed, there was no direct support for move semantics. So, there was no obvious and efficient way to return a lot of data from an algorithm. Some programmers used explicit indirection (e.g., a pointer, reference, or iterator) or some clever trickery. Today, we can do better:

Click here to view code image

template<typename Cont, typename Pred>
vector<Value_type<Cont>*>
find_all(Cont& c, Pred p)
{
     static_assert(Range<Cont>(), "find_all(): Cont argument not a Range");
     static_assert(Predicate<Pred>(), "find_all(): Pred argument not a Predicate");

     vector<Value_type<Cont>*> res;
     for (auto& x : c)
           if (p(x)) res.push_back(&x);
     return res;
}

In C++98, this find_all() would have been a bad performance bug whenever the number of matches was large. If the choice of standard-library algorithms seems restrictive or insufficient, extension with new versions of STL algorithms or new algorithms is often a viable and superior alternative to just writing “random code” to work around the problem.

Note that whatever an STL algorithm returns, it cannot be an argument container. The arguments to STL algorithms are iterators (Chapter 33), and an algorithm has no knowledge of the data structure those iterators point into. Iterators exist primarily to isolate algorithms from the data structure on which they operate, and vice versa.

32.3. Policy Arguments

Most standard-library algorithms come in two versions:

• A “plain” version that performs its action using conventional operations, such as < and ==

• A version that takes key operations as arguments

For example:

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template<class Iter>
void sort(Iter first, Iter last)
{
     // ... sort using e1<e2 ...
}

template<class Iter, class Pred>
void sort(Iter first, Iter last, Pred pred)
{
     // ... sort using pred(e1,e2) ...
}

This greatly increases the flexibility of the standard library and its range of uses.

The usual two versions of an algorithm can be implemented as two (overloaded) function templates or as a single function template with a default argument. For example:

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template<typename Ran, typename Pred = less<Value_type<Ran>>>  // use a default template argument
sort(Ran first, Ran last, Pred pred ={})
{
     // ... use pred(x,y) ...
}

The difference between having two functions and having one with a default argument can be observed by someone taking pointers to functions. However, thinking of many of the variants of the standard algorithms as simply “the version with the default predicate” roughly halves the number of template functions you need to remember.

In some cases, an argument could be interpreted as either a predicate or a value. For example:

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bool pred(int);

auto p = find(b,e,pred);  // find element pred or apply predicate'pred()? (the latter)

In general, a compiler cannot disambiguate such examples, and programmers would get confused even in the cases where the compiler could disambiguate.

To simplify the task for the programmer, the _if suffix is often used to indicate that an algorithm takes a predicate. The reason to distinguish by using two names is to minimize ambiguities and confusion. Consider:

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using Predicate = bool(*)(int);

void f(vector<Predicate>& v1, vector<int>& v2)
{
     auto p1 = find(v1.begin(),v1.end(),pred);       // find element with the value pred
     auto p2 = find_if(v2.begin(),v2.end(),pred);    // count elements for which pred() returns true
}

Some operations passed as arguments to an algorithm are meant to modify the element to which they are applied (e.g., some operations passed to for_each(); §32.4.1), but most are predicates (e.g., a comparison object for sort()). Unless otherwise stated, assume that a policy argument passed to an algorithm should not modify an element. In particular, do not try to modify elements through predicates:

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int n_even(vector<int>& v)                        // don't do this
     // count the number of even values in v
{
     return find_if(v.begin(),v.end(),[](int& x) {++x; return x&1; });
}

Modifying an element through a predicate obscures what is being done. If you are really sneaky, you could even modify the sequence (e.g., by inserting or removing an element using the name of a container being iterated over), so that the iteration would fail (probably in obscure ways). To avoid accidents, you may pass arguments to predicates by const reference.

Similarly, a predicate should not carry state that changes the meaning of its operation. The implementation of an algorithm may copy a predicate, and we rarely want repeated uses of a predicate on the same value to give different results. Some function objects passed to algorithms, such as random number generators, do carry mutable state. Unless you are really sure that an algorithm doesn’t copy, keep a function object argument’s mutable state in another object and access it through a pointer or a reference.

The == and < operations on pointer elements are rarely appropriate for an STL algorithm: they compare machine addresses rather than the values pointed to. In particular, do not sort or search containers of C-style strings using the default == and < (§32.6).

32.3.1. Complexity

As for containers (§31.3), the complexity of algorithms is specified by the standard. Most algorithms are linear, O(n), for some n, which is usually the length of an input sequence.

As ever, these are asymptotic complexities, and you have to know what n measures to have an idea of the implications. For example, if n<3, a quadratic algorithm may be the best choice. The cost of each iteration can vary dramatically. For example, traversing a list can be much slower than traversing a vector, even though the complexity in both cases is linear (O(n)). Complexity measures are not a substitute for common sense and actual time measurements; they are one tool among many to ensure quality code.

32.4. Nonmodifying Sequence Algorithms

A nonmodifying algorithm just reads the values of elements of its input sequences; it does not rearrange the sequence and does not change the values of the elements. Typically, user-supplied operations to an algorithm don’t change the values of elements either; they tend to be predicates (which may not modify their arguments).

32.4.1. for_each()

The simplest algorithm is for_each(), which just applies an operation to each element of a sequence:

When possible, prefer a more specific algorithm.

The operation passed to for_each() may modify elements. For example:

Click here to view code image

void increment_all(vector<int>& v) // increment each element of v
{
     for_each(v.begin(),v.end(), [](int& x) {++x;});
}

32.4.2. Sequence Predicates

For example:

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vector<double> scale(const vector<double>& val, const vector<double>& div)
{
     assert(val.size()<div.size());
     assert(all_of(div.begin(),div.end(),[](double x){ return 0<x; });

     vector res(val.size());
     for (int i = 0; i<val.size(); ++i)
           res[i] = val[i]/div[i];
     return res;
}

When one of these sequence predicates fails, it does not tell which element caused the failure.

32.4.3. count()

For example:

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void f(const string& s)
{
     auto n_space = count(s.begin(),s.end(),' ');
     auto n_whitespace = count_if(s.begin(),s.end(),isspace);
     // ...
}

The isspace() predicate (§36.2) lets us count all whitespace characters, rather than just space.

32.4.4. find()

The find() family of algorithms do linear searches for some element or predicate match:

The algorithms find() and find_if() return an iterator to the first element that matches a value and a predicate, respectively.

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void f(const string& s)
{
     auto p_space = find(s.begin(),s.end(),' ');
     auto p_whitespace = find_if(s.begin(),s.end(), isspace);
     // ...
}

The find_first_of() algorithms find the first occurrence in a sequence of an element from another sequence. For example:

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array<int> x = {1,3,4 };
array<int> y = {0,2,3,4,5};

void f()
{
     auto p = find_first_of(x.begin(),x.end(),y.begin(),y.end);     // p = &x[1]
     auto q = find_first_of(p+1,x.end(),y.begin(),y.end());         // q = &x[2]
}

The iterator p will point to x[1] because 3 is the first element of x with a match in y. Similarly, q will point to x[2].

32.4.5. equal() and mismatch()

The equal() and mismatch() algorithms compare pairs of sequences:

The mismatch() looks for the first pair of elements of two sequences that compare unequal and returns iterators to those elements. No end is specified for the second sequence; that is, there is no last2. Instead, it is assumed that there are at least as many elements in the second sequence as in the first, and first2+(last–first) is used as last2. This technique is used throughout the standard library, where pairs of sequences are used for operations on pairs of elements. We could implement mismatch() like this:

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template<class In, class In2, class Pred = equal_to<Value_type<In>>>
pair<In, In2> mismatch(In first, In last, In2 first2, Pred p ={})
{
     while (first != last && p(*first,*first2)) {
           ++first;
           ++first2;
     }
     return {first,first2};
}

I used the standard function object equal_to (§33.4) and the type function Value_type (§28.2.1).

32.4.6. search()

The search() and search_n() algorithms find one sequence as a subsequence in another:

The search() algorithm looks for its second sequence as a subsequence of its first. If that second sequence is found, an iterator for the first matching element in the first sequence is returned. As usual, the end of the sequence is used to represent “not found.” For example:

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string quote {"Why waste time learning, when ignorance is instantaneous?"};

bool in_quote(const string& s)
{
     auto p = search(quote.begin(),quote.end(),s.begin(),s.end()); // find s in quote
     return p!=quote.end();
}

void g()
{
     bool b1 = in_quote("learning");    // b1 = true
     bool b2 = in_quote("lemming");     // b2 = false
}

Thus, search() is a useful algorithm for finding a substring generalized to all sequences.

Use find() or binary_search() (§32.6) to look for just a single element.

32.5. Modifying Sequence Algorithms

The modifying algorithms (also called mutating sequence algorithms) can (and often do) modify elements of their argument sequences.

Somewhat confusingly, transform() doesn’t necessarily change its input. Instead, it produces an output that is a transformation of its input based on a user-supplied operation. The one-input-sequence version of transform() may be defined like this:

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template<class In, class Out, class Op>
Out transform(In first, In last, Out res, Op op)
{
     while (first!=last)
           *res++ = op(*first++);
     return res;
}

The output sequence may be the same as the input sequence:

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void toupper(string& s)  // remove case
{
     transform(s.begin(),s.end(),s.begin(),toupper);
}

This really transforms the input s.

32.5.1. copy()

The copy() family of algorithms copy elements from one sequence into another. The following sections list versions of copy() combined with other algorithms, such as replace_copy() (§32.5.3).

The target of a copy algorithm need not be a container. Anything that can be described by an output iterator (§38.5) will do. For example:

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void f(list<Club>& lc, ostream& os)
{
     copy(lc.begin(),lc.end(),ostream_iterator<Club>(os));
}

To read a sequence, we need a pair of iterators describing where to begin and where to end. To write, we need only an iterator describing where to write to. However, we must take care not to write beyond the end of the target. One way to ensure that we don’t do this is to use an inserter (§33.2.2) to grow the target as needed. For example:

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void f(const vector<char>& vs, vector<char>& v)
{
     copy(vs.begin(),vs.end(),v.begin());          // might overwrite end of v
     copy(vs.begin(),vs.end(),back_inserter(v));   // add elements from vs to end of v
}

The input sequence and the output sequence may overlap. We use copy() when the sequences do not overlap or if the end of the output sequence is in the input sequence.

We use copy_if() to copy only elements that fulfill some criterion. For example:

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void f(list<int>&ld, int n, ostream& os)
{
     copy_if(ld.begin(),ld.end(),
         ostream_iterator<int>(os),
         [](int x) { return x>n); });
}

See also remove_copy_if().

32.5.2. unique()

The unique() algorithm removes adjacent duplicate elements from a sequence:

The unique() and unique_copy() algorithms eliminate adjacent duplicate values. For example:

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void f(list<string>& ls, vector<string>& vs)
{
     ls.sort();    // list sort (§31.4.2)
     unique_copy(ls.begin(),ls.end(),back_inserter(vs));
}

This copies ls to vs, eliminating duplicates in the process. I used sort() to get equal strings adjacent.

Like other standard algorithms, unique() operates on iterators. It does not know which container these iterators point into, so it cannot modify that container. It can only modify the values of the elements. This implies that unique() does not eliminate duplicates from its input sequence in the way we naively might expect. Therefore, this does not eliminate duplicates in a vector:

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void bad(vector<string>& vs)       // warning: doesn't do what it appears to do!
{
     sort(vs.begin(),vs.end());    // sort vector
     unique(vs.begin(),vs.end());  // eliminate duplicates (no it doesn't!)
}

Rather, unique() moves unique elements toward the front (head) of a sequence and returns an iterator to the end of the subsequence of unique elements. For example:

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int main()
{
     string s ="abbcccde";

     auto p = unique(s.begin(),s.end());
     cout << s << ' ' << p–s.begin() << '\n';
}

produces

abcdecde 5

That is, p points to the second c (that is, the first of the duplicates).

Algorithms that might have removed elements (but can’t) generally come in two forms: the “plain” version that reorders elements in a way similar to unique() and a _copy version that produces a new sequence in a way similar to unique_copy().

To eliminate duplicates from a container, we must explicitly shrink it:

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template<class C>
void eliminate_duplicates(C& c)
{
     sort(c.begin(),c.end());            // sort
     auto p = unique(c.begin(),c.end()); // compact
     c.erase(p,c.end());                 // shrink
}

I could equivalently have written c.erase(unique(c.begin(),c.end()),c.end()), but I don’t think such terseness improves readability or maintainability.

32.5.3. remove() and replace()

The remove() algorithm “removes” elements to the end of a sequence:

The replace() algorithm assigns new values to selected elements:

These algorithms cannot change the size of their input sequence, so even remove() leaves the size of its input sequence unchanged. Like unique(), it “removes” by moving elements to the left. For example:

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string s {"*CamelCase*IsUgly*"};
cout << s << '\n';                                  // *CamelCase*IsUgly*
auto p = remove(s.begin(),s.end(),'*');
copy(s.begin(),p,ostream_iterator<char>{cout});     // CamelCaseIsUgly
cout << s << '\n';                                  // CamelCaseIsUglyly*

32.5.4. rotate(), random_shuffle(), and partition()

The rotate(), random_shuffle(), and partition() algorithms provide systematic ways of moving elements around in a sequence:

The movement of elements done by rotate() (and by the shuffle and partition algorithms) is done using swap().

A shuffle algorithm shuffles its sequence much in the way we would shuffle a pack of cards. That is, after a shuffle, the elements are in a random order, where “random” is defined by the distribution produced by the random number generator.

By default, random_shuffle() shuffles its sequence using a uniform distribution random number generator. That is, it chooses a permutation of the elements of the sequence so that each permutation has the same chances of being chosen. If you want a different distribution or a better random number generator, you can supply one. For a call random_shuffle(b,e,r), the generator is called with the number of elements in the sequence (or a subsequence) as its argument. For example, for a call r(e–b) the generator must return a value in the range [0,e–b). If My_rand is such a generator, we might shuffle a deck of cards like this:

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void f(deque<Card>& dc, My_rand& r)
{
     random_shuffle(dc.begin(),dc.end(),r);
     // ...
}

The partition algorithm separates a sequence into two parts based on a partition criterion:

32.5.5. Permutations

The permutation algorithms provide a systematic way of generating all permutations of a sequence.

Permutations are used to generate combinations of elements of a sequence. For example, the permutations of abc are acb, bac, bca, cab, and cba.

The next_permutation() takes a sequence [b:e) and transforms it into the next permutation. The next permutation is found by assuming that the set of all permutations is lexicographically sorted. If such a permutation exists, next_permutation() returns true; otherwise, it transforms the sequence into the smallest permutation, that is, the ascendingly sorted one (abc in the example), and returns false. So, we can generate the permutations of abc like this:

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vector<char> v {'a','b','c'};
while(next_permutation(v.begin(),v.end()))
     cout << v[0] << v[1] << v[2] << ' ';

Similarly, the return value for prev_permutation() is false if [b:e) already contains the first permutation (abc in the example); in that case, it returns the last permutation (cba in the example).

32.5.6. fill()

The fill() family of algorithms provide ways of assigning to and initializing elements of a sequence:

The fill() algorithm repeatedly assigns the specified value, whereas generate() assigns values obtained by calling its function argument repeatedly. For example, using the random number generators Randint and Urand from §40.7:

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int v1[900];
array<int,900> v2;
vector v3;

void f()
{
     fill(begin(v1),end(v1),99);                       // set all elements of v1 to 99
     generate(begin(v2),end(v2),Randint{});            // set to random values (§40.7)

     // output 200 random integers in the interval [0:100):
     generate_n(ostream_iterator<int>{cout},200,Urand{100});    // see §40.7

     fill_n(back_inserter{v3},20,99);                 // add 20 elements with the value 99 to v3
}

The generate() and fill() functions assign rather than initialize. If you need to manipulate raw storage, say, to turn a region of memory into objects of well-defined type and state, you use one of the uninitialized_ versions (presented in <memory>).

Uninitialized sequences should only occur at the lowest level of programming, usually inside the implementation of containers. Elements that are targets of uninitialized_fill() or uninitialized_copy() must be of built-in type or uninitialized. For example:

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vector<string> vs {"Breugel","El Greco","Delacroix","Constable"};
vector<string> vs2 {"Hals","Goya","Renoir","Turner"};
copy(vs.begin(),vs.end(),vs2.begin());                     // OK
uninitialized_copy(vs.begin(),vs.end(),vs2.begin());       // leaks!

A few more facilities for dealing with uninitialized memory are described in §34.6.

32.5.7. swap()

A swap() algorithm exchanges the values of two objects:

for example:

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void use(vector<int>& v, int* p)
{
     swap_ranges(v.begin(),v.end(),p);  // exchange values
}

The pointer p had better point to an array with at least v.size() elements.

The swap() algorithm is possibly the simplest and arguably the most crucial algorithm in the standard library. It is used as part of the implementaton of many of the most widely used algorithms. Its implementation is used as an example in §7.7.2 and the standard-library version is presented in §35.5.2.

32.6. Sorting and Searching

Sorting and searching in sorted sequences are fundamental, and the needs of programmers are quite varied. Comparison is by default done using the < operator, and equivalence of values a and b is determined by !(a<b)&&!(b<a) rather than requiring operator ==.

In addition to the “plain sort” there are many variants:

The sort() algorithms require random-access iterators (§33.1.2).

Despite its name, is_sorted_until() returns an iterator, rather than a bool.

The standard list (§31.3) does not provide random-access iterators, so lists should be sorted using the specific list operations (§31.4.2) or by copying their elements into a vector, sorting that vector, and then copying the elements back into the list:

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template<typename List>
void sort_list(List& lst)
{
     vector v {lst.begin(),lst.end()};   // initialize from lst
     sort(v);                            // use container sort (§32.2)
     copy(v,lst);
}

The basic sort() is efficient (on average N*log(N)). If a stable sort is required, stable_sort() should be used, that is, an N*log(N)*log(N) algorithm that improves toward N*log(N) when the system has sufficient extra memory. The get_temporary_buffer() function may be used for getting such extra memory (§34.6). The relative order of elements that compare equal is preserved by stable_sort() but not by sort().

Sometimes, only the first elements of a sorted sequence are needed. In that case, it makes sense to sort the sequence only as far as is needed to get the first part in order, that is, a partial sort. The plain partial_sort(b,m,e) algorithms put the elements in the range [b:m) in order. The partial_sort_copy() algorithms produce N elements, where N is the lower of the number of elements in the output sequence and the number of elements in the input sequence. We need to specify both the start and the end of the result sequence because that’s what determines how many elements we need to sort. For example:

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void f(const vector<Book>& sales) // find the top ten books
{
     vector<Book> bestsellers(10);
     partial_sort_copy(sales.begin(),sales.end(),
               bestsellers.begin(),bestsellers.end(),
               [](const Book& b1, const Book& b2) { return b1.copies_sold()>b2.copies_sold(); });
     copy(bestsellers.begin(),bestsellers.end(),ostream_iterator<Book>{cout,"\n"});
}

Because the target of partial_sort_copy() must be a random-access iterator, we cannot sort directly to cout.

If the number of elements desired to be sorted by a partial_sort() is small compared to the total number of elements, these algorithms can be significatly faster than a complete sort(). Then, their complexity approaches O(N) compared to sort()’s O(N*log(N)).

The nth_element() algorithm sorts only as far as is necessary to get the Nth element to its proper place with no element comparing less than the Nth element placed after it in the sequence. For example:

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vector<int> v;
for (int i=0; i<1000; ++i)
      v.push_back(randint(1000));        // §40.7
constexpr int n = 30;
nth_element(v.begin(), v.begin()+n, v.end());
cout << "nth: " << v[n] < '\n';
for (int i=0; i<n; ++i)
      cout << v[i] << ' ';

This produces:

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nth: 24
10 8 15 19 21 15 8 7 6 17 21 2 18 8 1 9 3 21 20 18 10 7 3 3 8 11 11 22 22 23

The nth_element() differs from partial_sort() in that the elements before n are not necessarily sorted, just all less than the nth element. Replacing nth_element with partial_sort in that example (and using the same seed for the random number generator to get the same sequence), I got:

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nth: 995
1 2 3 3 3 6 7 7 8 8 8 8 9 10 10 11 11 15 15 17 18 18 19 20 21 21 21 22 22 23

The nth_element() algorithm is particularly useful for people – such as economists, sociologists, and teachers – who need to look for medians, percentiles, etc.

Sorting C-style strings requires an explicit sorting criterion. The reason is that C-style strings are simply pointers with a set of conventions for their use, so < on pointers compares machine addresses rather than character sequences. For example:

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vector<string> vs = {"Helsinki","Copenhagen","Oslo","Stockholm"};
vector<char*> vcs = {"Helsinki","Copenhagen","Oslo","Stockholm"};

void use()
{
     sort(vs); // I have defined a range version of sort()
     sort(vcs);

     for (auto& x : vs)
           cout << x << ' '
     cout << '\n';
     for (auto& x : vcs)
           cout << x << ' ';

This prints:

Copenhagen Helsinki Stockholm Oslo
Helsinki Copenhagen Oslo Stockholm

Naively, we might have expected the same output from both vectors. However, to sort C-style strings by string value rather than by address we need a proper sort predicate. For example:

sort(vcs, [](const char* p, const char* q){ return strcmp(p,q)<0; });

The standard-library function strcmp() is described in §43.4.

Note that I did not have to supply a == to sort C-style strings. To simplify the user interface, the standard library uses !(x<y>||y<x) rather than x==y to compare elements (§31.2.2.2).

32.6.1. Binary Search

The binary_search() family of algorithms provide binary searches of ordered (sorted) sequences:

A sequential search such as find() (§32.4) is terribly inefficient for large sequences, but it is about the best we can do without sorting or hashing (§31.4.3.2). Once a sequence is sorted, however, we can use a binary search to determine whether a value is in a sequence. For example:

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void f(vector<int>& c)
{
     if (binary_search(c.begin(),c.end(),7)){  // is 7 in c?
           // ...
     }
     // ...
}

A binary_search() returns a bool indicating whether a value is present. As with find(), we often also want to know where the elements with that value are in that sequence. However, there can be many elements with a given value in a sequence, and we often need to find either the first or all such elements. Consequently, algorithms are provided for finding a range of equal elements, equal_range(), and algorithms for finding the lower_bound() and upper_bound() of that range. These algorithms correspond to the operations on multimaps (§31.4.3). We can think of lower_bound() as a fast find() and find_if() for sorted sequences. For example:

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void g(vector<int>& c)
{
     auto p = find(c.begin(),c.end(),7);         // probably slow: O(N); c needn't be sorted
     auto q = lower_bound(c.begin(),c.end(),7);  // probably fast: O(log(N)); c must be sorted
     // ...
}

If lower_bound(first,last,k) doesn’t find k, it returns an iterator to the first element with a key greater than k, or last if no such greater element exists. This way of reporting failure is also used by upper_bound() and equal_range(). This means that we can use these algorithms to determine where to insert a new element into a sorted sequence so that the sequence remains sorted: just insert before the second of the returned pair.

Curiously enough, the binary search algorithms do not require random-access iterators: a forward iterator suffices.

32.6.2. merge()

The merge algorithms combine two ordered (sorted) sequences into one:

The merge() algorithm can take different kinds of sequences and elements of different types. For example:

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vector<int> v {3,1,4,2};
list<double> lst {0.5,1.5,2,2.5};    // lst is in order

sort(v.begin(),v.end());             // put v in order

vector<double> v2;
merge(v.begin(),v.end(),lst.begin(),lst.end(),back_inserter(v2));    // merger v and lst into v2
for (double x : v2)
      cout << x << ", ";

For inserters, see §33.2.2. The output is:

0.5, 1, 1.5, 2, 2, 2.5, 3, 4,

32.6.3. Set Algorithms

These algorithms treat a sequence as a set of elements and provide the basic set operations. The input sequences are supposed to be sorted and the output sequences are also sorted.

For example:

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string s1 = "qwertyasdfgzxcvb";
string s2 = "poiuyasdfg/.,mnb";
sort(s1.begin(),s1.end());               // the set algorithms require sorted sequences
sort(s2.begin(),s2.end());

string s3(s1.size()+s2.size(),'*');      // set aside enough space for the largest possible result
cout << s3 << '\n';
auto up = set_union(s1.begin(),s1.end(),s2.begin(),s2.end(),s3.begin());
cout << s3 << '\n';
for (auto p = s3.begin(); p!=up; ++p)
      cout << *p;
cout << '\n';

s3.assign(s1.size()+s2.size(),'+');
up = set_difference(s1.begin(),s1.end(),s2.begin(),s2.end(),s3.begin());
cout << s3 << '\n';
for (auto p = s3.begin(); p!=up; ++p)
      cout << *p;
cout << '\n';

This little test produces:

Click here to view code image

*******************************
,./abcdefgimnopqrstuvxyz
ceqrtvwxz++++++++++++++++++++++
ceqrtvwxz

32.6.4. Heaps

A heap is a compact data structure that keeps the element with the highest value first. Think of a heap as a representation of a binary tree. The heap algorithms allow a programmer to treat a random-access sequence as a heap:

Think of the end, e, of a heap [b:e) as a pointer, which it decremented by pop_heap() and incremented by push_heap(). The largest element is extracted by reading through b (e.g., x=*b) and then doing a pop_heap(). A new element is inserted by writing through e (e.g., *e=x) and then doing a push_heap(). For example:

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string s = "herewego";
make_heap(s.begin(),s.end());      // rogheeew
pop_heap(s.begin(),s.end());       // rogheeew
pop_heap(s.begin(),s.end()–1);     // ohgeeerw
pop_heap(s.begin(),s.end()–2);     // hegeeorw

*(s.end()–3)='f';
push_heap(s.begin(),s.end()–2);    // hegeefrw
*(s.end()–2)='x';
push_heap(s.begin(),s.end()–1);    // xeheefge
*(s.end()–1)='y';
push_heap(s.begin(),s.end());      // yxheefge
sort_heap(s.begin(),s.end());      // eeefghxy
reverse(s.begin(),s.end());        // yxhgfeee

The way to understand the changes to s is that a user reads only s[0] and writes only s[x] where x is the index of the current end of the heap. The heap removes an element (always s[0]) by swapping it with s[x].

The point of a heap is to provide fast addition of elements and fast access to the element with the highest value. The main use of heaps is to implement priority queues.

32.6.5. lexicographical_compare()

A lexicographical compare is the rule we use to order words in dictionaries.

We might implement lexicographical_compare(b,e,b2,e2) like this:

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template<class In, class In2>
bool lexicographical_compare(In first, In last, In2 first2, In2 last2)
{
     for (; first!=last && first2!=last2; ++first,++last) {
            if (*first<*first2)
                   return true;   // [first:last)<[first2:last2)
            if (*first2<*first)
                   return false;  // [first2:last2)<[first:last)
     }
     return first==last && first2!=last2; // [first:last)<[first2:last2) if [first:last) is shorter
}

That is, a string compares as a sequence of characters. For example:

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string n1 {"10000"};
string n2 {"999"};

bool b1 = lexicographical_compare(n1.begin(),n1.end(),n2.begin(),n2.end());    // b1 == true

n1 = "Zebra";
n2 = "Aardvark";
bool b2 = lexicographical_compare(n1.begin(),n1.end(),n2.begin(),n2.end());    // b2 == false

32.7. Min and Max

Value comparisons are useful in many contexts:

If we compare two lvalues, the result is a reference to the result; otherwise, an rvalue is returned. Unfortunately, the versions that take lvalues take const lvalues, so you can never modify the result of one of these functions. For example:

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int x = 7;
int y = 9;

++min(x,y);    // the result of min(x,y) is a const int&
++min({x,y});  // error: the result of min({x,y}) is an rvalue (an initializer_list is immutable)

The _element functions return iterators and the minmax function returns pairs, so we can write:

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string s = "Large_Hadron_Collider";
auto p = minmax_element(s.begin(),s.end(),
                      [](char c1,char c2) { return toupper(c1)<toupper(c2); });
cout << "min==" << *(p.first) << ' ' << "max==" << *(p.second) << '\n';

With the ACSII character set on my machine, this little test produces:

min==a max==_

32.8. Advice

[1] An STL algorithm operates on one or more sequences; §32.2.

[2] An input sequence is half-open and defined by a pair of iterators; §32.2.

[3] When searching, an algorithm usually returns the end of the input sequence to indicate “not found”; §32.2.

[4] Prefer a carefully specified algorithm to “random code”; §32.2.

[5] When writing a loop, consider whether it could be expressed as a general algorithm; §32.2.

[6] Make sure that a pair of iterator arguments really do specify a sequence; §32.2.

[7] When the pair-of-iterators style becomes tedious, introduce a container/range algorithm; §32.2.

[8] Use predicates and other function objects to give standard algorithms a wider range of meanings; §32.3.

[9] A predicate must not modify its argument; §32.3.

[10] The default == and < on pointers are rarely adequate for standard algorithms; §32.3.

[11] Know the complexity of the algorithms you use, but remember that a complexity measure is only a rough guide to performance; §32.3.1.

[12] Use for_each() and transform() only when there is no more-specific algorithm for a task; §32.4.1.

[13] Algorithms do not directly add or subtract elements from their argument sequences; §32.5.2, §32.5.3.

[14] If you have to deal with uninitialized objects, consider the uninitialized_* algorithms; §32.5.6.

[15] An STL algorithm uses an equality comparison generated from its ordering comparison, rather than ==; §32.6.

[16] Note that sorting and searching C-style strings requires the user to supply a string comparison operation; §32.6.

33. STL Iterators

The reason that STL containers and algorithms work so well together is that they know nothing of each other.

– Alex Stepanov

• Introduction

• Iterator Model

Iterator Categories; Iterator Traits; Iterator Operations

• Iterator Adaptors

Reverse Iterators; Insert Iterators; Move Iterator

• Range Access Functions

• Function Objects

• Function Adaptors

bind(); mem_fn(); function

• Advice

33.1. Introduction

This chapter presents the STL iterators and utilities, notably standard-library function objects. The STL consists of the iterator, container, algorithm, and function object parts of the standard library. The rest of the STL is presented in Chapter 31 and Chapter 32.

Iterators are the glue that ties standard-library algorithms to their data. Conversely, you can say that iterators are the mechanism used to minimize an algorithm’s dependence on the data structures on which it operates:

33.1.1. Iterator Model

An iterator is akin to a pointer in that it provides operations for indirect access (e.g., * for dereferencing) and for moving to point to a new element (e.g., ++ for moving to the next element). A sequence is defined by a pair of iterators defining a half-open range [begin:end):

That is, begin points to the first element of the sequence, and end points to the one-beyond-the-last element of the sequence. Never read from or write to *end. Note that the empty sequence has begin==end; that is, [p:p) is the empty sequence for any iterator p.

To read a sequence, an algorithm usually takes a pair of iterators (b,e) and iterates using ++ until the end is reached:

Click here to view code image

while (b!=e) {       // use != rather than <
   // do something
   ++b;   // go to next element
}

The reason to use != rather than < for testing whether we have reached the end is partially because that is the more precise statement of what we are testing for and partially because only random-access iterators support <.

Algorithms that search for something in a sequence usually return the end of the sequence to indicate “not found”; for example:

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auto p = find(v.begin(),v.end(),x);      // look for x in v

if (p!=v.end()) {
    // x found at p
}
else {
   // x not found in [v.begin():v.end())
}

Algorithms that write to a sequence often are given only an iterator to its first element. In that case, it is the programmer’s responsibility not to write beyond the end of that sequence. For example:

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template<typename Iter>
void forward(Iter p, int n)
{
    while (n>0)
           *p++ = ––n;
}

void user()
{
     vector<int> v(10);
     forward(v.begin(),v.size());    // OK
     forward(v.begin(),1000);        // big trouble
}

Some standard-library implementations range check – that is, throw an exception for that last call of forward() – but you can’t rely on that for portable code: many implementations don’t check. For a simple and safe alternative use an insert iterator (§33.2.2).

33.1.2. Iterator Categories

The standard library provides five kinds of iterators (five iterator categories):

• Input iterator : We can iterate forward using ++ and read each element (repeatedly) using *. We can compare input iterators using == and !=. This is the kind of iterator that istream offers; see §38.5.

• Output iterator: We can iterate forward using ++ and write an element once only using *. This is the kind of iterator that ostream offers; see §38.5.

• Forward iterator: We can iterate forward repeatedly using ++ and read and write (unless the elements are const) elements repeatedly using *. If a forward iterator points to a class object, we can use –> to refer to a member. We can compare forward iterators using == and !=. This is the kind of iterator forward_list offers (§31.4).

• Bidirectional iterator: We can iterate forward (using ++) and backward (using ––) and read and write (unless the elements are const) elements repeatedly using *. If a bidirectional iterator points to a class object, we can use –> to refer to a member. We can compare bidirectional iterators using == and !=. This is the kind of iterator that list, map, and set offer (§31.4).

• Random-access iterator: We can iterate forward (using ++ or +=) and backward (using – or –=) and read and write (unless the elements are const) elements repeatedly using * or []. If a random-access iterator points to a class object, we can use –> to refer to a member. We can subscript a random-access iterator using [], add an integer using +, and subtract an integer using –. We can find the distance between two random-access iterators to the same sequence by subtracting one from the other. We can compare random-access iterators using ==, !=, <, <=, >, and >=. This is the kind of iterator that vector offers (§31.4).

Logically, these iterators are organized in a hierarchy (§iso.24.2):

The iterator categories are concepts (§24.3) rather than classes, so this hierarchy is not a class hierarchy implemented using derivation. If you need to do something advanced with iterator categories, use iterator_traits (directly or indirectly).

33.1.3. Iterator Traits

In <iterator>, the standard library provides a set of type functions that allow us to write code specialized for specific properties of an iterator:

The iterator tags are types used to select among algorithms based on the type of an iterator. For example, a random-access iterator can go directly to an element:

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template<typename Iter>
void advance_helper(Iter p, int n, random_access_iterator_tag)
{
     p+=n;
}

On the other hand, a forward iterator must get to the nth element by moving one step at a time (e.g., following links on a list):

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template<typename Iter>
void advance_helper(Iter p, int n, forward_iterator_tag)
{
     if (0<n)
           while (n––) ++p;
     else if (n<0)
           while (n++) ––p;
}

Given these helpers, advance() can consistently use the optimal algorithm:

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template<typename Iter>
void advance(Iter p, int n)  // use the optimal algorithm
{
     advance_helper(p,n,typename iterator_traits<Iter>::iterator_category{});
}

Typically, advance() and/or advance_helper() will be inlined to ensure that no run-time overhead is introduced by this tag dispatch technique. Variants of this technique are pervasive in the STL.

The key properties of an iterator are described by the aliases in iterator_traits:

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template<typename Iter>
struct iterator_traits {
     using value_type = typename Iter::value_type;
     using difference_type = typename Iter::difference_type;
     using pointer = typename Iter::pointer;                     // pointer type
     using reference = typename Iter::reference;                 // reference type
     using iterator_category = typename Iter::iterator_category; // (tag)
};

For an iterator that does not have these member types (e.g., an int*), we provide a specialization of iterator_traits:

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template<typename T>
struct iterator_traits<T*>{              // specialization for pointers
     using difference_type = ptrdiff_t;
     using value_type = T;
     using pointer = T*;
     using reference = T& reference;
     using iterator_category = random_access_iterator_tag;
};

We cannot in general say:

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template<typename Iter>
typename Iter::value_type read(Iter p, int n)    // not general
{
     // ... do some checking ...
     return p[n];
{

This is an error waiting to happen. Calling this read() with a pointer argument would be an error. The compiler would catch it, but the error messages might be voluminous and obscure. Instead, we can write:

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template<typename Iter>
typename iterator_traits<Iter>::value_type read(Iter p, int n)    // more general
{
     // ... do some checking ...
     return p[n];
{

The idea is that to find a property of an iterator, you look in its iterator_traits (§28.2.4), rather than at the iterator itself. To avoid directly referring to the iterator_traits, which after all is just an implementation detail, we can define an alias. For example:

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template<typename Iter>
using Category<Iter> = typename std::iterator_traits<Iter>::iterator_category;

template<typename Iter>
using Difference_type<Iter> = typename std::iterator_traits<Iter>::difference_type;

So, if we want to know the type of the difference between two iterators (pointing to the same sequence), we have some choices:

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tempate<typename Iter>
void f(Iter p, Iter q)
{
     Iter::difference_type d1 = distance(p,q);          // syntax error: "typename" missing

     typename Iter::difference_type d2 = distance(p,q); // doesn't work for pointers, etc.

     typename iterator_traits<Iter>::distance_type d3 = distance(p,q);         // OK, but ugly
     Distance_type<Iter> d4 = distance(p,q);                                   // OK, much better

     auto d5 = distance(p,q);      // OK, if you don't need to mention the type explicitly
     // ...
}

I recommend the last two alternatives.

The iterator template simply bundles the key properties of an iterator into a struct for the convenience of iterator implementers and provides a few defaults:

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template<typename Cat, typename T, typename Dist = ptrdiff_t, typename Ptr = T*, typename Ref = T&>
struct iterator {
     using value_type = T;
     using difference_type = Dist ;   // type used by distance()
     using pointer = Ptr;             // pointer type
     using reference = Ref;           // reference type
     using iterator_category = Cat;   // category (tag)
};

33.1.4. Iterator Operations

Depending on its category (§33.1.2), an iterator provides some or all of these operations:

A ++p returns a reference to p, whereas p++ must return a copy of p holding the old value. Thus, for more complicated iterators, ++p is likely to be more efficient than p++.

The following operations work for every iterator for which they can be implemented, but they may work more efficiently for random-access iterators (see §33.1.2):

In each case, if p is not a random-access iterator, the algorithm will take n steps.

33.2. Iterator Adaptors

In <iterator>, the standard library provides adaptors to generate useful related iterator types from a given iterator type:

Iterators for iostreams are described in §38.5.

33.2.1. Reverse Iterator

Using an iterator we can traverse a sequence [b:e) from b to e. If the sequence allows bidirectional access, we can also traverse the sequence in reverse order, from e to b. An iterator that does that is called a reverse_iterator. A reverse_iterator iterates from the end of the sequence defined by its underlying iterator to the beginning of that sequence. To get a half-open sequence, we must consider b–1 as one past the end and e–1 as the start of the sequence: [e–1, b–1). Thus, the fundamental relation between a reverse iterator and its corresponding iterator is &*(reverse_iterator(p))==&*(p–1). In particular, if v is a vector, v.rbegin() points to its last element, v[v.size()–1]. Consider:

This sequence can be viewed like this using a reverse_iterator:

The definition of reverse_iterator looks something like this:

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template<typename Iter>
class reverse_iterator
     : public iterator<Iterator_category<Iter>,
                      Value_type<Iter>,
                      Difference_type<Iter>,
                      Pointer<Iter>,
                      Reference<Iter>> {
public:
     using iterator_type = Iter;

     reverse_iterator(): current{} { }
     explicit reverse_iterator(Iter p): current{p} { }
     template<typename Iter2>
         reverse_iterator(const reverse_iterator<Iter2>& p) :current(p.base()) { }

     Iter base() const { return current; } // current iterator value

     reference operator*() const { tmp = current; return *––tmp; }
     pointer operator–>() const;
     reference operator[](difference_type n) const;

     reverse_iterator& operator++() { ––current; return *this; }     // note: not ++
     reverse_iterator operator++(int) { reverse_iterator t = current; ––current; return t; }
     reverse_iterator& operator––() { ++current; return *this; }     // note: not ––
     reverse_iterator operator––(int) { reverse_iterator t = current; ++current; return t; }

     reverse_iterator operator+(difference_type n) const;
     reverse_iterator& operator+=(difference_type n);
     reverse_iterator operator–(difference_type n) const;
     reverse_iterator& operator–=(difference_type n);
     // ...
protected:
     Iterator current;   // current points to the element after the one *this refers to
private:
     // ...
     iterator tmp;       // for temporaries that need to outlive a function scope
};

A reverse_iterator<Iter> has the same member types and operations as Iter. In particular, if Iter is a random-access operator, its reverse_iterator<Iter> has [], +, and <. For example:

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void f(vector<int>& v, list<char>& lst)
{
     v.rbegin()[3] = 7;              // OK: random-access iterator
     lst.rbegin()[3] = '4';          // error: bidirectional iterator doesn't support []
     *(next(lst.rbegin(),3)) = '4';  // OK!
}

I use next() to move the iterator because (like []) + wouldn’t work for a bidirectional iterator, such as list<char>::iterator.

Reverse iterators allow us to use algorithms in a way that views a sequence in the reverse order. For example, to find the last occurrence of an element in a sequence, we can apply find() to its reverse sequence:

auto ri = find(v.rbegin(),v.rend(),val);    // last occurrence

Note that C::reverse_iterator is not the same type as C::iterator. So, if I wanted to write a find_last() algorithm using a reverse sequence, I would have to decide which type of iterator to return:

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template<typename C, typename Val>
auto find_last(C& c, Val v) –> decltype(c.begin())    // use C's iterator in the interface
{
     auto ri = find(c.rbegin(),c.rend(),v);
     if (ri == c.rend()) return c.end();              // use c.end() to indicate "not found"
     return prev(ri.base());
}

For a reverse_iterator, ri.base() returns an iterator pointing one beyond the position pointed to by ri. So, to get an iterator pointing to the same element as the reverse iterator ri, I have to return ri.base()–1. However, my container may be a list that does not support – for its iterators, so I use prev() instead.

A reverse iterator is a perfectly ordinary iterator, so I could write the loop explicitly:

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template<typename C, Val v>
auto find_last(C& c, Val v) –> decltype(c.begin())
{
     for (auto p = c.rbegin(); p!=c.rend(); ++p)    // view sequence in reverse order
           if (*p==v) return ––p.base();
     return c.end();                                // use c.end() to indicate "not found"
}

The equivalent code searching backward using a (forward) iterator is:

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template<typename C>
auto find_last(C& c, Val v) –> decltype(c.begin())
{
     for (auto p = c.end(); p!=c.begin(); )    // search backward from end
           if (*––p==v) return p;
     return c.end();                           // use c.end() to indicate "not found"
}

As for the earlier definitions of find_last(), this version requires at least a bidirectional iterator.

33.2.2. Insert Iterators

Producing output through an iterator into a container implies that elements following the one pointed to by the iterator can be overwritten. This implies the possibility of overflow and consequent memory corruption. For example:

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void f(vector<int>& vi)
{
     fill_n(vi.begin(),200,7);     // assign 7 to vi[0]..[199]
}

If vi has fewer than 200 elements, we are in trouble.

In <iterator>, the standard library provides a solution in the form of an inserter: when written to, an inserter inserts a new element into a sequence rather than overwriting an existing element. For example:

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void g(vector<int>& vi)
{
     fill_n(back_inserter(vi),200,7);     // add 200 7s to the end of vi
}

When writing to an element through an insert iterator, the iterator inserts its value rather than overwriting the element pointed to. So, a container grows by one element each time a value is written to it through an insert iterator. Inserters are as simple and efficient as they are useful.

There are three insert iterators:

• insert_iterator inserts before the element pointed to using insert().

• front_insert_iterator inserts before the first element of a sequence using push_front().

• back_insert_iterator inserts after the last element of the sequence using push_back().

An inserter is usually constructed by a call to a helper function:

The iterator passed to inserter() must be an iterator into the container. For a sequence container, that implies that it must be a bidirectional iterator (so that you can insert before it). For example, you can’t use inserter() to make an iterator to insert into a forward_list. For an associative container, where that iterator is only used as a hint for where to insert, a forward iterator (e.g., as provided by an unordered_set) can be acceptable.

An inserter is an output iterator:

The front_insert_iterator and back_insert_iterator differ in that their constructors don’t require an iterator. For example:

vector<string> v;
back_insert_iterator<v> p;

You cannot read through an inserter.

33.2.3. Move Iterator

A move iterator is an iterator where reading from the pointed-to element moves rather than copies. We usually make a move iterator from another iterator using a helper function:

A move iterator has the same operations as the iterator from which it is made. For example, we can do ––p if the move iterator p was made from a bidirectional iterator. A move iterator’s operator*() simply returns an rvalue reference (§7.7.2) to the element pointed to: std::move(q). For example:

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vector<string> read_strings(istream&);
auto vs = read_strings(cin);               // get some strings

vector<string> vs2;
copy(vs,back_inserter(vs2));               // copy strings from vs into vs2

vector<string> vs3;
copy(vs2,make_move_iterator(back_inserter(vs3)));    // move strings from vs2 into vs3

This assumes that a container version of std::copy() has been defined.

33.3. Range Access Functions

In <iterator>, the standard library provides a nonmember begin() and end() functions for containers:

These functions are very simple:

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template<typename C>
    auto begin(C& c) –> decltype(c.begin());
template<typename C>
    auto begin(const C& c) –> decltype(c.begin());
template<typename C>
    auto end(C& c) –> decltype(c.end());
template<typename C>
    auto end(const C& c) –> decltype(c.end());

template<typename T, size_t N>            // for built-in arrays
    auto begin(T (&array)[N]) –> T*;
template<typename T, size_t N>
    auto end(T (&array)[N]) –> T*;

These functions are used by the range-for-statement (§9.5.1) but can of course also be used directly by users. For example:

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template<typename Cont>
void print(Cont& c)
{
     for(auto p=begin(c); p!=end(c); ++p)
          cout << *p << '\n';
}

void f()
{
     vector<int> v {1,2,3,4,5};
     print(v);

     int a[] {1,2,3,4,5};
     print(a);
}

Had I said c.begin() and c.end(), the call print(a) would have failed.

A user-defined container with member begin() and end() automatically gets nonmember versions when <iterator> is #included. To provide nonmember begin() and end() for a container, My_container, that doesn’t have them, I have to write something like:

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template<typename T>
Iterator<My_container<T>> begin(My_container<T>& c)
{
     return Iterator<My_container<T>>{&c[0]};             // iterator to first element
}

template<typename T>
Iterator<My_container<T>> end(My_container<T>& c)
{
     return Iterator<My_container<T>>{&c[0]+c.size()};    // iterator to last element
}

Here, I assume that passing the address of the first element is a way to create an iterator to the first element of My_container and that My_container has a size().

33.4. Function Objects

Many of the standard algorithms take function objects (or functions) as arguments to control the way they work. Common uses are comparison criteria, predicates (functions returning bool), and arithmetic operations. In <functional>, the standard library supplies a few common function objects:

For example:

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vector<int> v;
// ...
sort(v.begin(),v.end(),greater<int>{});          // sort v into decreasing order

Such predicates are roughly equivalent to simple lambdas. For example:

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vector<int> v;
// ...
sort(v.begin(),v.end(),[](int a, int b) { return a>b; });     // sort v into decreasing order

Note that logical_and and logical_or always evaluate both their arguments (&& and || do not).

33.5. Function Adaptors

A function adaptor takes a function as argument and returns a function object that can be used to invoke the original function.

The bind() and mem_fn() adaptors do argument binding, also called Currying or partial evaluation. These binders, and their deprecated predecessors (such as bind1st(), mem_fun(), and mem_fun_ref()), were heavily used in the past, but most uses seem to be more easily expressed using lambdas (§11.4).

33.5.1. bind()

Given a function and a set of arguments, bind() produces a function object that can be called with “the remaining” arguments, if any, of the function. For example:

double cube(double);

auto cube2 = bind(cube,2);

A call cube2() will invoke cube with the argument 2, that is, cube(2). We don’t have to bind every argument of a function. For example:

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using namespace placeholders;

void f(int,const string&);
auto g = bind(f,2,_1);      // bind f()'s first argument to 2
f(2,"hello");
g("hello");                 // also calls f(2,"hello");

The curious _1 argument to the binder is a placeholder telling bind() where arguments to the resulting function object should go. In this case, g()’s (first) argument is used as f()’s second argument.

The placeholders are found in the (sub)namespace std::placeholders that is part of <functional>. The placeholder mechanism is very flexible. Consider:

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f(2,"hello");
bind(f)(2,"hello");        // also calls f(2,"hello");
bind(f,_1,_2)(2,"hello");  // also calls f(2,"hello");
bind(f,_2,_1)("hello",2);  // reverse order of arguments: also calls f(2,"hello");

auto g = [](const string& s, int i) { f(i,s); } // reverse order of arguments
g("hello",2);                                   // also calls f(2,"hello");

To bind arguments for an overloaded function, we have to explicitly state which version of the function we want to bind:

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int pow(int,int);
double pow(double,double);   // pow() is overloaded

auto pow2 = bind(pow,_1,2);                           // error: which pow()?
auto pow2 = bind((double(*)(double,double))pow,_1,2); // OK (but ugly)

Note that bind() takes ordinary expressions as arguments. This implies that references are dereferenced before bind() gets to see them. For example:

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void incr(int& i)
{
     ++i;
}

void user()
{
     int i = 1;
     incr(i);                         // i becomes 2
     auto inc = bind(incr,_1);
     inc(i);                          // i stays 2; inc(i) incremented a local copy of i
}

To deal with that, the standard library provides yet another pair of adaptors:

This solves the “reference problem” for bind():

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void user()
{
     int i = 1;
     incr(i);                      // i becomes 2
     auto inc = bind(incr,_1);
     inc(ref(i));                  // i becomes 3
}

This ref() is needed to pass references as arguments to threads because thread constructors are variadic templates (§42.2.2).

So far, I either used the result of bind() immediately or assigned it to a variable declared using auto. This saves me the bother of specifying the return type of a call of bind(). That can be useful because the return type of bind() varies with the type of function to be called and the argument values stored. In particular, the returned function object is larger when it has to hold values of bound parameters. However, we sometimes want to be specific about the types of the arguments required and the type of result returned. If so, we can specify them for a function (§33.5.3).

33.5.2. mem_fn()

The function adaptor mem_fn(mf) produces a function object that can be called as a nonmember function. For example:

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void user(Shape* p)
{
     p–>draw();
     auto draw = mem_fn(&Shape::draw);
     draw(p);
}

The major use of mem_fn() is when an algorithm requires an operation to be called as a nonmember function. For example:

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void draw_all(vector<Shape*>& v)
{
     for_each(v.begin(),v.end(),mem_fn(&Shape::draw));
}

Thus, mem_fn() can be seen as a mapping from the object-oriented calling style to the functional one.

Often, lambdas provide a simple and general alternative to binders. For example:

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void draw_all(vector<Shape*>& v)
{
     for_each(v.begin(),v.end(),[](Shape* p) { p–>draw(); });
}

33.5.3. function

A bind() can be used directly, and it can be used to initialize an auto variable. In that, bind() resembles a lambda.

If we want to assign the result of bind() to a variable with a specific type, we can use the standard-library type function. A function is specified with a specific return type and a specific argument type.

For example:

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int f(double);
function<int(double)> fct {f};  // initialize to f
int g(int);

void user()
{
     fct = [](double d) { return round(d); };     // assign lambda to fct
     fct = f;                                     // assign function to fct
     fct = g;                                     // error: incorrect return type
}

The target functions are provided for the rare cases where someone wants to examine a function, rather than simply call it as usually intended.

The standard-library function is a type that can hold any object you can invoke using the call operator () (§2.2.1, §3.4.3, §11.4, §19.2.2). That is, an object of type function is a function object. For example:

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int round(double x) { return static_cast<double>(floor(x+0.5)); }  // conventional 4/5 rounding

function<int(double)> f; // f can hold anything that can be called with a double and return an int

enum class Round_style { truncate, round };

struct Round {   // function object carrying a state
     Round_style s;
     Round(Round_style ss) :s(ss) { }
     int operator()(double x) const { return (s==Round_style::round) ? (x+0.5) : x; };
};
void t1()
{
     f = round;
     cout << f(7.6) << '\n';                             // call through f to the function round

     f = Round(Round_style::truncate);
     cout << f(7.6) << '\n';                             // call the function object

     Round_style style = Round_style::round;
     f = [style] (double x){ return (style==Round_style::round) ? x+0.5 : x; };

     cout << f(7.6) << '\n';                             // call the lambda

     vector<double> v {7.6};
     f = Round(Round_style::round);
     std::transform(v.begin(),v.end(),v.begin(),f);      // pass to algorithm

     cout << v[0] << '\n';                               // transformed by the lambda
}

We get 8, 8, 7, and 8.

Obviously, functions are useful for callbacks, for passing operations as arguments, etc.

33.6. Advice

[1] An input sequence is defined by a pair of iterators; §33.1.1.

[2] An output sequence is defined by a single iterator; avoid overflow; §33.1.1.

[3] For any iterator p, [p:p] is the empty sequence; §33.1.1.

[4] Use the end of a sequence to indicate “not found”; §33.1.1.

[5] Think of iterators as more general and often better behaved pointers; §33.1.1.

[6] Use iterator types, such as list<char>::iterator, rather than pointers to refer to elements of a container; §33.1.1.

[7] Use iterator_traits to obtain information about iterators; §33.1.3.

[8] You can do compile-time dispatch using iterator_traits; §33.1.3.

[9] Use iterator_traits to select an optimal algorithm based on an iterator’s category; §33.1.3.

[10] iterator_traits are an implementation detail; prefer to use them implicitly; §33.1.3.

[11] Use base() to extract an iterator from a reverse_iterator; §33.2.1.

[12] You can use an insert iterator to add elements to a container; §33.2.2.

[13] A move_iterator can be used to make copy operations into move operations; §33.2.3.

[14] Make sure that your containers can be traversed using a range-for; §33.3.

[15] Use bind() to create variants of functions and function objects; §33.5.1.

[16] Note that bind() dereferences references early; use ref() if you want to delay dereferencing; §33.5.1.

[17] A mem_fn() or a lambda can be used to convert the p–>f(a) calling convention into f(p,a); §33.5.2.

[18] Use function when you need a variable that can hold a variety of callable objects; §33.5.3.

34. Memory and Resources

Anyone can have an idea; it’s what you do with the idea that’s the important thing.

– Terry Pratchett

• Introduction

• “Almost Containers”

array; bitset; vector<bool>; Tuples

• Resource Management Pointers

unique_ptr; shared_ptr; weak_ptr

• Allocators

The Default Allocator; Allocator Traits; Pointer Traits; Scoped Allocators

• The Garbage Collection Interface

• Uninitialized Memory

Temporary Buffers; raw_storage_iterator

• Advice

34.1. Introduction

The STL (Chapter 31, Chapter 32, Chapter 33) is the most highly structured and general part standard-library facilities for the management and manipulation of data. This chapter presents facilities that are more specialized or deal with raw memory (as opposed to typed objects).

34.2. “Almost Containers”

The standard library provides several containers that don’t fit perfectly into the STL framework (§31.4, §32.2, §33.1). Examples are built-in arrays, array, and string. I sometimes refer to those as “almost containers” (§31.4), but that is not quite fair: they hold elements, so they are containers, but each has restrictions or added facilities that make them awkward in the context of the STL. Describing them separately also simplifies the description of the STL.

Why does the standard library provide so many containers? They serve common but different (often overlapping) needs. If the standard library didn’t provide them, many people would have to design and implement their own. For example:

• pair and tuple are heterogeneous; all other containers are homogeneous (all elements are of the same type).

• array, vector, and tuple elements are contiguously allocated; forward_list and map are linked structures.

• bitset and vector<bool> hold bits and access them through proxy objects; all other standard-library containers can hold a variety of types and access elements directly.

• basic_string requires its elements to be some form of character and to provide string manipulation, such as concatenation and locale-sensitive operations (Chapter 39) and valarray requires its elements to be numbers and to provide numerical operations.

All of these containers can be seen as providing specialized services needed by large communities of programmers. No single container could serve all of these needs because some needs are contradictory, for example, “ability to grow” vs. “guaranteed to be allocated in a fixed location,” and “elements do not move when elements are added” vs. “contiguously allocated.” Furthermore, a very general container would imply overhead deemed unacceptable for individual containers.

34.2.1. array

An array, defined in <array>, is a fixed-size sequence of elements of a given type where the number of elements is specified at compile time. Thus, an array can be allocated with its elements on the stack, in an object, or in static storage. The elements are allocated in the scope where the array is defined. An array is best understood as a built-in array with its size firmly attached, without implicit, potentially surprising conversions to pointer types, and with a few convenience functions provided. There is no overhead (time or space) involved in using an array compared to using a built-in array. An array does not follow the “handle to elements” model of STL containers. Instead, an array directly contains its elements:

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template<typename T, size_t N>              // an array of N Ts (§iso.23.3.2)
struct array {
/*
     types and operations like vector's (§31.4),
     except operations that change the container size, constructors, and assign() functions
*/
     void fill(const T& v);// assign N copies of v
     void swap(array&) noexcept(noexcept(swap(declval<T&>(), declval<T&>())));

     T __elem[N];  // implementation detail
};

No “management information” (e.g., a size) is stored in an array. This implies that moving (§17.5) an array is no more efficient than copying it (unless the array’s elements are resource handles with efficient moves). An array does not have a constructor or an allocator (because it does not directly allocate anything).

The number of elements and subscript values for array are of an unsigned type (size_t), just like vector’s, but different from the built-in array’s. So, array<int,–1> might be accepted by an inattentive compiler. Hope for a warning.

An array can be initialized by an initializer list:

array<int,3> a1 = { 1, 2, 3 };

The number of elements in the initializer must be equal to or less than the number of elements specified for the array. As usual, if the initializer list provides values for some but not all elements, the remainder is initialized with the appropriate default value. For example:

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void f()
{
     array<string, 4> aa = {"Churchill", "Clare"};
     //
}

The last two elements will be empty strings.

The element count is not optional:

array<int> ax = { 1, 2, 3 }; // error size not specified

To save us from a special case, the number of elements can be zero:

int<int,0> a0;

The element count must be a constant expression:

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void f(int n)
{
     array<string,n> aa = {"John's", "Queens' "};     // error: size not a constant expression
     //
}

If you need the element count to be variable, use vector. On the other hand, since array’s element count is known at compile time, array’s size() is a constexpr function.

There is no constructor for array that copies an argument value (as there is for vector; §31.3.2). Instead, a fill() operation is provided:

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void f()
{
     array<int,8> aa;   // uninitialized, so far
     aa.fill(99);       // assign eight copies of 99
     // ...
}

Because an array doesn’t follow the “handle to elements” model, swap() has to actually swap elements so that swapping two array<T,N>s applies swap() to N pairs of Ts. The declaration of array<T,N>::swap() basically says that if a swap() of Ts can throw, then so can a swap() of an array<T,N>. Obviously, throwing swap()s should be avoided like the plague.

When necessary, an array can be explicitly passed to a C-style function that expects a pointer. For example:

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void f(int* p, int sz); // C-style interface

void g()
{
     array<int,10> a;

     f(a,a.size());             // error: no conversion
     f(&a[0],a.size());         // C-style use
     f(a.data(),a.size());      // C-style use

     auto p = find(a.begin(),a.end(),777);       // C++/STL-style use
     // ...
}

Why would we use an array when vector is so much more flexible? Because an array is less flexible, it is simpler. Occasionally, there is a significant performance advantage to be had by directly accessing elements allocated on the stack rather than allocating elements on the free store, accessing them indirectly through the vector (a handle), and then deallocating them. On the other hand, the stack is a limited resource (especially on some embedded systems), and stack overflow is nasty.

Why would we use an array when we could use a built-in array? An array knows its size, so it is easy to use with standard-library algorithms, and it can be copied (using = or initialization). However, my main reason to prefer array is that it saves me from surprising nasty conversions to pointers. Consider:

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void h()
{
     Circle a1[10];
     array<Circle,10> a2;
     // ...
     Shape* p1 = a1;      // OK: disaster waiting to happen
     Shape* p2 = a2;      // error: no conversion of array<Circle,10> to Shape*
     p1[3].draw();        // disaster
}

The “disaster” comment assumes that sizeof(Shape)<sizeof(Circle), so that subscripting a Circle[] through a Shape* gives a wrong offset (§27.2.1, §17.5.1.4). All standard containers provide this advantage over built-in arrays.

An array can be seen as a tuple (§34.2.4) where all elements are of the same type. The standard library provides support for that view. The tuple helper type functions tuple_size and tuple_element can be applied to arrays:

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tuple_size<array<T,N>>::value        // N
tuple_element<S,array<T,N>>::type    // T

We can also use a get<i> function to access the ith element:

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template<size_t index, typename T, size_t N>
    T& get(array<T,N>& a) noexcept;
template<size_t index, typename T, size_t N>
    T&& get(array<T,N>&& a) noexcept;
template<size_t index, typename T, size_t N>
    const T& get(const array<T,N>& a) noexcept;

For example:

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array<int,7> a = {1,2,3,5,8,13,25};
auto x1 = get<5>(a);                                 // 13
auto x2 = a[5];                                      // 13
auto sz = tuple_size<decltype(a)>::value;            // 7
typename tuple_element<5,decltype(a)>::type x3 = 13; // x3 is an int

These type functions are for people writing code that expects tuples.

Use a constexpr function (§28.2.2) and a type alias (§28.2.1) to improve readability:

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auto sz = Tuple_size<decltype(a)>();        // 7

Tuple_element<5,decltype(a)> x3 = 13; // x3 is an int

The tuple syntax is meant for use in generic code.

34.2.2. bitset

Aspects of a system, such as the state of an input stream (§38.4.5.1), are often represented as a set of flags indicating binary conditions such as good/bad, true/false, and on/off. C++ supports the notion of small sets of flags efficiently through bitwise operations on integers (§11.1.1). Class bitset<N> generalizes this notion and offers greater convenience by providing operations on a sequence of N bits [0:N), where N is known at compile time. For sets of bits that don’t fit into a long long int, using a bitset is much more convenient than using integers directly. For smaller sets, bitset is usually optimized. If you want to name the bits, rather than numbering them, the alternatives are to use a set (§31.4.3), an enumeration (§8.4), or a bit-field (§8.2.7).

A bitset<N> is an array of N bits. It is presented in <bitset>. A bitset differs from a vector<bool> (§34.2.3) by being of fixed size, from set (§31.4.3) by having its bits indexed by integers rather than associatively by value, and from both vector<bool> and set by providing operations to manipulate the bits.

It is not possible to address a single bit directly using a built-in pointer (§7.2). Consequently, bitset provides a reference-to-bit (proxy) type. This is actually a generally useful technique for addressing objects for which a built-in pointer for some reason is unsuitable:

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template<size_t N>
class bitset {
public:
     class reference {         // reference to a single bit:
          friend class bitset;
          reference() noexcept;
     public:                  // support zero-based subscripting in [0:b.size())
          ~reference() noexcept;
          reference& operator=(bool x) noexcept;                     // for b[i] = x;
          reference& operator=(const reference&) noexcept;           // for b[i] = b[j];
          bool operator~() const noexcept;                           // return ~b[i]
          operator bool() const noexcept;                            // for x = b[i];
          reference& flip() noexcept;                                // b[i].flip();
     };
     // ...
};

For historical reasons, bitset differs in style from other standard-library classes. For example, if an index (also known as a bit position) is out of range, an out_of_range exception is thrown. No iterators are provided. Bit positions are numbered from right to left in the same way bits often are in a word, so the value of b[i] is pow(2,i). Thus, a bitset can be thought of as an N-bit binary number:

34.2.2.1. Constructors

A bitset can be constructed with a specified number of zeros, from the bits in an unsigned long long int, or from a string:

The position npos is string<C>’s “beyond the end” position, meaning “all characters until the end” (§36.3).

When an unsigned long long int argument is supplied, each bit in the integer is used to initialize the corresponding bit in the bitset (if any). A basic_string (§36.3) argument does the same, except that the character '0' gives the bit value 0, the character '1' gives the bit value 1, and other characters cause an invalid_argument exception to be thrown. For example:

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void f()
{
     bitset<10> b1; // all 0

     bitset<16> b2 = 0xaaaa;                        // 1010101010101010
     bitset<32> b3 = 0xaaaa;                        // 00000000000000001010101010101010

     bitset<10> b4 {"1010101010"};                  // 1010101010
     bitset<10> b5 {"10110111011110",4};            // 0111011110

     bitset<10> b6 {string{"1010101010"}};          // 1010101010
     bitset<10> b7 {string{"10110111011110"},4};              // 0111011110
     bitset<10> b8 {string{"10110111011110"},2,8};  // 0011011101

     bitset<10> b9 {string{"n0g00d"}};              // invalid_argument thrown
     bitset<10> b10 = string{"101001"};             // error: no implicit string to bitset conversion
}

A key idea in the design of bitset is that an optimized implementation can be provided for bitsets that fit in a single word. The interface reflects this assumption.

34.2.2.2. bitset Operations

A bitset provides the operators for accessing individual bits and for manipulating all bits in the set:

The >> and << are I/O operators when their first operand is an iostream; othewise, they are shift operators and their second operand must be an integer. For example:

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bitset<9> bs ("110001111"};
cout << bs << '\n';          // write "110001111" to cout
auto bs2 = bs<<3;            // bs2 == "001111000";
cout << bs2 << '\n';         // write "001111000" to cout
cin >> bs;                   // read from cin
bs2 = bs>>3;                 // bs2 == "000110001" if the input were "110001111"
cout << bs2 << '\n';         // write "000110001" to cout

When bits are shifted, a logical (rather than cyclic) shift is used. That implies that some bits “fall off the end” and that some positions get the default value 0. Note that because size_t is an unsigned type, it is not possible to shift by a negative number. It does, however, imply that b<<–1 shifts by a very large positive value, thus leaving every bit of the bitset b with the value 0. Your compiler should warn against this.

A bitset also supports common operations such as size(), ==, I/O, etc.:

The operations to_ullong() and to_string() provide the inverse operations to the constructors. To avoid nonobvious conversions, named operations were preferred over conversion operators. If the value of the bitset has so many significant bits that it cannot be represented as an unsigned long, to_ulong() throws overflow_error; so does to_ullong() if its bitset argument doesn’t fit.

Fortunately, the template arguments for the basic_string returned by to_string are defaulted. For example, we could write out the binary representation of an int:

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void binary(int i)
{
     bitset<8*sizeof(int)> b = i;          // assume 8-bit byte (see also §40.2)

     cout << b.to_string<char,char_traits<char>,allocator<char>>() << '\n'; // general and verbose
     cout << b.to_string<char>() << '\n'; // use default traits and allocator
     cout << b.to_string<>() << '\n';     // use all defaults
     cout << b.to_string() << '\n';       // use all defaults
}

This prints the bits represented as 1s and 0s from left to right, with the most significant bit leftmost, so that argument 123 would give the output

00000000000000000000000001111011
00000000000000000000000001111011
00000000000000000000000001111011
00000000000000000000000001111011

For this example, it is simpler to directly use the bitset output operator:

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void binary2(int i)
{
     bitset<8*sizeof(int)> b = i;   // assume 8-bit byte (see also §40.2)
     cout << b << '\n';
}

34.2.3. vector<bool>

The vector<bool> from <vector> is a specialization of vector (§31.4) providing compact storage of bits (bools):

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template<typename A>
class vector<bool,A> {  // specialization of vector<T,A> (§31.4)
public:
     using const_reference = bool;
     using value_type = bool;
     // like vector<T,A>

     class reference {    // support zero-based subscripting in [0:v.size())
          friend class vector;
          reference() noexcept;
     public:
          ~reference();
          operator bool() const noexcept;
          reference& operator=(const bool x) noexcept;         // v[i] = x
          reference& operator=(const reference& x) noexcept;   // v[i] = v[j]
          void flip() noexcept;                                // flip the bit: v[i]=~v[i]
     };

     void flip() noexcept; // flip all bits of v

     // ...
};

The similarity to bitset is obvious, but, unlike bitset but like vector<T>, vector<bool> has an allocator and can have its size changed.

As in a vector<T>, elements of a vector<bool> with higher indices have higher addresses:

This is exactly the opposite of the layout in a bitset. Also, there is no direct support for converting integers and strings to and from a vector<bool>.

Use vector<bool> as you would any other vector<T>, but expect operations on a single bit to be less efficient than the equivalent operations on a vector<char>. Also, it is impossible in C++ to completely faithfully mimic the behavior of a (built-in) reference with a proxy, so don’t try to be subtle about rvalue/lvalue distinctions when using a vector<bool>.

34.2.4. Tuples

The standard library provides two ways of grouping values of arbitrary types into a single object:

• A pair (§34.2.4.1) holds two values.

• A tuple (§34.2.4) holds zero or more values.

We use pair when it is useful to know (statically) that we have exactly two values. With tuple, we always have to deal with all possible numbers of values.

34.2.4.1. pair

In <utility>, the standard library provides class pair for manipulating pairs of values:

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template<typename T, typename U>
struct pair {
     using first_type = T;  // the type of the first element
     using second_type = U; // the type of the second element

     T first;     // first element
     U second;    // second element

     // ...
};

An operation on pair is noexcept if the corresponding operations on its elements are. Similarly, copy or move operations exist for a pair if the corresponding operations on its elements do.

The elements first and second are members that we can directly read and write. For example:

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void f()
{
     pair<string,int> p {"Cambridge",1209};
     cout << p.first;     // print "Cambridge"
     p.second += 800;     // update year
     // ...
}

The piecewise_construct is the name of an object of type piecewise_construct_t used to distinguish between constructing a pair with members of tuple types and constructing a pair using tuples as argument lists for its first and second. For example:

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struct Univ {
     Univ(const string& n, int r) : name{n}, rank{r} { }
     string name;
     int rank;
     string city = "unknown";
};
     using Tup = tuple<string,int>;
     Tup t1 {"Columbia",11};           // U.S. News 2012
     Tup t2 {"Cambridge",2};

     pair<Tub,Tub> p1 {t1,t2};                          // pair of tuples
     pair<Univ,Univ> p2 {piecewise_construct,t1,t2};    // pair of Univs

That is, p1.second is t2, that is, {"Cambridge",2}. To contrast, p2.second is Univ{t2}, that is, {"Cambridge",2,"unknown"}.

The make_pair function avoids explicit mention of the element types of a pair. For example:

auto p = make_pair("Harvard",1736);

34.2.4.2. tuple

In <tuple>, the standard library provides class tuple and various supporting facilities. A tuple is a sequence of N elements of arbitrary types:

template<typename ... Types>
class tuple {
public:
    // ...
};

The number of elements is zero or positive.

For details of tuple design, implementation, and use, see §28.5 and §28.6.4.

The types of tuple and operands of = and arguments to swap(), etc., are not required to be the same. An operation is valid if (and only if) the implied operations on elements are valid. For example, we can assign one tuple to another if each element of the assigned tuple can be assigned to the target element. For example:

tuple<string,vector<double>,int> t2 = make_tuple("Hello, tuples!",vector<int>{1,2,3},'x');

An operation is noexcept if all the element operations are, and an operation throws only if a member operation throws. Similarly, a tuple operation is constexpr if the element operations are.

The number of elements in each tuple of a pair of operands (or arguments) must be the same.

Note that the general tuple constructor is explicit. In particular, this does not work:

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tuple<int,int,int> rotate(tuple<int,int,int> t)
{
     return {t.get<2>(),t.get<0>(),t.get<1>()}; // error: explicit tuple constructor
}

auto t2 = rotate({3,7,9}); // error: explicit tuple constructor

If all you need is two elements, you can use pair:

pair<int,int> rotate(pair<int,int> p)
{
     return {p.second,p.first};
}

auto p2 = rotate({3,7});

For more examples, see §28.6.4.

For example, tie() can be used to extract elements from a tuple:

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auto t = make_tuple(2.71828,299792458,"Hannibal");
double c;
string name;
tie(c,ignore,name) = t;      // c=299792458; name="Hannibal"

The name ignore refers to an object of a type that ignores assignments. Thus, an ignore in a tie() implies that attempts to assign to its tuple position are ignored. An alternative would be:

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double c = get<0>(t);        // c=299792458
string name = get<2>(t);     // name="Hannibal"

Obviously, this would be more interesting if the tuple came from “elsewhere” so that we didn’t trivially know the element values. For example:

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tuple<int,double,string> compute();
// ...
double c;
string name;
tie(c,ignore,name) = t;      // results in c and name

34.3. Resource Management Pointers

A pointer points to an object (or not). However, a pointer does not indicate who (if anyone) owns the objects. That is, looking just at a pointer, we have no idea who is supposed to delete the object pointed to, or how, or if at all. In <memory>, we find “smart pointers” to express ownership:

• unique_ptr (§34.3.1) to represent exclusive ownership

• shared_ptr (§34.3.2) to represent shared ownership

• weak_ptr (§34.3.3) to break loops in circular shared data structures

These resource handles are introduced in §5.2.1.

34.3.1. unique_ptr

The unique_ptr (defined in <memory>) provides a semantics of strict ownership:

• A unique_ptr owns the object to which it holds a pointer. That is, it is the unique_ptr’s obligation to destroy the object pointed to (if any) by its contained pointer.

• A unique_ptr cannot be copied (has no copy constructor or copy assignment). However, it can be moved.

• A unique_ptr stores a pointer and deletes the object pointed to (if any) using the associated deleter (if any) when it is itself destroyed (such as when a thread of control leaves the unique_ptr’s scope; §17.2.2).

The uses of unique_ptr include:

• Providing exception safety for dynamically allocated memory (§5.2.1, §13.3)

• Passing ownership of dynamically allocated memory to a function

• Returning dynamically allocated memory from a function

• Storing pointers in containers

Think of unique_ptr as being represented by a simple pointer (“the contained pointer”) or (if it has a deleter) as a pair of pointers:

When a unique_ptr is destroyed, its deleter is called to destroy the owned object. The deleter represents what it means to destroy an object. For example:

• A deleter for a local variable should do nothing.

• A deleter for a memory pool should return the object to the memory pool and destroy it or not, depending on how that pool is defined.

• The default (“no deleter”) version of unique_ptr uses delete. It doesn’t even store the default deleter. It can be a specialization or rely on the empty-base optimization (§28.5).

This way unique_ptr supports general resource management (§5.2).

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template<typename T, typename D = default_delete<T>>
class unique_ptr {
public:
     using pointer = ptr; // type of the contained pointer;
                          // ptr is D::pointer if that is defined, otherwise T*
     using element_type = T;
     using deleter_type = D;

     // ...
};

The contained pointer is not directly accessible to users.

Note: unique_ptr does not offer a copy constructor or copy assignment. Had it done so, the meaning of “ownership” would have been very hard to define and/or use. If you feel the need for copies, consider using a shared_ptr (§34.3.2).

It is possible to have a unique_ptr for a built-in array. For example:

unique_ptr<int[]> make_sequence(int n)
{
     unique_ptr p {new int[n]};
     for (int i=0; i<n; ++i)
           p[i]=i;
     return p;
}

This is provided as a specialization:

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template<typename T, typename D>
class unique_ptr<T[],D> {  // specialization for arrays (§iso.20.7.1.3)
                           // the default D=default_delete<T> comes from the general unique_ptr
public:
//   ... like the unique_ptr for individual objects, but with [] instead of * and -> ...
};

To avoid slicing (§17.5.1.4), a Derived[] is not accepted as an argument to a unique_ptr<Base[]> even if Base is a public base of Derived. For example:

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class Shape {
     // ...
};

class Circle : public Base {
     // ...
};

unique_ptr<Shape> ps {new Circle{p,20}};                              // OK
unique_ptr<Shape[]> pa {new Circle[] {Circle{p,20}, Circle{p2,40}};   // error

How can we best think of a unique_ptr? What are the best ways to use a unique_ptr? It is called a pointer (_ptr) and I pronounce it “unique pointer,” but clearly it is not just an ordinary pointer (or there would be no point in defining it). Consider a simple technical example:

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unique_ptr<int> f(unique_ptr<int> p)
{
     ++*p;
     return p;
}

void f2(const unique_ptr<int>& p)
{
     ++*p;
}

void use()
{
     unique_ptr<int> p {new int{7}};
     p=f(p);            // error: no copy constructor
     p=f(move(p));      // transfer ownership there and back
     f2(p);             // pass a reference
}

The f2() body is slightly shorter than f() and f2() is simpler to call, but I find f() easier to think about. The style illustrated by f() is explicit about ownership (and the use of unique_ptr is typically motivated by ownership issues). See also the discussion of the use of non-const references in §7.7.1. On balance, a notation f(x) that modifies x is more error-prone than a y=f(x) notation that does not.

It is a fair estimate that the call of f2() is one or two machine instructions faster than a call of f() (because of the need to place a nullptr in the original unique_ptr), but that is unlikely to be significant. On the other hand, access to the contained pointer involves an extra indirection in f2() compared to f(). This, too, is unlikely to be significant in most programs, so the choice between the styles of f() and f2() has to be made on reasoning about code quality.

Here is a simple example of a deleter used to provide guaranteed release of data obtained from a C program fragment using malloc() (§43.5):

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extern "C" char* get_data(const char* data); // get data from C program fragment

using PtoCF = void(*)(void*);

void test()
{
  unique_ptr<char,PtoCF> p {get_data("my_data"),free};
  // ... use *p ...
} // implicit free(p)

Currently, there is no standard-library make_unique() similar to make_pair() (§34.2.4.1) and make_shared() (§34.3.2). However, it is easily defined:

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template<typename T, typename ... Args>
unique_ptr<T> make_unique(Args&&... args)    // default deleter version
{
    return unique_ptr<T>{new T{args...}};
}

34.3.2. shared_ptr

A shared_ptr represents shared ownership. It is used where two pieces of code need access to some data but neither has exclusive ownership (in the sense of being responsible for destroying the object). A shared_ptr is a kind of counted pointer where the object pointed to is deleted when the use count goes to zero. Think of a shared pointer as a structure with two pointers: one to the object and one to the use count:

The deleter is what is used to delete the shared object when the use count goes to zero. The default deleter is the usual delete (invoke the destructor, if any, and deallocate free store).

For example, consider a Node in a general graph used by an algorithm that adds and removes both nodes and connections between nodes (edges). Obviously, to avoid resource leaks, a Node must be deleted if and only if no other node refers to it. We could try:

struct Node {
     vector<Node*> edges;
     // ...
};

Given that, answering questions such as “How many nodes points to this node?” is very hard and requires much added “housekeeping” code. We could plug in a garbage collector (§34.5), but that could have negative performance implications if the graph was only a small part of a large application data space. Worse, if the container contained non-memory resources, such as thread handles, file handles, locks, etc., even a garbage collector would leak resources.

Instead, we can use a shared_ptr:

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struct Node {
     vector<shared_ptr<Node>> edges;
     thread worker;
     // ...
};

Here, Node’s destructor (the implicitly generated destructor will do fine) deletes its edges. That is, the destructor for each edges[i] is invoked, and the Node pointed to (if any) is deleted if edges[i] was the last pointer to it.

Don’t use a shared_ptr just to pass a pointer from one owner to another; that’s what unique_ptr is for, and unique_ptr does it better and more cheaply. If you have been using counted pointers as return values from factory functions (§21.2.4) and the like, consider upgrading to unique_ptr rather than shared_ptr.

Do not thoughtlessly replace pointers with shared_ptrs in an attempt to prevent memory leaks; shared_ptrs are not a panacea nor are they without costs:

• A circular linked structure of shared_ptrs can cause a resource leak. You need some logical complication to break the circle, for example, use a weak_ptr (§34.3.3).

• Objects with shared ownership tend to stay “live” for longer than scoped objects (thus causing higher average resource usage).

• Shared pointers in a multi-threaded environment can be expensive (because of the need to prevent data races on the use count).

• A destructor for a shared object does not execute at a predictable time, so the algorithms/logic for the update of any shared object are easier to get wrong than for an object that’s not shared. For example, which locks are set at the time of the destructor’s execution? Which files are open? In general, which objects are “live” and in appropriate states at the (unpredictable) point of execution?

• If a single (last) node keeps a large data structure alive, the cascade of destructor calls triggered by its deletion can cause a significant “garbage collection delay.” That can be detrimental to real-time response.

A shared_ptr represents shared ownership and can be very useful, even essential, but shared ownership isn’t my ideal, and it always carries a cost (independently of how you represent the sharing). It is better (simpler) if an object has a definite owner and a definite, predictable life span. When there is a choice:

• Prefer unique_ptr to shared_ptr.

• Prefer ordinary scoped objects to objects on the heap owned by a unique_ptr.

The shared_ptr provides a fairly conventional set of operations:

In addition, the standard library provides a few helper functions:

For example:

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struct S {
     int i;
     string s;
     double d;
     // ...
};

auto p = make_shared<S>(1,"Ankh Morpork",4.65);

Now, p is a shared_ptr<S> pointing to an object of type S allocated on the free store, containing {1,string{"Ankh Morpork"},4.65}.

Note that unlike unique_ptr::get_deleter(), shared_ptr’s deleter is not a member function.

34.3.3. weak_ptr

A weak_ptr refers to an object managed by a shared_ptr. To access the object, a weak_ptr can be converted to a shared_ptr using the member function lock(). A weak_ptr allows access to an object, owned by someone else, that

• You need access to (only) if it exists

• May get deleted (by someone else) at any time

• Must have its destructor called after its last use (usually to delete a non-memory resource)

In particular, we use weak pointers to break loops in data structures managed using shared_ptrs.

Think of a weak_ptr as a structure with two pointers: one to the (potentially shared) object and one to the use count structure of that object’s shared_ptrs:

The “weak use count” is needed to keep the use count structure alive because there may be weak_ptrs after the last shared_ptr for an object (and the object) is destroyed.

template<typename T>
class weak_ptr {
public:
     using element_type = T;
     // ...
};

A weak_ptr has to be converted to a shared_ptr to access “its” object, so it provides relatively few operations:

Consider an implementation of the old “asteroid game.” All asteroids are owned by “the game,” but each asteroid must keep track of neighboring asteroids and handle collisions. A collision typically leads to the destruction of one or more asteroids. Each asteroid must keep a list of other asteroids in its neighborhood. Note that being on such a neighbor list should not keep an asteroid “alive” (so a shared_ptr would be inappropriate). On the other hand, an asteroid must not be destroyed while another asteroid is looking at it (e.g., to calculate the effect of a collision). And obviously, an asteroid destructor must be called to release resources (such as a connection to the graphics system). What we need is a list of asteroids that might still be intact and a way of “grabbing onto one” for a while. A weak_ptr does just that:

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void owner()
{
     // ...
     vector<shared_ptr<Asteroid>> va(100);
     for (int i=0; i<va.siz e(); ++i) {
           // ... calculate neighbors for new asteroid ...
           va[i].reset(new Asteroid(weak_ptr<Asteroid>(va[neighbor]));
           launch(i);
     }
     // ...
}

Obviously, I radically simplified “the owner” and gave each new Asteroid just one neighbor. The key is that we give the Asteroid a weak_ptr to that neighbor. The owner keeps a shared_ptr to represent the ownership that’s shared whenever an Asteroid is looking (but not otherwise). The collision calculation for an Asteroid will look something like this:

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void collision(weak_ptr<Asteroid> p)
{
     if (auto q = p.lock()) {        // p.lock returns a shared_ptr to p's object
           // ... that Asteroid still existed: calculate ...
     }
     else {        // Oops: that Asteroid has already been destroyed
          p.reset();
     }
}

Note that even if a user decides to shut down the game and deletes all Asteroids (by destroying the shared_ptrs representing ownership), every Asteroid that is in the middle of calculating a collision still finishes correctly: after the p.lock(), it holds a shared_ptr that will not become invalid.

34.4. Allocators

The STL containers (§31.4) and string (Chapter 36) are resource handles that acquire and release memory to hold their elements. To do so, they use allocators. The basic purpose of an allocator is to provide a source of memory for a given type and a place to return that memory to once it is no longer needed. Thus, the basic allocator functions are:

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p=a.allocate(n);    // acquire space for n objects of type T
a.deallocate(p,n);  // release space for n objects of type T pointed to by p

For example:

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template<typename T>
struct Simple_alloc {          // use new[] and delete[] to allocate and deallocate bytes
     using value_type = T;

     Simple_alloc() {}

     T* allocate(size_t n)
           { return reinterpret_cast<T*>(new char[n*sizeof(T)]); }
     void deallocate(T* p, size_t n)
           { delete[] reinterpret_cast<char*>(p); }

     // ...
};

Simple_alloc happens to be the simplest standards-conforming allocator. Note the casts to and from char*: allocate() does not invoke constructors and deallocate() does not invoke destructors; they deal in memory, not typed objects.

I can build my own allocator to allocate from an arbitrary area of memory:

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class Arena {
     void* p;
     int s;
public:
     Arena(void* pp, int ss); // allocate from p[0..ss-1]
};

template<typename T>
struct My_alloc {        // use an Arena to allocate and deallocate bytes
     Arena& a;
     My_alloc(Arena& aa) : a(aa) { }
     My_alloc() {}
     // usual allocator stuff
};

Once Arenas are made, objects can be constructed in the memory allocated:

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constexpr int sz {100000};
Arena my_arena1{new char[sz],sz};
Arena my_arena2{new char[10*sz],10*sz};

vector<int> v0; // allocate using default allocator

vector<int,My_alloc<int>> v1 {My_alloc<int>{my_arena1}};     // construct in my_arena1

vector<int,My_alloc<int>> v2 {My_alloc<int>{my_arena2}};     // construct in my_arena2

vector<int,Simple_alloc<int>> v3;                            // construct on free store

Typically, the verbosity would be alleviated by the use of aliases. For example:

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template<typename T>
    using Arena_vec = std::vector<T,My_alloc<T>>;
template<typename T>
    using Simple_vec = std::vector<T,Simple_alloc<T>>;

My_alloc<int> Alloc2 {my_arena2};     // named allocator object

Arena_vec<complex<double>> vcd {{{1,2}, {3,4}}, Alloc2};             // explicit allocator
Simple_vec<string> vs {"Sam Vimes", "Fred Colon", "Nobby Nobbs"};    // default allocator

An allocator imposes space overhead in a container only if its objects actually have state (like My_alloc). This is usually achieved by relying on the empty-base optimization (§28.5).

34.4.1. The Default Allocator

A default allocator that allocates using new and deallocates using delete is used (by default) by all standard-library containers.

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template<typename T>
class allocator {
public:
     using size_type = size_t;
     using difference_type = ptrdiff_t;
     using pointer = T*;
     using const_pointer = const T*;
     using reference = T&;
     using const_reference = const T&;
     using value_type = T;

     template<typename U>
         struct rebind { using other = allocator<U>; };

     allocator() noexcept;
     allocator(const allocator&) noexcept;
     template<typename U>
         allocator(const allocator<U>&) noexcept;
     ~allocator();

     pointer address(reference x) const noexcept;
     const_pointer address(const_reference x) const noexcept;

     pointer allocate(size_type n, allocator<void>::const_pointer hint = 0);    // allocate n bytes
     void deallocate(pointer p, size_type n);                                   // deallocate n bytes

     size_type max_size() const noexcept;

     template<typename U, typename... Args>
         void construct(U* p, Args&&... args);          // new(p) U{args}
     template<typename U>
         void destroy(U* p);                            // p->~U()
};

The curious rebind template is an archaic alias. It should have been:

template<typename U>
using other = allocator<U>;

However, allocator was defined before such aliases were supported by C++. It is provided to allow an allocator to allocate objects of arbitrary type. Consider:

using Link_alloc = typename A::template rebind<Link>::other;

If A is an allocator, then rebind<Link>::other is an alias for allocator<Link>. For example:

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template<typename T, typename A = allocator<T>>
class list {
private:
     class Link { /* ... */ };

     using Link_alloc = typename A:: template rebind<Link>::other;   // allocator<Link>

     Link_alloc a; // link allocator
     A alloc;      // list allocator
     // ...
};

A more restricted specialization of allocator<T> is provided:

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template<>
class allocator<void> {
public:
     typedef void* pointer;
     typedef const void* const_pointer;
     typedef void value_type;
     template<typename U> struct rebind { typedef allocator<U> other; };
};

This allows us to avoid special cases: We can mention allocator<void> as long as we don’t dereference its pointers.

34.4.2. Allocator Traits

The allocators are “wired together” using allocator_traits. A property of an allocator, say, its pointer type, is found in its trait: allocator_traits<X>::pointer. As usual, the traits technique is used so that I can build an allocator for a type that does not have member types matching the requirements of an allocator, such as int, and a type designed without any thought of allocators.

Basically, allocator_traits provide defaults for the usual set of type aliases and allocator functions. Compared to the default allocator (§34.4.1), address() is missing and select_on_container_copy_construction() is added:

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template<typename A>                        // §iso.20.6.8
struct allocator_traits {
     using allocator_type = A;
     using value_type = A::value_type;
     using pointer = value_type;                                                  // trick
     using const_pointer = Pointer_traits<pointer>::rebind<const value_type>;     // trick
     using void_pointer = Pointer_traits<pointer>::rebind<void>;                  // trick
     using const_void_pointer = Pointer_traits<pointer>::rebind<const void>;      // trick
     using difference_type = Pointer_traits<pointer>::difference_type;            // trick
     using size_type = Make_unsigned<difference_type>;                            // trick
     using propagate_on_container_copy_assignment = false_type;                   // trick
     using propagate_on_container_move_assignment = false_type;                   // trick
     using propagate_on_container_swap = false_type;                              // trick

     template<typename T> using rebind_alloc = A<T,Args>;                         // trick
     template<typename T> using rebind_traits = Allocator_traits<rebind_alloc<T>>;

     static pointer allocate(A& a, size_type n) { return a.allocate(n); }         // trick
     static pointer allocate(A& a, size_type n, const_void_pointer hint)          // trick
           { return a.allocate(n,hint); }
     static void deallocate(A& a, pointer p, size_type n) { a.deallocate(p, n); } // trick

     template<typename T, typename ... Args>
           static void construct(A& a, T* p, Args&&... args)                      // trick
           { ::new (static_cast<void*>(p)) T(std::forward<Args>(args)...); }
     template<typename T>
           static void destroy(A& a, T* p) { p–>T(); }                            // trick

     static size_type max_size(const A& a)                                        // trick
           { return numeric_limits<size_type>::max() }
     static A select_on_container_copy_construction(const A& rhs) { return a; }   // trick
};

The “trick” is to use the equivalent member of the allocator A if it exists; otherwise, the default specified here. For allocate(n,hint), A::allocate(n) will be called if A has no allocate() taking a hint. The Args are any type arguments needed by A.

I am no fan of trickery in the definition of the standard library, but liberal use of enable_if() (§28.4) allows this to be implemented in C++.

To make the declarations readable, I assume a few type aliases.

34.4.3. Pointer Traits

An allocator uses pointer_traits to determine properties of pointers and proxy types for pointers:

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template<typename P>                         // §iso.20.6.3
struct pointer_traits {
     using pointer = P;
     using element_type = T;                 // trick
     using difference_type = ptrdiff_t;      // trick
     template<typename U>
        using rebind = T*;                   // trick

     static pointer pointer_to(a);           // trick
};

template<typename T>
struct pointer_traits<T*>{
     using pointer = T*;
     using element_type = T;
     using difference_type = ptrdiff_t;
     template<typename U>
         using rebind = U*;

     static pointer pointer_to(x) noexcept { return addressof(x); }
};

The “trick” is the same as used by allocator_traits (§34.4.2): to use the equivalent member of the pointer P if it exists; otherwise, the default specified here. To use the T, the template argument P must be the first argument of a Ptr<T,args> template.

This specification does violence to the C++ language.

34.4.4. Scoped Allocators

A rather sneaky problem can occur when using containers and user-defined allocators: Should an element be in the same allocation area as its container? For example, if you use Your_allocator for Your_string to allocate its elements and I use My_allocator to allocate elements of My_vector then which allocator should be used for string elements in My_vector<Your_allocator>>?

The solution is the ability to tell a container which allocator to pass to elements. The key to that is the class scoped_allocator, which provides the mechanism to keep track of an outer allocator (to be used for elements) and an inner allocator (to be passed to elements for their use):

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template<typename OuterA, typename... InnerA>         // §iso.20.12.1
class scoped_allocator_adaptor : public OuterA {
private:
     using Tr = allocator_traits<OuterA>;
public:
     using outer_allocator_type = OuterA;
     using inner_allocator_type = see below;
     using value_type = typename Tr::value_type;
     using size_type = typename Tr::size_type;
     using difference_type = typename Tr::difference_type;
     using pointer = typename Tr::pointer;
     using const_pointer = typename Tr::const_pointer;
     using void_pointer = typename Tr::void_pointer;
     using const_void_pointer = typename Tr::const_void_pointer;
     using propagate_on_container_copy_assignment = /* see §iso.20.12.2 */;
     using propagate_on_container_move_assignment = /* see §iso.20.12.2 */;
     using propagate_on_container_swap = /* see §iso.20.12.2 */;

     // ...
};

We have four alternatives for allocation of vectors of strings:

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// vector and string use their own (the default) allocator:
using svec0 = vector<string>;
svec0 v0;

// vector (only) uses My_alloc and string uses its own allocator (the default):
using Svec1 = vector<string,My_alloc<string>>;
Svec1 v1 {My_alloc<string>{my_arena1}};

// vector and string use My_alloc (as above):
using Xstring = basic_string<char,char_traits<char>, My_alloc<char>>;
using Svec2 = vector<Xstring,scoped_allocator_adaptor<My_alloc<Xstring>>>;
Svec2 v2 {scoped_allocator_adaptor<My_alloc<Xstring>>{my_arena1}};

// vector uses its own alloctor (the default) and string uses My_alloc:
using Xstring2 = basic_string<char, char_traits<char>, My_alloc<char>>;
using Svec3 = vector<xstring2,scoped_allocator_adaptor<My_alloc<xstring>,My_alloc<char>>>;
Svec3 v3 {scoped_allocator_adaptor<My_alloc<xstring2>,My_alloc<char>>{my_arena1}};

Obviously, the first variant, Svec0, will be by far the most common, but for systems with serious memory-related performance constraints, the other versions (especially Svec2) can be important. A few more aliases would make that code a bit more readable, but it is good that this is not the kind of code you have to write every day.

The definition of scoped_allocator_adaptor is somewhat involved, but basically it is an allocator much like the default allocator (§34.4.1) that also keeps track of its “inner” allocator to be passed along for use by contained containers, such as string:

34.5. The Garbage Collection Interface

Garbage collection (automatic recycling of unreferenced regions of memory) is sometimes presented as a panacea. It is not. In particular, resources that are not pure memory can be leaked by a garbage collector. Examples are file handles, thread handles, and locks. I see garbage collection as a convenient last resort after the usual techniques for preventing leaks have been exhausted:

[1] Use resource handles with the proper semantics for an application whenever possible. The standard library provides string, vector, unordered_map, thread, lock_guard, and more. Move semantics allow such objects to be efficiently returned from a function.

[2] Use unique_ptrs to hold on to objects that do not implicitly manage their own resources (such as pointers), need to be protected from premature deletion (because they don’t have proper destructors), or need to be allocated in ways that require special attention (deleters).

[3] Use shared_ptrs to hold objects that require shared ownership.

If consistently used, this sequence of techniques ensures the absence of leaks (i.e., no garbage collection is needed because no garbage is generated). However, in a very large number of real-world programs these techniques (all based on RAII; §13.3) are not consistently used and cannot be easily applied because they involve huge amounts of code structured in different ways. These “different ways” often involve complicated pointer uses, naked news and deletes, explicit type conversions that obscure resource ownership, and similar error-prone low-level techniques. In such cases, a garbage collector is an appropriate last resort. It can reclaim/recycle memory, even if it cannot handle non-memory resources. Don’t even think of using general “finalizers” called at collection time to try to deal with non-memory resources. A garbage collector can sometimes extend the running time for leaking systems (even systems that leak non-memory resources) significantly. For example, a garbage collector might extend the time between resource exhaustion from hours to days for a system that is taken down every night for maintenance. Also, a garbage collector can be instrumented to find the sources of leaks.

It is worth remembering that a garbage-collected system can have its own variants of leaks. For example, if we put a pointer to an object into a hash table and forget its key, the object is de facto leaked. Similarly, a resource referred to by an infinite thread can live forever, even if the thread wasn’t meant to be infinite (e.g., it could be waiting for input that never arrives). Sometimes, resources “living” for an excessive time can be as bad for a system as a permanent leak.

From this basic philosophy it follows that garbage collection is optional in C++. A garbage collector will not be invoked unless explicitly installed and activated. A garbage collector is not even a required part of a standard C++ implementation, but good free and commercial collectors are available. C++ provides a definition of what a garbage collector can do if one is used and an ABI (Application Binary Interface) to help control its actions.

The rules for pointers and lifetimes are expressed in terms of safely-derived pointers (§iso.3.7.4.3). A safely-derived pointer is (roughly) “a pointer to something allocated by new or to a subobject thereof.” Here are some examples of pointers that are not safely derived, also known as disguised pointers. Make a pointer point “elsewhere” for a while:

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int* p = new int[100];
p+=10;
// ... collector may run here ...
p –=10;
*p = 10; // can we be sure that the int is still there?

Hide the pointer in an int:

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int* p = new int;
int x = reinterpret_cast<int>(p);     // not even portable
p = nullptr;
// ... collector may run here ...
p = reinterpret_cast<int*>(x);
*p = 10;  // can we be sure that the int is still there?

Write a pointer to a file and read it back later:

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int* p = new int;
cout << p;
p = nullptr;
// ... collector may run here ...
cin >> p;
*p = 10; // can we be sure that the int is still there?

Use the “xor trick” to compress doubly-linked lists:

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using Link = pair<Value,long>;

long xor(Link* pre, Link* suc)
{
     static_assert(sizeof(Link*)<=sizeof(long),"a long is smaller than a pointer");
     return long{pre}^long{suc};
}

void insert_between(Value val, Link* pre, Link* suc)
{
     Link* p = new Link{val,xor(pre,suc)};
     pre–>second = xor(xor(pre–>second,suc),p);
     suc–>second = xor(p,xor(suc–>second,pre));
}

Using that trick, no undisguised pointers to links are stored.

Don’t use such tricks in a program you want to be considered well behaved and comprehensible to ordinary mortals – even if you don’t plan to use a garbage collector. There are many more and even nastier tricks, such as scattering the bits of a pointer around in different words.

There are legitimate reasons to disguise pointers (e.g., the xor trick in exceptionally memory-constrained applications), but not as many as some programmers think.

A disguised pointer can still be found by a careful garbage collector if its bitpattern is stored in memory with a wrong type (e.g., long or char[4]) and is still properly aligned. Such pointers are called traceable.

The standard library allows a programmer to specify where there are no pointers to be found (e.g., in an image) and what memory should not be reclaimed even if the collector can’t find a pointer into it (§iso.20.6.4):

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void declare_reachable(void* p);        // the object pointed to by p must not be collected
template<typename T>
    T* undeclare_reachable(T* p);       // undo a declare_reachable()

void declare_no_pointers(char* p, size_t n);       // p[0:n) holds no pointers
void undeclare_no_pointers(char* p, size_t n);     // undo a declare_no_pointers()

C++ garbage collectors have traditionally been conservative collectors; that is, they do not move objects around in memory and have to assume that every word in memory might contain a pointer. Conservative garbage collection is more efficient than it is reputed to be, especially when a program doesn’t generate much garbage, but declare_no_pointers() can make it very efficient by safely eliminating large parts of memory from consideration. For example, we might use declare_no_pointers() to tell the collector where our photographic images are in an application, so as to allow the collector to ignore potentially gigabytes of non-pointer data.

A programmer can inquire which rules for pointer safety and reclamation are in force:

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enum class pointer_safety {relaxed, preferred, strict };

pointer_safety get_pointer_safety();

The standard says (§iso.3.7.4.3): “a pointer value that is not a safely-derived pointer value is an invalid pointer value unless the referenced complete object is of dynamic storage duration and has previously been declared reachable ... the effect of using an invalid pointer value (including passing it to a deallocation function) is undefined.”

The enumerators mean:

• relaxed: Safely-derived and not safely-derived pointers are treated equivalently (as in C and C++98). Collect every object that does not have a safely derived or traceable pointer to it.

• preferred: Like relaxed, but a garbage collector may be running as a leak detector and/or a detector of dereferences of “bad pointers.”

• strict: Safely-derived and not safely-derived pointers may be treated differently; that is, a garbage collector may be running and will ignore pointers that’s not safely derived.

There is no standard way of saying which alternative you prefer. Consider that a quality-of-implementation issue or a programming environment issue.

34.6. Uninitialized Memory

Most of the time, it is best to avoid uninitialized memory. Doing so simplifies programming and eliminates many kinds of errors. However, in relatively rare cases, such as when writing memory allocators, implementing containers, and dealing directly with hardware, direct use of uninitialized memory, also known as raw memory, is essential.

In addition to the standard allocator, the <memory> header provides the fill* family of functions for dealing with uninitialized memory (§32.5.6). They share the dangerous and occasionally essential property of using a type name T to refer to space sufficient to hold an object of type T rather than to a properly constructed object of type T. These functions are intended primarily for implementers of containers and algorithms. For example, reserve() and resize() are most easily implemented using these functions (§13.6).

34.6.1. Temporary Buffers

Algorithms often require temporary space to perform acceptably. Often, such temporary space is best allocated in one operation but not initialized until a particular location is actually needed. Consequently, the library provides a pair of functions for allocating and deallocating uninitialized space:

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template<typename T>
    pair<T*,ptrdiff_t> get_temporary_buffer(ptrdiff_t); // allocate, don't initialize
template<typename T>
    void return_temporary_buffer(T*);                   // deallocate, don't destroy

A get_temporary_buffer<X>(n) operation tries to allocate space for n or more objects of type X. If it succeeds in allocating some memory, it returns a pointer to the first uninitialized space and the number of objects of type X that will fit into that space; otherwise, the second value of the pair is zero. The idea is that a system may keep space ready for fast allocation so that requesting space for n objects of a given size may yield space for more than n. It may also yield less, however, so one way of using get_temporary_buffer() is to optimistically ask for a lot and then use what happens to be available.

A buffer obtained by get_temporary_buffer() must be freed for other use by a call of return_temporary_buffer(). Just as get_temporary_buffer() allocates without constructing, return_temporary_buffer() frees without destroying. Because get_temporary_buffer() is low-level and likely to be optimized for managing temporary buffers, it should not be used as an alternative to new or allocator::allocate() for obtaining longer-term storage.

34.6.2. raw_storage_iterator

The standard algorithms that write into a sequence assume that the elements of that sequence have been previously initialized. That is, the algorithms use assignment rather than copy construction for writing. Consequently, we cannot use uninitialized memory as the immediate target of an algorithm. This can be unfortunate because assignment can be significantly more expensive than initialization, and to initialize immediately before overwriting is a waste. The solution is to use a raw_storage_iterator from <memory> that initializes instead of assigns:

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template<typename Out, typename T>
class raw_storage_iterator : public iterator<output_iterator_tag,void,void,void,void> {
     Out p;
public:
     explicit raw_storage_iterator(Out pp) : p{pp} { }
     raw_storage_iterator& operator*() { return *this; }

     raw_storage_iterator& operator=(const T& val)
     {
         new(&*p) T{val};   // place val in *p (§11.2.4)
         return *this;
     }

     raw_storage_iterator& operator++() {++p; return *this; }    // pre-increment
     raw_storage_iterator operator++(int)                        // post-increment
     {
         auto t = *this;
         ++p;
         return t;
     }
};

A raw_storage_iterator should never be used to write to initialized data. This tends to limit its use to the depth of implementations of containers and algorithms. Consider generating a set of permutations (§32.5.5) of strings for use in testing:

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void test1()
{
     auto pp = get_temporary_buffer<string>(1000);    // get uninitialized space
     if (pp.second<1000) {
          // ... handle allocation failure ...
     }
     auto p = raw_storage_iterator<string*,string>(pp.first); // the iterator
     generate_n(p,a.size(),
         [&]{ next_permutation(seed,seed+sizeof(seed)–1); return seed; });
     // ...
     return_temporary_buffer(p);
}

This is a somewhat contrived example because I see nothing wrong in allocating default initialized storage for the strings and then assigning the test strings. Also, it fails to use RAII (§5.2, §13.3).

Note that there are no == or != operators for raw_storage_iterator, so don’t try to use it to write to a [b:e) range. For example iota(b,e,0) (§40.6) will not work if b and e are raw_storage_iterators. Don’t mess with uninitialized memory unless you absolutely have to.

34.7. Advice

[1] Use array where you need a sequence with a constexpr size; §34.2.1.

[2] Prefer array over built-in arrays; §34.2.1.

[3] Use bitset if you need N bits and N is not necessarily the number of bits in a built-in integer type; §34.2.2.

[4] Avoid vector<bool>; §34.2.3.

[5] When using pair, consider make_pair() for type deduction; §34.2.4.1.

[6] When using tuple, consider make_tuple() for type deduction; §34.2.4.2.

[7] Use unique_ptr to represent exclusive ownership; §34.3.1.

[8] Use shared_ptr to represent shared ownership; §34.3.2.

[9] Minimize the use of weak_ptrs; §34.3.3.

[10] Use allocators (only) when the usual new/delete semantics is insufficient for logical or performance reasons; §34.4.

[11] Prefer resource handles with specific semantics to smart pointers; §34.5.

[12] Prefer unique_ptr to shared_ptr; §34.5.

[13] Prefer smart pointers to garbage collection; §34.5.

[14] Have a coherent and complete strategy for management of general resources; §34.5.

[15] Garbage collection can be really useful for dealing with leaks in programs with messy pointer use; §34.5.

[16] Garbage collection is optional; §34.5.

[17] Don’t disguise pointers (even if you don’t use garbage collection); §34.5.

[18] If you use garbage collection, use declare_no_pointers() to let the garbage collector ignore data that cannot contain pointers; §34.5.

[19] Don’t mess with uninitialized memory unless you absolutely have to; §34.6.

35. Utilities

The time you enjoy wasting is not wasted time.

– Bertrand Russell

• Introduction

• Time

duration; time_point; Clocks; Time Traits

• Compile-Time Rational Arithmetic

• Type Functions

Type Traits; Type Generators

• Minor Utilities

move() and forward(); swap(); Relational Operators; Comparing and Hashing type_info

• Advice

35.1. Introduction

The standard library provides many “utility components” that are so widely useful that they are not easily classified as part of some major standard-library component.

35.2. Time

In <chrono>, the standard library provides facilities for dealing with time durations and time points. All chrono facilities are in the std::chrono (sub)namespace, so we have to either explicitly qualify with chrono:: or add a using-directive:

using namespace std::chrono;

We often want to time things or to do things that depend on timing. For example, the standard-library mutexes and locks provide the option for a thread to wait for a period of time (a duration) or to wait until a given point in time (a time_point).

If you want to know the current time_point, you can call now() for one of three clocks: system_clock, steady_clock, high_resolution_clock. For example:

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steady_clock::time_point t = steady_clock::now();
// ... do something ...
steady_clock::duration d = steady_clock::now()–t;    // something took d time units

A clock returns a time_point, and a duration is the difference between two time_points from the same clock. As usual, if you are not interested in details, auto is your friend:

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auto t = steady_clock::now();
// ... do something ...
auto d = steady_clock::now()–t;   // something took d time units
cout << "something took " << duration_cast<milliseconds>(d).count() << "ms"; // print as milliseconds

The time facilities here are intended to efficiently support uses deep in the system; they do not provide convenience facilities to help you maintain your social calendar. In fact, the time facilities originated with the stringent needs of high-energy physics.

It turns out that “time” is far more complicated to deal with than we usually think. For example, we have leap seconds, clocks that are not accurate and must be adjusted (possibly causing time as reported by a clock to go backward), clocks of differing precision, etc. Furthermore, language facilities for dealing with short time spans (e.g., nanoseconds) must not themselves take significant time. Consequently, the chrono facilities are not simple, but many uses of those facilities can be very simple.

The C-style time utilities can be found in §43.6.

35.2.1. duration

In <chrono>, the standard library provides type duration to represent the time between two points in time (time_points §35.2.2):

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template<typename Rep, typename Period = ratio<1>>
class duration {
public:
     using rep = Rep;
     using period = Period;
     // ...
};

We can define a duration with a specific period value. For example:

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duration<long long,milli> d1 {7};  // 7 milliseconds
duration<double,pico> d2 {3.33};   // 3.33 picoseconds
duration<int,ratio<1,1>> d3 {};    // 0 seconds

A duration’s period holds the number of clock ticks of the period.

cout << d1.count() << '\n';       // 7
cout << d2.count() << '\n';       // 3.33
cout << d3.count() << '\n';       // 0

Naturally, the value of count() depends on the period:

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d2=d1;
cout << d1.count() << '\n';        // 7
cout << d2.count() << '\n';        // 7e+009
if (d1!=d2) cerr<<"insane!";

Here, d1 and d2 are equal but report very different count() values.

Care is taken to avoid truncation or loss of precision during initialization (even if the {} notation is not used). For example:

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duration<int, milli> d {3};         // OK
duration<int, milli> d {3.5};       // error: 3.5 to int is narrowing

duration<int, milli> ms {3};
duration<int, micro> us {ms};       // OK
duration<int, milli> ms2 {us};      // error: we could lose many microseconds

The standard library provides meaningful arithmetic operations on durations:

The period is a unit system, so there is no = or += taking a plain value. Allowing that would be like allowing the addition of 5 of an unknown SI unit to a length in meters. Consider:

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duration<long long,milli> d1 {7};  // 7 milliseconds
d1 += 5;       // error

duration<int,ratio<1,1>> d2 {7};         // 7 seconds
d2 = 5;        // error
d2 += 5;       // error

What would 5 mean here? 5 seconds? 5 milliseconds? Something else? If you know what you mean, be explicit about it. For example:

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d1 += duration<long long,milli>{5}; // OK: milliseconds
d3 += decltype(d2){5};              // OK: seconds

Arithmetic involving durations with different representations is allowed as long as the combination makes sense (§35.2.4):

Comparisons between and explicit conversion between durations with compatible representations are supported:

The standard library provides some convenience aliases using the SI units from <ratio> (§35.3):

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using nanoseconds = duration<si64,nano>;
using microseconds = duration<si55,micro>;
using milliseconds = duration<si45,milli>;
using seconds = duration<si35>;
using minutes = duration<si29,ratio<60>>;
using hours = duration<si23,ratio<3600>>;

Here, siN means “an implementation-defined signed integer type of at least N bits.”

The duration_cast is used to get a duration with a known unit of measurement. For example:

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auto t1 = system_clock::now();
f(x); // do something
auto t2 = system_clock::now();

auto dms = duration_cast<milliseconds>(t2–t1);
cout << "f(x) took " << dms.count() << " milliseconds\n";

auto ds = duration_cast<seconds>(t2–t1);
cout << "f(x) took " << ds.count() << " seconds\n";

The reason we need a cast in this example is that we are throwing away information: on the system I used, the system_clock counts in nanoseconds.

Alternatively, we can simply (try to) construct a suitable duration:

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auto t1 = system_clock::now();
f(x); // do something
auto t2 = system_clock::now();

cout << "f(x) took " << milliseconds(t2–t1).count() << " milliseconds\n";        // error: truncation
cout << "f(x) took " << microseconds(t2–t1).count() << " microseconds\n";

The precision of a clock is implementation-dependent.

35.2.2. time_point

In <chrono>, the standard library provides type time_point to represent a point in time of a given epoch as measured by a given clock:

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template<typename Clock, typename Duration = typename Clock::duration>
class time_point {
public:
     using clock = Clock;
     using duration = Duration;
     using rep = typename duration::rep;
     using period = typename duration::period;
     // ...
};

An epoch is a range of time determined by a clock, measured in terms of a duration, starting at the duration::zero():

For example:

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void test()
{
     time_point<steady_clock,milliseconds> tp1(milliseconds(100));
     time_point<steady_clock,microseconds> tp2(microseconds(100*1000));

     tp1=tp2;     // error: would truncate
     tp2=tp1;     // OK

     if (tp1!=tp2) cerr << "Insane!";
}

As for durations, meaningful arithmetic and comparisons are supported for time_points:

For example:

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void test2()
{
     auto tp = steady_clock::now();
     auto d1 = time_point_cast<hours>(tp).time_since_epoch().count()/24; // days since start of epoch

     using days = duration<long,ratio<24*60*60,1>>;                      // a day's duration
     auto d2 = time_point_cast<days>(tp).time_since_epoch().count();     // days since start of epoch

     if (d1!=d2) cout << "Impossible!\n";
}

The time_point operations that do not access a clock can be constexpr, but are not currently guaranteed to be so.

35.2.3. Clocks

The time_point and duration values are ultimately obtained from hardware clocks. In <chrono>, the standard library provides basic interfaces for clocks. Class system_clock represents “wall clock time” as obtained from a system’s real-time clock:

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class system_clock {
public:
     using rep = /* implementation-defined signed type */;
     using period = /* implementation-defined ratio<> */;
     using duration = chrono::duration<rep,period>;
     using time_point = chrono::time_point<system_clock>;
     // ...
};

All data and function members are static. We don’t explicitly deal with clock objects. Instead, we use clock types:

For example:

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void test3()
{
     auto t1 = system_clock::now();
     f(x); // do something
     auto t2 = system_clock::now();
     cout << "f(x) took " << duration_cast<milliseconds>(t2–t1).count() << " ms";
}

A system provides three named clocks:

These three clocks need not be different; a standard-library clock name may be an alias.

We can determine the basic properties of the clocks like this:

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cout << "min " << system_clock::duration::min().count()
     << ", max " << system_clock::duration::max().count()
     << ", " << (treat_as_floating_point<system_clock::duration>::value ? "FP" : "integral") << '\n';

cout << (system_clock::is_steady?"steady\n": "not steady\n");

When I ran it on one of my systems, this produced:

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min –9223372036854775808, max 9223372036854775807, integral
not steady

Different systems and different clocks can give different results.

35.2.4. Time Traits

Implementations of the chrono facilities depend on a few standard facilities, collectively known as time traits.

The conversion rules for duration and time_point depend on whether their representation is floating-point (so that rounding is acceptable) or integral:

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template<typename Rep>
struct treat_as_floating_point : is_floating<Rep> { };

A few standard values are provided:

The common type of two durations is determined by computing their greatest common denominator (GCD):

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template<typename Rep1, typename P1, typename Rep2, typename P2>
struct common_type<duration<Rep1,P1>, duration<Rep2, P2>> {
     using type = duration<typename common_type<Rep1,Rep2>::type, GCD<P1,P2>> ;
};

This makes type an alias for the duration with the largest possible tick period so that both duration arguments will convert to it without requiring a division operation. This implies that common_type<R1,P1,R2,P2>::type can hold any value from duration<R1,R2> and duration<R2,P2> without truncation error. However, floating-point durations may have round-off errors.

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template<typename Clock, typename Duration1, typename Duration2>
struct common_type<time_point<Clock, Duration1>, time_point<Clock, Duration2>> {
     using type = time_point<Clock, typename common_type<Duration1, Duration2>::type>;
};

In words, to have a common_type, two time_points must have a common clock type. Their common_type is a time_point with the common_type of their durations.

35.3. Compile-Time Rational Arithmetic

In <ratio>, we find class ratio, which provides compile-time rational arithmetic. The standard library uses ratio to provide a compile-time representation of time duration and time points (§35.2):

template<intmax_t N, intmax_t D = 1>
struct ratio {
     static constexpr intmax_t num;
     static constexpr intmax_t den;

     using type = ratio<num,den>;
};

The basic idea is to encode the numerator and denominator of a rational number as (value) template arguments. The denominator must always be nonzero.

For example:

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static_asser t(ratio_add<ratio<1,3>, ratio<1,6>>::num == 1, "problem: 1/3+1/6 != 1/2");
static_asser t(ratio_add<ratio<1,3>, ratio<1,6>>::den == 2, "problem: 1/3+1/6 != 1/2");
static_asser t(ratio_multiply<ratio<1,3>, ratio<3,2>>::num == 1, "problem: 1/3*3/2 != 1/2");
static_asser t(ratio_multiply<ratio<1,3>, ratio<3,2>>::den == 2, "problem: 1/3*3/2 != 1/2");

Obviously, this is not a convenient way of expressing numbers and arithmetic. In <chrono>, we find the conventional notation (e.g., + and *) for rational arithmetic for time (§35.2). Similarly, to help express unit values, the standard library provides common SI magnitude names:

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using yocto  = ratio<1,1000000000000000000000000>;     // conditionally supported
using zepto  = ratio<1,1000000000000000000000>;  // conditionally supported
using atto   = ratio<1,1000000000000000000>;
using femto  = ratio<1,1000000000000000>;
using pico   = ratio<1,1000000000000>;
using nano   = ratio<1,1000000000>;
using micro  = ratio<1,1000000>;
using milli  = ratio<1,1000>;
using centi  = ratio<1,100>;
using deci   = ratio<1,10>;
using deca   = ratio<10,1>;
using hecto  = ratio<100,1>;
using kilo   = ratio<1000,1>;
using mega   = ratio<1000000,1>;
using giga   = ratio<1000000000,1>;
using tera   = ratio<1000000000000,1>;
using peta   = ratio<1000000000000000,1>;
using exa    = ratio<1000000000000000000,1>;
using zetta  = ratio<1000000000000000000000,1>;   // conditionally supported
using yotta  = ratio<1000000000000000000000000,1>;      // conditionally supported

For an example of use, see §35.2.1.

35.4. Type Functions

In <type_traits>, the standard library provides type functions (§28.2) to determine properties of types (type traits; §35.4.1) and to generate new types from existing ones (type generators; §35.4.2). These type functions are primarily used at compile time to support simple, and not so simple, metaprogramming.

35.4.1. Type Traits

In <type_traits>, the standard library provides a large set of type functions that allow a programmer to determine properties of a type or a pair of types. Their names are mostly self-explanatory. The primary type predicates test fundamental properties of a type:

A type trait returns a value that is used as a Boolean. To access that value, use the suffix ::value. For example:

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template<typename T>
void f(T& a)
{
     static_asser t(std::is_floating_point<T>::value ,"FP type expected");
     // ...
}

If you tire of the ::value notation, define a constexpr function (§28.2.2):

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template<typename T>
constexpr bool Is_floating_point<T>()
{
    return std::is_floating_point<T>::value;
}

template<typename T>
void f(T& a)
{
     static_asser t(Is_floating_point<T>(),"FP type expected");
     // ...
}

Ideally, use a library that provides such functions for all standard library type traits.

Some type functions inquire about a combination of fundamental properties:

These composite type predicates simply offer notational convenience. For example, is_reference<X> is true if X is either an lvalue reference or an rvalue reference.

Like the primary type predicates, type property predicates provide tests for fundamental aspects of a type:

For example:

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template<typename T>
class Cont {
     T* elem; // store elements in an array pointed to by elem
     int sz;  // sz elements
     // ...
     Cont(const Cont& a)     // copy constructor
         :sz(a.sz), elem(new T[a.elem])
     {
         static_asser t(Is_copy_constructable<T>(),"Cont::Cont(): no copy");
         if (Is_trivially_copyable<T>())
                memcpy(elem,a.elem,sz*sizeof(T));    // memcopy optimization
         else
                uninitialized_copy(a.begin(),a.end(),elem); // use copy constructors
     }
     // ...
}

This optimization may be unnecessary, though, because uninitialized_copy() is likely to already have been optimized in this way.

For a class to be empty, it can have no virtual functions, no virtual bases, and no base classes for which !is_empty<Base>::value.

The type property predicates don’t do access checking depending on where they are used. Instead, they consistently give the result you would expect for a use outside members and friends. For example:

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class X {
public:
     void inside();
private:
     X& operator=(const X&);
     ~X();
};

void X::inside()
{
     cout << "inside =: " << is_copy_assignable<X>::value << '\n';
     cout << "inside ~: " << is_destructible<X>::value << '\n';
}

void outside()
{
     cout << "outside =: " << is_copy_assignable<X>::value << '\n';
     cout << "outside ~: " << is_destructible<X>::value << '\n';
}

Both inside() and outside() will write 00 to report that an X is neither destructible nor copy assignable. Also, if you want to eliminate an operation, use =delete (§17.6.4) rather than relying as private.

For example, consider how we might optimize the destructor for a container type:

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template<class T>
Cont::~Cont()         // destructor for a container Cont
{
    if (!Is_trivially_destructible<T>())
           for (T* p = elem; p!=p+sz; ++p)
                 p–>~T();
}

Like sizeof(T), a property query returns a numeric value related to a type argument:

For example:

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template<typename T>
void f(T a)
{
     static_asser t(Is_array<T>(), "f(): not an array");
     constexpr int dn {Extent<a,2>()};     // the number of elements in the 2nd dimension (zero based)
     // ..
}

Here, I again used constexpr versions of the type functions returning numeric values (§28.2.2).

The type relations are predicated on two types:

For example:

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template<typename T>
void draw(T t)
{
     static_assert(Is_same<Shape*,T>() || Is_base_of<Shape,Remove_pointer<T>>(), "");
     t–>draw();
}

35.4.2. Type Generators

In <type_traits>, the standard library provides type functions for producing a type given other types as arguments.

A type transformer returns a type. To access that type, use the suffix ::type. For example:

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template<typename K, typename V>
class My_map {
{
     pair<typename add_const<K>::type,V> default_node;
     // ...
};

If you tire of the ::type define a type alias (§28.2.1):

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template<typename T>
using Add_const = typename add_const<T>::type;

template<typename K, typename V>
class My_map {
{
     pair<Add_const<K>,V> default_node;
     // ...
};

Ideally, use a support library that provides such aliases systematically for the standard-library type transformers.

The decay functions handles array decay as well as reference dereferencing.

The type functions for adding and removing references are important for when writing templates that should work with an argument that may be reference or not. For example:

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template<typename T>
void f(T v)
{
     Remove_reference<T> x = v;  // copy of v
     T y = v;                    // maybe copy of v; maybe a reference to x
     ++x;                        // increment local variable
     ++y;
     // ...
}

Here, x really is a copy of v, but if T is a reference type, y is a reference to v:

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void user()
{
     int val = 7;
     f(val);    // call f<int&>(): the ++y in f() will increment val
     f(7);      // call f<int>(): the ++y in f will increment a local copy
}

In both calls, ++x will increment a local copy.

For built-in arrays, we sometimes want to get the element type or to remove a dimension:

For example:

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int a[10][20];
Remove_extent<decltype(a)> a10; // an array[10]
Remove_all_extents<decltype(a)> i;    // an int

We can make a pointer type pointing to an arbitrary type, or find the pointed-to type:

For example:

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template<typename T>
void f(T x)
{
     Add_pointer<T> p = new Remove_reference<T>{};
     T* p = new T{};   // would not work if T is a reference
     // ...
}

When dealing with memory at the lowest levels of a system, we must sometimes consider alignment (§6.2.9):

The standard mentions this as a possible implementation of aligned_storage:

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template<std::size_t N, std::size_t A>
struct aligned_storage {
     using type = struct { alignas(A) unsigned char data[N]; };   // N chars aligned to A (§6.2.9)
};

The final type functions for type selection, computing common types, etc. are arguably the most useful:

For examples of enable_if and conditional, see §28.3.1.1 and §28.4.

It is often useful to find a type that can be used for operations on more than one type, such as the result of an addition of two values of related but different types. The type function common_type finds such common types. A type is the common type of itself (obviously):

template<typename... T>
struct common_type;

template<typename T>
struct common_type<T> {
     using type = T;
};

The common type of two types is what the rules for ?: (§11.1.3) give us:

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template<typename T, typename U>
struct common_type<T, U> {
     using type = decltype(true ? declval<T>() : declval<U>());
};

The declval<T>() type function returns the type of an unevaluated variable of type T.

The common type for N types is found by applying the rules for N==1 and N==2 recursively:

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template<typename T, typename U, typename ... V>
struct common_type<T, U, V...> {
     using type = typename common_type<typename common_type<T, U>::type, V...>::type;
};

For example:

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template<typename T, typename U>
using Common_type = typename common_type<T,U>::type;

Common_type<int,double> x1;               // x1 is a double
Common_type<int,string> x2;               // error: no common type
Common_type<int,short,long,long long> x3; // x3 is a long long
Common_type<Shape*,Circle*> x4;           // x4 is a Shape*
Common_type<void*,double*,Shape*> x5;     // x5 is a void*

Result_of is used to extract the type of the result of a callable type:

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int ff(int) { return 2; }                      // function

typedef bool (*PF)(int);                       // pointer to function

struct Fct {                                   // function object
     double operator()(string);
     string operator()(int,int);
};

auto fx = [](char ch) { return tolower(ch); }; // lambda

Result_of<decltype(&ff)()> r1 = 7;         // r1 is a int
Result_of<PF(int)> r2 = true;              // r2 is a bool
Result_of<Fct(string)> r3 = 9.9;           // r3 is a double
Result_of<Fct(int,int)> r4 = "Hero";       // r4 is a string
Result_of<decltype(fx)(char)> r5 = 'a';    // r5 is a char

Note that Result_of can distinguish between the two versions of Fct::operator()().

Curiously enough, the same does not apply to nonmember functions. For example:

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int f();                               // function
string f(int);
Result_of<decltype(&f)()> r1 = 7;      // error: no overload resolution for pointer to function

Unfortunately, we don’t do overload resolution for pointers to functions, but why did I use Result_of in such a roundabout way, instead of:

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Result_of<ff> r1 = 7;                 // error: no argument specification,
                                      // and ff is a function rather than a type
Result_of<ff()> r1 = 7;               // error: the argument to Result_of must be a type
Result_of<decltype(f)()> r2 = 7;      // error: decltype(f) is a function type
                                      // rather than a pointer to function type
Result_of<decltype(f)*()> r3 = 7;     // OK: r3 is an int

Naturally, Result_of is usually found in templates where we can’t easily look up the answer in the program text. For example:

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template<typename F, typename A>
auto temp(F f, A a) –> Result_of<F(A)>
{
     // ...
}

void f4()
{
     temp(ff,1);
     temp(fx,'a');
     temp(Fct(),"Ulysses");
}

Note that the function ff is converted to a pointer function in the call, so the reliance on pointers to functions in Result_of isn’t as odd as it may seem at first.

The declval() type function is unusual in the standard library because it is actually a function (without users needing to wrap it). It returns a value that must never be used. The intent is to use declval<X> as a type where the type of a variable of type X is needed. For example:

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template<typename T, size_t N>
void array<T,N> swap(array& y) noexcept(noexcept(swap(declval<T&>(), declval<T&>())))
{
     for (int i=0; i<a.size(); ++i)
           swap((*this)[i],a[i]);
}

See also the definition of common_type.

35.5. Minor Utilities

These utilities are minor in size, but not in importance. They don’t fit into a larger grouping.

35.5.1. move() and forward()

In <utility>, we find some of the most useful small functions:

A move() is simply a cast to an rvalue:

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template<typename T>
Remove_reference<T>&& move(T&& t) noexcept
{
   return static_cast<Remove_reference<T>&&>(t);
}

In my opinion, move() should have been called rvalue(), because it doesn’t actually move anything. Instead, it produces an rvalue for its argument, so that the object referred to can be moved from.

A move() is used to tell the compiler that an object will not be used anymore in a context, so that its value can be moved and an empty object left behind. The simplest example is the implementation of swap() (§35.5.2).

A forward() produces an rvalue from an rvalue only:

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template<typename T>
T&& forward(Remove_reference<T>& t) noexcept
{
    return static_cast<T&&>(t);
}

template<typename T>
T&& forward(Remove_reference<T>&& t) noexcept;
{
    static_assert(!Is_lvalue_reference<T>,"forward of lvalue");
    return static_cast<T&&>(t);
}

This pair of forward() functions are meant always to be available together, and selection between them should be done by overload resolution. In that case, any lvalue goes to the first version and every rvalue to the second. For example:

int i = 7;
forward(i);       // call first version
forward(7);       // call second version

The assert is there for programmer who are too clever for their own good and calls the second version with an explicit template argument and an lvalue.

The archetypical use of forward() is for “perfect forwarding” of an argument from one function to another (§23.5.2.1, §28.6.3). The standard-library make_shared<T>(x) (§34.3.2) is a good example.

Use move() when the intent is to “steal the representation” of an object with a move operation, and use forward() for forwarding. Thus, forward(x) is safe, whereas move(x) marks x for destruction so that move(x) should be used with care. The only safe use of an x after a move(x) is destruction or as a target for an assignment. Obviously a particular type could provide further guarantees, and ideally the class’s invariant is left intact. However, don’t rely on that unless you really know.

35.5.2. swap()

In <utility>, the standard library provides a general swap() and a specialization for built-in arrays:

The relatively obvious implementation swap() is:

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template<typename T>
void swap(T& a, T& b) noexcept(Is_nothrow_move_constructible<T>()
                          && Is_nothrow_move_assignable<T>())
{
     T tmp {move(a)};
     a = move(b);
     b = move(tmp);
}

This implies that swap() cannot be used to exchange rvalues:

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vector<int> v1 {1,2,3,4};
swap(v,vecor<int>{});        // error: second argument is an rvalue
v.clear();                   // clearer (less obscure)

35.5.3. Relational Operators

In <utility>, we find relational operators for arbitrary types in a sub-namespace rel_ops:

This requires that the programmer has made sure that x==y and x<y work.

For example:

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struct Val {
     double d;
     bool operator==(Val v) const { return v.d==d; }
};

void my_algo(vector<Val>& vv)
{
     using namespace std::rel_ops;

     for (int i=0; i<ww.size(); ++i)
           if (0>ww[i]) ww[i]=abs(ww[i]); // OK: > from rel_ops
}

It can be hard to use rel_ops without polluting a namespace. In particular:

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namespace Mine {
   struct Val {
        double d;
        bool operator==(Val v) const { return v.d==d; }
   };

   using namespace std::rel_ops;
}

This could expose the perfectly general templates from rel_ops to be found by argument-dependent lookup (§14.2.4) and applied to types for which they may be inappropriate. A safer approach is to place using-directives in local scopes.

35.5.4. Comparing and Hashing type_info

In <typeindex>, the standard library provides support for comparing and hashing type_indexs. A type_index is created from a type_info (§22.5), specifically to allow such comparison and hashing.

For example:

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unordered_map<type_index,type_info*> types;
// ...
types[type_index{something}] = &typeid(something);

35.6. Advice

[1] Use <chrono> facilities, such as steady_clock, duration, and time_point for timing; §35.2.

[2] Prefer <clock> facilities over <ctime> facilities; §35.2.

[3] Use duration_cast to get durations in known units of time; §35.2.1.

[4] Use system_clock::now() to get the current time; §35.2.3.

[5] You can inquire about properties of types at compile time; §35.4.1.

[6] Use move(obj) only when the value of obj cannot be used again; §35.5.1.

[7] Use forward() for forwarding; §35.5.1.

36. Strings

Prefer the standard to the offbeat.

– Strunk & White

• Introduction

• Character Classification

Classification Functions; Character Traits

• Strings

string vs. C-Style Strings; Constructors; Fundamental Operations; String I/O; Numeric Conversions; STL-like Operations; The find Family; Substrings

• Advice

36.1. Introduction

The standard library offers character classification operations in <cctype> (§36.2), strings with associated operations in <string> (§36.3), regular expression matching in <regex> (Chapter 37), and support for C-style strings in <cstring> (§43.4). Handling of different character sets, encodings, and conventions (locales) is discussed in Chapter 39.

A simplified string implementation is presented in §19.3.

36.2. Character Classification

The standard library provides classification functions to help users to manipulate strings (and other character sequences) and traits specifying properties of a character type to help implementers of operations on strings.

36.2.1. Classification Functions

In <cctype>, the standard library provides functions to classify the characters from the basic execution character set:

In addition, the standard library provides two useful functions for removing case differences:

The equivalent functions for wide characters are provided in <cwctype>.

The character classification functions are sensitive to the "C" locale (§39.5.1, §39.5.2). Equivalent functions for other locales are provided in <locale> (§39.5.1).

One reason that these character classification functions are useful is that character classification can be trickier than it might appear. For example, a novice might write:

if ('a'<ch && ch<'z') // a character

This is more verbose (and most likely slower) than:

if (islower(ch))      // a lowercase character

Also, there is no guarantee that the characters are contiguous in a code space. Furthermore, the use of standard character classifications are far easier to convert to another locale:

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if (islower,danish)   // a lowercase character in Danish
                      // (assuming "danish" is the name for a Danish locale)

Note that Danish has three more lowercase characters than English, so that the initial explicit test using 'a' and 'z' would be flat wrong.

36.2.2. Character Traits

As shown in §23.2, a string template can, in principle, use any type with proper copy operations as its character type. However, efficiency can be improved and implementations can be simplified for types that don’t have user-defined copy operations. Consequently, the standard string requires that a type used as its character type be a POD (§8.2.6). This also helps to make I/O of strings simple and efficient.

The properties of a character type are defined by its char_traits. A char_traits is a specialization of the template:

template<typename C> struct char_traits { };

All char_traits are defined in std, and the standard ones are presented in <string>. The general char_traits itself has no properties; only char_traits specializations for a particular character type have. Consider char_traits<char>:

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template<>
struct char_traits<char> {   // char_traits operations should not throw exceptions
     using char_type = char;
     using int_type = int;            // type of integer value of character
     using off_type = streamoff;      // offset in stream
     using pos_type = streampos;      // position in stream
     using state_type = mbstate_t;    // multibyte stream state (§39.4.6)
     // ...
};

The standard provides four specializations of char_traits (§iso.21.2.3):

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template<> struct char_traits<char>;
template<> struct char_traits<char16_t>;
template<> struct char_traits<char32_t>;
template<> struct char_traits<wchar_t>;

The members of the standard char_traits are all static functions:

Comparing with eq() is often not simply an ==. For example, a case-insensitive char_traits would define its eq() so that eq('b','B') would return true.

Because copy() does not protect against overlapping ranges, it may be faster than move(). The compare() function uses lt() and eq() to compare characters. It returns an int, where 0 represents an exact match, a negative number means that its first argument comes lexicographically before the second, and a positive number means that its first argument comes after its second.

The I/O-related functions are used by the implementation of low-level I/O (§38.6).

36.3. Strings

In <string>, the standard library provides a general string template basic_string:

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template<typename C,
         typename Tr = char_traits<C>,
         typename A = allocator<C>>
class basic_string {
public:
     using traits_type = Tr;
     using value_type = typename Tr::char_type;
     using allocator_type = A;
     using size_type = typename allocator_traits<A>::size_type;
     using difference_type = typename allocator_traits<A>::difference_type;
     using reference = value_type&;
     using const_reference = const value_type&;
     using pointer = typename allocator_traits<A>::pointer;
     using const_pointer = typename allocator_traits<A>::const_pointer;
     using iterator = /* implementation-defined */;
     using const_iterator = /* implementation-defined */;
     using reverse_iterator = std::reverse_iterator<iterator>;
     using const_reverse_iterator = std::reverse_iterator<const_iterator>;

     static const size_type npos = –1;  // integer representing end-of-string

     // ...
};

The elements (characters) are stored contiguously, so that low-level input operations can safely use a basic_string’s sequence of characters as a source or target.

The basic_string offers the strong guarantee (§13.2): if a basic_string operation throws, the string is left unchanged.

Specializations are offered for a few standard character types:

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using string = basic_string<char>;
using u16string = basic_string<char16_t>;
using u32string = basic_string<char32_t>;
using wstring = basic_string<wchar_t>;

All these strings provide a host of operations.

Like containers (Chapter 31), basic_string is not meant to be used as a base class and offers move semantics so that it can be efficiently returned by value.

36.3.1. string vs. C-Style Strings

I assume some familiarity with string from the many examples in this book, so I start with a few examples contrasting string use with the use of C-style strings (§43.4) which are popular with programmers primarily familiar with C and C-style C++.

Consider making up an email address by concatenating a user identifier and a domain name:

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string address(const string& identifier, const string& domain)
{
     return identifier + '@' + domain;
}

void test()
{
     string t = address("bs","somewhere");
     cout << t << '\n';
}

This is trivial. Now consider a plausible C-style version. A C-style string is a pointer to an array of zero-terminated characters. The user controls allocation and is responsible for deallocation:

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char* address(const char* identifier, const char* domain)
{
     int iden_len = strlen(identifier);
     int dom_len = strlen(domain);
     char* addr = (char*)malloc(iden_len+dom_len+2);      // remember space for 0 and '@'
     strcpy(identifier,addr);
     addr[iden_len] = '@';
     strcpy(domain,addr+iden_len+1);
     return addr;
}

void test2()
{
     char* t = address("bs","somewhere");
     printf("%s\n",t);
     free(t);
}

Did I get that right? I hope so. At least it gave the output I expected. Like most experienced C programmers, I got the C version correct (I hope) the first time, but there are a lot of details to get right. However, experience (i.e., error logs) shows that this is not always the case. Often, such simple programming tasks are given to relative novices who still don’t know all the techniques needed to get it right. The implementation of the C-style address() contains a lot of tricky pointer manipulation, and its use requires the caller to remember to free the returned memory. Which code would you prefer to maintain?

Sometimes, it is claimed that C-style strings are more efficient than strings. However, for most uses, the string does fewer allocations and deallocations than a C-style equivalent (because of the small-string optimization and move semantics; §19.3.3, §19.3.1). Also, strlen() is a log(N) operation, whereas string::size() is a simple read. In the example, this implies that the C-style code traverses each input string twice, whereas the string version does only one traversal per input. Efficiency concerns at this level are often misguided, but the string version has a fundamental edge.

The fundamental difference between C-style strings and string is that string is a proper type with conventional semantics, whereas the C-style string is a set of conventions supported by a few useful functions. Consider assignment and comparison:

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void test3()
{
     string s1 = "Ring";
     if (s1!="Ring") insanity();
     if (s1<"Opera")cout << "check";
     string s2 = address(s1,"Valkyrie");

     char s3[] = "Ring";
     if (strcmp(s3,"Ring")!=0) insanity();
     if (strcmp(s3,"Opera")<0) cout << "check";
     char* s4 = address(s3,"Valkyrie");
     free(s4);
}

Finally, consider sorting:

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void test4()
{
     vector<string> vs = {"Grieg", "Williams", "Bach", "Handel" };
     sort(vs.begin(),vs.end());   // assuming that I haven't defined sort(vs)

     const char* as[] = {"Grieg", "Williams", "Bach", "Handel" };
     qsort(as,sizeof(*as),sizeof(as)/sizeof(*as),(int(*)(const void*,const void*))strcmp);
}

The C-style string sort function qsort() is presented in §43.7. Again, sort() is as fast as (and typically much faster than) qsort(), so there is no performance reason to choose the lower-level, more verbose, and less maintainable programming style.

36.3.2. Constructors

A basic_string offers a bewildering variety of constructors:

The most common variants are also the simplest:

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string s0;                          // the empty string
string s1 {"As simple as that!"};   // construct from C-style string
string s2 {s1};                     // copy constructor

Almost always, the destructor is implicitly invoked.

There is no string constructor that takes only a number of elements:

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string s3 {7};       // error: no string(int)
string s4 {'a'};     // error: no string(char)
string s5 {7,'a'};   // OK: 7 'a's
string s6 {0};       // danger: passing nullptr

The declaration of s6 shows a mistake sometimes made by programmers used to C-style strings:

const char* p = 0;     // set p to "no string"

Unfortunately, the compiler cannot catch the definition of s6 or the even nastier case of a const char* holding the nullptr:

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string s6 {0};       // danger: passing nullptr
string s7 {p};       // may or may not be OK depending on the value of p
string s8 {"OK"};    // OK: pass pointer to C-style string

Don’t try to initialize a string with a nullptr. At best, you get a nasty run-time error. At worst, you get mysterious undefined behavior.

If you try to construct a string with more characters than your implementation can handle, the constructor throws std::length_error. For example:

string s9 {string::npos,'x'};  // throw length_error

The value string::npos represents a position beyond a string’s length and is generally used to mean “the end of the string.” For example:

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string ss {"Fleetwood Mac"};
string ss2 {ss,0,9};                // "Fleetwood"
string ss3 {ss,10,string::npos};    // "Mac"

Note that the substring notation is (position,length) rather than [start,end).

There are no literals of type string. A user-defined literal could be used for that (§19.2.6), for example, "The Beatles"s and "Elgar"s. Note the s suffix.

36.3.3. Fundamental Operations

A basic_string offers comparisons, control of size and capacity, and access operations.

For more comparison operations, see §36.3.8.

The size and capacity mechanisms for basic_string are the same as those for vector (§31.3.3):

A resize() or reserve() that would cause size() to exceed max_size() will throw std::length_error.

An example:

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void fill(istream& in, string& s, int max)
     // use s as target for low-level input (simplified)
{
     s.reserve(max);               // make sure there is enough allocated space
     in.read(&s[0],max);
     const int n = in.gcount();    // number of characters read
     s.resize(n);
     s.shrink_to_fit();            // discard excess capacity
}

Here, I “forgot” to make use of the number of characters read. That’s sloppy.

An out-of-range access using at() throws std::out_of_range. A +=(), push_back(), or + that would cause size() to exceed max_size() will throw std::length_error.

There is no implicit conversion of a string to a char*. That was tried in many places and found to be error-prone. Instead, the standard library provides the explicit conversion function c_str() to const char*.

A string can contain a zero value character (e.g., '\0'). Using a function, such as strcmp(), that assumes C-style string conventions on the result of s.c_str() or s.data() on a string containing a zero character may cause surprise.

36.3.4. String I/O

A basic_string can be written using << (§38.4.2) and read into using >> (§38.4.1):

An input operation that would cause size() to exceed max_size() will throw std::length_error.

A getline() removes its terminator character (by default '\n') from the input stream but does not enter it into the string. This simplifies handling of lines. For example:

vector<string> lines;
for (string s; getline(cin,s);)
      lines.push_back(s);

The string I/O operations all return a reference to their input stream, so that operations can be chained. For example:

string first_name;
string second_name;
cin >> first_name >> second_name;

The string target of an input operation is set to empty before reading and expands to hold the characters read. A read operation can also be terminated by reaching end-of-file (§38.3).

36.3.5. Numeric Conversions

In <string>, the standard library provides a set of functions for extracting numeric values from their character representation in a string or wstring (note: not a basic_string<C,Tr,A>). The desired numeric types are encoded in the function names:

Each of these sto* (String to) functions has three variants, like stoi. For example:

string s = "123.45";
auto  x1 = stoi(s);      // x1 = 123
auto  x2 = stod(s);      // x2 = 123.45

The second argument of a sto* function is a pointer used to indicate how far into the string the search for a numeric value progressed. For example:

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string ss = "123.4567801234";
size_t dist = 0;             // put number of characters read here
auto x = stoi(ss,&dist);     // x = 123 (an int)
++dist;                      // ignore the dot
auto y = stoll(&ss[dist]);   // x = 4567801234 (a long long)

This is not my favorite interface for parsing several numbers from a string. I prefer to use a string_stream (§38.2.2).

Initial whitespace is skipped. For example:

string s = " 123.45";
auto  x1 = stoi(s);           // x1 = 123

The base argument can be in the range [2:36] with the 0123456789abcdefghijklmnopqrstuvwxyz used as “digits” with their value determined by their position in this sequence. Any further base value will be an error or an extension. For example:

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string s4 = "149F";
auto x5 = stoi(s4);                // x5 = 149
auto x6 = stoi(s4,nullptr,10);     // x6 = 149
auto x7 = stoi(s4,nullptr,8);      // x7 = 014
auto x8 = stoi(s4,nullptr,16);     // x8 = 0x149F

string s5 = "1100101010100101";    // binary
auto x9 = stoi(s5,nullptr,2);      // x9 = 0xcaa5

If a conversion function doesn’t find characters in its string argument that it can convert to a number, it throws invalid_argument. If it finds a number that it cannot represent in its target type, it throws out_of_range; in addition, the conversions to floating-point types set errno to ERANGE (§40.3). For example:

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stoi("Hello, World!");              // throws std::invalid_argument
stoi("12345678901234567890");       // throws std::out_of_range; errno=ERANGE
stof("123456789e1000");             // throws std::out_of_range; errno=ERANGE

The sto* functions encode their target type in their names. This makes them unsuitable for generic code where the target can be a template parameter. In such cases, consider to<X> (§25.2.5.1).

36.3.6. STL-like Operations

The basic_string provides the usual set of iterators:

Because string has the required member types and the functions for obtaining iterators, strings can be used together with the standard algorithms (Chapter 32). For example:

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void f(string& s)
{
     auto p = find_if(s.begin(),s.end(),islower);
     // ...
}

The most common operations on strings are supplied directly by string. Hopefully, these versions will be optimized for strings beyond what would be easy to do for general algorithms.

The standard algorithms (Chapter 32) are not as useful for strings as one might think. General algorithms tend to assume that the elements of a container are meaningful in isolation. This is typically not the case for a string.

A basic_string offers complex assignment()s:

We can insert(), append(), and erase() in a basic_string:

For example:

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void add_middle(string& s, const string& middle)     // add middle name
{
     auto p = s.find(' ');
     s.insert(p,' '+middle);
}

void test()
{
     string dmr = "Dennis Ritchie";
     add_middle(dmr,"MacAlistair");
     cout << dmr << '\n';
}

As for vectors, append()ing (adding characters at the end) is typically more efficient than insert()ing elsewhere.

In the following, I use s[b:e) to denote a sequence of elements [b:e) in s:

The replace() replaces one substring with another and adjusts the string’s size accordingly. For example:

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void f()
{
     string s = "but I have heard it works even if you don't believe in it";
     s.replace(0,4,"");                        // erase initial "but "
     s.replace(s.find("even"),4,"only");
     s.replace(s.find(" don't"),6,"");         // erase by replacing with ""
     assert(s=="I have heard it works only if you believe in it");
}

Code relying on “magic” constants like the number of characters to be replaced is error-prone.

A replace() returns a reference to the object for which it was called. This can be used for chaining operations:

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void f2()
{
     string s = "but I have heard it works even if you don't believe in it";
     s.replace(0,4,"").replace(s.find("even"),4,"only").replace(s.find(" don't"),6,"");
     assert(s=="I have heard it works only if you believe in it");
}

36.3.7. The find Family

There is a bewildering variety of functions for finding substrings. As usual, find() searches from s.begin() onward, whereas rfind() searches backward from s.end(). The find functions use string::npos (“not a position”) to represent “not found.”

For example:

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void f()
{
     string s {"accdcde"};

     auto i1 = s.find("cd");      // i1==2 s[2]=='c' && s[3]=='d'
     auto i2 = s.rfind("cd");     // i2==4 s[4]=='c' && s[5]=='d'
}

The find_*_of() functions differ from find() and rfind() by looking for a single character, rather than a whole sequence of characters:

For example:

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string s {"accdcde"};

auto i1 = s.find("cd");                  // i1==2 s[2=='c' && s[3]=='d'
auto i2 = s.rfind("cd");                 // i2==4 s[4]=='c' && s[5]=='d'

auto i3 = s.find_first_of("cd");         // i3==1 s[1]=='c'
auto i4 = s.find_last_of("cd");          // i4==5 s[5]=='d'
auto i5 = s.find_first_not_of("cd");     // i5==0 s[0]!='c' && s[0]!='d'
auto i6 = s.find_last_not_of("cd");      // i6==6 s[6]!='c' && s[6]!='d'

36.3.8. Substrings

A basic_string offers a low-level notion of substring:

Note that substr() creates a new string:

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void user()
{
     string s = "Mary had a little lamb";
     string s2 = s.substr(0,4);      // s2 == "Mary"
     s2 = "Rose";                    // does not change s
}

We can compare substrings:

For example:

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void f()
{
     string s = "Mary had a little lamb";
     string s2 = s.substr(0,4);      // s2 == "Mary"
     auto i1 = s.compare(s2);        // i1 is positive
     auto i2 = s.compare(0,4,s2);    // i2==0
}

This explicit use of constants to denote positions and lengths is brittle and error-prone.

36.4. Advice

[1] Use character classifications rather than handcrafted checks on character ranges; §36.2.1.

[2] If you implement string-like abstractions, use character_traits to implement operations on characters; §36.2.2.

[3] A basic_string can be used to make strings of characters on any type; §36.3.

[4] Use strings as variables and members rather than as base classes; §36.3.

[5] Prefer string operations to C-style string functions; §36.3.1.

[6] Return strings by value (rely on move semantics); §36.3.2.

[7] Use string::npos to indicate “the rest of the string”; §36.3.2.

[8] Do not pass a nullptr to a string function expecting a C-style string; §36.3.2.

[9] A string can grow and shrink, as needed; §36.3.3.

[10] Use at() rather than iterators or [] when you want range checking; §36.3.3, §36.3.6.

[11] Use iterators and [] rather than at() when you want to optimize speed; §36.3.3, §36.3.6.

[12] If you use strings, catch length_error and out_of_range somewhere; §36.3.3.

[13] Use c_str() to produce a C-style string representation of a string (only) when you have to; §36.3.3.

[14] string input is type sensitive and doesn’t overflow; §36.3.4.

[15] Prefer a string_stream or a generic value extraction function (such as to<X>) over direct use of str* numeric conversion functions; §36.3.5.

[16] Use the find() operations to locate values in a string (rather than writing an explicit loop); §36.3.7.

[17] Directly or indirectly, use substr() to read substrings and replace() to write substrings; §36.3.8.

37. Regular Expressions

If the code and the comments disagree, then both are probably wrong.

– Norm Schryer

• Regular Expressions

Regular Expression Notation

• regex

Match Results; Formatting

• Regular Expression Functions

regex_match(); regex_search(); regex_replace()

• Regular Expression Iterators

regex_iterator; regex_token_iterator

• regex_traits

• Advice

37.1. Regular Expressions

In <regex>, the standard library provides regular expressions:

• regex_match(): Match a regular expression against a string (of known size).

• regex_search(): Search for a string that matches a regular expression in an (arbitrarily long) stream of data.

• regex_replace(): Search for strings that match a regular expression in an (arbitrarily long) stream of data and replace them.

• regex_iterator: iterate over matches and submatches.

• regex_token_iterator: iterate over non-matches.

The result of a regex_search() is a collection of matches, typically represented as an smatch:

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void use()
{
     ifstream in("file.txt");     // input file
     if (!in) cerr << "no file\n";

     regex pat {R"(\w{2}\s*\d{5}(–\d{4})?)"};  // U.S. postal code pattern

     int lineno = 0;
     for (string line; getline(in,line);) {
           ++lineno;
           smatch matches;    // matched strings go here
           if (regex_search(line, matches, pat)) {
                 cout << lineno << ": " << matches[0] << '\n'; // the complete match
                 if (1<matches.size() && matches[1].matched)
                       cout << "\t: " << matches[1] << '\n';// submatch
           }
     }
}

This function reads a file looking for U.S. postal codes, such as TX77845 and DC 20500–0001. An smatch type is a container of regex results. Here, matches[0] is the whole pattern and matches[1] is the optional four-digit subpattern. I used a raw string (§7.3.2.1) which is particularly suitable for regular expressions because they tend to contain a lot of backslashes. Had I used a conventional string, the pattern definition would have been:

regex pat {"\\w{2}\\s*\\d{5}(–\\d{4})?"};  // U.S. postal code pattern

The regular expression syntax and semantics are designed so that regular expressions can be compiled into state machines for efficient execution [Cox,2007]. The regex type performs this compilation at run time.

37.1.1. Regular Expression Notation

The regex library can recognize several variants of the notation for regular expressions (§37.2). Here, I first present the default notation used, a variant of the ECMA standard used for ECMAScript (more commonly known as JavaScript).

The syntax of regular expressions is based on characters with special meaning:

For example, we can specify a line starting with zero or more As followed by one or more Bs followed by an optional C like this:

^A*B+C?$

Examples that match:

AAAAAAAAAAAABBBBBBBBBC
BC
B

Examples that do not match:

AAAAA       // no B
  AAAABC    // initial space
AABBCC      // too many Cs

A part of a pattern is considered a subpattern (which can be extracted separately from an smatch) if it is enclosed in parentheses.

A pattern can be optional or repeated (the default is exactly once) by adding a suffix:

For example:

A{3}B{2,4}C*

Examples that match:

AAABBC
AAABBB

Example that do not match:

AABBC        // too few As
AAABC        // too few Bs
AAABBBBBCCC  // too many Bs

A suffix ? after any of the repetition notations makes the pattern matcher “lazy” or “non-greedy.” That is, when looking for a pattern, it will look for the shortest match rather than the longest. By default, the pattern matcher always looks for the longest match (similar to C++’s Max Munch rule; §10.3). Consider:

ababab

The pattern (ab)* matches all of ababab. However, (ab)*? matches only the first ab.

The most common character classifications have names:

Several character classes are supported by shorthand notation:

In addition, languages supporting regular expressions often provide:

For full portability, use the character class names rather than these abbreviations.

As an example, consider writing a pattern that describes C++ identifiers: an underscore or a letter followed by a possibly empty sequence of letters, digits, or underscores. To illustrate the subtleties involved, I include a few false attempts:

Click here to view code image

[:alpha:][:alnum:]*             // wrong: characters from the set ":alph" followed by ...
[[:alpha:]][[:alnum:]]*         // wrong: doesn't accept underscore ('_' is not alpha)
([[:alpha:]]|_)[[:alnum:]]*     // wrong: underscore is not part of alnum either
([[:alpha:]]|_)([[:alnum:]]|_)*       // OK, but clumsy
[[:alpha:]_][[:alnum:]_]*             // OK: include the underscore in the character classes
[_[:alpha:]][_[:alnum:]]*             // also OK
[_[:alpha:]]\w*                       // \w is equivalent to [_[:alnum:]]

Finally, here is a function that uses the simplest version of regex_match() (§37.3.1) to test whether a string is an identifier:

bool is_identifier(const string& s)
{
     regex pat {"[_[:alpha:]]\\w*"};
     return regex_match(s,pat);
}

Note the doubling of the backslash to include a backslash in an ordinary string literal. As usual, backslashes can also denote special characters:

To add to the opportunities for confusion, two further logically different uses of the backslash are provided:

Using raw string literals alleviates many problems with special characters. For example:

bool is_identifier(const string& s)
{
     regex pat {R"([_[:alpha:]]\w*)"};
     return regex_match(s,pat);
}

Here are some examples of patterns:

Click here to view code image

Ax*            // A, Ax, Axxxx
Ax+            // Ax, Axxx     Not A
\d–?\d         // 1-2, 12      Not 1--2
\w{2}–\d{4,5}  // Ab-1234, XX-54321, 22-5432       Digits are in \w
(\d*:)?(\d+)   // 12:3, 1:23, 123, :123  Not 123:
(bs|BS)        // bs, BS       Not bS
[aeiouy]       // a, o, u      An English vowel, not x
[^aeiouy]      // x, k         Not an English vowel, not e
[a^eiouy]      // a, ^, o, u   An English vowel or ^

A group (a subpattern) potentially to be represented by a sub_match is delimited by parentheses. If you need parentheses that should not define a subpattern, use (? rather than plain (. For example:

(\s|:|,)*(\d*)   // spaces, colons, and/or commas followed by a number

Assuming that we were not interested in the characters before the number (presumably separators), we could write:

(?\s|:|,)*(\d*)  // spaces, colons, and/or commas followed by a number

This would save the regular expression engine from having to store the first characters: the (? variant has only one subpattern.

That last pattern is useful for parsing XML. It finds tag/end-of-tag markers. Note that I used a non-greedy match (a lazy match), .*?, for the subpattern between the tag and the end tag. Had I used plain .*, this input would have caused a problem:

Always look for the <b>bright</b> side of <b>life</b>.

A greedy match for the first subpattern would match the first < with the last >. A greedy match on the second subpattern would match the first <b> with the last </b>. Both would be correct behavior, but unlikely what the programmer wanted.

It is possible to vary details of the regular expression notation using options (§37.2). For example, if regex_constants::grep is used, a?x:y is a sequence of five ordinary characters because ? does not mean “optional” in grep.

For a more exhaustive presentation of regular expressions, see [Friedl,1997].

37.2. regex

A regular expression is a matching engine (usually a state machine) constructed from a sequence of characters, such as a string:

Click here to view code image

template<class C, class traits = regex_traits<C>>
class basic_regex {
public:
     using value_type = C;
     using traits_type = traits;
     using string_type = typename traits::string_type;
     using flag_type = regex_constants::syntax_option_type;
     using locale_type = typename traits::locale_type;
     ~basic_regex(); //not virtual; basic_regex is not meant to be used as a base class
     // ...
};

The regex_traits are presented in §37.5.

Like string, regex is an alias for the version that uses chars:

using regex = basic_regex<char>;

The meaning of regular expression patterns is controlled by syntax_option_type constants defined identically in regex_constants and regex:

Use the default unless you have a good reason not to. Good reasons include a large body of existing regular expressions in a non-default notation.

A regex object can be constructed from a string or similar sequence of characters:

The main use of regex is through the search, match, and replace functions (§37.3), but there are also a few operations on regex itself:

You can determine the locale or a regex by a call of getloc() and learn what flags are used from flags(), but unfortunately there is no (standard) way of reading out its pattern. If you need to output a pattern, keep a copy of the string used to initialize. For example:

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regex pat1 {R"(\w+\d*)"};    // no way of outputting the pattern in pat1

string s {R"(\w+\d*)"};
regex pat2 {s};
cout << s << '\n';          // the pattern in pat2

37.2.1. Match Results

Results from a regular expression match are gathered in a match_results object which contains one or more sub_match objects:

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template<class Bi>
class sub_match : public pair<Bi,Bi> {
public:
     using value_type = typename iterator_traits<Bi>::value_type;
     using difference_type = typename iterator_traits<Bi>::difference_type;
     using iterator = Bi;
     using string_type = basic_string<value_type>;

     bool matched; // true if *this contains a match
     // ...
};

Bi must be a bidirectional iterator (§33.1.2). A sub_match can be seen as a pair of iterators into the string being matched.

For example:

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regex pat ("<(.*?)>(.*?)</(.*?)>");

string s = "Always look for the <b> bright </b> side of <b> death </b>";

if (regex_search(s1,m,p2))
      if (m[1]==m[3]) cout << "match\n";

The output is match.

A match_results is a container of sub_matches:

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template<class Bi, class A = allocator<sub_match<Bi>>
class match_results {
public:
     using value_type = sub_match<Bi>;
     using const_reference = const value_type&;
     using reference = const_reference;
     using const_iterator = /* implementation-defined */;
     using iterator = const_iterator;
     using difference_type = typename iterator_traits<Bi>::difference_type;
     using size_type = typename allocator_traits<A>::size_type;
     using allocator_type = A;
     using char_type = typename iterator_traits<Bi>::value_type;
     using string_type = basic_string<char_type>;

     ~match_results(); // not virtual

     // ...
};

Bi must be a bidirectional iterator (§33.1.2).

As for basic_string and basic_ostream, a few standard aliases are provided for the most common match_results:

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using cmatch = match_results<const char*>;               // C-style string
using wcmatch = match_results<const wchar_t*>;           // wide C-style string
using smatch = match_results<string::const_iterator>;    // string
using wsmatch = match_results<wstring::const_iterator>;  // wstring

A match_results provides access to its match string, its sub_matches, and the characters before and after the match:

A match_results provides a conventional set of operations:

We can subscript a regex_match to access a sub_match, for example, m[i]. If a subscript, i, refers to a nonexistent sub_match, the result of m[i] represents an unmatched sub_match. For example:

Click here to view code image

void test()
{
     regex pat ("(AAAA)(BBB)?");
     string s = "AAAA";
     smatch m;
     regex_search(s,m,pat);

     cout << boolalpha;
     cout << m[0].matched << '\n';     // true: we found a match
     cout << m[1].matched << '\n';     // true: there was a first sub_match
     cout << m[2].matched << '\n';     // false: no second sub_match
     cout << m[3].matched << '\n';     // false: there couldn't be a third sub_match for pat
}

37.2.2. Formatting

In regex_replace(), formatting is done using a format() function:

Formats can contain formatting characters:

For an example, see §37.3.3.

The details of formatting done by format() are controlled by a set of options (flags):

37.3. Regular Expression Functions

The functions for applying regular expression patterns to data are regex_search() for searching in a sequence of characters, regex_match() for matching a fixed-length sequence of characters, and regex_replace() for doing replacement of patterns.

The details of matching are controlled by a set of options (flags):

37.3.1. regex_match()

To look for a pattern matching a whole sequence with a known length, such as a line of text, use regex_match():

As an example, consider a naive program for validating the format of a table. If the table format is as expected, the program writes “all is well” to cout; if not, it writes error messages to cerr. A table is a series of rows, each with four tab-separated fields, except for the first (title row) which may have only three fields. For example:

The numbers are supposed to add up horizontally and vertically.

The program reads the title line and then does the sums for each line until it reaches the final line labeled “Total”:

Click here to view code image

int main()
{
     ifstream in("table.txt");    // input file
     if (!in) cerr << "no file\n";

     string line;   // input buffer
     int lineno = 0;

     regex header {R"(^[\w ]+(\t[\w ]+)*$)"};                // tab-separated words
     regex row {R"(^([\w ]+)(\t\d+)(\t\d+)(\t\d+)$)"}; // label followed by three tab-separated numbers

     if (getline(in,line)) { // check and discard the header line
           smatch matches;
           if (!regex_match(line,matches,header))
                  cerr << "no header\n";
     }

     int boys = 0;        // running totals
     int girls = 0;

     while (getline(in,line)) {
          ++lineno;
          smatch matches;                                  // submatches go here

          if (!regex_match(line,matches,row))
                 cerr << "bad line: " << lineno << '\n';

          int curr_boy = stoi(matches[2]);                 // for stoi() see §36.3.5
          int curr_girl = stoi(matches[3]);
          int curr_total = stoi(matches[4]);
          if (curr_boy+curr_girl != curr_total) cerr << "bad row sum \n";

          if (matches[1]=="Total") {                       // last line
               if (curr_boy != boys) cerr << "boys do not add up\n";
               if (curr_girl != girls) cerr << "girls do not add up\n";
               cout << "all is well\n";
               return 0;
          }
          boys += curr_boy;
          girls += curr_girl;
     }

     cerr << "didn't find total line\n")
     return 1;
}

37.3.2. regex_search()

To look for a pattern in a part of a sequence, such as a file, use regex_search():

For example, I could look for some of the more popular misspellings of my name like this:

Click here to view code image

regex pat {"[Ss]tro?u?v?p?stra?o?u?p?b?"};

smatch m;
for (string s; cin>>s; )
           if (regex_search(s,m,pat))
                 if (m[0]!="stroustrup" && m[0]!="Stroustrup")
                       cout << "Found: " << m[0] << '\n';

Given suitable input, this will output misspellings of Stroustrup, such as:

Found: strupstrup
Found: Strovstrup
Found: stroustrub
Found: Stroustrop

Note that regex_search() will find its pattern even if it is “hidden” among other characters. For example, it will find strustrub in abstrustrubal. If you want to match a pattern against every character in an input string, use regex_match (§37.3.1).

37.3.3. regex_replace()

To make simple substitutions of a pattern in a part of a sequence, such as a file, use regex_replace():

Copying a format is done using the regex’s format() (§37.2.2) with the $ prefix notation, for example, $& for the match and $2 for the second submatch. Here is a little test program that takes a string of word and number pairs and outputs them as {word,number}, one per line:

Click here to view code image

void test1()
{
     string input {"x 1 y2 22 zaq 34567"};
     regex pat {"(\w+)\s(\d+)"};    // word space number
     string format {"{$1,$2}\n"};

     cout << regex_replace(input,pat,format);
}

The output is:

{x,1}
 {y2,22}
 {zaq,34567}

Note the annoying “spurious” spaces at the beginning of the lines. By default, regex_match() copies unmatched characters to its output, so the two spaces that were not matched by pat are printed.

To eliminate those spaces, we can use the format_no_copy option (§37.2.2):

cout << regex_replace(input,pat,format,regex_constants::format_no_copy);

Now we get:

{x,1}
{y2,22}
{zaq,34567}

Submatches do not have to be output in order:

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void test2()
{
     string input {"x 1 y 2 z 3"};
     regex pat {"(\w)\s(\d+)"};  // word space number
     string format {"$2: $1\n"};

     cout << regex_replace(input,pat,format,regex_constants::format_no_copy);
}

Now we get:

1: x
22: y2
34567: zeq

37.4. Regular Expression Iterators

The regex_search() function allows us to find a single occurrence of a pattern in a data stream. What if we wanted to find and do something to all such occurrences? If the data is organized as a sequence of easily recognized lines or records, we can iterate over those and use regex_match() for each. If what we want to do with each occurrence of a pattern is a simple substitution, we can use regex_replace(). If we want to iterate over a sequence of characters doing something for each occurrence of a pattern, we use a regex_iterator.

37.4.1. regex_iterator

A regex_iterator is a bidirectional iterator that searches a sequence for the next match of a pattern when incremented:

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template<class Bi,
         class C = typename iterator_traits<Bi>::value_type,
         class Tr = typename regex_traits<C>::type>
class regex_iterator {
public:
     using regex_type = basic_regex<C,Tr>;
     using value_type = match_results<Bi>;
     using difference_type = ptrdiff_t;
     using pointer = const value_type*;
     using reference = const value_type&;
     using iterator_category = forward_iterator_tag;
     // ...
}

The regex_traits are described in §37.5.

The usual set of aliases is provided:

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using cregex_iterator = regex_iterator<const char*>;
using wcregex_iterator = regex_iterator<const wchar_t*>;
using sregex_iterator = regex_iterator<string::const_iterator>;
using wsregex_iterator = regex_iterator<wstring::const_iterator>;

A regex_iterator provides a minimal set of iterator operations:

A regex_iterator is a bidirectional iterator, so we cannot directly iterate over an istream.

As an example, we can output all whitespace-separated words in a string:

Click here to view code image

void test()
{
     string input = "aa as; asd ++e^asdf asdfg";
     regex pat {R"(\s+(\w+))"};
     for (sregex_iterator p(input.begin(),input.end(),pat); p!=sregex_iterator{}; ++p)
           cout << (*p)[1] << '\n';
}

This outputs:

as
asd
asdfg

Note that we are missing the first word, aa, because it has no preceding whitespace. If we simplify the pattern to R"((\ew+))", we get

aa
as
asd
e
asdf
asdfg

You cannot write through a regex_iterator and regex_iterator{} is the only possible end-of-sequence.

37.4.2. regex_token_iterator

A regex_token_iterator is an adaptor for regex_iterator that iterates over sub_matches of the match_results found:

Click here to view code image

template<class Bi,
     class C = typename iterator_traits<Bi>::value_type,
     class Tr = typename regex_traits<C>::type>
class regex_token_iterator {
public:
     using regex_type = basic_regex<C,Tr>;
     using value_type = sub_match<Bi>;
     using difference_type = ptrdiff_t;
     using pointer = const value_type*;
     using reference = const value_type&;
     using iterator_category = forward_iterator_tag;
     // ...

The regex_traits are described in §37.5.

The usual set of aliases is provided:

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using cregex_token_iterator = regex_token_iterator<const char*>;
using wcregex_token_iterator = regex_token_iterator<const wchar_t*>;
using sregex_token_iterator = regex_token_iterator<string::const_iterator>;
using wsregex_token_iterator = regex_token_iterator<wstring::const_iterator>;

A regex_token_iterator provides a minimal set of iterator operations:

The x argument lists the sub_matches to be included in the iteration. For example (iterating over matches 1 and 3):

Click here to view code image

void test1()
{
     string input {"aa::bb cc::dd ee::ff"};
     regex pat {R"((\w+)([[:punct:]]+)(\w+)\s*)"};
     sregex_token_iterator end {};
     for (sregex_token_iterator p{input.begin(),input.end(),pat,{1,3}}; p!=end; ++p)
           cout << *p << '\n';
}

This gives the output:

aa
bb
cc
dd
ee
ff

The –1 option basically inverts the strategy for reporting matches by representing each character sequence that does not match as a sub_match. This is often referred to as token splitting (that is, splitting a character stream into tokens) because when your pattern matches the token separators, option –1 leaves you with the tokens. For example:

Click here to view code image

void test2()
{
     string s {"1,2 , 3 ,4,5, 6 7"};   // input
     regex pat {R"(\s*,\s*)"};         // use comma as token    separator
     copy(sregex_token_iterator{s.begin(),s.end(),pat,–1)},
         sregex_token_iterator{},
         ostream_iterator<string>{cout,"\n"});
}

The output is:

1
2
3
4
5
6 7

This could equivalently be written using an explicit loop:

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void test3()
{
     sregex_token_iterator end{};
     for (sregex_token_iterator p {s.begin(),s.end(),pat,–1}; p!=end; ++p)
           cout << *p << '\n';
}

37.5. regex_traits

A regex_traits<T> represents the correspondence between a character type, a string type, and a locale as needed for a regex implementer:

Click here to view code image

template<class C>
struct regex_traits {
public:
     using char_type = C;
     using string_type = basic_string<char_type>;
     using locale_type = locale;
     using char_class_type = /* implementation-defined bitmask type */;
     // ...
};

The standard library provides specializations regex_traits<char> and regex_traits<wchar_t>.

A transform is used to generate strings for fast comparisons in pattern-matching implementations.

A classification name is one of the character classifications listed in §37.1.1, such as alpha, s, and xdigit.

37.6. Advice

[1] Use regex for most conventional uses of regular expressions; §37.1.

[2] The regular expression notation can be adjusted to match various standards; §37.1.1, §37.2.

[3] The default regular expression notation is that of ECMAScript; §37.1.1.

[4] For portability, use the character class notation to avoid nonstandard abbreviations; §37.1.1.

[5] Be restrained; regular expressions can easily become a write-only language; §37.1.1.

[6] Prefer raw string literals for expressing all but the simplest patterns; §37.1.1.

[7] Note that \i allows you to express a subpattern in terms of a previous subpattern; §37.1.1.

[8] Use ? to make patterns “lazy”; §37.1.1, §37.2.1.

[9] regex can use ECMAScript, POSIX, awk, grep, and egrep notation; §37.2.

[10] Keep a copy of the pattern string in case you need to output it; §37.2.

[11] Use regex_search() for looking at streams of characters and regex_match() to look for fixed layouts; §37.3.2, §37.3.1.

38. I/O Streams

What you see is all you get.

– Brian W. Kernighan

• Introduction

• The I/O Stream Hierarchy

File Streams; String Streams

• Error Handling

• I/O Operations

Input Operations; Output Operations; Manipulators; Stream State; Formatting

• Stream Iterators

• Buffering

Output Streams and Buffers; Input Streams and Buffers; Buffer Iterators

• Advice

38.1. Introduction

The I/O stream library provides formatted and unformatted buffered I/O of text and numeric values. The definitions for I/O stream facilities are found in <istream>, <ostream>, etc.; see §30.2.

An ostream converts typed objects to a stream of characters (bytes):

An istream converts a stream of characters (bytes) to typed objects:

An iostream is a stream that can act as both an istream and an ostream. The buffers in the diagrams are stream buffers (streambufs; §38.6). You need them to define a mapping from an iostream to a new kind of device, file, or memory. The operations on istreams and ostreams are described in §38.4.1 and §38.4.2.

Knowledge of the techniques used to implement the stream library is not needed to use the library. So I present only the general ideas needed to understand and use iostreams. If you need to implement the standard streams, provide a new kind of stream, or provide a new locale, you need a copy of the standard, a good systems manual, and examples of working code in addition to what is presented here.

The key components of the stream I/O system can be represented graphically like this:

The solid arrows represent “derived from.” The dotted arrows represent “pointer to.” The classes marked with <> are templates parameterized by a character type and containing a locale.

The I/O stream operations:

• Are type-safe and type sensitive

• Are extensible (when someone designs a new type, matching I/O stream operators can be added without modifying existing code)

• Are locale sensitive (Chapter 39)

• Are efficient (though their potential is not always fully realized)

• Are interoperable with C-style stdio (§43.3)

• Include formatted, unformatted, and character-level operations

The basic_iostream is defined based on basic_istream (§38.6.2) and basic_ostream (§38.6.1):

Click here to view code image

template<typename C, typename Tr = char_traits<C>>
class basic_iostream :
     public basic_istream<C,Tr>, public basic_ostream<C,Tr> {
public:
     using char_type = C;
     using int_type = typename Tr::int_type;
     using pos_type = typename Tr::pos_type;
     using off_type = typename Tr::off_type;
     using traits_type = Tr;

     explicit basic_iostream(basic_streambuf<C,Tr>* sb);
     virtual ~basic_iostream();
protected:
     basic_iostream(const basic_iostream& rhs) = delete;
     basic_iostream(basic_iostream&& rhs);

     basic_iostream& operator=(const basic_iostream& rhs) = delete;
     basic_iostream& operator=(basic_iostream&& rhs);
     void swap(basic_iostream& rhs);
};

The template parameters specify the character type and the traits used to manipulate characters (§36.2.2), respectively.

Note that no copy operations are provided: sharing or cloning the fairly complex state of a stream would be difficult to implement and expensive to use. The move operations are intended for use by derived classes and are therefore protected. Moving an iostream without moving the state of its defining derived class (e.g., an fstream) would lead to errors.

There are three standard streams:

Forward declarations for stream types and stream objects are provided in <iosfwd>.

38.2. The I/O Stream Hierarchy

An istream can be connected to an input device (e.g., a keyboard), a file, or a string. Similarly, an ostream can be connected to an output device (e.g., a text window or an HTML engine), a file, or a string. The I/O stream facilities are organized in a class hierarchy:

The classes suffixed by <> are templates parameterized on the character type. A dotted line indicates a virtual base class (§21.3.5).

The key class is basic_ios in which most of the implementation and many of the operations are defined. However, most casual (and not-so-casual) users never see it: it is mostly an implementation detail of the streams. It is described in §38.4.4. Most of its facilities are described in the context of their function (e.g., formatting; §38.4.5).

38.2.1. File Streams

In <fstream>, the standard library provides streams to and from a file:

• ifstreams for reading from a file

• ofstreams for writing to a file

• fstreams for reading from and writing to a file

The file streams follow a common pattern, so I describe only fstream:

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template<typename C, typename Tr=char_traits<C>>
class basic_fstream
: public basic_iostream<C,Tr> {
public:
     using char_type = C;
     using int_type = typename Tr::int_type;
     using pos_type = typename Tr::pos_type;         // for positions in file
     using off_type = typename Tr::off_type;  // for offsets in file
     using traits_type = Tr;
     // ...
};

The set of fstream operations is fairly simple:

In addition, the string streams override the basic_ios protected virtual functions underflow(), pback-fail(), overflow(), setbuf(), seekoff(), and seekpos() (§38.6).

A file stream does not have copy operations. If you want two names to refer to the same file stream, use a reference or a pointer, or carefully manipulate file streambufs (§38.6).

If an fstream fails to open, the stream is in the bad() state (§38.3).

There are six file stream aliases defined in <fstream>:

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using ifstream = basic_ifstream<char>;
using wifstream = basic_ifstream<wchar_t>;
using ofstream = basic_ofstream<char>;
using wofstream = basic_ofstream<wchar_t>;
using fstream = basic_fstream<char>;
using wfstream = basic_fstream<wchar_t>;

You can open a file in one of several modes, as specified in ios_base (§38.4.4):

In each case, the exact effect of opening a file may depend on the operating system, and if an operating system cannot honor a request to open a file in a certain way, the result will be a stream that is in the bad() state (§38.3). For example:

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ofstream ofs("target");               // "o" for "output" implying ios::out
if (!ofs)
       error("couldn't open 'target' for writing");

fstream ifs;            // "i" for "input" implying ios::in
ifs.open("source",ios_base::in);
if (!ifs)
       error("couldn't open 'source' for reading");

For positioning in a file, see §38.6.1.

38.2.2. String Streams

In <sstream>, the standard library provides streams to and from a string:

• istringstreams for reading from a string

• ostringstreams for writing to a string

• stringstreams for reading from and writing to a string

The string streams follow a common pattern, so I describe only stringstream:

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template<typename C, typename Tr = char_traits<C>, typename A = allocator<C>>
class basic_stringstream
     : public basic_iostream<C,Tr> {
public:
     using char_type = C;
     using int_type = typename Tr::int_type;
     using pos_type = typename Tr::pos_type;        // for positions in string
     using off_type = typename Tr::off_type; // for offsets in string
     using traits_type = Tr;
     using allocator_type = A;

     // ...

The stringstream operations are:

The open modes are described in §38.4.4. For an istringstream, the default mode is ios_base::in. For an ostringstream, the default mode is ios_base::out.

In addition, the string streams override the basic_ios protected virtual functions underflow(), pbackfail(), overflow(), setbuf(), seekoff(), and seekpos() (§38.6).

A string stream does not have copy operations. If you want two names to refer to the same string stream, use a reference or a pointer.

There are six string stream aliases defined in <sstream>:

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using istringstream = basic_istringstream<char>;
using wistringstream = basic_istringstream<wchar_t>;
using ostringstream = basic_ostringstream<char>;
using wostringstream = basic_ostringstream<wchar_t>;
using stringstream = basic_stringstream<char>;
using wstringstream = basic_stringstream<wchar_t>;

For example:

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void test()
{
     ostringstream oss {"Label: ",ios::ate};            // write at end
     cout << oss.str() << '\n'; // writes "Label: "
     oss<<"val";
     cout << oss.str() << '\n'; // writes "Label: val" ("val" appended after "Label: ")

     ostringstream oss2 {"Label: "};                    // write at beginning
     cout << oss2.str() << '\n'; // writes "Label: "
     oss2<<"val";
     cout << oss2.str() << '\n'; // writes "valel: " (val overwrites "Label: ")
}

I tend to use str() only to read a result from an istringstream.

It is not possible to directly output a string stream; str() must be used:

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void test2()
{
     istringstream iss;
     iss.str("Foobar");         // Fill iss

     cout << iss << '\n';       // writes 1
     cout << iss.str() << '\n'; // OK: writes "Foobar"
}

The reason for the probably surprising 1 is that an iostream converts to its state for testing:

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if (iss) { // the last operation of iss succeeded; iss's state is good() or eof()
      // ...
}
else {
     // handle problem
}

38.3. Error Handling

An iostream can be in one of four states, defined in basic_ios from <ios> (§38.4.4):

Any operation attempted on a stream that is not in the good() state has no effect; it is a no-op. An iostream can be used as a condition. In that case, the condition is true (succeeds) if the state of the iostream is good(). That is the basis for the idiom for reading a stream of values:

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for (X x; cin>>x;) {  // read into an input buffer of type X
     // ... do something with x ...
}
// we get here when >> couldn't read another X from cin

After a read failure, we might be able to clear the stream and proceed:

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int i;
if (cin>>i) {
     // ... use i ...
} else if (cin.fail()){ // possibly a formatting error
     cin.clear();
     string s;
     if (cin>>s) {      // we might be able to use a string to recover
           // ... use s ...
     }
}

Alternatively, errors can be handled using exceptions:

For example, we can make cin throw a basic_ios::failure when its state is set to bad() (e.g., by a cin.setstate(ios_base::badbit)):

cin.exceptions(cin.exceptions()|ios_base::badbit);

For example:

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struct Io_guard {   // RAII class for iostream exceptions
     iostream& s;
     auto old_e = s.exceptions();
     Io_guard(iostream& ss, ios_base::iostate e) :s{ss} { s.exceptions(s.exceptions()|e); }
     ~Io_guard() { s.exceptions(old_e); }
};

void use(istream& is)
{
     Io_guard guard(is.ios_base::badbit);
     // ... use is ...
}
catch (ios_base::badbit) {
     // ... bail out! ...
}

I tend to use exceptions to handle iostream errors that I don’t expect to be able to recover from. That usually means all bad() exceptions.

38.4. I/O Operations

The complexity of the I/O operations reflects tradition, the need for I/O performance, and the variety of human expectations. The description here is based on the conventional English small character set (ASCII). The ways in which different character sets and different natural languages are handled are described in Chapter 39.

38.4.1. Input Operations

Input operations are provided by istream (§38.6.2), found in <istream> except for the ones reading into a string; those are found in <string>. The basic_istream is primarily intended as a base class for more specific input classes, such as istream and istringstream:

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template<typename C, typename Tr = char_traits<C>>
class basic_istream : virtual public basic_ios<C,Tr> {
public:
     using char_type = C;
     using int_type = typename Tr::int_type;
     using pos_type = typename Tr::pos_type;
     using off_type = typename Tr::off_type;
     using traits_type = Tr;

     explicit basic_istream(basic_streambuf<C,Tr>* sb);
     virtual ~basic_istream(); // release all resources

     class sentry;
     // ...
protected:
     // move but no copy:
     basic_istream(const basic_istream& rhs) = delete;
     basic_istream(basic_istream&& rhs);
     basic_istream& operator=(const basic_istream& rhs) = delete;
     basic_istream& operator=(basic_istream&& rhs);
     // ...
};

To users of an istream, the sentry class is an implementation detail. It provides common code for standard-library and user-defined input operations. Code that needs to be executed first (the “prefix code”) – such as flushing a tied stream – is provided as the sentry’s constructor. For example:

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template<typename C, typename Tr = char_traits<C>>
basic_ostream<C,Tr>& basic_ostream<C,Tr>::operator<<(int i)
{
     sentry s {*this};
     if (!s) {              // check whether all is well for output to start
            setstate(failbit);
            return *this;
     }

     // ... output the int ...
     return *this;
}

A sentry is used by implementers of input operations rather than by their users.

38.4.1.1. Formatted Input

Formatted input is primarily supplied by the >> (“input,” “get,” or “extraction”) operator:

Built-in types are “known” to istream (and ostream), so if x is a built-in type, cin>>x means cin.operator>>(x). If x is a user-defined type, cin>>x, means operator>>(cin,x) (§18.2.5). That is, iostream input is type sensitive, inherently type-safe, and extensible. A designer of a new type can provide I/O operations without direct access to the implementation of iostream.

If a pointer to a function is the target of >>, that function will be invoked with the istream as its argument. For example, cin>>pf yields pf(cin). This is the basis for the input manipulators, such as skipws (§38.4.5.2). Output stream manipulators are more common than input stream manipulators, so the technique is explained further in §38.4.3.

Unless otherwise stated, an istream operation returns a reference to its istream, so that we can “chain” operations. For example:

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template<typename T1, typename T2>
void read_pair(T1& x, T2& y)
{
     cin >> c1 >> x >> c2 >> y >> c3;
     if (c1!='{' || c2!=',' || c3!='}') {          // unrecoverable input format error
           cin.setstate(ios_base::badbit);         // set badbit
           throw runtime_error("bad read of pair");
     }
}

By default >> skips whitespace. For example:

for (int i; cin>>i && 0<i;)
      cout << i << '\n';

This will take a sequence of whitespace-separated positive integers and print them one to a line.

Skipping of whitespace can be suppressed using noskipws (§38.4.5.2).

The input operations are not virtual. That is, a user cannot do an in>>base where base is a class hierarchy and automatically have the >> resolved to an operation on the appropriate derived class. However, a simple technique can deliver that behavior; see §38.4.2.1. Furthermore, it is possible to extend such a scheme to be able to read objects of essentially arbitrary types from an input stream; see §22.2.4.

38.4.1.2. Unformatted Input

Unformatted input can be used for finer control of reading and potentially for improved performance. One use of unformatted input is the implementation of formatted input:

If you have a choice, use formatted input (§38.4.1.1) instead these low-level input functions.

The simple get(c) is useful when you need to compose your values out of characters. The other get() function and getline() read sequences of characters into a fixed-size area [p:...). They read until they reach the maximum number of characters or find their terminator character (by default '\n'). They place a 0 at the end of the characters (if any) written to; getline() removes its terminator from the input, if found, whereas get() does not. For example:

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void f()  // low-level, old-style line read
{
     char word[MAX_WORD][MAX_LINE];                // MAX_WORD arrays of MAX_LINE char each
     int i = 0;
     while(cin.getline(word[i++],MAX_LINE,'\n') && i<MAX_WORD)
          /* do nothing */ ;
     // ...
}

For these functions, it is not immediately obvious what terminated the read:

• We found the terminator.

• We read the maximum number of characters.

• We hit end-of-file.

• There was a non-format input error.

The last two alternatives are handled by looking at the file state (§38.3). Typically, the appropriate actions are quite different for these cases.

A read(p,n) does not write a 0 to the array after the characters read. Obviously, the formatted input operators are simpler to use and less error-prone than the unformatted ones.

The following functions depend on the detailed interaction between the stream buffer (§38.6) and the real data source and should be used only if necessary and then very carefully:

38.4.2. Output Operations

Output operations are provided by ostream (§38.6.1), found in <ostream> except for the ones writing out a string; those are found in <string>:

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template<typename C, typename Tr = char_traits<C>>
class basic_ostream : virtual public basic_ios<C,Tr> {
public:
     using char_type = C;
     using int_type = typename Tr::int_type;
     using pos_type = typename Tr::pos_type;
     using off_type = typename Tr::off_type;
     using traits_type = Tr;

     explicit basic_ostream(basic_streambuf<char_type, Tr>* sb);
     virtual ~basic_ostream(); // release all resources

     class sentry; // see §38.4.1
     // ...
protected:
     // move but no copy:
     basic_ostream(const basic_ostream& rhs) = delete;
     basic_ostream(basic_ostream&& rhs);
     basic_ostream& operator=(basic_ostream& rhs) = delete;
     basic_ostream& operator=(const basic_ostream&& rhs);
     // ...
};

An ostream offers formatted output, unformatted output (output of characters), and simple operations on its streambuf (§38.6):

Unless otherwise stated, an ostream operation returns a reference to its ostream, so that we can “chain” operations. For example:

cout << "The value of x is " << x << '\n';

Note that char values are output as characters rather than small integers. For example:

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void print_val(char ch)
{
     cout << "the value of '" << ch << "' is " << int{ch} << '\n';
}

void test()
{
     print_val('a');
     print_val('A');
}

This prints:

the value of 'a' is 97
the value of 'A' is 65

Versions of operator << for user-defined types are usually trivial to write:

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template<typename T>
struct Named_val {
     string name;
     T value;
};

ostream& operator<<(ostream& os, const Named_val& nv)
{
     return os << '{' << nv.name << ':' << nv.value << '}';
}

This will work for every Named_val<X> where X has a << defined. For full generality, << must be defined for basic_string<C,Tr>.

38.4.2.1. Virtual Output Functions

The ostream members are not virtual. The output operations that a programmer can add are not members, so they cannot be virtual either. One reason for this is to achieve close to optimal performance for simple operations such as putting a character into a buffer. This is a place where runtime efficiency is often crucial so that inlining is a must. Virtual functions are used to achieve flexibility for the operations dealing with buffer overflow and underflow only (§38.6).

However, a programmer sometimes wants to output an object for which only a base class is known. Since the exact type isn’t known, correct output cannot be achieved simply by defining a << for each new type. Instead, a virtual output function can be provided in an abstract base:

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class My_base {
public:
     // ...
     virtual ostream& put(ostream& s) const = 0; // write *this to s
};

ostream& operator<<(ostream& s, const My_base& r)
{
     return r.put(s); // use the right put()
}

That is, put() is a virtual function that ensures that the right output operation is used in <<.

Given that, we can write:

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class Sometype : public My_base {
public:
     // ...
     ostream& put(ostream& s) const override;   // the real output function
};

void f(const My_base& r, Sometype& s) // use << which calls the right put()
{
     cout << r << s;
}

This integrates the virtual put() into the framework provided by ostream and <<. The technique is generally useful to provide operations that act like virtual functions, but with the run-time selection based on their second argument. This is similar to the technique that under the name double dispatch is often used to select an operation based on two dynamic types (§22.3.1). A similar technique can be used to make input operations virtual (§22.2.4).

38.4.3. Manipulators

If a pointer to function is given as the second argument to <<, the function pointed to is called. For example, cout<<pf means pf(cout). Such a function is called a manipulator. Manipulators that take arguments can be useful. For example:

cout << setprecision(4) << angle;

This prints the value of the floating-point variable angle with four digits.

To do this, setprecision returns an object that is initialized by 4 and calls cout.precision(4) when invoked. Such a manipulator is a function object that is invoked by << rather than by (). The exact type of that function object is implementation-defined, but it might be defined like this:

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struct smanip {
     ios_base& (*f)(ios_base&,int);   // function to be called
     int i;                           // value to be used
     smanip(ios_base&(*ff)(ios_base&,int), int ii) :f{ff}, i{ii} { }
};

template<typename C, typename Tr>
basic_ostream<C,Tr>& operator<<(basic_ostream<C,Tr>& os, const smanip& m)
{
     m.f(os,m.i); // call m's f with m's stored value
     return os;
}

We can now define setprecision() like this:

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inline smanip setprecision(int n)
{
     auto h = [](ios_base& s, int x) –> ios_base& { s.precision(x); return s; };
     return smanip(h,n);      // make the function object
}

The explicit specification of the return type for the lambda is needed to return a reference. An ios_base cannot be copied by a user.

We can now write:

cout << setprecision(4) << angle;

A programmer can define new manipulators in the style of smanip as needed. Doing this does not require modification of the definitions of standard-library templates and classes.

The standard-library manipulators are described in §38.4.5.2.

38.4.4. Stream State

In <ios>, the standard library defines the base class ios_base defining most of the interface to a stream class:

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template<typename C, typename Tr = char_traits<C>>
class basic_ios : public ios_base {
public:
     using char_type = C;
     using int_type = typename Tr::int_type;
     using pos_type = typename Tr::pos_type;
     using off_type = Tr::off_type;
     using traits_type = Tr;
     // ...
};

The basic_ios class manages the state of a stream:

• The mapping between a stream and its buffers (§38.6)

• The formatting options (§38.4.5.1)

• The use of locales (Chapter 39)

• Error handling (§38.3)

• Connections to other streams and stdio (§38.4.4)

It might be the most complicated class in the standard library.

The ios_base holds information that does not depend on template arguments:

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class ios_base {
public:
     using fmtflags = /* implementation-defined type */;
     using iostate = /* implementation-defined type */;
     using openmode = /* implementation-defined type */;
     using seekdir = /* implementation-defined type */;

     class failure;       // exception class
     class Init;          // initialize standard iostreams
};

The implementation-defined types are all bitmask types; that is, they support bitwise logical operations, such as & and |. Examples are int (§11.1.2) and bitset (§34.2.2).

The ios_base controls an iostream’s connection (or lack thereof) to stdio (§43.3):

A call of sync_with_stdio(true) before the first iostream operation in the execution of a program guarantees that the iostream and stdio (§43.3) I/O operations share buffers. A call of sync_with_stdio(false) before the first stream I/O operation prevents buffer sharing and can improve I/O performance significantly on some implementations.

Note that ios_base has no copy or move operations.

Functions for reading these bits (good(), fail(), etc.) in a stream are provided by basic_ios.

The exact meaning of ios_base::binary is implementation-dependent. However, the usual meaning is that a character gets mapped to a byte. For example:

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template<typename T>
char* as_bytes(T& i)
{
     return static_cast<char*>(&i); // treat that memory as bytes
}

void test()
{
     ifstream ifs("source",ios_base::binary);       // stream mode is binary
     ofstream ofs("target",ios_base::binary);       // stream mode is binary

     vector<int> v;

     for (int i; ifs.read(as_bytes(i),sizeof(i));)  // read bytes from binary file
           v.push_back(i);

     // ... do something with v ...

     for (auto i : v)                               // write bytes to binary file:
           ofs.write(as_bytes(i),sizeof(i));
}

Use binary I/O when dealing with objects that are “just bags of bits” and do not have an obvious and reasonable character string representation. Images and sound/video streams are examples.

The seekg() (§38.6.2) and seekp() (§38.6.2) operations require a direction:

Classes derived from basic_ios format output and extract objects based on the information stored in their basic_io.

The ios_base operations can be summarized:

The conversion of an ios (including istreams and ostreams) to bool is essential to the usual idiom for reading many values:

for (X x; cin>>x;) {
     // ...
}

Here, the return value of cin>>x is a reference to cin’s ios. This ios is implicitly converted to a bool representing the state of cin. Thus, we could equivalently have written:

for (X x; !(cin>>x).fail();) {
     // ...
}

The tie() is used to ensure that output from a tied stream appears before an input from the stream to which it is tied. For example, cout is tied to cin:

cout << "Please enter a number: ";
int num;
cin >> num;

This code does not explicitly call cout.flush(), so had cout not been tied to cin, the user would see the request for input.

Sometimes, people want to add to the state of a stream. For example, one might want a stream to “know” whether a complex should be output in polar or Cartesian coordinates. Class ios_base provides a function xalloc() to allocate space for such simple state information. The value returned by xalloc() identifies a pair of locations that can be accessed by iword() and pword().

Sometimes, an implementer or a user needs to be notified about a change in a stream’s state. The register_callback() function “registers” a function to be called when its “event” occurs. Thus, a call of imbue(), copyfmt(), or ~ios_base() will call a function “registered” for an imbue_event, copyfmt_event, or erase_event, respectively. When the state changes, registered functions are called with the argument i supplied by their register_callback().

The event and event_callback types are defined in ios_base:

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enum event {
    erase_event,
    imbue_event,
    copyfmt_event
};
using event_callback = void (*)(event, ios_base&, int index);

38.4.5. Formatting

The format of stream I/O is controlled by a combination of object type, stream state (§38.4.4), format state (§38.4.5.1), locale information (Chapter 39), and explicit operations (e.g., manipulators; §38.4.5.2).

38.4.5.1. Formatting State

In <ios>, the standard library defines a set of formatting constants of an implementation-defined bit-mask type fmtflags as members of class ios_base:

Curiously, there are no defaultfloat or hexfloat flags. To get the equivalent, use manipulators default-float and hexfloat (§38.4.5.2), or manipulate the ios_base directly:

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ios.unsetf(ios_base::floatfield);                               // use the default floating-point format
ios.setf(ios_base::fixed | ios_base::scientific, ios_base::floatfield);           // use hexadecimal floats

An iostream’s format state can be read and written (set) by operations provided in its ios_base:

Precision is an integer that determines the number of digits used to display a floating-point number:

• The general format (defaultfloat) lets the implementation choose a format that presents a value in the style that best preserves the value in the space available. The precision specifies the maximum number of digits.

• The scientific format (scientific) presents a value with one digit before a decimal point and an exponent. The precision specifies the maximum number of digits after the decimal point.

• The fixed format (fixed) presents a value as an integer part followed by a decimal point and a fractional part. The precision specifies the maximum number of digits after the decimal point. For example, see §38.4.5.2.

Floating-point values are rounded rather than just truncated, and precision() doesn’t affect integer output. For example:

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cout.precision(8);
cout << 1234.56789 << ' ' << 1234.56789 << ' ' << 123456 << '\n';

cout.precision(4);
cout << 1234.56789 << ' ' << 1234.56789 << ' ' << 123456 << '\n';

This produces:

1234.5679 1234.5679 123456
1235 1235 123456

The width() function specifies the minimum number of characters to be used for the next standard-library << output operation of a numeric value, bool, C-style string, character, pointer, string, and bitset (§34.2.2). For example:

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cout.width(4);
cout << 12;   // print 12 preceded by two spaces

The “padding” or “filler” character can be specified by the fill() function. For example:

cout.width(4);
cout.fill('#');
cout << "ab";      // print ##ab

The default fill character is the space character, and the default field size is 0, meaning “as many characters as needed.” The field size can be reset to its default value like this:

cout.width(0);   // "as many characters as needed"

A call width(n) sets the minimum number of characters to n. If more characters are provided, they will all be printed. For example:

cout.width(4);
cout << "abcdef";   // print abcdef

It does not truncate the output to abcd. It is usually better to get the right output looking ugly than to get the wrong output looking just fine.

A width(n) call affects only the immediately following << output operation. For example:

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cout.width(4);
cout.fill('#');
cout << 12 << ':' << 13;   // print ##12:13

This produces ##12:13, rather than ##12###:##13.

If the explicit control of formatting options through many separate operations becomes tedious, we can combine them using a user-defined manipulator (§38.4.5.3).

An ios_base also allows the programmer to set an iostream’s locale (Chapter 39):

38.4.5.2. Standard Manipulators

The standard library provides manipulators corresponding to the various format states and state changes. The standard manipulators are defined in <ios>, <istream>, <ostream>, and <iomanip> (for manipulators that take arguments):

Each of these operations returns a reference to its first (stream) operand, s. For example:

cout << 1234 << ',' << hex << 1234 << ',' << oct << 1234 << '\n';       // print 1234,4d2,2322

We can explicitly set the output format for floating-point numbers:

     constexpr double d = 123.456;

     cout << d << "; "
          << scientific << d << "; "
          << hexfloat << d << "; "
          << fixed << d << "; "
          << defaultfloat << d << '\n';

This produces:

123.456; 1.234560e+002; 0x1.edd2f2p+6; 123.456000; 123.456

The floating-point format is “sticky”; that is, it persists for subsequent floating-point operations.

An ostream is flushed when it is destroyed, when a tie()d istream needs input (§38.4.4), and when the implementation finds it advantageous. Explicitly flushing a stream is very rarely necessary. Similarly, <<endl can be considered equivalent to <<'\n', but the latter is probably a bit faster. I find

cout << "Hello, World!\n";

easier to read and write than

cout << "Hello, World!" << endl;

If you have a genuine need for frequent flushing, consider cerr and unitbuf.

The time facets are found in §39.4.4 and the time formats in §43.6.

For example:

cout << '(' << setw(4) << setfill('#') << 12 << ") (" << 12 << ")\n";      // print (##12) (12)

By default >> skips whitespace (§38.4.1). This default can be modified by >>skipws and >>noskipws. For example:

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string input {"0 1 2 3 4"};
istringstream iss {input};
string s;
for (char ch; iss>>ch;)
      s += ch;
cout << s;                // print "01234"

istringstream iss2 {input};
iss>>noskipws;
for (char ch; iss2>>ch;)
      s += ch;
cout << s;                // print "0 1 2 3 4"
}

If you want to explicitly deal with whitespace (e.g., to make a newline significant) and still use >>, noskipws and >>ws become a convenience.

38.4.5.3. User-Defined Manipulators

A programmer can add manipulators in the style of the standard ones. Here, I present an additional style that I have found useful for formatting floating-point numbers.

Formatting is controlled by a confusing multitude of separate functions (§38.4.5.1). For example, a precision() persists for all output operations, but a width() applies to the next numeric output operation only. What I want is something that makes it simple to output a floating-point number in a predefined format without affecting future output operations on the stream. The basic idea is to define a class that represents formats, another that represents a format plus a value to be formatted, and then an operator << that outputs the value to an ostream according to the format. For example:

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Form gen4 {4};      // general format, precision 4

void f(double d)
{
     Form sci8;
     sci8.scientific().precision(8);       // scientific format, precision 8
     cout << d << ' ' << gen4(d) << ' ' << sci8(d) << ' ' << d << '\n';

     Form sci {10,ios_base::scientific};   // scientific format, precision 10
     cout << d << ' ' << gen4(d) << ' ' << sci(d) << ' ' << d << '\n';
}

A call f(1234.56789) writes:

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1234.57 1235 1.23456789e+003 1234.57
1234.57 1235 1.2345678900e+003 1234.57

Note how the use of a Form doesn’t affect the state of the stream, so that the last output of d has the same default format as the first.

Here is a simplified implementation:

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class Form;       // our formatting type

struct Bound_form {     // Form plus value
     const Form& f;
     double val;
};

class Form {
     friend ostream& operator<<(ostream&, const Bound_form&);

     int prc;  // precision
     int wdt;  // width 0 means "as wide as necessary"
     int fmt;  // general, scientific, or fixed (§38.4.5.1)
     // ...
public:
     explicit Form(int p =6, ios_base::fmtflags f =0, int w =0) : prc{p}, fmt{f}, wdt{w} {}

     Bound_form Form::operator()(double d) const          // make a Bound_form for *this and d
     {
         return Bound_form{*this,d};
     }

     Form& scientific() { fmt = ios_base::scientific; return *this; }
     Form& fixed() { fmt = ios_base::fixed; return *this; }
     Form& general() { fmt = 0; return *this; }

     Form& uppercase();
     Form& lowercase();
     Form& precision(int p) { prc = p; return *this; }

     Form& width(int w) { wdt = w; return *this; }       // applies to all types
     Form& fill(char);

     Form& plus(bool b = true);                          // explicit plus
     Form& trailing_zeros(bool b = true);                // print trailing zeros
     // ...
};

The idea is that a Form holds all the information needed to format one data item. The default is chosen to be reasonable for many uses, and the various member functions can be used to reset individual aspects of formatting. The () operator is used to bind a value with the format to be used to output it. A Bound_form (that is, a Form plus a value) can then be output to a given stream by a suitable << function:

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ostream& operator<<(ostream& os, const Bound_form& bf)
{
    ostringstream s;                 // §38.2.2
    s.precision(bf.f.prc);
    s.setf(bf.f.fmt,ios_base::floatfield);
    s << bf.val;               // compose string in s
    return os << s.str();      // output s to os
}

Writing a less simplistic implementation of << is left as an exercise.

Note that these declarations make the combination of << and () into a ternary operator; cout<<sci4{d} collects the ostream, the format, and the value into a single function before doing any real computation.

38.5. Stream Iterators

In <iterator>, the standard library provides iterators to allow input and output streams to be viewed as sequences [input-begin:end-of-input) and [output-begin:end-of-output):

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template<typename T,
         typename C = char,
         typename Tr = char_traits<C>,
         typename Distance = ptrdiff_t>
class istream_iterator
     :public iterator<input_iterator_tag, T, Distance, const T*, const T&> {
     using char_type = C;
     using traits_type = Tr;
     using istream_type = basic_istream<C,Tr>;
     // ...
};

template<typename T, typename C = char, typename Tr = char_traits<C>>
class ostream_iterator: public iterator<output_iterator_tag, void, void, void, void> {
     using char_type = C;
     using traits_type = Tr;
     using ostream_type = basic_ostream<C,Tr>;
     // ...
};

For example:

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copy(istream_iterator<double>{cin}, istream_iterator<double,char>{},
     ostream_iterator<double>{cout,";\n"});

When an ostream_iterator is constructed with a second (string) argument, that string is output as a terminator after every element value. So, if you enter 1 2 3 to that call of copy(), the output is:

1;
2;
3;

The operators provided for a stream_iterator are the same as for other iterator adaptors (§33.2.2):

Except for the constructors, these operations are typically used by general algorithms, such as copy(), rather than directly.

38.6. Buffering

Conceptually, an output stream puts characters into a buffer. Sometime later, the characters are then written to (“flushed to”) wherever they are supposed to go. Such a buffer is called a streambuf. Its definition is found in <streambuf>. Different types of streambufs implement different buffering strategies. Typically, the streambuf stores characters in an array until an overflow forces it to write the characters to their real destination. Thus, an ostream can be represented graphically like this:

The set of template arguments for an ostream and its streambuf must be the same, and they determine the type of character used in the character buffer.

An istream is similar, except that the characters flow the other way.

Unbuffered I/O is simply I/O where the streambuf immediately transfers each character, rather than holding on to characters until enough have been gathered for efficient transfer.

The key class in the buffering mechanisms is basic_streambuf:

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template<typename C, typename Tr = char_traits<C>>
class basic_streambuf {
public:
     using char_type = C;                       // the type of a character
     using int_type = typename Tr::int_type;    // the integer type to which
                                                // a character can be converted
     using pos_type = typename Tr::pos_type;    // type of position in buffer
     using off_type = typename Tr::off_type;    // type of offset from position in buffer
     using traits_type = Tr;
     // ...
     virtual ~basic_streambuf();
};

As usual, a couple of aliases are provided for the (supposedly) most common cases:

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using streambuf = basic_streambuf<char>;
using wstreambuf = basic_streambuf<wchar_t>;

The basic_streambuf has a host of operations. Many of the public operations simply call a protected virtual function that ensures that a function from a derived class implemented the operation appropriately for the particular kind of buffer:

All constructors are protected because basic_streambuf is designed as a base class.

The exact meaning of the virtual functions are determined by derived classes.

A streambuf has a put area into which << and other output operations write (§38.4.2), and a get area from which >> and other input operations read (§38.4.1). Each area is described by a beginning pointer, current pointer, and one-past-the-end pointer:

Overflow are handled by the virtual functions overflow(), underflow(), and uflow().

For a use of positioning, see §38.6.1.

The put-and-get interface is separated into a public and a protected one:

The protected interface provides simple, efficient, and typically inlined functions manipulating the put and get pointers. In addition, there are virtual functions to be overridden by derived classes.

The showmanyc() (“show how many characters”) function is an odd function intended to allow a user to learn something about the state of a machine’s input system. It returns an estimate of how many characters can be read “soon,” say, by emptying the operating system’s buffers rather than waiting for a disk read. A call to showmanyc() returns –1 if it cannot promise that any character can be read without encountering end-of-file. This is (necessarily) rather low-level and highly implementation-dependent. Don’t use showmanyc() without a careful reading of your system documentation and conducting a few experiments.

38.6.1. Output Streams and Buffers

An ostream provides operations for converting values of various types into character sequences according to conventions (§38.4.2) and explicit formatting directives (§38.4.5). In addition, an ostream provides operations that deal directly with its streambuf:

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template<typename C, typename Tr = char_traits<C>>
class basic_ostream : virtual public basic_ios<C,Tr> {
public:
     // ...
     explicit basic_ostream(basic_streambuf<C,Tr>* b);

     pos_type tellp();                                   // get current position
     basic_ostream& seekp(pos_type);                     // set current position
     basic_ostream& seekp(off_type, ios_base::seekdir);  // set current position

     basic_ostream& flush();                             // empty buffer (to real destination)

     basic_ostream& operator<<(basic_streambuf<C,Tr>* b);     // write from b
};

The basic_ostream functions override their equivalents in the basic_ostream’s basic_ios base.

An ostream is constructed with a streambuf argument, which determines how the characters written are handled and where they eventually go. For example, an ostringstream (§38.2.2) or an ofstream (§38.2.1) is created by initializing an ostream with a suitable streambuf (§38.6).

The seekp() functions are used to position an ostream for writing. The p suffix indicates that it is the position used for putting characters into the stream. These functions have no effect unless the stream is attached to something for which positioning is meaningful, such as a file. The pos_type represents a character position in a file, and the off_type represents an offset from a point indicated by an ios_base::seekdir.

Stream positions start at 0, so we can think of a file as an array of n characters. For example:

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int f(ofstream& fout)// fout refers to some file
{
      fout << "0123456789";
      fout.seekp(8);                    // 8 from beginning
      fout << '#';                      // add '#' and move position (+1)
      fout.seekp(–4,ios_base::cur);     // 4 backward
      fout << '*';                      // add '*' and move position (+1)
}

If the file was initially empty, we get:

01234*67#9

There is no similar way to do random access on elements of a plain istream or ostream. Attempting to seek beyond the beginning or the end of a file typically puts the stream into the bad() state (§38.4.4). However, some operating systems have operating modes where the behavior differs (e.g., positioning might resize a file).

The flush() operation allows the user to empty the buffer without waiting for an overflow.

It is possible to use << to write a streambuf directly into an ostream. This is primarily handy for implementers of I/O mechanisms.

38.6.2. Input Streams and Buffers

An istream provides operations for reading characters and converting them into values of various types (§38.4.1). In addition, an istream provides operations that deal directly with its streambuf:

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template<typename C, typename Tr = char_traits<C>>
class basic_istream : virtual public basic_ios<C,Tr> {
public:
     // ...
     explicit basic_istream(basic_streambuf<C,Tr>* b);
     pos_type tellg();                                     // get current position
     basic_istream& seekg(pos_type);                       // set current position
     basic_istream& seekg(off_type, ios_base::seekdir);    // set current position

     basic_istream& putback(C c);     // put c back into the buffer
     basic_istream& unget();          // put back most recent char read
     int_type peek();                 // look at next character to be read

     int sync();                      // clear buffer (flush)

     basic_istream& operator>>(basic_streambuf<C,Tr>* b);      // read into b
     basic_istream& get(basic_streambuf<C,Tr>& b, C t = Tr::newline());
     streamsize readsome(C* p, streamsize n);   // read at most n char
};

The basic_istream functions override their equivalents in the basic_istream’s basic_ios base.

The positioning functions work like their ostream counterparts (§38.6.1). The g suffix indicates that it is the position used for getting characters from the stream. The p and g suffixes are needed because we can create an iostream derived from both istream and ostream, and such a stream needs to keep track of both a get position and a put position.

The putback() function allows a program to put a character “back” into an istream to be the next character read. The unget() function puts the most recently read character back. Unfortunately, backing up an input stream is not always possible. For example, trying to back up past the first character read will set ios_base::failbit. What is guaranteed is that you can back up one character after a successful read. The peek() function reads the next character and also leaves that character in the streambuf so that it can be read again. Thus, c=peek() is logically equivalent to (c=get(),unget(),c). Setting failbit might trigger an exception (§38.3).

Flushing an istream is done using sync(). This cannot always be done right. For some kinds of streams, we would have to reread characters from the real source – and that is not always possible or desirable (e.g., for a stream attached to a network). Consequently, sync() returns 0 if it succeeded. If it failed, it sets ios_base::badbit (§38.4.4) and returns –1. Setting badbit might trigger an exception (§38.3). A sync() on a buffer attached to an ostream flushes the buffer to output.

The >> and get() operations that directly reads from a streambuf are primarily useful for implementers of I/O facilities.

The readsome() function is a low-level operation that allows a user to peek at a stream to see if there are any characters available to read. This can be most useful when it is undesirable to wait for input, say, from a keyboard. See also in_avail() (§38.6).

38.6.3. Buffer Iterators

In <iterator>, the standard library provides istreambuf_iterator and ostreambuf_iterator to allow a user (mostly an implementer of a new kind of iostream) to iterate over the contents of a stream buffer. In particular, these iterators are widely used by locale facets (Chapter 39).

38.6.3.1. istreambuf_iterator

An istreambuf_iterator reads a stream of characters from an istream_buffer:

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template<typename C, typename Tr = char_traits<C>> // §iso.24.6.3
class istreambuf_iterator
     :public iterator<input_iterator_tag, C, typename Tr::off_type, /*unspecified*/, C> {
public:
     using char_type = C;
     using traits_type = Tr;
     using int_type = typename Tr::int_type;
     using streambuf_type = basic_streambuf<C,Tr>;
     using istream_type = basic_istream<C,Tr>;
     // ...
};

The reference member of the iterator base is not used and is consequently left unspecified.

If you use an istreambuf_iterator as an input iterator, its effect is like that of other input iterators: a stream of characters can be read from input using c=* p++:

Note that any attempt to be clever when comparing istreambuf_iterators will fail: you cannot rely on two iterators referring to the same character while input is going on.

38.6.3.2. ostreambuf_iterator

An ostreambuf_iterator writes a stream of characters to an ostream_buffer:

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template<typename C, typename Tr = char_traits<C>>  // §iso.24.6.4
class ostreambuf_iterator
     :public iterator<output_iterator_tag, void, void, void, void> {
public:
     using char_type = C;
     using traits_type = Tr;
     using streambuf_type = basic_streambuf<C,Tr>;
     using ostream_type = basic_ostream<C,Tr>;
     // ...
};

By most measures, ostreambuf_iterator’s operations are odd, but the net effect is that if you use it as an output iterator, its effect is like that of other output iterators: a stream of characters can be written to output using *p++=c:

38.7. Advice

[1] Define << and >> for user-defined types with values that have meaningful textual representations; §38.1, §38.4.1, §38.4.2.

[2] Use cout for normal output and cerr for errors; §38.1.

[3] There are iostreams for ordinary characters and wide characters, and you can define an iostream for any kind of character; §38.1.

[4] There are standard iostreams for standard I/O streams, files, and strings; §38.2.

[5] Don’t try to copy a file stream; §38.2.1.

[6] Binary I/O is system specific; §38.2.1.

[7] Remember to check that a file stream is attached to a file before using it; §38.2.1.

[8] Prefer ifstreams and ofstreams over the generic fstream; §38.2.1.

[9] Use stringstreams for in-memory formatting; §38.2.2.

[10] Use exceptions to catch rare bad() I/O errors; §38.3.

[11] Use the stream state fail to handle potentially recoverable I/O errors; §38.3.

[12] You don’t need to modify istream or ostream to add new << and >> operators; §38.4.1.

[13] When implementing a iostream primitive operation, use sentry; §38.4.1.

[14] Prefer formatted input over unformatted, low-level input; §38.4.1.

[15] Input into strings does not overflow; §38.4.1.

[16] Be careful with the termination criteria when using get(), getline(), and read(); §38.4.1.

[17] By default >> skips whitespace; §38.4.1.

[18] You can define a << (or a >>) so that it behaves as a virtual function based on its second operand; §38.4.2.1.

[19] Prefer manipulators to state flags for controlling I/O; §38.4.3.

[20] Use sync_with_stdio(true) if you want to mix C-style and iostream I/O; §38.4.4.

[21] Use sync_with_stdio(false) to optimize iostreams; §38.4.4.

[22] Tie streams used for interactive I/O; §38.4.4.

[23] Use imbue() to make an iostream reflect “cultural differences” of a locale; §38.4.4.

[24] width() specifications apply to the immediately following I/O operation only; §38.4.5.1.

[25] precision() specifications apply to all following floating-point output operations; §38.4.5.1.

[26] Floating-point format specifications (e.g., scientific) apply to all following floating-point output operations; §38.4.5.2.

[27] #include <iomanip> when using standard manipulators taking arguments; §38.4.5.2.

[28] You hardly ever need to flush(); §38.4.5.2.

[29] Don’t use endl except possibly for aesthetic reasons; §38.4.5.2.

[30] If iostream formatting gets too tedious, write your own manipulators; §38.4.5.3.

[31] You can achieve the effect (and efficiency) of a ternary operator by defining a simple function object; §38.4.5.3.

39. Locales

When in Rome, do as the Romans do.

– Proverb

• Handling Cultural Differences

• Class locale

Named locales; Comparing strings

• Class facet

Accessing facets in a locale; A Simple User-defined facet; Uses of locales and facets

• Standard facets

string Comparison; Numeric Formatting; Money Formatting; Date and Time Formatting; Character Classification; Character Code Conversion; Messages

• Convenience Interfaces

Character Classifications; Character Conversions; String Conversions; Buffer Conversions

• Advice

39.1. Handling Cultural Differences

A locale is an object that represents a set of cultural preferences, such as how strings are compared, the way numbers appear as human-readable output, and the way characters are represented in external storage. The notion of a locale is extensible so that a programmer can add new facets to a locale representing locale-specific entities not directly supported by the standard library, such as postal codes (zip codes) and phone numbers. The primary use of locales in the standard library is to control the appearance of information written to an ostream and the format of data read by an istream.

This chapter describes how to use a locale, how a locale is constructed out of facets, and how a locale affects an I/O stream.

The notion of a locale is not primarily a C++ notion. Most operating systems and application environments have a notion of locale. Such a notion is – in principle – shared among all programs on a system, independently of which programming language they are written in. Thus, the C++ standard-library notion of a locale can be seen as a standard and portable way for C++ programs to access information that has very different representations on different systems. Among other things, a C++ locale is an interface to system information that is represented in incompatible ways on different systems.

Consider writing a program that needs to be used in several countries. Writing a program in a style that allows that is often called internationalization (emphasizing the use of a program in many countries) or localization (emphasizing the adaptation of a program to local conditions). Many of the entities that a program manipulates will conventionally be displayed differently in those countries. We can handle this by writing our I/O routines to take this into account. For example:

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void print_date(const Date& d)     // print in the appropriate format
{
     switch(where_am_I) {    // user-defined style indicator
     case DK:           // e.g., 7. marts 1999
          cout << d.day() << ". " << dk_month[d.month()] << " " << d.year();
          break;
     case ISO:          // e.g., 1999-3-7
          cout << d.year() << " – " << d.month() << " / " << d.day();
          break;
     case US:           // e.g., 3/7/1999
          cout << d.month() << "/" << d.day() << "/" << d.year();
          break;
     // ...
     }
}

This style of code does the job. However, such code is ugly and hard to maintain. In particular, we have to use this style consistently to ensure that all output is properly adjusted to local conventions. If we want to add a new way of writing a date, we must modify the application code. Worse yet, writing dates is only one of many examples of cultural differences.

Consequently, the standard library provides an extensible way of handling cultural conventions. The iostream library relies on this framework to handle both built-in and user-defined types (§38.1). For example, consider a simple loop copying (Date,double) pairs that might represent a series of measurements or a set of transactions:

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void cpy(istream& is, ostream& os)// copy (Date,double) stream
{
     Date d;
     double volume;

     while (is >> d >> volume)
           os << d << ' '<< volume << '\n';
}

Naturally, a real program would do something with the records and ideally also be a bit more careful about error handling.

How would we make this program read a file that conformed to French conventions (where a comma is the character used to represent the decimal point in a floating-point number; for example, 12,5 means twelve and a half) and write it according to American conventions? We can define locales and I/O operations so that cpy() can be used to convert between conventions:

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void f(istream& fin, ostream& fout, istream& fin2, ostream& fout2)
{
     fin.imbue(locale{"en_US.UTF–8"});       // American English
     fout.imbue(locale{"fr_FR.UTF–8"});      // French
     cpy(fin,fout);                          // read American English, write French
     // ...

     fin2.imbue(locale{"fr_FR.UTF–8"});      // French
     fout2.imbue(locale{"en_US.UTF–8"});     // American English
     cpy(fin2,fout2);                        // read French, write American English
     // ...
}

Given these streams:

Apr 12, 1999    1000.3
Apr 13, 1999    345.45
Apr 14, 1999    9688.321
...
3 juillet 1950  10,3
3 juillet 1951  134,45
3 juillet 1952  67,9
...

this program would produce:

12 avril 1999 1000,3
13 avril 1999 345,45
14 avril 1999 9688,321
...
July 3, 1950 10.3
July 3, 1951 134.45
July 3, 1952 67.9
...

Much of the rest of this chapter is devoted to describing the mechanisms that make this possible and explaining how to use them. However, most programmers will have little reason to deal with the details of locales and will never explicitly manipulate a locale. At most, they will simply retrieve a standard locale and imbue a stream with it (§38.4.5.1).

The concept of localization (internationalization) is simple. However, practical constraints make the design and implementation of locale quite intricate:

[1] A locale encapsulates cultural conventions, such as the appearance of a date. Such conventions vary in many subtle and unsystematic ways. These conventions have nothing to do with programming languages, so a programming language cannot standardize them.

[2] The concept of a locale must be extensible, because it is not possible to enumerate every cultural convention that is important to every C++ user.

[3] A locale is used in operations (e.g., I/O and sorting) from which people demand run-time efficiency.

[4] A locale must be invisible to the majority of programmers who want to benefit from facilities “doing the right thing” without having to know exactly what “the right thing” is or how it is achieved.

[5] A locale must be available to designers of facilities that deal with culture-sensitive information beyond the scope of the standard.

The mechanisms provided to compose those locales and to make them trivial to use constitute a little programming language of their own.

A locale is composed of facets that control individual aspects, such as the character used for punctuation in the output of a floating-point value (decimal_point(); §39.4.2) and the format used to read a monetary value (moneypunct; §39.4.3). A facet is an object of a class derived from class locale::facet (§39.3). We can think of a locale as a container of facets (§39.2, §39.3.1).

39.2. Class locale

The locale class and its associated facilities are presented in <locale>.

If a locale of a given name or a facet referred to doesn’t exist, the locale operation naming it throws a runtime_error.

Naming of locales is a bit curious. When you make a new locale from another plus a facet and the resulting locale has a name, that name is implementation-defined. Often, such an implementation-defined name includes the name of the locale that supplied most of the facets. For a locale without a name, name() returns "*".

A locale can be thought of as an interface to a map<id,facet*>, that is, something that allows us to use a locale::id to find a corresponding object of a class derived from locale::facet. A real implementation of locale is an efficient variant of this idea. The layout will be something like this:

Here, collate<char> and numpunct<char> are standard-library facets (§39.4). All facets are derived from locale::facet.

A locale is meant to be copied freely and cheaply. Consequently, a locale is almost certainly implemented as a handle to the specialized map<id,facet*> that constitutes the main part of its implementation. The facets must be quickly accessible in a locale. Consequently, the specialized map<id,facet*> will be optimized to provide array-like fast access. The facets of a locale are accessed by using the use_facet<Facet>(loc) notation; see §39.3.1.

The standard library provides a rich set of facets. To help the programmer manipulate facets in logical groups, the standard facets are grouped into categories, such as numeric and collate (§39.4):

There are no facilities for a programmer to specify a name string for a newly created locale. Name strings are either defined in the program’s execution environment or created as combinations of such names by locale constructors.

A programmer can replace facets from existing categories (§39.4, §39.4.2.1). However, there is no way for a programmer to define a new category. The notion of “category” applies to standard-library facets only, and it is not extensible. Thus, a facet need not belong to any category, and many user-defined facets do not.

If a locale x does not have a name string, it is undefined whether locale::global(x) affects the C global locale. This implies that a C++ program cannot reliably and portably set the C locale to a locale that wasn’t retrieved from the execution environment. There is no standard way for a C program to set the C++ global locale (except by calling a C++ function to do so). In a mixed C and C++ program, having the C global locale differ from global() is error prone.

By far the dominant use of locales is implicitly, in stream I/O. Each istream and ostream has its own locale. The locale of a stream is by default the global locale (§39.2.1) at the time of the stream’s creation. The locale of a stream can be set by the imbue() operation, and we can extract a copy of a stream’s locale using getloc() (§38.4.5.1).

Setting the global locale does not affect existing I/O streams; those still use the locales that they were imbued with before the global locale was reset.

39.2.1. Named locales

A locale is constructed from another locale and from facets. The simplest way of making a locale is to copy an existing one. For example:

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locale loc1;                          // copy of the current global locale
locale loc2 {""};                     // copy of "the user's preferred locale"

locale loc3 {"C"};                    // copy of the "C" locale
locale loc4 {locale::classic()};      // copy of the "C" locale

locale loc5 {"POSIX"};                // copy of the locale named "POSIX"
locale loc6 {"Danish_Denmark.1252"};  // copy of the locale named "Danish_Denmark.1252"
locale loc7 {"en_US.UTF–8"};          // copy of the locale named "en_US.UTF-8"

The meaning of locale{"C"} is defined by the standard to be the “classic” C locale; this is the locale that has been used throughout this book. Other locale names are implementation-defined.

The locale{""} is deemed to be “the user’s preferred locale.” This locale is set by extralinguistic means in a program’s execution environment. So to see your current “preferred locale,” write:

locale loc("");
cout << loc.name() << '\n';

On my Windows laptop, I got:

English_United States.1252

On my Linux box, I got:

en_US.UTF–8

The names of locales are not standardized for C++. Instead, a variety of organizations, such as POSIX and Microsoft, maintain their own (differing) standards across different programming languages. For example:

POSIX recommends a format of a lowercase language name, optionally followed by an uppercase country name, optionally followed by an encoding specifier, for example, sv_FI@euro (Swedish for Finland including the euro symbol).

Microsoft uses a language name followed by a country name optionally followed by a code page number. A code page is a named (or numbered) character encoding.

Most operating systems have ways of setting a default locale for a program. Typically, that is done through environment variables with names such as LC_ALL, LC_COLLATE, and LANG. Often, a locale suitable to the person using a system is chosen when that person first encounters a system. For example, I would expect a person who configures a Linux system to use Argentine Spanish as its default setting will find locale{""} to mean locale{"es_AR"}. However, these names are not standardized across platforms. So, to use named locales on a given system, a programmer must refer to system documentation and experiment.

It is generally a good idea to avoid embedding locale name strings in the program text. Mentioning a file name or a system constant in the program text limits the portability of a program and often forces a programmer who wants to adapt a program to a new environment to find and change such values. Mentioning a locale name string has similar unpleasant consequences. Instead, locales can be picked up from the program’s execution environment (for example, using locale("") or reading a file). Alternatively, a program can request a user to specify alternative locales by entering a string. For example:

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void user_set_locale(const string& question)
{
     cout << question;  // e.g., "If you want to use a different locale, please enter its name"
     string s;
     cin >> s;
     locale::global(locale{s}); // set global locale as specified by user
}

It is usually better to let a non-expert user pick from a list of alternatives. A function implementing this would need to know where and how a system keeps its locales. For example, many Linux systems keep their locales in the directory /usr/share/locale.

If the string argument doesn’t refer to a defined locale, the constructor throws the runtime_error exception (§30.4.1.1). For example:

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void set_loc(locale& loc, const char* name)
try
{
     loc = locale{name};
}
catch (runtime_error&) {
     cerr << "locale
     // ...
}

If a locale has a name string, name() will return it. If not, name() will return string("*"). A name string is primarily a way to refer to a locale stored in the execution environment. Secondarily, a name string can be used as a debugging aid. For example:

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void print_locale_names(const locale& my_loc)
{
     cout << "name of current global locale: " << locale().name() << "\n";
     cout << "name of classic C locale: " << locale::classic().name() << "\n";
     cout << "name of "user's preferred locale": " << locale("").name() << "\n";
     cout << "name of my locale: " << my_loc.name() << "\n";
}

39.2.1.1. Constructing New locales

A new locale is made by taking an existing locale and adding or replacing facets. Typically, a new locale is a minor variation on an existing one. For example:

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void f(const locale& loc, const My_money_io* mio)       // My_money_io defined in §39.4.3.1
{
     locale loc1(locale{"POSIX"},loc,locale::monetary); // use monetary facets from loc
     locale loc2 = locale(locale::classic(), mio);            // classic plus mio
     // ...
}

Here, loc1 is a copy of the POSIX locale modified to use loc’s monetary facets (§39.4.3). Similarly, loc2 is a copy of the C locale modified to use a My_money_io (§39.4.3.1). The resulting locales can be represented like this:

If a Facet* argument (here, My_money_io) is nullptr, the resulting locale is simply a copy of the locale argument.

In a construction locale{loc,f}, the f argument must identify a specific facet type. A plain facet* is not sufficient. For example:

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void g(const locale::facet* mio1, const money_put<char>* mio2)
{
     locale loc3 = locale(locale::classic(), mio1);    // error: type of facet not known
     locale loc4 = locale(locale::classic(), mio2);    // OK: type of facet known (moneyput<char>)
     // ...
}

The locale uses the type of the Facet* argument to determine the type of the facet at compile time. Specifically, the implementation of locale uses a facet’s identifying type, facet::id (§39.3), to find that facet in the locale (§39.3.1). The constructor

template<class Facet> locale(const locale& x, Facet* f);

is the only mechanism offered within the language for the programmer to supply a facet to be used through a locale. Other locales are supplied by implementers as named locales (§39.2.1). Named locales can be retrieved from the program’s execution environment. A programmer who understands the implementation-specific mechanism used for that might be able to add new locales.

The set of constructors for locale is designed so that the type of every facet is known either from type deduction (of the Facet template parameter) or because it came from another locale (that knew its type). Specifying a category argument specifies the type of facets indirectly, because the locale knows the type of the facets in the categories. This implies that the locale class can (and does) keep track of the types of facets so that it can manipulate them with minimal overhead.

The locale::id member type is used by locale to identify facet types (§39.3).

There is no way of modifying a locale. Instead, the locale operations provide ways of making new locales from existing ones. The fact that a locale is immutable after it has been created is essential for run-time efficiency. This allows someone using a locale to call virtual functions of a facet and to cache the values returned. For example, an istream can know what character is used to represent the decimal point and how true is represented without calling decimal_point() each time it reads a number and truename() each time it reads to a bool (§39.4.2). Only a call of imbue() for the stream (§38.4.5.1) can cause such calls to return a different value.

39.2.2. Comparing strings

Comparing two strings according to a locale is possibly the most common use of a locale outside I/O. Consequently, this operation is provided directly by locale so that users don’t have to build their own comparison function from the collate facet (§39.4.1). This string comparison function is defined as locale’s operator()(). For example:

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void user(const string s1, const string s2, const locale& my_locale)
{
     if (my_locale(s,s2)) {  // is s<s2 according to my_locale?
          // ...
     }
}

Having the comparison function as the () operator makes it directly useful as a predicate (§4.5.4). For example:

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void f(vector<string>& v, const locale& my_locale)
{
     sort(v.begin(),v.end());           // sort using < to compare elements
     // ...
     sort(v.begin(),v.end(),my_locale); // sort according to the rules of my_locale
     // ...
}

By default, the standard-library sort() uses < for the numerical value of the implementation character set to determine collation order (§32.6, §31.2.2.1).

39.3. Class facet

A locale is a collection of facets. A facet represents one specific cultural aspect, such as how a number is represented on output (num_put), how a date is read from input (time_get), and how characters are stored in a file (codecvt). The standard-library facets are listed in §39.4.

A user can define new facets, such as a facet determining how the names of the seasons are printed (§39.3.2).

A facet is represented in a program as an object of a class derived from std::locale::facet. Like all other locale facilities, facet is found in <locale>:

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class locale::facet {
protected:
     explicit facet(size_t refs = 0);
     virtual ~facet();
     facet(const facet&) = delete;
     void operator=(const facet&) = delete;
};

The facet class is designed to be a base class and has no public functions. Its constructor is protected to prevent the creation of “plain facet” objects, and its destructor is virtual to ensure proper destruction of derived-class objects.

A facet is intended to be managed through pointers stored in locales. A 0 argument to the facet constructor means that locale should delete the facet when the last reference to it goes away. Conversely, a nonzero constructor argument ensures that locale never deletes the facet. A nonzero argument is meant for the rare case in which the lifetime of a facet is controlled directly by the programmer rather than indirectly through a locale.

Each kind of facet interface must have a separate id:

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class locale::id {
public:
     id();
     void operator=(const id&) = delete;
     id(const id&) = delete;
};

The intended use of id is for the user to define a static member of type id of each class supplying a new facet interface (for example, see §39.4.1). The locale mechanisms use ids to identify facets (§39.2, §39.3.1). In the obvious implementation of a locale, an id is used as an index into a vector of pointers to facets, thereby implementing an efficient map<id,facet*>.

Data used to define a (derived) facet is defined in the derived class. This implies that the programmer defining a facet has full control over the data and that arbitrary amounts of data can be used to implement the concept represented by a facet.

A facet is intended to be immutable, so all member functions of a user-defined facet should be defined const.

39.3.1. Accessing facets in a locale

The facets of a locale are accessed using two template functions:

Think of these functions as doing a lookup in their locale argument for their template parameter F. Alternatively, think of use_facet as a kind of explicit type conversion (cast) of a locale to a specific facet. This is feasible because a locale can have only one facet of a given type. For example:

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void f(const locale& my_locale)
{
     char c = use_facet<numpunct<char>>(my_locale).decimal_point() // use standard facet
     // ...

     if (has_facet<Encrypt>(my_locale)) {   // does my_locale contain an Encrypt facet?
           const Encrypt& f = use_facet<Encrypt>(my_locale);     // retrieve Encrypt facet
           const Crypto c = f.get_crypto();                      // use Encrypt facet
           // ...
     }
     // ...
}

The standard facets are guaranteed to be available for all locales (§39.4), so we don’t need to use has_facet for standard facets.

One way of looking at the facet::id mechanism is as an optimized implementation of a form of compile-time polymorphism. A dynamic_cast can be used to get very similar results to what use_facet produces. However, the specialized use_facet can be implemented more efficiently than the general dynamic_cast.

An id identifies an interface and a behavior rather than a class. That is, if two facet classes have exactly the same interface and implement the same semantics (as far as a locale is concerned), they should be identified by the same id. For example, collate<char> and collate_byname<char> are interchangeable in a locale, so both are identified by collate<char>::id (§39.4.1).

If we define a facet with a new interface – such as Encrypt in f() – we must define a corresponding id to identify it (see §39.3.2 and §39.4.1).

39.3.2. A Simple User-Defined facet

The standard library provides standard facets for the most critical areas of cultural differences, such as character sets and I/O of numbers. To examine the facet mechanism in isolation from the complexities of widely used types and the efficiency concerns that accompany them, let me first present a facet for a trivial user-defined type:

enum Season { spring, summer, fall, winter }; // very simple user-defined type

The style of I/O outlined here can be used with little variation for most simple user-defined types.

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class Season_io : public locale::facet {
public:
     Season_io(int i = 0) : locale::facet{i} { }
     ~Season_io() { }           // to make it possible to destroy Season_io objects (§39.3)

     virtual const string& to_str(Season x) const = 0;            // string representation of x
     virtual bool from_str(const string& s, Season& x) const = 0; // place Season for s in x

     static locale::id id; // facet identifier object (§39.2, §39.3, §39.3.1)
};

locale::id Season_io::id; // define the identifier object

For simplicity, this facet is limited to strings of chars.

The Season_io class provides a general and abstract interface for all Season_io facets. To define the I/O representation of a Season for a particular locale, we derive a class from Season_io, defining to_str() and from_str() appropriately.

Output of a Season is easy. If the stream has a Season_io facet, we can use that to convert the value into a string. If not, we can output the int value of the Season:

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ostream& operator<<(ostream& os, Season x)
{
     locale loc {os.getloc()};  // extract the stream's locale (§38.4.4)

     if (has_facet<Season_io>(loc))
           return os << use_facet<Season_io>(loc).to_str(x); // string representation
     return os << static_cast<int>(x);                       // integer representation
}

For maximum efficiency and flexibility, standard facets tend to operate directly on stream buffers (§39.4.2.2, §39.4.2.3). However, for a simple user-defined type, such as Season, there is no need to drop to the streambuf level of abstraction.

As is typical, input is a bit more complicated than output:

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istream& operator>>(istream& is, Season& x)
{
     const locale& loc {is.getloc()};                      // extract the stream's locale (§38.4.4)

     if (has_facet<Season_io>(loc)) {
           const Season_io& f {use_facet<Season_io>(loc)}; // get hold of the locale's Season_io facet

           string buf;
           if (!(is>>buf && f.from_str(buf,x)))            // read alphabetic representation
                  is.setstate(ios_base::failbit);
           return is;
     }

     int i;
     is >> i;                                              // read numeric representation
     x = static_cast<Season>(i);
     return is;
}

The error handling is simple and follows the error-handling style for built-in types. That is, if the input string didn’t represent a Season in the chosen locale, the stream is put into the fail state. If exceptions are enabled, this implies that an ios_base::failure exception is thrown (§38.3).

Here is a trivial test program:

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int main()
     // a trivial test
{
     Season x;
     // use the default locale (no Season_io facet) implies integer I/O:
     cin >> x;
     cout << x << endl;

     locale loc(locale(),new US_season_io{});
     cout.imbue(loc);         // use locale with Season_io facet
     cin.imbue(loc);          // use locale with Season_io facet

     cin >> x;
     cout << x << endl;
}

Given the input

2
summer

this program responds:

2
summer

To get this, we must derive a class US_season_io from Season_io, and define an appropriate string representation of the seasons:

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class US_season_io : public Season_io {
     static const string seasons[];
public:
     const string& to_str(Season) const;
     bool from_str(const string&, Season&) const;

     // note: no US_season_io::id
};

const string US_season_io::seasons[] = {
     "spring",
     "summer",
     "fall",
     "winter"
};

Then, we override the Season_io functions that convert between the string representation and the enumerators:

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const string& US_season_io::to_str(Season x) const
{
    if (x<spring || winter<x) {
          static const string ss = "no–such–season";
          return ss;
    }
    return seasons[x];
}
bool US_season_io::from_str(const string& s, Season& x) const
{
    const string* p = find(begin(seasons),end(seasons),s);
    if (p==end)
          return false;

    x = Season(p–begin(seasons));
    return true;
}

Note that because US_season_io is simply an implementation of the Season_io interface, I did not define an id for US_season_io. In fact, if we want US_season_io to be used as a Season_io, we must not give US_season_io its own id. Operations on locales, such as has_facet (§39.3.1), rely on facets implementing the same concepts being identified by the same id (§39.3).

The only interesting implementation question is what to do if asked to output an invalid Season. Naturally, that shouldn’t happen. However, it is not uncommon to find an invalid value for a simple user-defined type, so it is realistic to take that possibility into account. I could have thrown an exception, but when dealing with simple output intended for humans to read, it is often helpful to produce an “out-of-range” representation for an out-of-range value. Note that for input, the error-handling policy is left to the >> operator, whereas for output, the facet function to_str() implements an error-handling policy. This was done to illustrate the design alternatives. In a “production design,” the facet functions would either implement error handling for both input and output or just report errors for >> and << to handle.

This Season_io design relies on derived classes to supply the locale-specific strings. An alternative design would have Season_io itself retrieve those strings from a locale-specific repository (see §39.4.7). The possibility of having a single Season_io class to which the season strings are passed as constructor arguments is left as an exercise.

39.3.3. Uses of locales and facets

The primary use of locales within the standard library is in I/O streams. However, the locale mechanism is a general and extensible mechanism for representing culture-sensitive information. The messages facet (§39.4.7) is an example of a facet that has nothing to do with I/O streams. Extensions to the iostream library and even I/O facilities that are not based on streams might take advantage of locales. Also, a user may use locales as a convenient way of organizing arbitrary culture-sensitive information.

Because of the generality of the locale/facet mechanism, the possibilities for user-defined facets are unlimited. Plausible candidates for representation as facets are dates, time zones, phone numbers, social security numbers (personal identification numbers), product codes, temperatures, general (unit,value) pairs, postal codes (zip codes), clothing sizes, and ISBN numbers.

As with every other powerful mechanism, facets should be used with care. That something can be represented as a facet doesn’t mean that it is best represented that way. The key issues to consider when selecting a representation for cultural dependencies are – as ever – how the various decisions affect the difficulty of writing code, the ease of reading the resulting code, the maintainability of the resulting program, and the efficiency in time and space of the resulting I/O operations.

39.4. Standard facets

In <locale>, the standard library provides these facets:

The details are explained in the referenced subsections.

When instantiating a facet from this table, C must be a character type (§36.1). These facets are guaranteed to be defined for char or wchar_t. In addition, ctype<C> is guaranteed to support char16_t and char32_t. A user who needs standard I/O to deal with another character type X must rely on implementation-specific facet specializations or provide suitable versions of facets for X. For example, codecvt<X,char,mbstate_t> (§39.4.6) might be needed to control conversions between X and char.

International can be true or false; true means that a three-character (plus zero terminator) “international” representation of a currency symbol is used (§39.4.3.1), such as USD and BRL.

A shift-state parameter, SS, is used to represent the shift states of a multibyte character representation (§39.4.6). In <cwchar>, mbstate_t is defined to represent any of the conversion states that can occur in an implementation-defined set of supported multibyte character encoding rules. The equivalent to mbstate_t for an arbitrary character type X is char_traits<X>::state_type (§36.2.2).

In and Out are input iterators and output iterators, respectively (§33.1.2, §33.1.4). Providing the _put and _get facets with these template arguments allows a programmer to provide facets that access nonstandard buffers (§39.4.2.2). Buffers associated with iostreams are stream buffers, so the iterators provided for those are ostreambuf_iterators (§38.6.3, §39.4.2.2). Consequently, the function failed() is available for error handling (§38.6.3).

Each standard facet has a _byname version. An F_byname facet is derived from the facet F. F_byname provides the identical interface to F, except that it adds a constructor taking a string argument naming a locale (e.g., see §39.4.1). The F_byname(name) provides the appropriate semantics for F defined in locale(name). For example:

sort(v.begin(),v.end(),collate_byname{"da_DK"}); // sort using character comparison from "da_DK"

The idea is to pick a version of a standard facet from a named locale (§39.2.1) in the program’s execution environment. This implies that _byname constructors are very slow compared to constructors that do not need to consult the environment. It is almost always faster to construct a locale and then to access its facets than it is to use _byname facets in many places in a program. Thus, reading a facet from the environment once and then using the copy in main memory repeatedly is usually a good idea. For example:

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locale dk {"da_DK"};    // read the Danish locale (including all of its facets) once
                  // then use the dk locale and its facets as needed

void f(vector<string>& v, const locale& loc)
{
     const collate<char>& col {use_facet<collate<char>>(dk)};
     const ctype<char>& ctyp {use_facet<ctype<char>>(dk)};

     locale dk1 {loc,&col};        // use Danish string comparison
     locale dk2 {dk1,&ctyp}; // use Danish character classification and string comparison

     sort(v.begin(),v.end(),dk2);
     // ...
}

This dk2 locale will use Danish-style strings but will retain the default conventions for numbers.

The notion of categories gives a simpler way of manipulating standard facets in locales. For example, given the dk locale, we can construct a locale that reads and compares strings according to the rules of Danish (which has three more vowels than English) but that retains the syntax of numbers used in C++:

locale dk_us(locale::classic(),dk,collate|ctype);  // Danish letters, American numbers

The presentations of individual standard facets contain more examples of facet use. In particular, the discussion of collate (§39.4.1) brings out many of the common structural aspects of facets.

Standard facets often depend on each other. For example, num_put depends on numpunct. Only if you have a detailed knowledge of individual facets can you successfully mix and match facets or add new versions of the standard facets. In other words, beyond the simple operations (such as imbue() for iostreams and using collate for sort()), the locale mechanisms are not meant to be directly used by novices. For an extensive discussion of locales, see [Langer,2000].

The design of an individual facet is often messy. The reason is partially that facets have to reflect messy cultural conventions outside the control of the library designer, and partially that the C++ standard library-facilities have to remain largely compatible with what is offered by the C standard library and various platform-specific standards.

On the other hand, the framework provided by locales and facets is general and flexible. A facet can be designed to hold any data, and the facet’s operations can provide any desired operation based on that data. If the behavior of a new facet isn’t overconstrained by convention, its design can be simple and clean (§39.3.2).

39.4.1. string Comparison

The standard collate facet provides ways of comparing arrays of characters:

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template<class C>
class collate : public locale::facet {
public:
     using char_type = C;
     using string_type = basic_string<C>;

     explicit collate(size_t = 0);

     int compare(const C* b, const C* e, const C* b2, const C* e2) const
          {return do_compare(b,e,b2,e2); }

     long hash(const C* b, const C* e) const
          {return do_hash(b,e); }
     string_type transform(const C* b, const C* e) const
          {return do_transform(b,e); }

     static locale::id id; // facet identifier object (§39.2, §39.3, §39.3.1)

protected:
     ~collate(); // note: protected destructor

     virtual int do_compare(const C* b, const C* e, const C* b2, const C* e2) const;
     virtual string_type do_transform(const C* b, const C* e) const;
     virtual long do_hash(const C* b, const C* e) const;
};

This defines two interfaces:

• The public interface for users of the facet.

• The protected interface for implementers of derived facets.

The constructor argument specifies whether a locale or a user is responsible for deleting the facet. The default (0) means “let the locale manage” (§39.3).

All standard-library facets share a common structure, so the salient facts about a facet can be summarized by the key functions:

To define a facet use collate as the pattern. To derive from a standard pattern, simply define the do_* versions of the key functions providing the facet’s functionality. The full declarations of functions are listed (rather than use patterns) to give sufficient information to write an overriding do_* function. For an example, see §39.4.1.1.

The hash() function calculates a hash value for its imput string. Obviously, this can be useful for building hash tables.

The transform() function produces a string that, when compared to another transform()ed string, gives the same result as comparing the strings. That is:

cf.compare(cf.transform(s),cf.transform(s2)) == cf.compare(s,s2)

The purpose of transform() is to allow optimization of code in which a string is compared to many others. This is useful when implementing a search among a set of strings.

The compare() function does the basic string comparison according to the rules defined for a particular collate. It returns:

1 if the first string is lexicographically greater than the second

0 if the strings are identical

–1 if the second string is greater than the first

For example:

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void f(const string& s1, const string& s2, const collate<char>& cmp)
{
     const char* cs1 {s1.data()};   // because compare() operates on char[]s
     const char* cs2 {s2.data()};

     switch (cmp.compare(cs1,cs1+s1.size(),cs2,cs2+s2.size()) {
     case 0:      // identical strings according to cmp
         // ...
         break;
     case –1:     // s1 < s2
         // ...
         break;
     case 1:      // s1 > s2
         // ...
         break;
     }
}

The collate member functions compare [b:e) ranges of C rather than basic_strings or zero-terminated C-style strings. In particular, a C with the numeric value 0 is treated as an ordinary character rather than as a terminator.

The standard-library string is not locale sensitive. That is, it compares strings according to the rules of the implementation’s character set (§6.2.3). Furthermore, the standard string does not provide a direct way of specifying comparison criteria (Chapter 36). To do a locale-sensitive comparison, we can use a collate’s compare(). For example:

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void f(const string& s1, const string& s2, const string& name)
{
     bool b {s1==s2};               // compare using implementation's character set values

     const char* s1b {s1.data()};              // get start of data
     const char* s1e {s1.data()+s1.size()}     // get end of data
     const char* s2b {s2.data()};
     const char* s2e {s2.data()+s2.size()}

     using Col = collate<char>;

     const Col& global {use_facet<Col>(locale{})};          // from the current global locale
     int i0 {global.compare(s1b,s1e,s2b,s2e)};

     const Col& my_coll {use_facet<Col>(locale{""})};       // from my preferred locale
     int i1 {my_coll.compare(s1b,s1e,s2b,s2e)};

     const Col& n_coll {use_facet<Col>(locale{name})};      // from a named locale
     int i2 {n_coll.compare(s1b,s1e,s2b,s2e)};
}

Notationally, it can be more convenient to use collate’s compare() indirectly through a locale’s operator() (§39.2.2). For example:

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void f(const string& s1, const string& s2, const string& name)
{
     int i0 = locale{}(s1,s2);      // compare using the current global locale
     int i1 = locale{""}(s1,s2);    // compare using my preferred locale
     int i2 = locale{name}(s1,s2);  // compare using the named locale
     // ...
}

It is not difficult to imagine cases in which i0, i1, and i2 differ. Consider this sequence of words from a German dictionary:

Dialekt, Diät, dich, dichten, Dichtung

According to convention, nouns (only) are capitalized, but the ordering is not case sensitive.

A case-sensitive German sort would place all words starting with D before d:

Dialekt, Diät, Dichtung, dich, dichten

The ä (umlaut a) is treated as “a kind of a,” so it comes before c. However, in most common character sets, the numeric value of ä is larger than the numeric value of c. Consequently, int('c')<int('ä'), and the simple default sort based on numeric values gives:

Dialekt, Dichtung, Diät, dich, dichten

Writing a compare function that orders this sequence correctly according to the dictionary is an interesting exercise.

39.4.1.1. Named collate

A collate_byname is a version of collate for a locale named by a constructor string argument:

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template<class C>
class collate_byname : public collate<C> {   // note: no id and no new functions
public:
     typedef basic_string<C> string_type;

     explicit collate_byname(const char*, size_t r = 0); // construct from named locale
     explicit collate_byname(const string&, size_t r = 0);
protected:
     ~collate_byname(); // note: protected destructor

     int do_compare(const C* b, const C* e, const C* b2, const C* e2) const override;
     string_type do_transform(const C* b, const C* e) const override;
     long do_hash(const C* b, const C* e) const override;
};

Thus, a collate_byname can be used to pick out a collate from a locale named in the program’s execution environment (§39.4). One obvious way of storing facets in an execution environment would be as data in a file. A less flexible alternative would be to represent a facet as program text and data in a _byname facet.

39.4.2. Numeric Formatting

Numeric output is done by a num_put facet writing into a stream buffer (§38.6). Conversely, numeric input is done by a num_get facet reading from a stream buffer. The format used by num_put and num_get is defined by a “numerical punctuation” facet called numpunct.

39.4.2.1. Numeric Punctuation

The numpunct facet defines the I/O format of built-in types, such as bool, int, and double:

The characters of the string returned by grouping() are read as a sequence of small integer values. Each number specifies a number of digits for a group. Character 0 specifies the rightmost group (the least significant digits), character 1 the group to the left of that, etc. Thus, "\004\002\003" describes a number such as 123–45–6789 (provided you use '–' as the separation character). If necessary, the last number in a grouping pattern is used repeatedly, so "\003" is equivalent to "\003\003\003". The most common use of grouping is to make large numbers more readable. The grouping() and thousands_sep() functions define a format for both input and output of integers and the integer part of floating-point values.

We can define a new punctuation style by deriving from numpunct. For example, I could define facet My_punct to write integer values using spaces to group the digits in sets of three and floating-point values, using a European-style comma as the “decimal point”:

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class My_punct : public numpunct<char> {
public:
     explicit My_punct(size_t r = 0) :numpunct<char>(r) { }
protected:
     char do_decimal_point() const override { return ','; }    // comma
     char do_thousands_sep() const override { return '_'; }    // underscore
     string do_grouping() const override { return "\003"; }    // 3-digit groups
};

void f()
{
     cout << "style A: " << 12345678
          << " *** " << 1234567.8
          << " *** " << fixed << 1234567.8 << '\n';
     cout << defaultfloat;              // reset floating format
     locale loc(locale(),new My_punct);
     cout.imbue(loc);
     cout << "style B: " << 12345678
          << " *** " << 1234567.8
          << " *** " << fixed << 1234567.8 << '\n';
}

This produces:

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style A: 12345678 *** 1.23457e+06 *** 1234567.800000
style B: 12_345_678 *** 1_234_567,800000 *** 1_234_567,800000

Note that imbue() stores a copy of its argument in its stream. Consequently, a stream can rely on an imbued locale even after the original copy of that locale has been destroyed. If an iostream has its boolalpha flag set (§38.4.5.1), the strings returned by truename() and falsename() are used to represent true and false, respectively; otherwise, 1 and 0 are used.

A _byname version (§39.4, §39.4.1) of numpunct is provided:

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template<class C>
class numpunct_byname : public numpunct<C> {
     // ...
};

39.4.2.2. Numeric Output

When writing to a stream buffer (§38.6), an ostream relies on the num_put facet:

The value of put() is that iterator positioned one past the last character position written.

The default specialization of num_put (the one where the iterator used to access characters is of type ostreambuf_iterator<C>) is part of the standard locales (§39.4). To write elsewhere using a num_put, we must define an appropriate specialization. For example, here is a very simple num_put for writing into a string:

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template<class C>
class String_numput : public num_put<C,typename basic_string<C>::iterator> {
public:
     String_numput() :num_put<C,typename basic_string<C>::iterator>{1} { }
};

I don’t mean for String_numput to go into a locale, so I used the constructor argument to retain ordinary lifetime rules. The intended use is something like this:

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void f(int i, string& s, int pos) // format i into s starting at pos
{
     String_numput<char> f;
     f.put(s.begin()+pos,cout,' ',i);   // format i into s; use cout's formatting rules
}

The ios_base argument (here, cout) provides information about formatting state and locale. For example:

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void test(iostream& io)
{
     locale loc = io.getloc();

     wchar_t wc = use_facet<ctype<char>>(loc).widen(c);               // char to C conversion
     string s = use_facet<numpunct<char>>(loc).decimal_point();       // default: '.'
     string false_name = use_facet<numpunct<char>>(loc).falsename();  // default: "false"
}

A standard facet, such as num_put<char>, is typically used implicitly through a standard I/O stream function. Consequently, most programmers need not know about it. However, the use of such facets by standard-library functions is interesting because they show how I/O streams work and how facets can be used. As ever, the standard library provides examples of interesting programming techniques.

Using num_put, the implementer of ostream might write:

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template<class C, class Tr>
basic_ostream<C,Tr>& basic_ostream<C,Tr>::operator<<(double d)
{
     sentry guard(*this);  // see §38.4.1
     if (!guard) return *this;

     try {
           if (use_facet<num_put<C,Tr>>(g etloc()).put(*this,*this,this–>fill(),d).failed())
                 setstate(badbit);
     }
     catch (...) {
           handle_ioexception(*this);
     }
     return *this;
}

A lot is going on here. The sentry ensures that all prefix and suffix operations are performed (§38.4.1). We get the ostream’s locale by calling its member function getloc() (§38.4.5.1). We extract num_put from that locale using use_facet (§39.3.1). That done, we call the appropriate put() function to do the real work. An ostreambuf_iterator can be constructed from an ostream (§38.6.3), and an ostream can be implicitly converted to its base class ios_base (§38.4.4), so the first two arguments to put() are easily supplied.

A call of put() returns its output iterator argument. This output iterator is obtained from a basic_ostream, so it is an ostreambuf_iterator. Consequently, failed() (§38.6.3) is available to test for failure and to allow us to set the stream state appropriately.

I did not use has_facet, because the standard facets (§39.4) are guaranteed to be present in every locale. If that guarantee is violated, bad_cast is thrown (§39.3.1).

The put() function calls the virtual do_put(). Consequently, user-defined code may be executed, and operator<<() must be prepared to handle an exception thrown by the overriding do_put(). Also, num_put may not exist for some character types, so use_facet() might throw bad_cast (§39.3.1). The behavior of a << for a built-in type, such as double, is defined by the C++ standard. Consequently, the question is not what handle_ioexception() should do but rather how it should do what the standard prescribes. If badbit is set in this ostream’s exception state (§38.3), the exception is simply re-thrown. Otherwise, an exception is handled by setting the stream state and continuing. In either case, badbit must be set in the stream state (§38.4.5.1):

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template<class C, class Tr>
void handle_ioexception(basic_ostream<C,Tr>& s)// called from catch-clause
{
     if (s.exceptions()&ios_base::badbit) {
           try {
                s.setstate(ios_base::badbit); // might throw basic_ios::failure
           }
           catch(...) {
               // ... do nothing ...
           }
           throw;     // re-throw
     }
     s.setstate(ios_base::badbit);
}

The try-block is needed because setstate() might throw basic_ios::failure (§38.3, §38.4.5.1). However, if badbit is set in the exception state, operator<<() must re-throw the exception that caused handle_ioexception() to be called (rather than simply throwing basic_ios::failure).

The << for a built-in type, such as double, must be implemented by writing directly to a stream buffer. When writing a << for a user-defined type, we can often avoid the resulting complexity by expressing the output of the user-defined type in terms of output of existing types (§39.3.2).

39.4.2.3. Numeric Input

When reading from a stream buffer (§38.6), an istream relies on the num_get facet:

Basically, num_get is organized like num_put (§39.4.2.2). Since it reads rather than writes, get() needs a pair of input iterators, and the argument designating the target of the read is a reference.

The iostate variable r is set to reflect the state of the stream. If a value of the desired type could not be read, failbit is set in r; if the end-of-input was reached, eofbit is set in r. An input operator will use r to determine how to set the state of its stream. If no error was encountered, the value read is assigned through v; otherwise, v is left unchanged.

A sentry is used to ensure that the stream’s prefix and suffix operations are performed (§38.4.1). In particular, the sentry is used to ensure that we try to read only if the stream is in a good state to start with. For example, an implementer of istream might write:

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template<class C, class Tr>
basic_istream<C,Tr>& basic_istream<C,Tr>::operator>>(double& d)
{
     sentry guard(*this);    // see §38.4.1
     if (!guard) return *this;

     iostate state = 0;      // good
     istreambuf_iterator<C,Tr> eos;
     try {
          double dd;
          use_facet<num_get<C,Tr>>(g etloc()).g et(*this,eos,*this,state,dd);
          if (state==0 || state==eofbit) d = dd;   // set value only if get() succeeded
          setstate(state);
     }
     catch (...) {
          handle_ioexception(*this);       // see §39.4.2.2
     }
     return *this;
}

I took care not to modify the target of the >> unless the read operation succeeded. Unfortunately, that cannot be guaranteed for all input operations.

Exceptions enabled for the istream will be thrown by setstate() in case of error (§38.3).

By defining a numpunct, such as My_punct from §39.4.2.1, we can read using nonstandard punctuation. For example:

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void f()
{
     cout << "style A: "
     int i1;
     double d1;
     cin >> i1 >> d1;           // read using standard "12345678" format

     locale loc(locale::classic(),new My_punct);
     cin.imbue(loc);
     cout << "style B: "
     int i2;
     double d2;
     cin >> i1 >> d2;          // read using the "12_345_678" format
}

If we want to read really unusual numeric formats, we have to override do_get(). For example, we might define a num_get that reads Roman numerals, such as XXI and MM.

39.4.3. Money Formatting

The formatting of monetary amounts is technically similar to the formatting of “plain” numbers (§39.4.2). However, the presentation of monetary amounts is even more sensitive to cultural differences. For example, a negative amount (a loss, a debit), such as –1.25, should in some contexts be presented as a (positive) number in parentheses: (1.25). Similarly, color is in some contexts used to ease the recognition of negative amounts.

There is no standard “money type.” Instead, the money facets are meant to be used explicitly for numeric values that the programmer knows to represent monetary amounts. For example:

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struct Money {                      // simple type to hold a monetary amount
     using Value = long long;       // for currencies that have suffered inflation
     Value amount;
};

// ...

void f(long int i)
{
     cout << "value= " << i << " amount= " << Money{i} << '\n';
}

The task of the monetary facets is to make it reasonably easy to write an output operator for Money so that the amount is printed according to local convention (see §39.4.3.2). The output would vary depending on cout’s locale. Possible outputs are:

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value= 1234567 amount= $12345.67
value= 1234567 amount= 12345,67 DKK
value= 1234567 amount= CAD 12345,67
value= –1234567 amount= $–12345.67
value= –1234567 amount= –€12345.67
value= –1234567 amount= (CHF12345,67)

For money, accuracy to the smallest currency unit is usually considered essential. Consequently, I adopted the common convention of having the integer value represent the number of cents (pence, øre, fils, cents, etc.) rather than the number of dollars (pounds, kroner, dinar, euro, etc.). This convention is supported by moneypunct’s frac_digits() function (§39.4.3.1). Similarly, the appearance of the “decimal point” is defined by decimal_point().

The facets money_get and money_put provide functions that perform I/O based on the format defined by the money_base facet.

A simple Money type can be used to control I/O formats or to hold monetary values. In the former case, we cast values of (other) types used to hold monetary amounts to Money before writing, and we read into Money variables before converting them to other types. It is less error-prone to consistently hold monetary amounts in a Money type; that way, we cannot forget to cast a value to Money before writing it, and we don’t get input errors by trying to read monetary values in locale- insensitive ways. However, it may be infeasible to introduce a Money type into a system that wasn’t designed for that. In such cases, applying Money conversions (casts) to read and write operations is necessary.

39.4.3.1. Money Punctuation

The facet controlling the presentation of monetary amounts, moneypunct, naturally resembles the facet for controlling plain numbers, numpunct (§39.4.2.1):

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class money_base {
public:
     enum part {                             // parts of value layout
         none, space, symbol, sign, value
     };

     struct pattern {                        // layout specification
         char field[4];
     };
};

template<class C, bool International = false>
class moneypunct : public locale::facet, public money_base {
public:
     using char_type = C;
     using string_type = basic_string<C>;
     // ...
};

The moneypunct member functions define the layout of money input and output:

The facilities offered by moneypunct are intended primarily for use by implementers of money_put and money_get facets (§39.4.3.2, §39.4.3.3).

A _byname version (§39.4, §39.4.1) of moneypunct is provided:

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template<class C, bool Intl = false>
class moneypunct_byname : public moneypunct<C, Intl> {
     // ...
};

The decimal_point(), thousands_sep(), and grouping() members behave as in numpunct.

The curr_symbol(), positive_sign(), and negative_sign() members return the string to be used to represent the currency symbol (for example, $, ¥, INR, DKK), the plus sign, and the minus sign, respectively. If the International template argument is true, the intl member will also be true, and “international” representations of the currency symbols will be used. Such an “international” representation is a four-character C-style string. For example:

"USD"
"DKK"
"EUR"

The last (invisible) character is a terminating zero. The three-letter currency identifier is defined by the ISO-4217 standard. When International is false, a “local” currency symbol, such as $, £, and ¥, can be used.

A pattern returned by pos_format() or neg_format() is four parts defining the sequence in which the numeric value, the currency symbol, the sign symbol, and whitespace occur. Most common formats are trivially represented using this simple notion of a pattern. For example:

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+$ 123.45     // { sign, symbol, space, value } where positive_sign() returns "+"
$+123.45      // { symbol, sign, value, none } where positive_sign() returns "+"
$123.45       // { symbol, sign, value, none } where positive_sign() returns ""
$123.45–      // { symbol, value, sign, none }
–123.45 DKK   // { sign, value, space, symbol }
($123.45)     // { sign, symbol, value, none } where negative_sign() returns "()"
(123.45DKK)   // { sign, value, symbol, none } where negative_sign() returns "()"

Representing a negative number using parentheses is achieved by having negative_sign() return a string containing the two characters (). The first character of a sign string is placed where sign is found in the pattern, and the rest of the sign string is placed after all other parts of the pattern. The most common use of this facility is to represent the financial community’s convention of using parentheses for negative amounts, but other uses are possible. For example:

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–$123.45             // { sign, symbol, value, none } where negative_sign() returns "–"
* $123.45 silly      // { sign, symbol, value, none } where negative_sign() returns "* silly"

Each of the values sign, value, and symbol must appear exactly once in a pattern. The remaining value can be either space or none. Where space appears, at least one and possibly more whitespace characters may appear in the representation. Where none appears, except at the end of a pattern, zero or more whitespace characters may appear in the representation.

Note that these strict rules ban some apparently reasonable patterns:

pattern pat = { sign, value, none, none };     // error: no symbol

The frac_digits() function indicates where the decimal_point() is placed. Often, monetary amounts are represented in the smallest currency unit (§39.4.3). This unit is typically one-hundredth of the major unit (for example, a ¢ is one-hundredth of a $), so frac_digits() is often 2.

Here is a simple format defined as a facet:

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class My_money_io : public moneypunct<char,true> {
public:
     explicit My_money_io(size_tr=0): moneypunct<char,true>(r) { }

     char_type do_decimal_point() const { return '.'; }
     char_type do_thousands_sep() const { return ','; }
     string do_grouping() const { return "\003\003\003"; }

     string_type do_curr_symbol() const { return "USD "; }
     string_type do_positive_sign() const { return ""; }
     string_type do_negative_sign() const { return "()"; }

     int do_frac_digits() const { return 2; } // two digits after decimal point

     pattern do_pos_format() const { return pat; }
     pattern do_neg_format() const { return pat; }
private:
     static const pattern pat;
};

const pattern My_money_io::pat { sign, symbol, value, none };

39.4.3.2. Money Output

The money_put facet writes monetary amounts according to the format specified by moneypunct. Specifically, money_put provides put() functions that place a suitably formatted character representation into the stream buffer of a stream:

The intl argument indicates whether a standard four-character “international” currency symbol or a “local” symbol is used (§39.4.3.1).

Given money_put, we can define an output operator for Money (§39.4.3):

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ostream& operator<<(ostream& s, Money m)
{
     ostream::sentry guard(s);        // see §38.4.1
     if (!guard) return s;

     try {
           const money_put<char>& f = use_facet<money_put<char>>(s.g etloc());
           if (m==static_cast<long long>(m)) { // m can be represented as a long long
                if (f.put(s,true,s,s.fill(),m).failed())
                       s.setstate(ios_base::badbit);
           }
           else {
                ostringstream v;
                v << m;             // convert to string representation
                if (f.put(s,true,s,s.fill(),v.str()).failed())
                       s.setstate(ios_base::badbit);
          }
     }
     catch (...) {
           handle_ioexception(s);     // see §39.4.2.2
     }
     return s;
}

If a long long doesn’t have sufficient precision to represent the monetary value exactly, I convert the value to its string representation and output that using the put() that takes a string.

39.4.3.3. Money Input

The money_get facet reads monetary amounts according to the format specified by moneypunct. Specifically, money_get provides get() functions that extract a suitably formatted character representation from the stream buffer of a stream:

A well-defined pair of money_get and money_put facets will provide output in a form that can be read back in without errors or loss of information. For example:

int main()
{
     Money m;
     while (cin>>m)
         cout << m << "\n";
}

The output of this simple program should be acceptable as its input. Furthermore, the output produced by a second run given the output from a first run should be identical to its input.

A plausible input operator for Money would be:

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istream& operator>>(istream& s, Money& m)
{
     istream::sentry guard(s);  // see _io.sentry_
     if (guard) try {
          ios_base::iostate state = 0; // good
          istreambuf_iterator<char> eos;
          string str;

          use_facet<money_get<char>>(s.g etloc()).g et(s,eos,true,state,str);

          if (state==0 || state==ios_base::eofbit) { // set value only if get() succeeded
                long long i = stoll(str);     // §36.3.5
                if (errno==ERANGE) {
                       state |= ios_base::failbit;
                }
                else {
                     m = i;        // set value only if conversion to long long succeeded
                }
                s.setstate(state);
          }
     }
     catch (...) {
            handle_ioexception(s);     // see §39.4.2.2
     }
     return s;
}

I use the get() that reads into a string because reading into a double and then converting to a long long could lead to loss of precision.

The largest value that can be exactly represented by a long double may be smaller than the largest value that can be represented by a long long.

39.4.4. Date and Time Formatting

Date and time formats are controlled by time_get<C,In> and time_put<C,Out>. The representation of dates and times used is tm (§43.6).

39.4.4.1. time_put

A time_put facet takes a point in time presented as a tm and produces a sequence of characters representing it using strftime() (§43.6) or an equivalent.

A call s=put(s,ib,fill,pt,b,e) copies [b:e) onto the output stream s. For each strftime() format character x, with optional modifier mod, it calls do_put(s,ib,pt,x,mod). The possible modifier values are 0 (the default meaning “none”), E, or O. An overriding p=do_put(s,ib,pt,x,mod) is supposed to format the appropriate parts of *pt into s and return a value pointing to the position in s after the last character written.

A _byname version (§39.4, §39.4.1) of messages is provided:

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template<class C, class Out = ostreambuf_iterator<C>>
class time_put_byname : public time_put<C,Out>
{
     // ...
};

39.4.4.2. time_get

The basic idea is that a get_time can read what is produced by a put_time using the same strftime() format (§43.6):

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class time_base {
public:
     enum dateorder {
         no_order, // meaning mdy
         dmy,      // meaning "%d%m%y"
         mdy,      // meaning "%m%d%y"
         ymd,      // meaning "%y%m%d"
         ydm       // meaning "%y%d%m"
     };
};

template<class C, class In = istreambuf_iterator<C>>
class time_get : public locale::facet, public time_base {
public:
     using char_type = C;
     using iter_type = In;
     // ...
}

In addition to reading according to a format, there are operations for examining the dateorder and for reading specific parts of date and time representations, such as weekday and monthname:

A get_*() function reads from [b:e) into *pt, getting its locale from b and setting err in case of error. It returns an iterator pointing to the first unread character in [b:e).

A call p=get(b,e,ib,err,pt,format,mod) reads as indicated by the format character format and modifier character mod, as specified by strftime(). If mod is not specified, mod==0 is used.

A call of get(b,e,ib,err,pt,fmtb,fmtb) uses a strftime() format presented as a string [fmtb:fmte). This overload, together with the one with the defaulted modifier, does not have do_get() interfaces. Instead, they are implemented by calls to the do_get() for the first get().

The obvious use of the time and date facets is to provide locale-sensitive I/O for a Date class. Consider a variant of the Date from §16.3:

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class Date {
public:
     explicit Date(int d ={}, Month m ={}, int year ={});
     // ...
     string to_string(const locale& = locale()) const;
};

istream& operator>>(istream& is, Date& d);
ostream& operator<<(ostream& os, Date d);

Date::to_string() produces a locale()-specific string using a stringstream (§38.2.2):

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string Date::to_string(const locale& loc) const
{
     ostringstream os;
     os.imbue(loc);
     return os << *this;
}

Given to_string(), the output operator is trivial:

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ostream& operator<<(ostream& os, Date d)
{
     return os<<to_string(d,os.getloc());
}

The input operator needs to be careful about state:

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istream& operator>>(istream& is, Date& d)
{
     if (istream::sentry guard{is}) {
            ios_base::iostate err = goodbit;
            struct tm t;
            use_facet<time_get<char>>(is.getloc()).get_date(is,0,is,err,&t);  // read into t
            if (!err) {
                   Month m = static_cast<Month>(t.tm_mon+1);
                   d = Date(t.tm_day,m,t.tm_year+1900);
            }
            is.setstate(err);
     }
     return is;
}

The +1900 is needed because year 1900 is year zero for tm (§43.6).

A _byname version (§39.4, §39.4.1) of messages is provided:

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template<class C, class In = istreambuf_iterator<C>>
class time_get_byname : public time_get<C, In> {
     // ...
};

39.4.5. Character Classification

When reading characters from input, it is often necessary to classify them to make sense of what is being read. For example, to read a number, an input routine needs to know which letters are digits. Similarly, §10.2.2 showed a use of standard character classification functions for parsing input.

Naturally, classification of characters depends on the alphabet used. Consequently, a facet ctype is provided to represent character classification in a locale.

The character classes are described by an enumeration called mask:

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class ctype_base {
public:
     enum mask {       // the actual values are implementation-defined
         space = 1,          // whitespace (in "C" locale: ' ', '\n', '\t', ...)
         print = 1<<1,       // printing characters
         cntrl = 1<<2,       // control characters
         upper = 1<<3,       // uppercase characters
         lower = 1<<4,       // lowercase characters
         alpha = 1<<5,       // alphabetic characters
         digit = 1<<6,       // decimal digits
         punct = 1<<7,       // punctuation characters
         xdigit = 1<<8,      // hexadecimal digits
         blank = 1 << 9;     // space and horizontal tab
         alnum=alpha|digit,  // alphanumeric characters
         graph=alnum|punct
     };
};

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template<class C>
class ctype : public locale::facet, public ctype_base {
public:
     using char_type = C;
     // ...
};

This mask doesn’t depend on a particular character type. Consequently, this enumeration is placed in a (non-template) base class.

Clearly, mask reflects the traditional C and C++ classification (§36.2.1). However, for different character sets, different character values fall into different classes. For example, for the ASCII character set, the integer value 125 represents the character }, which is a punctuation character (punct). However, in the Danish national character set, 125 represents the vowel å, which in a Danish locale must be classified as an alpha.

The classification is called a “mask” because the traditional efficient implementation of character classification for small character sets is a table in which each entry holds bits representing the classification. For example:

table['P'] == upper|alpha
table['a'] == lower|alpha|xdigit
table['1'] == digit|xdigit
table[' '] == space|blank

Given that implementation, table[c]&m is nonzero if the character c is an m and 0 otherwise.

The ctype facet is defined like this:

A call is(m,c) tests whether the character c belongs to the classification m. For example:

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int count_spaces(const string& s, const locale& loc)
{
     const ctype<char>& ct = use_facet<ctype<char>>(loc);
     int i = 0;

     for(auto p = s.begin(); p!=s.end(); ++p)
          if (ct.is(ctype_base::space,*p))         // whitespace as defined by ct
                 ++i;
     return i;
}

Note that it is also possible to use is() to check whether a character belongs to one of a number of classifications. For example:

ct.is(ctype_base::space|ctype_base::punct,c);     // is c whitespace or punctuation in ct?

A call is(b,e,v) determines the classification of each character in [b:e) and places it in the corresponding position in the array v.

A call scan_is(m,b,e) returns a pointer to the first character in [b:e) that is an m. If no character is classified as an m, e is returned. As ever for standard facets, the public member function is implemented by a call to its do_ virtual function. A simple implementation might be:

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template<class C>
const C* ctype<C>::do_scan_is(mask m, const C* b, const C* e) const
{
    while (b!=e && !is(m,*b))
         ++b;
    return b;
}

A call scan_not(m,b,e) returns a pointer to the first character in [b:e) that is not an m. If all characters are classified as m, e is returned.

A call toupper(c) returns the uppercase version of c if such a version exists in the character set used and c itself otherwise.

A call toupper(b,e) converts each character in the range [b:e) to uppercase and returns e. A simple implementation might be:

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template<class C>
const C* ctype<C>::to_upper(C* b, const C* e)
{
    for (; b!=e; ++b)
           *b = toupper(*b);
    return e;
}

The tolower() functions are similar to toupper() except that they convert to lowercase.

A call widen(c) transforms the character c into its corresponding C value. If C’s character set provides several characters corresponding to c, the standard specifies that “the simplest reasonable transformation” be used. For example:

wcout << use_facet<ctype<wchar_t>>(wcout.g etloc()).widen('e');

will output a reasonable equivalent to the character e in wcout’s locale.

Translation between unrelated character representations, such as ASCII and EBCDIC, can also be done by using widen(). For example, assume that an ebcdic locale exists:

char EBCDIC_e = use_facet<ctype<char>>(ebcdic).widen('e');

A call widen(b,e,v) takes each character in the range [b:e) and places a widened version in the corresponding position in the array v.

A call narrow(ch,def) produces a char value corresponding to the character ch from the C type. Again, “the simplest reasonable transformation” is to be used. If no such corresponding char exists, def is returned.

A call narrow(b,e,def,v) takes each character in the range [b:e) and places a narrowed version in the corresponding position in the array v.

The general idea is that narrow() converts from a larger character set to a smaller one and that widen() performs the inverse operation. For a character c from the smaller character set, we expect:

c == narrow(widen(c),0) // not guaranteed

This is true provided that the character represented by c has only one representation in “the smaller character set.” However, that is not guaranteed. If the characters represented by a char are not a subset of those represented by the larger character set (C), we should expect anomalies and potential problems with code treating characters generically.

Similarly, for a character ch from the larger character set, we might expect:

widen(narrow(ch,def)) == ch || widen(narrow(ch,def)) == widen(def) // not guaranteed

However, even though this is often the case, it cannot be guaranteed for a character that is represented by several values in the larger character set but only once in the smaller character set. For example, a digit, such as 7, often has several separate representations in a large character set. The reason for that is typically that a large character set has several conventional character sets as subsets and that the characters from the smaller sets are replicated for ease of conversion.

For every character in the basic source character set (§6.1.2), it is guaranteed that

widen(narrow(ch_lit,0)) == ch_lit

For example:

widen(narrow('x',0)) == 'x'

The narrow() and widen() functions respect character classifications wherever possible. For example, if is(alpha,c), then is(alpha,narrow(c,'a')) and is(alpha,widen(c)) wherever alpha is a valid mask for the locale used.

A major reason for using a ctype facet in general and for using narrow() and widen() functions in particular is to be able to write code that does I/O and string manipulation for any character set, that is, to make such code generic with respect to character sets. This implies that iostream implementations depend critically on these facilities. By relying on <iostream> and <string>, a user can avoid most direct uses of the ctype facet.

A _byname version (§39.4, §39.4.1) of ctype is provided:

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template<class C>
class ctype_byname : public ctype<C> {
     // ...
};

39.4.6. Character Code Conversion

Sometimes, the representation of characters stored in a file differs from the desired representation of those same characters in main memory. For example, Japanese characters are often stored in files in which indicators (“shifts”) indicate to which of the four common character sets (kanji, katakana, hiragana, and romaji) a given sequence of characters belongs. This is a bit unwieldy because the meaning of each byte depends on its “shift state,” but it can save memory because only a kanji requires more than 1 byte for its representation. In main memory, these characters are easier to manipulate when represented in a multibyte character set where every character has the same size. Such characters (for example, Unicode characters) are typically placed in wide characters (wchar_t; §6.2.3). Consequently, the codecvt facet provides a mechanism for converting characters from one representation to another as they are read or written. For example:

This code conversion mechanism is general enough to provide arbitrary conversions of character representations. It allows us to write a program to use a suitable internal character representation (stored in char, wchar_t, or whatever) and to then accept a variety of input character stream representations by adjusting the locale used by iostreams. The alternative would be to modify the program itself or to convert input and output files from/to a variety of formats.

The codecvt facet provides conversion between different character sets when a character is moved between a stream buffer and external storage:

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class codecvt_base {
public:
     enum result {        // result indicators
         ok, partial, error, noconv
     };
};

template<class In, class Ex, class SS>
class codecvt : public locale::facet, public codecvt_base {
public:
     using intern_type = In;
     using extern_type = Ex;
     using state_type = SS;
     // ...
};

A codecvt facet is used by basic_filebuf (§38.2.1) to read or write characters. A basic_filebuf obtains this facet from the stream’s locale (§38.1).

The State template argument is the type used to hold the shift state of the stream being converted.State can also be used to identify different conversions by specifying a specialization. The latter is useful because characters of a variety of character encodings (character sets) can be stored in objects of the same type. For example:

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class JISstate { /* .. */ };

p = new codecvt<wchar_t,char,mbstate_t>;       // standard char to wide char
q = new codecvt<wchar_t,char,JISstate>;        // JIS to wide char

Without the different State arguments, there would be no way for the facet to know which encoding to assume for the stream of chars. The mbstate_t type from <cwchar> or <wchar.h> identifies the system’s standard conversion between char and wchar_t.

A new codecvt can also be created as a derived class and identified by name. For example:

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class JIScvt : public codecvt<wchar_t,char,mbstate_t> {
    // ...
};

A call in(st,b,e,next,b2,e2,next2) reads each character in the range [b:e) and tries to convert it. If a character is converted, in() writes its converted form to the corresponding position in the [b2:e2) range; if not, in() stops at that point. Upon return, in() stores the position one beyond the last character read in next (the next character to be read) and the position one beyond the last character written in next2 (the next character to be written). The result value returned by in() indicates how much work was done:

Note that a partial conversion is not necessarily an error. Possibly more characters have to be read before a multibyte character is complete and can be written, or maybe the output buffer has to be emptied to make room for more characters.

The state_type argument st indicates the state of the input character sequence at the start of the call of in(). This is significant when the external character representation uses shift states. Note that st is a (non-const) reference argument: at the end of the call, st holds the shift state of the input sequence. This allows a programmer to deal with partial conversions and to convert a long sequence using several calls to in().

A call out(st,b,e,next,b2,e2,next2) converts [b:e) from the internal to the external representation in the same way the in() converts from the external to the internal representation.

A character stream must start and end in a “neutral” (unshifted) state. Typically, that state is state_type{}.

A call unshift(ss,b,e,next) looks at st and places characters in [b:e) as needed to bring a sequence of characters back to that unshifted state. The result of unshift() and the use of next are done just like out().

A call length(st,b,e,max) returns the number of characters that in() could convert from [b:e). Return values from encoding() mean:

–1 The encoding of the external character set uses state (for example, uses shift and unshift character sequences).

0   The encoding uses varying number of bytes to represent individual characters (for example, a character representation might use a bit in a byte to indicate whether 1 or 2 bytes are used to represent that character).

n   Every character of the external character representation is n bytes.

A call always_noconv() returns true if no conversion is required between the internal and the external character sets and false otherwise. Clearly, always_noconv()==true opens the possibility for the implementation to provide the maximally efficient implementation that simply doesn’t invoke the conversion functions.

A call cvt.max_length() returns the maximum value that cvt.length(ss,p,q,n) can return for a valid set of arguments.

The simplest code conversion that I can think of is one that converts input to uppercase. Thus, this is about as simple as a codecvt can be and still perform a service:

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class Cvt_to_upper : public codecvt<char,char,mbstate_t> { // convert to uppercase
public:
     explicit Cvt_to_upper(size_t r = 0) : codecvt(r) { }

protected:
     // read external representation, write internal representation:
     result do_in(State& s,
                    const char* from, const char* from_end, const char*& from_next,
                    char* to, char* to_end, char*& to_next
                ) const override;

     // read internal representation, write external representation:
     result do_out(State& s,
                    const char* from, const char* from_end, const char*& from_next,
                    char* to, char* to_end, char*& to_next
                ) const override;
     result do_unshift(State&, E* to, E* to_end, E* & to_next) const override { return ok; }

     int do_encoding() const noexcept override { return 1; }
     bool do_always_noconv() const noexcept override { return false; }

     int do_length(const State&, const E* from, const E* from_end, size_t max) const override;
     int do_max_length() const noexcept override;          // maximum possible length()
};

codecvt<char,char,mbstate_t>::result
Cvt_to_upper::do_out(State& s,
                  const char* from, const char* from_end, const char*& from_next,
                  char* to, char* to_end, char*& to_next) const
{
     return codecvt<char,char,mbstate_t>::do_out(s,from,from_end,from_next,to,to_end,to_next);
}

codecvt<char,char,mbstate_t>::result
Cvt_to_upper::do_in(State& s,
                  const char* from, const char* from_end, const char*& from_next,
                  char* to, char* to_end, char*& to_next) const
{
     // ...
}

int main() // trivial test
{
     locale ulocale(locale(), new Cvt_to_upper);

     cin.imbue(ulocale);

     for (char ch; cin>>ch;)
           cout << ch;
}

A _byname version (§39.4, §39.4.1) of codecvt is provided:

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template<class I, class E, class State>
class codecvt_byname : public codecvt<I,E,State> {
     // ...
};

39.4.7. Messages

Naturally, most end users prefer to use their native language to interact with a program. However, we cannot provide a standard mechanism for expressing locale-specific general interactions. Instead, the library provides a simple mechanism for keeping a locale-specific set of strings from which a programmer can compose simple messages. In essence, messages implements a trivial read-only database:

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class messages_base {
public:
     using catalog = /* implementation-defined integer type */; // catalog identifier type
};

template<class C>
class messages : public locale::facet, public messages_base {
public:
     using char_type = C;
     using string_type = basic_string<C>;
     // ...
};

The messages interface is comparatively simple:

A call open(s,loc) opens a “catalog” of messages called s for the locale loc. A catalog is a set of strings organized in an implementation-specific way and accessed through the messages::g et() function. A negative value is returned if no catalog named s can be opened. A catalog must be opened before the first use of get().

A call close(cat) closes the catalog identified by cat and frees all resources associated with that catalog.

A call get(cat,set,id,"foo") looks for a message identified by (set,id) in the catalog cat. If a string is found, get() returns that string; otherwise, get() returns the default string (here, string("foo")).

Here is an example of a messages facet for an implementation in which a message catalog is a vector of sets of “messages” and a “message” is a string:

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struct Set {
     vector<string> msgs;
};

struct Cat {
     vector<Set> sets;
};

class My_messages : public messages<char> {
     vector<Cat>& catalogs;
public:
     explicit My_messages(size_t = 0) :catalogs{*new vector<Cat>} { }

     catalog do_open(const string& s, const locale& loc) const;     // open catalog s
     string do_get(catalog cat, int s, int m, const string&) const; // get message (s,m) in cat
     void do_close(catalog cat) const
     {
          if (catalogs.size()<=cat)
                catalogs.erase(catalogs.begin()+cat);
     }
     ~My_messages() { delete &catalogs; }
};

All messages’ member functions are const, so the catalog data structure (the vector<Set>) is stored outside the facet.

A message is selected by specifying a catalog, a set within that catalog, and a message string within that set. A string is supplied as an argument, to be used as a default result in case no message is found in the catalog:

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string My_messages::do_get(catalog cat, int set, int id, const string& def) const
{
     if (catalogs.size()<=cat)
           return def;
     Cat& c = catalogs[cat];
     if (c.sets.size()<=set)
           return def;
     Set& s = c.sets[set];
     if (s.msgs.size()<=msg)
           return def;
     return s.msgs[id];
}

Opening a catalog involves reading a textual representation from disk into a Cat structure. Here, I chose a representation that is trivial to read. A set is delimited by <<< and >>>, and each message is a line of text:

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messages<char>::catalog My_messages::do_open(const string& n, const locale& loc) const
{
    string nn = n + locale().name();
    ifstream f(nn.c_str());
    if (!f) return –1;

    catalogs.push_back(Cat{});               // make in-core catalog
    Cat& c = catalogs.back();

    for(string s; f>>s && s=="<<<"; ) {      // read Set
          c.sets.push_back(Set{});
          Set& ss = c.sets.back();
          while (getline(f,s) && s != ">>>") // read message
               ss.msgs.push_back(s);
    }
    return catalogs.size()–1;
}

Here is a trivial use:

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int main()
     // a trivial test
{
     if (!has_facet<My_messages>(locale())) {
           cerr << "no messages facet found in" << locale().name() << '\n';
           exit(1);
     }

     const messages<char>& m = use_facet<My_messages>(locale());
     extern string message_directory;  // where I keep my messages

     auto cat = m.open(message_directory,locale());
     if (cat<0) {
           cerr << "no catalog found\n";
           exit(1);
     }
     cout << m.get(cat,0,0,"Missed again!") << endl;
     cout << m.get(cat,1,2,"Missed again!") << endl;
     cout << m.get(cat,1,3,"Missed again!") << endl;
     cout << m.get(cat,3,0,"Missed again!") << endl;
}

If the catalog is:

<<<
hello
goodbye
>>>
<<<
yes
no
maybe
>>>

this program prints

hello
maybe
Missed again!
 Missed again!

39.4.7.1. Using Messages from Other facets

In addition to being a repository for locale-dependent strings used to communicate with users, messages can be used to hold strings for other facets. For example, the Season_io facet (§39.3.2) could have been written like this:

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class Season_io : public locale::facet {
     const messages<char>& m;           // message directory
     messages_base::catalog cat;        // message catalog
public:
     class Missing_messages { };

     Season_io(size_t i = 0)
           : locale::facet(i),
             m(use_facet<Season_messages>(locale())),
             cat(m.open(message_directory,locale()))
     {
           if (cat<0)
                 throw Missing_messages();
     }

     ~Season_io() { }    // to make it possible to destroy Season_io objects (§39.3)

     const string& to_str(Season x) const;                 // string representation of x

     bool from_str(const string& s, Season& x) const;      // place Season corresponding to s in x

     static locale::id id; // facet identifier object (§39.2, §39.3, §39.3.1)
};

locale::id Season_io::id; // define the identifier object

string Season_io::to_str(Season x) const
{
     return m–>get(cat,0,x,"no–such–season");
}

bool Season_io::from_str(const string& s, Season& x) const
{
     for (int i = Season::spring; i<=Season::winter; i++)
           if (m–>get(cat,0,i,"no–such–season") == s) {
                 x = Season(i);
                 return true;
           }
     return false;
}

This messages-based solution differs from the original solution (§39.3.2) in that the implementer of a set of Season strings for a new locale needs to be able to add them to a messages directory. This is easy for someone adding a new locale to an execution environment. However, since messages provides only a read-only interface, adding a new set of season names may be beyond the scope of an application programmer.

A _byname version (§39.4, §39.4.1) of messages is provided:

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template<class C>
class messages_byname : public messages<C> {
     // ...
};

39.5. Convenience Interfaces

Beyond simply imbuing an iostream, the locale facilities can be complicated to use. Consequently, convenience interfaces are provided to simplify notation and minimize mistakes.

39.5.1. Character Classification

The most common use of the ctype facet is to inquire whether a character belongs to a given classification. Consequently, a set of functions is provided for that:

These functions are trivially implemented using use_facet. For example:

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template<class C>
inline bool isspace(C c, const locale& loc)
{
     return use_facet<ctype<C>>(loc).is(space,c);
}

The one-argument versions of these functions (§36.2.1) use the current C global locale. Except for the rare cases in which the C global locale and the C++ global locale differ (§39.2.1), we can think of a one-argument version as the two-argument version applied to locale(). For example:

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inline int isspace(int i)
{
     return isspace(i,locale());    // almost
}

39.5.2. Character Conversions

Case conversions can be locale sensitive:

39.5.3. String Conversions

Character code conversions can be locale sensitive. Class template wstring_convert performs conversions between a wide string and a byte string. It lets you specify a code conversion facet (such as codecvt) to perform the conversions, without affecting any streams or locales. For example, you might use a code conversion facet called codecvt_utf8 directly to output a UTF-8 multibyte sequence to cout without altering cout’s locale:

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wstring_convert<codecvt_utf8<wchar_t>> myconv;
string s = myconv.to_bytes(L"Hello\n");
cout << s;

The definition of wstring_convert is fairly conventional:

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template<class Codecvt,
         class Wc = wchar_t,
         class Wa = std::allocator<Wc>,      // wide-character allocator
         class Ba = std::allocator<char>     // byte allocator
       >
class wstring_convert {
public:
     using byte_string = basic_string<char, char_traits<char>, Ba>;
     using wide_string = basic_string<Wc, char_traits<Wc>, Wa>;
     using state_type = typename Codecvt::state_type;
     using int_type = typename wide_string::traits_type::int_type;
     // ...
};

The wstring_convert constructors allow us to specify a character conversion facet, an initial conversion state, and values to be used in case of errors:

If a conversion to a wide_string fails, functions on a cvt constructed with a non-default w_err string return that string (as an error message); otherwise, they throw range_error.

If a conversion to a byte_string fails, functions on a cvt constructed with a non-default b_err string return that string (as an error message); otherwise, they throw range_error.

An example:

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void test()
{
     wstring_convert<codecvt_utf8_utf16<wchar_t>> converter;

     string s8 = u8"This is a UTF–8 string";
     wstring s16 = converter.from_bytes(s8);
     string s88 = converter.to_bytes(s16);

     if (s8!=s88)
           cerr <"Insane!\n";
}

39.5.4. Buffer Conversions

We can use a code conversion facet (§39.4.6) to write directly into or to read directly from a stream buffer (§38.6):

Click here to view code image

template<class Codecvt,
         class C = wchar_t,
         class Tr = std::char_traits<C>
      >
class wbuffer_convert
     : public std::basic_streambuf<C,Tr> {
public:
     using state_type = typename Codecvt::state_type;
     // ...
};

39.6. Advice

[1] Expect that every nontrivial program or system that interacts directly with people will be used in several different countries; §39.1.

[2] Don’t assume that everyone uses the same character set as you do; §39.1, §39.4.1.

[3] Prefer using locales to writing ad hoc code for culture-sensitive I/O; §39.1.

[4] Use locales to meet external (non-C++) standards; §39.1.

[5] Think of a locale as a container of facets; §39.2.

[6] Avoid embedding locale name strings in program text; §39.2.1.

[7] Keep changes of locale to a few places in a program; §39.2.1.

[8] Minimize the use of global format information; §39.2.1.

[9] Prefer locale-sensitive string comparisons and sorts; §39.2.2, §39.4.1.

[10] Make facets immutable; §39.3.

[11] Let locale handle the lifetime of facets; §39.3.

[12] You can make your own facets; §39.3.2.

[13] When writing locale-sensitive I/O functions, remember to handle exceptions from user-supplied (overriding) functions; §39.4.2.2.

[14] Use numput if you need separators in numbers; §39.4.2.1.

[15] Use a simple Money type to hold monetary values; §39.4.3.

[16] Use simple user-defined types to hold values that require locale-sensitive I/O (rather than casting to and from values of built-in types); §39.4.3.

[17] The time_put facet can be used for both <chrono>- and <ctime>-style time §39.4.4.

[18] Prefer the character classification functions in which the locale is explicit; §39.4.5, §39.5.

40. Numerics

The purpose of computing is insight, not numbers.

– R. W. Hamming

... but for the student,
numbers are often the best road to insight.

– A. Ralston

• Introduction

• Numerical Limits

Limit Macros

• Standard Mathematical Functions

• complex Numbers

• A Numerical Array: valarray

Constructors and Assignments; Subscripting; Operations; Slices; slice_array; Generalized Slices

• Generalized Numerical Algorithms

accumulate(); inner_product(); partial_sum() and adjacent_difference(); iota()

• Random Numbers

Engines; Random Device; Distributions; C-Style Random Numbers

• Advice

40.1. Introduction

C++ was not designed primarily with numeric computation in mind. However, numeric computation typically occurs in the context of other work – such as database access, networking, instrument control, graphics, simulation, and financial analysis – so C++ becomes an attractive vehicle for computations that are part of a larger system. Furthermore, numeric methods have come a long way from being simple loops over vectors of floating-point numbers. Where more complex data structures are needed as part of a computation, C++’s strengths become relevant. The net effect is that C++ is widely used for scientific, engineering, financial, and other computation involving sophisticated numerics. Consequently, facilities and techniques supporting such computation have emerged. This chapter describes the parts of the standard library that support numerics. I make no attempt to teach numeric methods. Numeric computation is a fascinating topic in its own right. To understand it, you need a good course in numerical methods or at least a good textbook – not just a language manual and tutorial.

In addition to the standard-library facilities described here, Chapter 29 is an extended example of numerical programming: an N-dimensional matrix.

40.2. Numerical Limits

To do anything interesting with numbers, we typically need to know something about the general properties of built-in numeric types. To allow the programmer to best take advantage of hardware, these properties are implementation-defined rather than fixed by the rules of the language itself (§6.2.8). For example, what is the largest int? What is the smallest positive float? Is a double rounded or truncated when assigned to a float? How many bits are there in a char?

Answers to such questions are provided by the specializations of the numeric_limits template presented in <limits>. For example:

Click here to view code image

void f(double d, int i)
{
     char classification[numeric_limits<unsigned char>::max()];

     if (numeric_limits<unsigned char>::digits==numeric_limits<char>::digits) {
           // chars are unsigned
     }
     if (i<numeric_limits<short>::min() || numeric_limits<short>::max()<i) {
           // i cannot be stored in a short without loss of digits
     }
     if (0<d && d<numeric_limits<double>::epsilon()) d = 0;

     if (numeric_limits<Quad>::is_specialized) {
          // limits information is available for type Quad
     }
}

Each specialization provides the relevant information for its argument type. Thus, the general numeric_limits template is simply a notational handle for a set of constants and constexpr functions:

Click here to view code image

template<typename T>
class numeric_limits {
public:
     static const bool is_specialized = false; // is information available for numeric_limits<T>?
     // ... uninteresting defaults ...
};

The real information is in the specializations. Each implementation of the standard library provides a specialization of numeric_limits for each fundamental numeric type (the character types, the integer types, the floating-point types, and bool) but not for any other plausible candidates such as void, enumerations, or library types (such as complex<double>).

For an integral type such as char, only a few pieces of information are of interest. Here is numeric_limits<char> for an implementation in which a char has 8 bits and is signed:

Click here to view code image

template<>
class numeric_limits<char> {
public:
     static const bool is_specialized = true; // yes, we have information

     static const int digits = 7;             // number of bits ("binary digits") excluding sign

     static const bool is_signed = true;      // this implementation has char signed
     static const bool is_integer = true;     // char is an integral type

     static constexpr char min() noexcept { return –128; }     // smallest value
     static constexpr char max() noexcept { return 127; }      // largest value

     // lots of declarations not relevant to a char
};

The functions are constexpr, so that they can be used where a constant expression is required and without run-time overhead.

Most members of numeric_limits are intended to describe floating-point numbers. For example, this describes one possible implementation of float:

Click here to view code image

template<>
class numeric_limits<float> {
public:
     static const bool is_specialized = true;

     static const int radix = 2;        // base of exponent (in this case, binary)
     static const int digits = 24;      // number of radix digits in mantissa
     static const int digits10 = 9;     // number of base 10 digits in mantissa

     static const bool is_signed = true;
     static const bool is_integer = false;
     static const bool is_exact = false;

     static constexpr float min() noexcept { return 1.17549435E–38F; } // smallest positive
     static constexpr float max() noexcept { return 3.40282347E+38F; } // largest positive
     static constexpr float lowest() noexcept { return –3.40282347E+38F; }  // smallest value

     static constexpr float epsilon() noexcept { return 1.19209290E–07F; }
     static constexpr float round_error() noexcept { return 0.5F; }   // maximum rounding error

     static constexpr float infinity() noexcept { return /* some value */; }
     static constexpr float quiet_NaN() noexcept { return /* some value */; }
     static constexpr float signaling_NaN() noexcept { return /* some value */; }
     static constexpr float denorm_min() noexcept { return min(); }

     static const int min_exponent = –125;
     static const int min_exponent10 = –37;
     static const int max_exponent = +128;
     static const int max_exponent10 = +38;

     static const bool has_infinity = true;
     static const bool has_quiet_NaN = true;
     static const bool has_signaling_NaN = true;
     static const float_denorm_style has_denorm = denorm_absent;
     static const bool has_denorm_loss = false;

     static const bool is_iec559 = true; // conforms to IEC-559
     static const bool is_bounded = true;
     static const bool is_modulo = false;
     static const bool traps = true;
     static const bool tinyness_before = true;

     static const float_round_style round_style = round_to_nearest;
};

Note that min() is the smallest positive normalized number and that epsilon is the smallest positive floating-point number such that 1+epsilon–1 is larger than 0.

When defining a scalar type along the lines of the built-in ones, it is a good idea also to provide a suitable specialization of numeric_limits. For example, if I write a quadruple-precision type Quad, a user could reasonably expect me to provide numeric_limits<Quad>. Conversely, if I use a nonnumeric type, Dumb_ptr, I would expect for numeric_limits<Dumb_ptr<X>> to be the primary template that has is_specialized set to false, indicating that no information is available.

We can imagine specializations of numeric_limits describing properties of user-defined types that have little to do with floating-point numbers. In such cases, it is usually better to use the general technique for describing properties of a type than to specialize numeric_limits with properties not considered in the standard.

40.2.1. Limit Macros

From C, C++ inherited macros that describe properties of integers. They are found in <climits>:

Analogously named macros for signed chars, long long, etc., are also provided.

Similarly, <cfloat> and <float.h> define macros describing properties of floating-point numbers:

Analogously named macros for long double are also provided.

40.3. Standard Mathematical Functions

In <cmath> we find what are commonly called the standard mathematical functions:

There are versions taking float, double, long double, and complex (§40.4) arguments. For each function, the return type is the same as the argument type.

Errors are reported by setting errno from <cerrno> to EDOM for a domain error and to ERANGE for a range error. For example:

Click here to view code image

void f()
{
     errno = 0; // clear old error state
     sqrt(–1);
     if (errno==EDOM) cerr << "sqrt() not defined for negative argument";
     pow(numeric_limits<double>::max(),2);
     if (errno == ERANGE) cerr << "result of pow() too large to represent as a double";
}

For historical reasons, a few mathematical functions are found in <cstdlib> rather than in <cmath>:

The l*() versions are there because C does not support overloading. The results of the ldiv() functions are structs div_t, ldiv_t, and lldiv_t, respectively. These structs have members quot (for quotient) and rem (for remainder) of implementation-defined types.

There is a separate ISO standard for special mathematical functions [C++Math,2010]. An implementation may add these functions to <cmath>:

If you don’t know these functions, you are unlikely to need them.

40.4. complex Numbers

The standard library provides complex number types complex<float>, complex<double>, and complex<long double>. A complex<Scalar> where Scalar is some other type supporting the usual arithmetic operations usually works but is not guaranteed to be portable.

Click here to view code image

template<typename Scalar>
class complex {
     // a complex is a pair of scalar values, basically a coordinate pair
     Scalar re, im;
public:
     complex(const Scalar & r = Scalar{}, const Scalar & i = Scalar{}) :re(r), im(i) { }

     Scalar real() const { return re; }      // real part
     void real(Scalar r) { re=r; }
     Scalar imag() const { return im; }      // imaginary part
     void imag(Scalar i) { im = i; }

     template<typename X>
         complex(const complex<X>&);

     complex<T>& operator=(const T&);
     complex& operator=(const complex&);
     template<typename X>
         complex<T>& operator=(const complex<X>&);

     complex<T>& operator+=(const T&);
     template<typename X>
        complex<T>& operator+=(const complex<X>&);

     // similar for operators -=, *=, /=
};

The standard-library complex does not protect against narrowing:

Click here to view code image

complex<float> z1 = 1.33333333333333333; // narrows
complex<double> z2 = 1.33333333333333333;// narrows
z1=z2;                                   // narrows

To protect against accidental narrowing, use {} initialization:

complex<float> z3 {1.33333333333333333}; // error: narrowing conversion

In addition to the members of complex, <complex> offers a host of useful operations:

The standard mathematical functions (§40.3) are also available for complex numbers. Note that complex does not provide < or %. For more details, see §18.3.

40.5. A Numerical Array: valarray

Much numeric work relies on relatively simple single-dimensional vectors of floating-point values. In particular, such vectors are well supported by high-performance machine architectures, libraries relying on such vectors are in wide use, and very aggressive optimization of code using such vectors is considered essential in many fields. The valarray from <valarray> is a single-dimensional numerical array. It provides the usual numeric vector arithmetic operations for an array type plus support for slices and strides:

The fundamental idea of valarray was to provide Fortran-like facilities for dense multidimensional arrays with Fortran-like opportunities for optimization. This can only be achieved with the active support of compiler and optimization suppliers and the addition of more library support on top of the very basic facilities provided by valarray. So far, that has not happened for all implementations.

40.5.1. Constructors and Assignments

The valarray constructors allow us to initialize valarrays from the auxiliary numeric array types and from single values:

For example:

Click here to view code image

valarray<double> v0;               // placeholder, we can assign to v0 later
valarray<float> v1(1000);          // 1000 elements with value float()==0.0F
valarray<int> v2(–1,2000);         // 2000 elements with value –1
valarray<double> v3(100,9.8064);   // bad mistake: floating-point valarray size

valarray<double> v4 = v3;          // v4 has v3.size() elements

valarray<int> v5 {–1,2000};        // two elements

In the two-argument constructors, the value comes before the number of elements. This differs from the convention for standard containers (§31.3.2).

The number of elements of an argument valarray to a copy constructor determines the size of the resulting valarray.

Most programs need data from tables or input. In addition to initializer lists, this is supported by a constructor that copies elements from a built-in array. For example:

Click here to view code image

void f(const int* p, int n)
{
     const double vd[] = {0,1,2,3,4};
     const int vi[] = {0,1,2,3,4};

     valarray<double> v1{vd,4};     // 4 elements: 0,1,2,3
     valarray<double> v2{vi,4};     // type error: vi is not pointer to double
     valarray<double> v3{vd,8};     // undefined: too few elements in initializer
     valarray<int> v4{p,n};         // p had better point to at least n ints
}

The valarray and its auxiliary facilities were designed for high-speed computing. This is reflected in a few constraints on users and by a few liberties granted to implementers. Basically, an implementer of valarray is allowed to use just about every optimization technique you can think of. The valarray operations are assumed to be free of side effects (except on their explicit arguments, of course), valarrays are assumed to be alias free, and the introduction of auxiliary types and the elimination of temporaries is allowed as long as the basic semantics are maintained. There is no range checking. The elements of a valarray must have the default copy semantics (§8.2.6).

Assignment can be with another valarray, a scalar, or a subset of a valarray:

A valarray can be assigned to another of the same size. As one would expect, v1=v2 copies every element of v2 into its corresponding position in v1. If valarrays have different sizes, the result of assignment is undefined.

In addition to this conventional assignment, it is possible to assign a scalar to a valarray. For example, v=7 assigns 7 to every element of the valarray v. This may be surprising to some programmers and is best understood as an occasionally useful degenerate case of the operator assignment operations. For example:

valarray<int> v {1,2,3,4,5,6,7,8};
v *= 2;     // v=={2,4,6,10,12,14,16}
v = 7;      // v=={7,7,7,7,7,7,7,7}

40.5.2. Subscripting

Subscripting can be used to select an element of a valarray or a subset of its elements:

Each operator[] returns a subset of the elements from a valarray. The return type (the type of the object representing the subset) depends on the argument type.

For const arguments, the result contains copies of elements. For non-const arguments, the result holds references to elements. Since C++ doesn’t directly support arrays of references (e.g., we can’t say valarray<int&>), the implementation will somehow simulate this. This can be done efficiently. An exhaustive list, with examples (based on §iso.26.6.2.5), is in order. In each case, the subscript describes the elements to be returned, and v1 must be a vallaray with an appropriate length and element type:

• A slice of a const valarray:

Click here to view code image

   valarray<T> operator[](slice) const;// copy of elements
   // ...
   const valarray<char> v0 {"abcdefghijklmnop",16};
   valarray<char> v1 {v0[slice(2,5,3)]};  // {"cfilo",5}

• A slice of a non-const valarray:

Click here to view code image

   slice_array<T> operator[](slice);  // references to elements
   // ...
   valarray<char> v0 {"abcdefghijklmnop",16};
   valarray<char> v1 {"ABCDE",5};
   v0[slice(2,5,3)] = v1;  // v0=={"abAdeBghCjkDmnEp",16}

• A gslice of a const valarray:

Click here to view code image

   valarray<T> operator[](const gslice&) const;   // copies of elements
   // ...
   const valarray<char> v0 {"abcdefghijklmnop",16};
   const valarray<size_t> len {2,3};
   const valarray<size_t> str {7,2};
   valarray<char> v1 {v0[gslice(3,len,str)]};     // v1=={"dfhkmo",6}

• A gslice of a non-const valarray:

Click here to view code image

   gslice_array<T> operator[](const gslice&); // references to elements
   // ...
   valarray<char> v0 {"abcdefghijklmnop",16};
   valarray<char> v1 {"ABCDE",5};
   const valarray<size_t> len {2,3};
   const valarray<size_t> str {7,2};
   v0[gslice(3,len,str)] = v1;   // v0=={"abcAeBgCijDlEnFp",16}

• A valarray<bool> (a mask) of a const valarray:

Click here to view code image

   valarray<T> operator[](const valarray<bool>&) const;        // copies of elements
   // ...
   const valarray<char> v0 {"abcdefghijklmnop",16};
   const bool vb[] {false, false, true, true, false, true};
   valarray<char> v1 {v0[valarray<bool>(vb, 6)]};              // v1=={"cdf",3}

• A valarray<bool> (a mask) of a non-const valarray:

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   mask_array<T> operator[](const valarray<bool>&);            // references to elements
   // ...
   valarray<char> v0 {"abcdefghijklmnop", 16};
   valarray<char> v1 {"ABC",3};
   const bool vb[] {false, false, true, true, false, true};
   v0[valarray<bool>(vb,6)] = v1;         // v0=={"abABeCghijklmnop",16}

• A valarray<size_t> (a set of indices) of a const valarray:

Click here to view code image

   valarray<T> operator[](const valarray<size_t>&) const;     // references to elements
   // ...
   const valarray<char> v0 {"abcdefghijklmnop",16};
   const size_t vi[] {7, 5, 2, 3, 8};
   valarray<char> v1 {v0[valarray<size_t>(vi,5)]};            // v1=={"hfcdi",5}

• A valarray<size_t> (a set of indices) of a non-const valarray:

Click here to view code image

   indirect_array<T> operator[](const valarray<size_t>&);    // references to elements
   // ...
   valarray<char> v0 {"abcdefghijklmnop",16};
   valarray<char> v1 {"ABCDE",5};
   const size_t vi[] {7, 5, 2, 3, 8};
   v0[valarray<size_t>(vi,5)] {v1}; // v0=={"abCDeBgAEjklmnop",16}

Note that subscripting with a mask (a valarray<bool>) yields a mask_array, and subscripting with a set of indices (a valarray<size_t>) yields an indirect_array.

40.5.3. Operations

The purpose of valarray is to support computation, so a host of basic numerical operations are directly supported:

There is no range checking: the effect of using a function that tries to access an element of an empty valarray is undefined.

Note that resize() does not retain any old values.

The binary operations are defined for valarrays and for combinations of a valarray and its scalar type. A scalar type is treated as a valarray of the right size with every element having the scalar’s value. For example:

Click here to view code image

void f(valarray<double>& v, valarray<double>& v2, double d)
{
     valarray<double> v3 = v*v2;   // v3[i] = v[i]*v2[i] for all i
     valarray<double> v4 = v*d;           // v4[i] = v[i]*d for all i
     valarray<double> v5 = d*v2;   // v5[i] = d*v2[i] for all i
     valarray<double> v6 = cos(v); // v6[i] = cos(v[i]) for all i
}

These vector operations all apply their operations to each element of their operand(s) in the way indicated by the * and cos() examples. Naturally, an operation can be used only if the corresponding operation is defined for the scalar type. Otherwise, the compiler will issue an error when trying to specialize the operator or function.

Where the result is a valarray, its length is the same as its valarray operand. If the lengths of the two arrays are not the same, the result of a binary operator on two valarrays is undefined.

These valarray operations return new valarrays rather than modifying their operands. This can be expensive, but it doesn’t have to be when aggressive optimization techniques are applied.

For example, if v is a valarray, it can be scaled like this: v*=0.2, and this: v/=1.3. That is, applying a scalar to a vector means applying the scalar to each element of the vector. As usual, *= is more concise than a combination of * and = (§18.3.1) and easier to optimize.

Note that the non-assignment operations construct a new valarray. For example:

Click here to view code image

double incr(double d) { return d+1; }

void f(valarray<double>& v)
{
     valarray<double> v2 = v.apply(incr);   // produce incremented valarray
     // ...
}

This does not change the value of v. Unfortunately, apply() does not accept a function object (§3.4.3, §11.4) as an argument.

The logical and cyclic shift functions, shift() and cshift(), return a new valarray with the elements suitably shifted and leave the original one unchanged. For example, the cyclic shift v2=v.cshift(n) produces a valarray so that v2[i]==v[(i+n)%v.size()]. The logical shift v3=v.shift(n) produces a valarray so that v3[i] is v[i+n] if i+n is a valid index for v. Otherwise, the result is the default element value. This implies that both shift() and cshift() shift left when given a positive argument and right when given a negative argument. For example:

Click here to view code image

void f()
{
     int alpha[] = { 1, 2, 3, 4, 5 ,6, 7, 8 };
     valarray<int> v(alpha,8);                // 1, 2, 3, 4, 5, 6, 7, 8
     valarray<int> v2 = v.shift(2);           // 3, 4, 5, 6, 7, 8, 0, 0
     valarray<int> v3 = v<<2;                 // 4, 8, 12, 16, 20, 24, 28, 32
     valarray<int> v4 = v.shift(–2);          // 0, 0, 1, 2, 3, 4, 5, 6
     valarray<int> v5 = v>>2;                 // 0, 0, 0, 1, 1, 1, 1, 2
     valarray<int> v6 = v.cshift(2);          // 3, 4, 5, 6, 7, 8, 1, 2
     valarray<int> v7 = v.cshift(–2);         // 7, 8, 1, 2, 3, 4, 5, 6
}

For valarrays, >> and << are bit shift operators, rather than element shift operators or I/O operators. Consequently, <<= and >>= can be used to shift bits within elements of an integral type. For example:

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void f(valarray<int> vi, valarray<double> vd)
{
     vi <<= 2;       // vi[i]<<=2 for all elements of vi
     vd <<= 2;       // error: shift is not defined for floating-point values
}

All of the operators and mathematical functions on valarrays can also be applied to slice_arrays (§40.5.5), gslice_arrays (§40.5.6), mask_arrays (§40.5.2), indirect_arrays (§40.5.2), and combinations of these types. However, an implementation is allowed to convert an operand that is not a valarray to a valarray before performing a required operation.

40.5.4. Slices

A slice is an abstraction that allows us to manipulate a one-dimensional array (e.g., a built-in array, a vector, or a valarray) efficiently as a matrix of arbitrary dimension. It is the key notion of Fortran vectors and of the BLAS (Basic Linear Algebra Subprograms) library, which is the basis for much numeric computation. Basically, a slice is every nth element of some part of an array:

Click here to view code image

class std::slice {
     // starting index, a length, and a stride
public:
     slice();                    // slice{0,0,0}
     slice(size_t start, size_t size, size_t stride);

     size_t start() const;       // index of first element
     size_t size() const;        // number of elements
     size_t stride() const;      // element n is at start()+n*stride()
};

A stride is the distance (in number of elements) between two elements of the slice. Thus, a slice describes a mapping of non-negative integers into indices. The number of elements (the size()) doesn’t affect the mapping (addressing) but allows us to find the end of a sequence. This mapping can be used to simulate two-dimensional arrays within a one-dimensional array (such as valarray) in an efficient, general, and reasonably convenient way. Consider a 3-by-4 matrix (three rows, each with four elements):

valarray<int> v {
     {00,01,02,03},    // row 0
     {10,11,12,13},    // row 1
     {20,21,22,23}     // row 2
};

or graphically:

Following the usual C/C++ conventions, the valarray is laid out in memory with row elements first (row-major order) and contiguous:

for (int x : v) cout << x << ' ' ;

This produces:

0 1 2 3 10 11 12 13 20 21 22 23

or graphically:

Row x is described by slice(x*4,4,1). That is, the first element of row x is the x*4th element of the vector, the next element of the row is the (x*4+1)th, etc., and there are 4 elements in each row. For example, slice{0,4,1} describes the first row of v (row 0): 00, 01, 02, 03, and slice{1,4,1} describes the second row (row 1).

Column y is described by slice(y,3,4). That is, the first element of column y is the yth element of the vector, the next element of the column is the (y+4)th, etc., and there are 3 elements in each column. For example, slice{0,3,4} describes the first column (column 0): 00, 10, 20, and slice{1,3,4} describes the second column (column 1).

In addition to its use for simulating two-dimensional arrays, a slice can describe many other sequences. It is a fairly general way of specifying very simple sequences. This notion is explored further in §40.5.6.

One way of thinking of a slice is as an odd kind of iterator: a slice allows us to describe a sequence of indices for a valarray. We could build an STL-style iterator based on that:

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template<typename T>
class Slice_iter {
     valarray<T>*v;
     slice s;
     size_t curr;    // index of current element

     T& ref(size_t i) const { return (*v)[s.start()+i*s.stride()]; }
public:
     Slice_iter(valarray<T>*vv, slice ss, size_t pos =0)
          :v{vv}, s{ss}, curr{0} { }

     Slice_iter end() const { return {this,s,s.size()}; }

     Slice_iter& operator++() { ++curr; return *this; }
     Slice_iter operator++(int) { Slice_iter t = *this; ++curr; return t; }

     T& operator[](size_t i) { return ref(i); }      // C-style subscript
     T& operator()(size_t i) { return ref(i); }      // Fortran-style subscript
     T& operator*() { return ref(curr); }            // current element

     bool operator==(const Slice_iter& q) const
     {
          return curr==q.curr && s.stride()==q.s.stride() && s.start()==q.s.start();
     }

     bool operator!=(const Slice_iter& q) const
     {
          return !(*this==q);
     }

     bool operator<(const Slice_iter& q) const
     {
          return curr<q.curr && s.stride()==q.s.stride() && s.start()==q.s.start();
     };
}

Since a slice has a size, we could even provide range checking. Here, I have taken advantage of slice::size() to provide an end() operation to provide an iterator for the one-past-the-end element of the slice.

Since a slice can describe either a row or a column, the Slice_iter allows us to traverse a valarray by row or by column.

40.5.5. slice_array

From a valarray and a slice, we can build something that looks and feels like a valarray but is really simply a way of referring to the subset of the array described by the slice.

A user cannot directly create a slice_array. Instead, the user subscripts a valarray to create a slice_array for a given slice. Once the slice_array is initialized, all references to it indirectly go to the valarray for which it is created. For example, we can create something that represents every second element of an array like this:

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void f(valarray<double>& d)
{
     slice_array<double>& v_even = d[slice(0,d.size()/2+d.size()%2,2)];
     slice_array<double>& v_odd = d[slice(1,d.size()/2,2)];

     v_even *= v_odd;  // multiply element pairs and store results in even elements
     v_odd = 0;        // assign 0 to every odd element of d
}

A slice_array can be copied. For example:

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slice_array<double> row(valarray<double>& d, int i)
{
     slice_array<double> v = d[slice(0,2,d.size()/2)];
     // ...
     return d[slice(i%2,i,d.size()/2)];
}

40.5.6. Generalized Slices

A slice (§29.2.2, §40.5.4) can describe a row or a column of an n-dimensional array. However, sometimes we need to extract a subarray that is not a row or a column. For example, we might want to extract the 3-by-2 matrix from the top-left corner of a 4-by-3 matrix:

Unfortunately, these elements are not allocated in a way that can be described by a single slice:

A gslice is a “generalized slice” that contains (almost) the information from n slices:

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class std::gslice {
     // instead of 1 stride and one size like slice, gslice holds n strides and n sizes
public:
     gslice();
     gslice(size_t sz, const valarray<size_t>& lengths, const valarray<size_t>& strides);

     size_t start() const;               // index of first element
     valarray<size_t> size() const;      // number of elements in dimension
     valarray<size_t> stride() const;    // stride for index[0], index[1], ...
};

The extra values allow a gslice to specify a mapping between n integers and an index to be used to address elements of an array. For example, we can describe the layout of the 3-by-2 matrix by a pair of (length,stride) pairs:

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size_t gslice_index(const gslice& s, size_t i, size_t j)   // max (i,j) to their corresponding index
{
     return s.start()+i*s.stride()[0]+j*s.stride()[1];
}
valarray<size_t> lengths {2,3};// 2 elements in the first dimension
                                 // 3 elements in the second dimension
valarray<size_t> strides {3,1};  // 3 is the stride for the first index
                                 // 1 is the stride for the second index

void f()
{
     gslice s(0,lengths,strides);

     for (int i=0; i<3; ++i)       // for each row
           for (int j=0; j<2; ++j) // for each element in row
                 cout << "(" << i << "," << j << ")–>" << gslice_index(s,i,j) << "; "; // print mapping
}

This prints:

(0,0)–>0; (0,1)–>1; (1,0)–>3; (1,1)–>4; (2,0)–>6; (2,1)–>7

In this way, a gslice with two (length,stride) pairs describes a subarray of a two-dimensional array, a gslice with three (length,stride) pairs describes a subarray of a three-dimensional array, etc. Using a gslice as the index of a valarray yields a gslice_array consisting of the elements described by the gslice. For example:

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void f(valarray<float>& v)
{
     gslice m(0,lengths,strides);
     v[m] = 0;                    // assign 0 to v[0],v[1],v[3],v[4],v[6],v[7]
}

The gslice_array offers the same set of members as slice_array (§40.5.5). A gslice_array is the result of using a gslice as the subscript of a valarray (§40.5.2).

40.6. Generalized Numerical Algorithms

In <numeric>, the standard library provides a few generalized numeric algorithms in the style of the non-numeric algorithms from <algorithm> (Chapter 32). These algorithms provide general versions of common operations on sequences of numerical values:

These algorithms generalize common operations such as computing a sum by letting them apply to all kinds of sequences and by making the operation applied to elements of those sequences a parameter. For each algorithm, the general version is supplemented by a version applying the most common operator for that algorithm.

40.6.1. accumulate()

The simple version of accumulate() adds elements of a sequence using their + operator:

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template<typename In, typename T>
T accumulate(In first, In last, T init)
{
     for (; first!=last; ++first)   // for all elements in [first:last)
            init = init + *first;   // plus
     return init;
}

It can be used like this:

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void f(vector<int>& price, list<float>& incr)
{
     int i = accumulate(price.begin(),price.end(),0);   // accumulate in int
     double d = 0;
     d = accumulate(incr.begin(),incr.end(),d);         // accumulate in double

     int prod = accumulate(price.begin,price.end(),1,[](int a, int b) { return a*b; });
     // ...
}

The type of the initial value passed determines the return type.

We can provide an initial value and an operation for “combining elements” as arguments to accumulate(), so accumulate() is not all about addition.

Extracting a value from a data structure is common operation for accumulate(). For example:

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struct Record {
     // ...
     int unit_price;
     int number_of_units;
};

long price(long val, const Record& r)
{
     return val + r.unit_price * r.number_of_units;
}

void f(const vector<Record>& v)
{
     cout << "Total value: " << accumulate(v.begin(),v.end(),0,price) << '\n';
}

Operations similar to accumulate are called reduce, reduction, and fold in some communities.

40.6.2. inner_product()

Accumulating from a sequence is very common, and accumulating from a pair of sequences is not uncommon:

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template<typename In, typename In2, typename T>
T inner_product(In first, In last, In2 first2, T init)
{
     while (first != last)
          init = init + *first++ **first2++;
     return init;
}

template<typename In, typename In2, typename T, typename BinOp, typename BinOp2>
T inner_product(In first, In last, In2 first2, T init, BinOp op, BinOp2 op2)
{
     while (first != last)
          init = op(init,op2(*first++,*first2++));
     return init;
}

As usual, only the beginning of the second input sequence is passed as an argument. The second input sequence is assumed to be at least as long as the first.

The key operation in multiplying a Matrix by a valarray is an inner_product:

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valarray<double> operator*(const Matrix& m, valarray<double>& v)
{
     valarray<double> res(m.dim2());

     for (size_t i=0; i<m.dim2(); i++) {
           auto& ri = m.row(i);
           res[i] = inner_product(ri,ri.end(),&v[0],double(0));
     }
     return res;
}

valarray<double> operator*(valarray<double>& v, const Matrix& m)
{
     valarray<double> res(m.dim1());

     for (size_t i=0; i<m.dim1(); i++) {
           auto& ci = m.column(i);
           res[i] = inner_product(ci,ci.end(),&v[0],double(0));
     }
     return res;
}

Some forms of inner_product are referred to as “dot product.”

40.6.3. partial_sum() and adjacent_difference()

The partial_sum() and adjacent_difference() algorithms are inverses of each other and deal with the notion of incremental change.

Given a sequence a, b, c, d, etc., adjacent_difference() produces a, b–a, c–b, d–c, etc.

Consider a vector of temperature readings. We could transform it into a vector of temperature changes like this:

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vector<double> temps;

void f()
{
     adjacent_difference(temps.begin(),temps.end(),temps.begin());
}

For example, 17, 19, 20, 20, 17 turns into 17, 2, 1, 0, –3.

Conversely, partial_sum() allows us to compute the end result of a set of incremental changes:

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template<typename In, typename Out, typename BinOp>
Out partial_sum(In first, In last, Out res, BinOp op)
{
     if (first==last) return res;
     *res = *first;
     T val = *first;
     while (++first != last) {
          val = op(val,*first);
          *++res = val;
     }
     return ++res;
}

template<typename In, typename Out>
Out partial_sum(In first, In last, Out res)
{
     return partial_sum(first,last,res,plus);   // use std::plus (§33.4)
}

Given a sequence a, b, c, d, etc., partial_sum() produces a, a+b, a+b+c, a+b+c+d, etc. For example:

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void f()
{
     partial_sum(temps.begin(),temps.end(),temps.begin());
}

Note the way partial_sum() increments res before assigning a new value through it. This allows res to be the same sequence as the input; adjacent_difference() behaves similarly. Thus,

partial_sum(v.begin(),v.end(),v.begin());

turns the sequence a, b, c, d into a, a+b, a+b+c, a+b+c+d, and

adjacent_difference(v.begin(),v.end(),v.begin());

reproduces the original value. Thus, partial_sum() turns 17, 2, 1, 0, –3 back into 17, 19, 20, 20, 17.

For people who think of temperature differences as a boring detail of meteorology or science lab experiments, I note that analyzing changes in stock prices or sea levels involves exactly the same two operations. These operations are useful for analyzing any series of changes.

40.6.4. iota()

A call iota(b,e,n) assigns n+i to the ith element of [b:e). For example:

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vector<int> v(5);
iota(v.begin(),v.end(),50);
vector<int> v2 {50,51,52,53,54}

if (v!=v2)
       error("complain to your library vendor");

The name iota is the Latin spelling of the Greek letter , which was used for that function in APL.

Do not confuse iota() with the non-standard, but not uncommon, itoa() (int-to-alpha; §12.2.4).

40.7. Random Numbers

Random numbers are essential to many applications, such as simulations, games, sampling-based algorithms, cryptography, and testing. For example, we might want to choose the TCP/IP address for a router simulation, decide whether a monster should attack or scratch its head, or generate a set of values for testing a square root function. In <random>, the standard library defines facilities for generating (pseudo-)random numbers. These random numbers are sequences of values produced according to mathematical formulas, rather than unguessable (“truly random”) numbers that could be obtained from a physical process, such as radioactive decay or solar radiation. If the implementation has such a truly random device, it will be represented as a random_device (§40.7.1).

Four kinds of entities are provided:

• A uniform random number generator is a function object returning unsigned integer values such that each value in the range of possible results has (ideally) equal probability of being returned.

• A random number engine (an engine) is a uniform random number generator that can be created with a default state E{} or with a state determined by a seed E{s}.

• A random number engine adaptor (an adaptor) is a random number engine that takes values produced by some other random number engine and applies an algorithm to those values in order to deliver a sequence of values with different randomness properties.

• A random number distribution (a distribution) is a function object returning values that are distributed according to an associated mathematical probability density function p(z) or according to an associated discrete probability function P(zi).

For details see §iso.26.5.1.

In simpler terms, the users’ terms, a random number generator is an engine plus a distribution. The engine produces a uniformly distributed sequence of values, and the distribution bends those into the desired shape (distribution). That is, if you take lots of numbers from a random number generator and draw them, you should get a reasonably smooth graph of their distribution. For example, binding a normal_distribution to the default_random_engine gives me a random number generator that produces a normal distribution:

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auto gen = bind(normal_distribution<double>{15,4.0},default_random_engine{});

for (int i=0; i<500; ++i) cout << gen();

The standard-library function bind() makes a function object that will invoke its first argument given its second argument (§33.5.1).

Using ASCII graphics (§5.6.3), I got:

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3   **
4   *
5   *****
6   ****
7   ****
8   ******
9   ************
10  ***************************
11  ***************************
12  **************************************
13  **********************************************************
14  ***************************************************
15  *******************************************************
16  ********************************
17  **************************************************
18  *************************************
19  **********************************
20  ***************
21  ************
22  ************
23  *******
24  *****
25  ****
26  *
27  *

Most of the time, most programmers just need a simple uniform distribution of integers or floating-point numbers in a given range. For example:

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void test()
{
     Rand_int ri {10,20};        // uniform distribution of ints in [10:20)
     Rand_double rd {0,0.5};     // uniform distribution of doubles in [0:0.5)

     for (int i=0; i<100; ++i)
           cout << ri() << ' ';
     for (int i=0; i<100; ++i)
           cout << rd() << ' ';
}

Unfortunately, Ran_int and Rand_double are not standard classes, but they are easy to build:

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class Rand_int {
     Rand_int(int lo, int hi) : p{lo,hi} { }   // store the parameters
     int operator()() const { return r(); }
private:
     uniform_int_distribution<>::param_type p;
     auto r = bind(uniform_int_distribution<>{p},default_random_engine{});
};

I store the parameters using the distribution’s standard param_type alias (§40.7.3) so that I can use auto to avoid having to name the result of the bind().

Just for variation, I use a different technique for Rand_double:

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class Rand_double {
public:
     Rand_double(double low, double high)
         :r(bind(uniform_real_distribution<>(low,high),default_random_engine())) { }
     double operator()() { return r(); }
private:
     function<double()> r;
};

One important use of random numbers is for sampling algorithms. In such algorithms we need to choose a sample of some size from a much larger population. Here is algorithm R (the simplest algorithm) from a famous old paper [Vitter,1985]:

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template<typename Iter, typename Size, typename Out, typename Gen>
Out random_sample(Iter first, Iter last, Out result, Size n, Gen&& gen)
{
     using Dist = uniform_int_distribution<Size>;
     using Param = typename Dist::param_type;

     // Fill the reservoir and advance first:
     copy(first,n,result);
     advance(first,n);

     // Sample the remaining values in [first+n:last) by selecting a random
     // number r in the range [0:k], and, if r<n, replace it.
     // k increases with each iteration, making the probability smaller.
     // For random access iterators, k = i-first (assuming we increment i and not first).

     Dist dist;
     for (Size k = n; first!=last; ++first,++k) {
           Size r = dist(gen,Param{0,k});
           if(r < n)
                  *(result + r) = *first;
   }
   return result;
}

40.7.1. Engines

A uniform random number generator is a function object that produces an approximately uniformly distributed sequence of values of its result_type:

A random number engine is a uniform random number generator with additional properties to make it widely useful:

A seed is a value in the range [0:2³²) that can be used to initialize a particular engine. A seed sequence, g, is an object that provides a function g.generate(b,e) that when called fills [b:e) with newly generated seeds (§iso.26.5.1.2).

The UI parameter for a standard random number engine must be an unsigned integer type. For linear_congruential_engine<UI,a,c,m>, if the modulus m is 0, the value numeric_limits<result_type>::max()+1 is used. For example, this writes out the index of the first repetition of a number:

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map<int,int> m;
linear_congruential_engine<unsigned int,17,5,0> linc_eng;
for (int i=0; i<1000000; ++i)
      if (1<++m[linc_eng()]) cout << i << '\n';

I was lucky; the parameters were not too bad and I got no duplicate values. Try <unsigned int,16,5,0> instead and see the difference. Use the default_random_engine unless you have a real need and know what you are doing.

A random number engine adaptor takes a random number engine as an argument and produces a new random number engine with different randomness properties.

For example:

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independent_bits_engine<default_random_engine,4,unsigned int> ibe;
for (int i=0; i<100; ++i)
      cout << '0'+ibe() << ' ';

This will produce 100 numbers in the range [48:63] ([’0’:’0’+2⁴-1)).

A few aliases are defined for useful engines:

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using minstd_rand0 = linear_congruential_engine<uint_fast32_t, 16807, 0, 2147483647>;
using minstd_rand = linear_congruential_engine<uint_fast32_t, 48271, 0, 2147483647>;
using mt19937 = mersenne_twister_engine<uint_fast32_t, 32,624,397,
                       31,0x9908b0df,
                       11,0xffffffff,
                       7,0x9d2c5680,
                       15,0xefc60000,
                       18,1812433253>
using mt19937_64 = mersenne_twister_engine<uint_fast64_t, 64,312,156,
                       31,0xb5026f5aa96619e9,
                       29, 0x5555555555555555,
                       17, 0x71d67fffeda60000,
                       37, 0xfff7eee000000000,
                       43, 6364136223846793005>;
using ranlux24_base = subtract_with_carry_engine<uint_fast32_t, 24, 10, 24>;
using ranlux48_base = subtract_with_carry_engine<uint_fast64_t, 48, 5, 12>;
using ranlux24 = discard_block_engine<ranlux24_base, 223, 23>;
using ranlux48 = discard_block_engine<ranlux48_base, 389, 11>;
using knuth_b = shuffle_order_engine<minstd_rand0,256>;

40.7.2. Random Device

If an implementation is able to offer a truly random number generator, that source of random numbers is presented as a uniform random number generator called random_device:

Think of s as the name of a random number source, such as a Geiger counter, a Web service, or a file/device containing the record of a truly random source. The entropy() is defined as

for a device with n states whose respective probabilities are P₀,..., Pn–1. The entropy is an estimate of the randomness, the degree of unpredictability, of the generated numbers. In contrast to thermodynamics, high entropy is good for random numbers because that means that it is hard to guess subsequent numbers. The formula reflects the result of repeatedly throwing a perfect n-sided dice.

The random_device is intended to be useful for cryptograpic applications, but it would be against all rules of that kind of application to trust an implementation of random_device without first studying it closely.

40.7.3. Distributions

A random number distribution is a function object that, when called with a random number generator argument, produces a sequence of values of its result_type:

In the following tables, a template argument R means a real is required in the mathematical formula and double is the default. An I means that an integer is required and int is the default.

The precondition field specifies requirements on the distribution arguments. For example:

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uniform_int_distribution<int> uid1 {1,100};  // OK
uniform_int_distribution<int> uid2 {100,1};  // error: a>b

The default field specifies default arguments. For example:

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uniform_real_distribution<double> urd1 {};       // use a==0.0 and b==1.0
uniform_real_distribution<double> urd2 {10,20};  // use a==10.0 and b==20.0
uniform_real_distribution<> urd3 {};             // use double and a==0.0 and b==1.0

The result field specifies the range of the results. For example:

uniform_int_distribution<> uid3 {0,5};
default_random_engine e;
for (int i=0; i<20; ++i)
      cout << uid3(e) << ' ';

The range for uniform_int_distribution is closed, and we see the six possible values:

2 0 2 5 4 1 5 5 0 1 1 5 0 0 5 0 3 4 1 4

For uniform_real_distribution, as for all other distributions with floating-point results, the range is half-open.

Bernoulli distributions reflect sequences of tosses of coins with varying degrees of loading:

Poisson distributions express the probability of a given number of events occurring in a fixed interval of time and/or space:

Normal distributions map real values into real values. The simplest is the famous “bell curve” that distributes values symmetrically around a peak (mean) with the distance of elements from the mean being controlled by a standard deviation parameter:

To get a feeling for these distributions, look at graphical representations for a variety of parameters. Such representations are easily generated and even more easily found on the Web.

Sampling distributions map integers into a specific range according to their probability density function P:

40.7.4. C-Style Random Numbers

In <cstdlib> and <stdlib.h>, the standard library provides a simple basis for the generation of random numbers:

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#define RAND_MAX implementation_defined /* large positive integer */

int rand();                  // pseudo-random number between 0 and RAND_MAX
void srand(unsigned int i);  // seed random number generator by i

Producing a good random number generator isn’t easy, and unfortunately not all systems deliver a good rand(). In particular, the low-order bits of a random number are often suspect, so rand()%n is not a good portable way of generating a random number between 0 and n–1. Often, int((double(rand())/RAND_MAX)*n) gives acceptable results. However, for serious applications, generators based on uniform_int_distribution (§40.7.3) will give more reliable results.

A call srand(s) starts a new sequence of random numbers from the seed, s, given as argument. For debugging, it is often important that a sequence of random numbers from a given seed be repeatable. However, we often want to start each real run with a new seed. In fact, to make games unpredictable, it is often useful to pick a seed from the environment of a program. For such programs, some bits from a real-time clock often make a good seed.

40.8. Advice

[1] Numerical problems are often subtle. If you are not 100% certain about the mathematical aspects of a numerical problem, either take expert advice, experiment, or do both; §29.1.

[2] Use variants of numeric types that are appropriate for their use; §40.2.

[3] Use numeric_limits to check that the numeric types are adequate for their use; §40.2.

[4] Specialize numeric_limits for a user-defined numeric type; §40.2.

[5] Prefer numeric_limits over limit macros; §40.2.1.

[6] Use std::complex for complex arithmetic; §40.4.

[7] Use {} initialization to protect against narrowing; §40.4.

[8] Use valarray for numeric computation when run-time efficiency is more important than flexibility with respect to operations and element types; §40.5.

[9] Express operations on part of an array in terms of slices rather than loops; §40.5.5.

[10] Slices is a generally useful abstraction for access of compact data; §40.5.4, §40.5.6.

[11] Consider accumulate(), inner_product(), partial_sum(), and adjacent_difference() before you write a loop to compute a value from a sequence; §40.6.

[12] Bind an engine to a distribution to get a random number generator; §40.7.

[13] Be careful that your random numbers are sufficiently random; §40.7.1.

[14] If you need genuinely random numbers (not just a pseudo-random sequence), use random_device; §40.7.2.

[15] Prefer a random number class for a particular distribution over direct use of rand(); §40.7.4.

41. Concurrency

Keep it simple:

as simple as possible,

but no simpler.

– A. Einstein

• Introduction

• Memory Model

Memory Location; Instruction Reordering; Memory Order; Data Races

• Atomics

atomic Types; Flags and Fences

• volatile

• Advice

41.1. Introduction

Concurrency – the execution of several tasks simultaneously – is widely used to improve throughput (by using several processors for a single computation) or to improve responsiveness (by allowing one part of a program to progress while another is waiting for a response).

The C++ standard support for concurrency is introduced in a tutorial manner in §5.3. This chapter and the next provide a more detailed and systematic view.

We call an activity potentially executed concurrently with other activities a task. A thread is the system-level representation of a computer’s facilities for executing a task. A standard-library thread (§42.2) can execute a task. A thread may share an address space with other threads. That is, all threads in a single address space can access the same memory locations. One of the central challenges of the programmer of a concurrent system is to make sure that threads access memory in a sensible manner.

The standard library’s support for concurrency includes:

• A memory model: a set of guarantees for concurrent access to memory (§41.2) that basically ensures that simple and ordinary access works as one would naively expect

• Support for programming without locks: fine-grained low-level mechanisms for avoiding data races (§41.3)

• A thread library: a set of components supporting traditional threads-and-locks-style system-level concurrent programming, such as thread, condition_variable, and mutex (§42.2)

• A task support library: a few facilities supporting task-level concurrent programming: future, promise, packaged_task, and async() (§42.4)

These topics are ordered from the most fundamental and low-level to the highest-level. The memory model is common to all programming. For programmer productivity and error minimization, work at the highest feasible level. For example, prefer a future over a mutex for exchanging information and a mutex over an atomic for anything but simple counters and the like. Leave the complexities to standard-library implementers whenever feasible.

In the context of the C++ standard library, a lock is a mutex (a mutual exclusion variable) and any abstraction built upon a mutex to provide mutually exclusive access to a resource or to synchronize the progress of several concurrent tasks.

The topic of processes, that is, threads of execution in their own address spaces and communicating though inter-process communication mechanisms [Tanenbaum,2007], is not addressed in this book. I suspect that after reading about the problems with and techniques for managing shared data, you may become sympathetic to my view that explicitly shared data is best avoided. Naturally, communication implies some form of sharing, but that sharing most often need not be directly managed by the application programmer.

Please also note that as long as you don’t pass pointers to your local data to other threads, your local data is free of the problems mentioned here. This is yet another reason to avoid global data.

This chapter is not a comprehensive guide to concurrent programming or even a complete explanation of the C++ standard-library facilities for concurrent programming. It provides:

• A basic description of the problems facing a programmer who has to deal with concurrency at the system level

• A fairly detailed overview of the concurrency facilities provided by the standard

• An introduction to the basic uses of the standard-library concurrency features at the threads-and-locks level and above It does not:

• Go into details of the relaxed memory models or lock-free programming

• Teach advanced concurrent programming and design techniques

Concurrent and parallel programming have been popular topics of research and widely used for more than 40 years, so there is an extensive specialized literature (for example, for C++-based concurrency see [Wilson,1996]). In particular, just about any presentation of POSIX threads can be used as a source of examples that can be easily improved by using the standard-library facilities described here.

In contrast to the C-style POSIX facilities and to many older C++ thread-support libraries, the standard-library thread support is type-safe. There is no longer any reason to mess around with macros or void**s to pass information among threads. Similarly, we can define tasks as function objects (e.g., lambdas) and pass them to threads without using casts or worrying about type violations. Furthermore, there is no reason to invent elaborate conventions for reporting errors from one thread to another; futures (§5.3.5.1, §42.4.4) can transmit exceptions. Given that concurrent software is often complex and that code running in different threads is often separately developed, I consider type safety and a standard (preferably exception-based) error-handling strategy even more important than for single-threaded software. The standard-library thread support also greatly simplifies notation.

41.2. Memory Model

The C++ concurrency mechanisms are mostly supplied as standard-library components. These components rely on a set of language guarantees known as the memory model. A memory model is the result of discussions between machine architects and compiler writers about how best to represent computer hardware. The memory model, as specified in the ISO C++ standard, represents a contract between the implementers and the programmers to ensure that most programmers do not have to think about the details of modern computer hardware.

To understand the problems involved, keep one simple fact in mind: operations on an object in memory are never directly performed on the object in memory. Instead, the object is loaded into a processor register, modified there, and then written back. Worse still, an object is typically first loaded from the main memory into a cache memory and from there to a register. For example, consider incrementing a simple integer x:

// add one to x:
     load x into cache element Cx
     load Cx into register Rx
     Rx=Rx+1;
     store Rx back into Cx
     store Cx back into x

Memory can be shared by several threads, and cache memory may (depending on the machine architecture) be shared among threads running on the same or different “processing units” (usually called something like processors, cores, or hyper-threads; this is an area of rapid evolution of both system facilities and terminology). This opens a host of opportunities for a simple operation (such as “add one to x”) to get corrupted. It will be obvious to machine architecture experts that I am simplifying. For the few who notice that I have not mentioned store buffers, I recommend Appendix C of [McKenney,2012].

41.2.1. Memory Location

Consider two global variables b and c:

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// thread 1:                // thread 2:
       char c = 0;                 char b = 0;
       void f()                    void g()
       {                           {
            c = 1;                      b = 1;
            int x = c;                int y = b;
       }                           }

Now, x==1 and y==1 as anyone would expect. Why is this even worth saying? Consider what might happen if a linker allocated c and b in the same word in memory and (like most modern hardware) the machine could not load or store anything smaller than a word:

Without a well-defined and reasonable memory model, thread 1 might read the word containing b and c, change c, and write the word back into memory. At the same time, thread 2 could do the same with b. Then, whichever thread managed to read the word first and whichever thread managed to write its result back into memory last would determine the result. We might get 10, 01, or 11 (but not 00). The memory model saves us from such chaos; we get 11. The reason that 00 cannot happen is that the initializations of b and c are done (by the compiler or the linker) before either thread starts.

The C++ memory model guarantees that two threads of execution can update and access separate memory locations without interfering with each other. This is exactly what we would naively expect. It is the compiler’s job to protect us from the sometimes very strange and subtle behaviors of modern hardware. How a compiler and hardware combination achieves that is up to the compiler. We program a “machine” that is provided by a combination of hardware and very low-level (compiler-generated) software.

Bit-fields (§8.2.7) give access to parts of a word. If two threads simultaneously access two fields of the same word, all bets are off. If b and c are two fields of the same word, most hardware has no way of avoiding the problem (the race condition) from the b-and-c example without using some form of (potentially very expensive) locking. Lock and unlock operations are not a cost we could implicitly impose on bit-fields, which are commonly used in critical device drivers. Consequently, the language defines memory location as the unit of memory for which sensible behavior is guaranteed to exclude individual bit-fields.

A memory location is either an object of arithmetic type (§6.2.1), a pointer, or a maximal sequence of adjacent bit-fields all having nonzero width. For example:

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struct S {
      char a;                  // location #1
      int b:5;                 // location #2
      unsigned c:11;
      unsigned :0;             // note: :0 is "special" (§8.2.7)
      unsigned d:8;            // location #3
      struct { int ee:8; } e;  // location #4
};

Here, S has exactly four separate memory locations. Don’t try to update bit-fields b and c from separate threads without explicit synchronization.

From the explanation above, you might conclude that if x and y are of the same type, x=y is guaranteed to result in x being a copy of y. This is true if and only if you don’t have a data race (§41.2.4) and if x and y are memory locations. However, if x and y are of a multiword struct they are not a single memory location, and if you have a data race, all behavior is undefined, so make sure you have proper synchronization in place if you share data (§41.3, §42.3.1).

41.2.2. Instruction Reordering

To gain performance, compilers, optimizers, and hardware reorder instructions. Consider:

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// thread 1:
      int x;
      bool x_init;

      void init()
      {
           x = initialize(); // no use of x_init in initialize()
           x_init = true;
           // ...
     }

For this piece of code there is no stated reason to assign to x before assigning to x_init. The optimizer (or the hardware instruction scheduler) may decide to speed up the program by executing x_init=true first.

We probably meant for x_init to indicate whether x had been initialized by initializer() or not. However, we did not say that, so the hardware, the compiler, and the optimizer do not know that.

Add another thread to the program:

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// thread 2:
      extern int x;
      extern bool x_init;

      void f2()
      {
         int y;
         while (!x_init)         // if necessary, wait for initialization to complete
               this_thread::sleep_for(milliseconds{10});
         y = x;
         // ...
      }

Now we have a problem: thread 2 may never wait and thus will assign an uninitialized x to y.

Even if thread 1 did not set x_init and x in “the wrong order,” we still may have a problem. In thread 2, there are no assignments to x_init, so an optimizer may decide to lift the evaluation of !x_init out of the loop, so that thread 2 either never sleeps or sleeps forever.

41.2.3. Memory Order

The time needed to get the value of a word from memory into a cache, then into a register, can be (on a processor’s time scale) very long. At best, maybe 500 instructions are executed before the value reaches the register, and another 500 instructions are executed before a new value reaches its intended location. The figure 500 is a guess that depends on machine architecture and varies over time, but for the last decades it has steadily increased. When there is no rush to load and store a particular value because the computation is optimized for throughput, the time taken can be much higher. A value can be “away from its location” for tens of thousands of instruction cycles. This is one of the facts that give modern hardware its amazing performance, but it also opens huge opportunities for confusion as different threads look at a value at different times and in different places in the memory hierarchy. For example, my simplified description mentions only a single cache; many popular architectures use a three-level cache. To illustrate, here is a diagram of a possible two-level cache architecture where each core has its own level-2 cache, a pair of cores share a level-1 cache, and all cores share the memory:

Memory ordering is the term used to describe what a programmer can assume about what a thread sees when it looks at a value from memory. The simplest memory order is called sequentially consistent. In a sequentially consistent memory model, every thread sees the effects of every operation done in the same order. The order is as if the instructions were done sequentially in a single thread. A thread can still reorder operations, but at every point where another thread might observe a variable, the set of operations performed before and (therefore) the value of the memory location observed must be well defined and the same for all threads. An operation that “observes” a value and thereby forces a consistent view of a memory location is called an atomic operation (see §41.3). A simple read or write does not impose an order.

There are many possible sequentially consistent orders for a given set of threads. Consider:

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// thread 1:                 // thread 2:
      char c = 0;                  char b = 0;
      extern char b;               extern char c;
      void f1()                    void f2()
      {                            {
           c = 1;                       b=1;
           int x = b;                   int y = c;
      }                            }

Assuming that the initialization of c and b is done statically (before any thread starts), there are three possible executions:

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c = 1;      b = 1;      c = 1;
x = b;      y = c;      b = 1;
b = 1;      c = 1;      x = b;
y = c;      x = b;      y = c;

The results are 01, 10, and 11, respectively. The only result we cannot get is 00. Obviously, to get a predictable result, you need some form of synchronization of the access to the shared variables.

The sequential consistent order is just about all a programmer can effectively reason about, but on some machine architectures it imposes significant synchronization costs that can be eliminated by relaxing the rules. For example, two threads running on separate cores might decide to initiate the reads of x and y before the writes of a and b or at least before the writes had completed. That could give the nonsequentially consistent result 00. More relaxed memory models allow that.

41.2.4. Data Races

From these examples, every sensible person will conclude that we have to be very careful when programming threads. But how? First, we must avoid data races. Two threads have a data race if both can access a memory location (as defined in §41.2.1) simultaneously and at least one of their accesses is a write. Note that defining “simultaneously” precisely is not trivial. If two threads have a data race, no language guarantees hold: the behavior is undefined. This may sound drastic, but the effects of a data race can (as shown in §41.2.2) be drastic. An optimizer (or a hardware instruction scheduler) may reorder code based on assumptions about values and may execute sections of code (affecting apparently unrelated data) or not based on such assumptions.

There are many ways of avoiding data races:

• Use only a single thread. That eliminates the benefits of concurrency (unless you use processes or co-routines).

• Put a lock on every data item that might conceivably be subject to a data race. That can eliminate the benefits of concurrency almost as effectively as single threading because we easily get into a situation where all but one thread waits. Worse still, heavy use of locks increases the chances of deadlock, where a thread waits for another forever, and other locking problems.

• Try to look carefully at the code and avoid data races by selectively adding locks. This may be the currently most popular approach, but it is error-prone.

• Have a program detect all data races and either report them for the programmer to fix or automatically insert locks. Programs that can do that for programs of commercial size and complexity are not common. Programs that can do that and also guarantee the absence of deadlocks are still research projects.

• Design the code so that threads communicate only through simple put-and-get-style interfaces that do not require two threads to directly manipulate a single memory location (§5.3.5.1, §42.4).

• Use a higher-level library or tool that makes data sharing and/or concurrency implicit or sufficiently stylized to make sharing manageable. Examples include parallel implementations of algorithms in a library, directive-based tools (e.g., OpenMP), and transactional memory (often abbreviated to TM).

One way of looking at the rest of this chapter is as a bottom-up approach to arrive at support for one variant of that last style of programming. In the process, we encounter the tools needed to support just about every way of avoiding data races.

Why must programmers suffer all this complexity? An alternative would be to provide only a simple, sequentially consistent model with minimal (or no) opportunities for data races. I can offer two reasons:

[1] That is not the way the world is. The complexities of machine architectures are real, and a systems programming language, such as C++, must provide the tools for programmers to live with them. Maybe someday machine architects will deliver simpler alternatives, but for now someone must deal with a bewildering variety of low-level facilities provided by machine architects to deliver the performance that their customers demand.

[2] We (the C++ standards committee) seriously considered that. We would have liked to provide a memory model that was an improved version of what Java and C# provide. That would have saved a lot of work for the committee and for some programmers. However, this idea was effectively vetoed by the providers of operating systems and virtual machines: they insisted that they needed roughly what was then provided by the various C++ implementations – what is now provided by the C++ standard. The alternative would be for your operating systems and your virtual machines to slow down “by a factor of two or more.” I guess that programming language fanatics might have welcomed an opportunity to simplify C++ at the expense of other languages, but doing so would have been neither practical nor professional.

Fortunately, most programmers never have to work directly at the lowest level of the hardware. Most programmers do not need to understand a memory model at all and can think of reordering problems as amusing curiosities:

Write data-race-free code and don’t mess with memory order (§41.3); then the memory model guarantees that code executes as naively expected. It’s even better than sequential consistency. I find machine architecture a fascinating topic (e.g., see [Hennesey,2011] [McKenney,2012]), but as sensible and productive programmers, we stay away from the lowest levels of software whenever we can. Leave those for the experts and enjoy the higher levels that those experts provide for you.

41.3. Atomics

Lock-free programming is a set of techniques for writing concurrent programs without using explicit locks. Instead, the programmer relies on primitive operations (directly supported by hardware) to avoid data races (§41.2.4) for small objects (typically a single word or a double word). Primitive operations that do not suffer data races, often called atomic operations, can then be used in the implementation of higher-level concurrency mechanisms, such as locks, threads, and lock-free data structures.

With the notable exception of simple atomic counters, lock-free programming is for specialists. In addition to an understanding of language mechanisms, a detailed understanding of specific machine architectures and a knowledge of somewhat specialized implementation techniques are needed. Do not try lock-free programming with only the information provided here. The primary logical advantage of lock-free techniques over lock-based techniques is that classical locking problems, such as deadlock and starvation, cannot happen. For each atomic operation, it is guaranteed that every thread will eventually (and typically soon) make progress even if other threads compete for access to an atomic object. In addition, lock-free techniques can be significantly faster than lock-based alternatives.

The standard atomic types and operations provide a portable alternative to traditional ways of expressing lock-free code. Those typically either rely on assembly code or system-specific primitives. In this sense, the standard support for atomics is another step in C and C++’s long tradition of increasing portable and relatively comprehensible support for systems programming.

A synchronization operation is something that determines when a thread sees the effects of another thread; it determines what is considered to have happened before something else. Between synchronization operations a compiler and a processor are free to reorder code as long as the semantic rules of the language are maintained. In principle, nobody is looking and all that is affected is performance. A synchronization operation on one or more memory locations is a consume operation, an acquire operation, a release operation, or both an acquire and release operation (§iso.1.10).

• For an acquire operation, other processors will see its effect before any subsequent operation’s effect.

• For a release operation, other processors will see every preceding operation’s effect before the effect of the operation itself.

• A consume operation is a weaker form of an acquire operation. For a consume operation, other processors will see its effect before any subsequent operation’s effect, except that effects that do not depend on the consume operation’s value may happen before the consume operation.

An atomic operation ensures that the state of the memory is as required by the specified memory order (§41.2.2). By default, the memory order is memory_order_seq_cst (sequentially consistent; §41.2.2). The standard memory orders are (§iso.29.3):

enum memory_order {
     memory_order_relaxed,
     memory_order_consume,
     memory_order_acquire,
     memory_order_release,
     memory_order_acq_rel,
     memory_order_seq_cst
};

The enumerations represent:

• memory_order_relaxed: No operation orders memory.

• memory_order_release, memory_order_acq_rel, and memory_order_seq_cst: A store operation performs a release operation on the affected memory location.

• memory_order_consume: A load operation performs a consume operation on the affected memory location

• memory_order_acquire, memory_order_acq_rel, and memory_order_seq_cst: a load operation performs an acquire operation on the affected memory location.

As an example, consider (§iso.29.3) using atomic loads and stores (§41.3.1) to express a relaxed memory order:

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// thread 1:
      r1 = y.load(memory_order_relaxed);
      x.store(r1,memory_order_relaxed);

// thread 2:
      r2 = x.load(memory_order_relaxed);
      y.store(42,memory_order_relaxed);

This is allowed to produce r2==42, making it appear that time went backward in thread 2. That is, memory_order_relaxed allows this execution order:

y.store(42,memory_order_relaxed);
r1 = y.load(memory_order_relaxed);
x.store(r1,memory_order_relaxed);
r2 = x.load(memory_order_relaxed);

For explanations, see the specialist literature, for example, [Boehm,2008] and [Williams,2012].

It is entirely architecture-specific whether a given memory order makes sense. Clearly, a relaxed memory model is not something to be directly used in applications programming. Utilizing a relaxed memory model is an even more specialized task than general lock-free programming. I see it as something done by a small subset of operating system kernel, device driver, and virtual machine implementers. It can also be useful in machine-generated code (as gotos can be). If two threads really do not directly share data, some machine architectures deliver significant performance improvements through the use of a relaxed memory model at the cost of complexity in the implementation of message-passing primitives (e.g., future and promise; §42.4.4).

To allow significant optimizations for architectures with relaxed memory models, the standard provides an attribute [[carries_dependency]] for transmitting memory order dependencies across function calls (§iso.7.6.4). For example:

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[[carries_dependency]] struct foo* f(int i)
{
      // let the caller use memory_order_consume for the result:
      return foo_head[i].load(memory_order_consume);
}

You can also put [[carries__dependency]] on function arguments, and there is a function kill_dependency() for stopping the propagation of such dependencies.

One of the designers of the C++ memory model, Lawrence Crowl, summarizes:

“Dependency ordering is probably the most complex concurrency feature. It’s really worth using when

• you have a machine for which it matters,

• you have a very high bandwidth read-mostly atomic data structure, and

• you’re willing to spend a couple of weeks in testing and external reviews.

This is real expert territory.”

Consider yourself warned.

41.3.1. atomic Types

An atomic type is a specialization of the atomic template. An operation on an object of an atomic type is atomic. That is, it is performed by a single thread without interference from other threads.

The operations on atomics are very simple: loads and stores, swapping, incrementing, etc., on a simple object (usually a single memory location; §41.2.1). They have to be simple or the hardware can’t handle them directly.

The following tables aim to give a first impression and an overview (only). Unless explicitly stated, the memory order is memory_order_seq_cst (sequentially consistent).

There are no copy or move operations for atomics. The assignment operator and constructor take values of the contained type T and access the contained value.

A default atomic (without an explicit {}) is uninitialized to allow the C standard library to be compatible.

The is_lock_free() operation is there so that you can test if these operations are lock free or if they have been implemented using a lock. On all major implementations, is_lock_free() returns true for integral and pointer types.

The atomic facilities are designed for types that map to a simple built-in type. Expect atomic<T> to be implemented using locks if T objects are large. The template argument type T must be trivially copyable (must not have user-defined copy operations).

The initialization of an atomic variable is not an atomic operation, so an initialization may have a data race with an access from another thread (§iso.29.6.5). However, a data race with an initialization is quite hard to achieve. As ever, keep initialization of nonlocal objects simple and prefer to initialize with constant expressions (you can’t have a data race before the program starts).

A simple atomic variable is close to ideal for a shared counter, such as a use count for a shared data structure. For example:

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template<typename T>
class shared_ptr {
public:
     // ...
     ~shared_ptr()
     {
        if (––**puc) delete p;
     }
private:
      T* p;               // pointer to shared object
      atomic<int>*puc;    // pointer to use count
};

Here, *puc is an atomic (allocated somewhere by a shared_ptr constructor), so that the decrement operation (––) is atomic and the new value is correctly reported in the thread destroying a shared_ptr.

The first argument of a compare-and-exchange operation (rt in the table) is a reference so that the object referred to can be updated if the operation fails to update its target (x in the table).

The difference between compare_exchange_strong() and compare_exchange_weak() is that the weak version can fail for “spurious reasons.” That is, some peculiarity of the hardware or the implementation of x.compare_exchange_weak(rt,t) may cause a failure even if x.val==rt. Allowing such failures makes compare_exchange_weak() implementable on architectures where compare_exchange_strong() would be difficult or relatively expensive.

The classic compare-and-swap loop can be written like this:

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atomic<int> val = 0;
// ...
int expected = val.load();         // read current value
do {
      int next = fct(expected);    // calculate new value
} while (!val.compare_exchange_weak(expected,next)); // write next to val or to expected

The atomic val.compare_exchange_weak(expected,next) reads the current value of val and compares it to expected; if equal, it writes next to val. If some other thread has written to val since we read it in preparation to an update, we have to try again. When we try again, we use the new value of expected obtained from compare_exchange_weak(). Eventually, the expected value will be written. The value of expected is “the current value of val as seen by this thread.” So, since expected is updated to the current value each time the compare_exchange_weak() is executed, we should never get an infinite loop.

Operations like compare_exchange_strong() are widely known as compare-and-swap operations (CAS operations). There is a potentially serious problem with all CAS operations (in any language and on any machine) known as the ABA problem. Consider adding a node at the head of a very simple lock-free singly-linked list if the data value is less than the head’s data:

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extern atomic<Link*> head;               // the shared head of a linked list

Link* nh = new Link(data,nullptr);       // make a link ready for insertion
Link* h = head.load();                   // read the shared head of the list
do {
     if (h–>data<data) break;            // if so, insert elsewhere
     nh–>next = h;                       // next element is the previous head
} while (!head.compare_exchange_weak(h,nh));   // write nh to head or to h

This is a simplified version of code that would insert data at the right position in an ordered linked list. I read the head, use it as the next of my new Link, and then write the pointer to my new Link to head. I do that repeatedly until no other thread has managed to change the head while I was getting nh ready.

Let us examine this code in some detail. Call the value of head that I read A. If no other thread changed the value of head before I executed my compare_exchange_weak(), it finds A in head and succeeds in replacing it with my nh. If some other thread changed the value of head to B after I read A, my compare_exchange_weak() will fail, and I’ll go around my loop to read head again.

This looks right. What could possibly go wrong? Well, after I read the value A, some other thread changed the value of head to B and recycled the Link. Then, some thread reused the node A and reinserted it at the head of the list. Now my compare_exchange_weak() finds A and does the update. However, the list had changed; the value of head went from A to B and then back to A. That change may be significant in many different ways, but in this simplified example, A–>data may have changed so that the critical data comparison may be wrong. ABA problems can be very subtle and hard to detect. There are a variety of ways of dealing with the ABA problem [Dechev,2010]. I mention it here primarily to warn about the subtleties of lock-free programming.

Integral atomic types offer atomic arithmetic and bit operations:

Consider the popular double-checked locking idiom. The basic idea is that if initializing some x must be done under a lock, you may not want to incur the cost of acquiring that lock every time you access x to see if the initialization has been done. Instead, you lock and initialize only if a variable x_init is false:

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X x;                             // we need a lock to initialize an X
mutex lx;                        // the mutex to be used to lock x during initialization
atomic<bool> x_init {false};     // an atomic used to minimize locking

void some_code()
{
    if (!x_init) {            // proceed if x is uninitialized
          lx.lock();
          if (!x_init) {      // proceed if x is still uninitialized
               // ... initialize x ...
               x_init = true;
         }
         lx.unlock();
   }
   // ... use x ...
}

Had init_x not been atomic, instruction reordering could have moved the initialization of x ahead of the apparently unrelated test of init_x (see §41.2.2). Making init_x atomic prevents that.

The !x_init relies on the implicit conversion from an atomic<T> to a T.

This code can be simplified further by using RAII (§42.3.1.4).

The double-checked locking idiom is represented in the standard library by once_flag and call_once() (§42.3.3), so you don’t have to write such code directly.

The standard library also supports atomic pointers:

To allow the C standard library to be compatible, the atomic member function types have freestanding equivalents:

41.3.2. Flags and Fences

In addition to the support for atomic types, the standard library offers two lower-level synchronization facilities: atomic flags and fences. The primary use of these is to implement the lowest-level atomic facilities, such as spinlocks and the atomic types. They are the only lock-free mechanisms that are guaranteed to be supported on every implementation (though all major platforms support atomic types).

Essentially no programmers need to use flags or fences. Those who do usually work closely with machine architects.

41.3.2.1. atomic Flags

An atomic_flag is the simplest atomic type and the only one with operations guaranteed to be atomic for every implementation. An atomic_flag represents a single bit of information. If necessary, the other atomic types can be implemented using atomic_flag.

The two possible values of an atomic_flag are called set and clear.

The bool return values are true for set and false for clear.

Using {} to initialize atomic_flag seems to make sense. However, there is no guarantee that 0 represents clear. A machine where clear is 1 is rumored to exist. Clearing using ATOMIC_FLAG_INIT is the only portable and reliable way of initializing an atomic_flag. The ATOMIC_FLAG_INIT is an implementation-supplied macro.

You can think of an atomic_flag as a very simple spin lock:

Click here to view code image

class spin_mutex {
      atomic_flag flag = ATOMIC_FLAG_INIT;
public:
      void lock() { while(flag.test_and_set()); }
      void unlock() { flag.clear(); }
};

Note that spin locks can easily become very expensive.

As usual, I leave the memory orders and their proper use to the specialist literature.

41.3.2.2. Fences

A fence, also known as a memory barrier, is an operation that restricts operation reordering according to some specified memory ordering (§41.2.3). The fence operations do not do anything else. Think of them as simply slowing down a program to a safe speed, allowing the memory hierarchy to reach a reasonably well-defined state.

Fences are used in combination with atomics (needed to observe the effects of the fences).

41.4. volatile

The volatile specifier is used to indicate that an object can be modified by something external to the thread of control. For example:

volatile const long clock_register; // updated by the hardware clock

A volatile specifier basically tells the compiler not to optimize away apparently redundant reads and writes. For example:

auto t1 {clock_register};
// ... no use of clock_register here ...
auto t2 {clock_register};

Had clock_register not been volatile, the compiler would have been perfectly entitled to eliminate one of the reads and assume t1==t2.

Do not use volatile except in low-level code that deals directly with hardware.

Do not assume that volatile has special meaning in the memory model. It does not. It is not – as in some later languages – a synchronization mechanism. To get synchronization, use an atomic (§41.3), a mutex (§42.3.1), or a condition_variable (§42.3.4).

41.5. Advice

[1] Use concurrency to improve responsiveness or to improve throughput; §41.1.

[2] Work at the highest level of abstraction that you can afford; §41.1.

[3] Prefer packaged_task and futures over direct use of threads and mutexes; §41.1.

[4] Prefer mutexes and condition_variables over direct use of atomics except for simple counters; §41.1.

[5] Avoid explicitly shared data whenever you can; §41.1.

[6] Consider processes as an alternative to threads; §41.1.

[7] The standard-library concurrency facilities are type safe; §41.1.

[8] The memory model exists to save most programmers from having to think about the machine architecture level of computers; §41.2.

[9] The memory model makes memory appear roughly as naively expected; §41.2.

[10] Separate threads accessing separate bit-fields of a struct may interfere with each other; §41.2.

[11] Avoid data races; §41.2.4.

[12] Atomics allow for lock-free programming; §41.3.

[13] Lock-free programming can be essential for avoiding deadlock and to ensure that every thread makes progress; §41.3.

[14] Leave lock-free programming to experts; §41.3.

[15] Leave relaxed memory models to experts; §41.3.

[16] A volatile tells the compiler that the value of an object can be changed by something that is not part of the program; §41.4.

[17] A C++ volatile is not a synchronization mechanism; §41.4.

42. Threads and Tasks

Keep Calm and Carry On.

– English slogan

• Introduction

• Threads

Identity; Construction; Destruction; join(); detach(); Namespace this_thread; Killing a thread; thread_local Data

• Avoiding Data Races

Mutexes; Multiple Locks; call_once(); Condition Variables

• Task-Based Concurrency

future and promise; promise; packaged_task; future; shared_future; async(); A Parallel find() Example

• Advice

42.1. Introduction

Concurrency – the execution of several tasks simultaneously – is widely used to improve throughput (by using several processors for a single computation) or to improve responsiveness (by allowing one part of a program to progress while another is waiting for a response).

The C++ standard support for concurrency is introduced in a tutorial manner in §5.3. This chapter and the previous one provide a more detailed and systematic view.

We call an activity potentially executed concurrently with other activities a task. A thread is the system-level representation of a computer’s facilities for executing a task. A thread can execute a task. A thread may share an address space with other threads. That is, all threads in a single address space can access the same memory locations. One of the central challenges of the programmer of a concurrent system is to make sure that threads access memory in a sensible manner.

42.2. Threads

A thread is an abstraction of the computer hardware’s notion of a computation. The C++ standard-library threads are intended to map one-to-one with the operating system’s threads. We use threads when several tasks in a program need to progress concurrently. On a system with several processing units (“cores”), threads allows us to use those units. All threads work in the same address space. If you want hardware protection against data races, use some notion of a process. Stacks are not shared between threads, so local variables are not subject to data races, that is, unless you incautiously pass a pointer to a local variable to another thread. In particular, beware of by-reference context bindings in lambdas (§11.4.3). Deliberate and careful sharing of stack memory is useful and common, for example, we might pass sections of a local array to a parallel sort.

If a thread cannot proceed (e.g., because it has encountered a mutex owned by another thread), it is said to be blocked or asleep.

A thread represents a system resource, a system thread, possibly even with dedicated hardware:

Consequently, a thread can be moved but not copied.

After being the source of a move, a thread no longer represents a thread of computation. In particular, it cannot be join()ed.

The thread::hardware_concurrency() operation reports the number of tasks that can simultaneously proceed with hardware support. The exact meaning of that is architecture-dependent, but it is usually less than the number of threads offered by the operating system (e.g., through time multiplexing or time slicing) and sometimes higher than the number of processors or “cores.” For example, my little two-core laptop reports four hardware threads (it is using what is sometimes called hyper-threading).

42.2.1. Identity

Each thread of execution has a unique identifier represented as a value of type thread::id. If a thread does not represent a thread of execution, its id is the default id{}. The id of a thread t can be obtained by a call of t.get_id().

The id of the current thread can be obtained by this_thread::get_id() (§42.2.6).

A thread can have its id be id{} if

• it has not had a task assigned,

• it has terminated,

• it has been moved from, or

• it has been detach()ed.

Every thread has an id, but a system thread may still be running even though it does not have an id (i.e., after a detach()).

A thread::id can be copied, and ids can be compared with the usual comparison operators (==, <, etc.), output using <<, and hashed with a specialization hash<thread::id> (§31.4.3.4). For example:

Click here to view code image

void print_id(thread& t)
{
     if (t.get_id()==id{})
            cout << "t not joinable\n";
     else
            cout << "t's id is " << t.get_id() << '\n';
}

Note that cout is a global shared object so that those output statements are not guaranteed to produce output characters in a recognizable sequence unless you make sure that no two threads are writing to cout at the same time (§iso.27.4.1).

42.2.2. Construction

A thread constructor takes a task to be executed and the arguments required by that task. The number and types of arguments must match what the task requires. For example:

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void f0();      // no arguments
void f1(int);   // one int argument

thread t1 {f0};
thread t2 {f0,1};                  // error: too many arguments
thread t3 {f1};                    // error: too few arguments
thread t4 {f1,1};
thread t5 {f1,1,2};                // error: too many arguments
thread t3 {f1,"I'm being silly"};  // error: wrong type of argument

After construction, a thread starts executing its task as soon as the run-time system can acquire resources for it to run. Think of that as “immediately.” There is no separate “start the thread” operation.

If you want to build a set of tasks and link them together (e.g., to communicate through message queues), you first build the tasks as function objects and then – when they are all ready to run – start threads. For example:

Click here to view code image

template<typename T>
class Sync_queue<T> {      // a queue providing put() and get() without data races (§42.3.4)
      // ...
};

struct Consumer {
      Sync_queue<Message>& head;
      Consumer(Sync_queue<Message>& q) :head(q) {}
      void operator()();   // get messages from head
};

struct Producer {
      Sync_queue<Message>& tail;
      Consumer(Sync_queue<Message>& q) :tail(q) {}
      void operator()();   // put messages on tail
};

Sync_queue<Message> mq;
Consumer c {mq};               // make tasks and "wire them together"
Producer p {mq};

thread pro {p};                // finally: start threads
thread con {c};

// ...

Trying to intersperse thread creation with the setup of connections among the tasks to be run by the threads can easily become complicated and error-prone.

The thread constructors are variadic templates (§28.6). This implies that to pass a reference to a thread constructor, we must use a reference wrapper (§33.5.1). For example:

Click here to view code image

void my_task(vector<double>& arg);

void test(vector<double>& v)
{
    thread my_thread1 {my_task,v};            // oops: pass a copy of v
    thread my_thread2 {my_task,ref(v)};       // OK: pass v by reference
    thread my_thread3 {[&v]{ my_task(v); }};  // OK: dodge the ref() problem
    // ...
}

The problem is that the variadic template uses bind() or some equivalent mechanism, so that a reference is by default dereferenced and the result copied. So, if v was {1,2,3} and my_task increments elements, thread1 would never have any effect on v. Note that all three threads have a data race on v; this is an example of calling conventions, not of good concurrent programming style.

A default-constructed thread is primarily useful as the target for a move. For example:

Click here to view code image

vector<thread> worker(1000);   // 1000 default threads

for (int i=0; i!=worker.size(); ++i) {
      // ... compute argument for worker[i] and create worker thread tmp ...
      worker[i] = move(tmp);
}

Moving a task from one thread to another does not affect its execution. A thread move simply changes what the threads refer to.

42.2.3. Destruction

Obviously, the thread destructor destroys the thread object. To prevent a system thread from accidentally outliving its thread, the thread destructor calls terminate() to terminate the program if the thread is joinable() (that is, if get_id()!=id{}). For example:

Click here to view code image

void heartbeat()
{
     while(true){
          output(steady_clock::now());
          this_thread::sleep_for(second{1}); // §42.2.6
     }
}

void run()
{
     thread t {heartbeat};
}    // terminate because heartbeat() is still running at the end of t's scope

If you really need to have a system thread proceed beyond the lifetime of its thread see §42.2.5.

42.2.4. join()

A t.join() tells the current thread not to proceed until t completes. For example:

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void tick(int n)
{
     for (int i=0; i!=n; ++i) {
           this_thread::sleep_for(second{1}); // §42.2.6
           output("Alive!");
     }
}

int main()
{
     thread timer {tick,10};
     timer.join();
}

This will output Alive! ten times at about 1-second intervals. Had the timer.join() been missing, the program would have terminated before tick() could have printed anything. The join() made the main program wait for the timer to complete.

As mentioned in §42.2.3, trying to have a thread execute past the end of its scope (or more generally, after its destructor is run) without calling detach() is considered a fatal (for the program) error. However, we can forget to join() a thread. When we view a thread as a resource, we see that we should consider RAII (§5.2, §13.3). Consider a simple test example:

Click here to view code image

void run(int i, int n) // warning: really poor code
{
     thread t1 {f};
     thread t2;
     vector<Foo> v;
     // ...
     if (i<n) {
           thread t3 {g};
           // ...
           t2 = move(t3); // move t3 to outer scope
      }
      v[i] = Foo{};    // might throw
      // ...
      t1.join();
      t2.join();
}

Here, I have made several bad mistakes. In particular:

• We may never reach the two join()s at the end. In that case, the destructor for t1 will terminate the program.

• We may reach the two join()s at the end without the move t2=move(t3) having executed. In that case, t2.join() will terminate the program.

For this kind of thread use, we need a destructor that implicitly join()s. For example:

Click here to view code image

struct guarded_thread : thread {
    using thread::thread;                            // §20.3.5.1
    ~guarded_thread() { if (t.joinable()) t.join(); }
};

Unfortunately, guarded_thread is not a standard-library class, but in the best RAII tradition guarded_thread makes our code shorter and less error-prone. For example:

Click here to view code image

void run2(int i, int n) // simple use of a guard
{
     guarded_thread t1 {f};
     guarded_thread t2;
     vector<Foo> v;
     // ...
     if (i<n) {
           thread t3 {g};
           // ...
           t2 = move(t3); // move t3 to outer scope
     }
     v[i] = Foo{};  // might throw
     // ...
}

But why doesn’t the thread’s destructor just join()? There is a long-standing tradition of using system threads that “live forever” or decide for themselves when to terminate. Had it worked, the timer executing tick() (§42.2.2) would have been an example of such a thread. Threads monitoring data structures provide many more examples. Such threads (and processes) are often called daemons. Another use for detached threads is to simply initiate a thread to complete a task and forget about it. Doing so leaves the “housekeeping” to the run-time system.

42.2.5. detach()

Accidentally letting a thread try to execute beyond its destructor is considered a very bad error. If you really want a system thread to outlive its thread (handle), use detach(). For example:

Click here to view code image

void run2()
{
     thread t {heartbeat};
     t.detach();         // let heartbeat run independently
}

I have a philosophical problem with detached threads. Given a choice, I would prefer to

• know exactly which threads are running,

• be able to determine if threads are making progress as expected,

• be able to check if threads that are supposed to delete themselves really do so,

• be able to know whether it is safe to use the results of a thread,

• be sure that all resources associated with a thread are properly released, and

• be sure that a thread does not try to access objects from the scope in which it was created after that scope has been destroyed.

Unless I go beyond the standard library (e.g., using get_native_handle() and “native” system facilities), I cannot do so for detached threads. Also, how do I debug a system where the behavior of detached threads cannot be directly observed? What happens if a detached thread holds a pointer to something in the scope in which it was created? That could lead to corrupted data, a system crash, or a security violation. Yes, obviously detached threads can be useful and debugged. After all, people have been doing it for decades. But people have been doing self-destructive things for centuries and deemed them useful. Given a choice, I prefer not to detach() threads.

Note that thread provides a move assignment and a move constructor. This allows threads to migrate out of the scope in which they were constructed and often provides an alternative to detach(). We can migrate threads to a “main module” of a program, access them through unique_ptrs or shared_ptrs, or place them in a container (e.g., vector<thread>) to avoid losing track of them. For example:

Click here to view code image

vector<thread> my_threads;    // keep otherwise detached threads here

void run()
{
     thread t {heartbeat};
     my_threads.push_back(move(t));
     // ...
     my_threads.emplace_back(tick,1000);
}

void monitor()
{
    for (thread& t : my_threads)
          cout << "thread " << t.get_id() << '\n';
}

For a more realistic example, I would associate some information with each thread in my_threads. Maybe I’d even launch monitor as a task.

If you must use a detach() a thread, do make sure that it does not refer to variables in its scope. For example:

Click here to view code image

void home()    // don't do this
{
     int var;
     thread disaster{[&]{ this_thread::sleep_for(second{7.3});++var; }}
     disaster.detach();
}

Apart from the warning comment and the evocative name, this code looks quite innocent. It is not: the system thread invoked by disaster() will “forever” keep writing to the address where home()’s var was allocated, corrupting any data that may later be allocated there. This kind of error is extremely hard to find because it is only loosely connected to the code in which it manifests itself, and repeated runs of the program will have different results – many runs may exhibit no symptoms. Such bugs have been called Heisenbugs in honor of the discoverer of the uncertainty principle.

Note that the root problem in that example is a violation of the simple and well known rule “Don’t pass a pointer to a local object out of its scope” (§12.1.4). However, with a lambda, it is easy (and almost invisible) to create a pointer to a local variable: [&]. Fortunately, we have to say detach() to allow a thread to exit its scope; don’t do that without a very good reason, and then only after carefully considering what its task might do.

42.2.6. Namespace this_thread

Operations for the current thread are found in namespace this_thread:

To get the identity of the current thread, call this_thread::get_id(). For example:

void helper(thread& t)
{
     thread::id me {this_thread::get_id()};
     // ...
     if (t.get_id()!=me) t.join();
     // ...
}

Similarly, we can use this_thread::sleep_until(tp) and this_thread::sleep_for(d) to put the current thread to sleep.

The this_thread::yield() is used to give another thread a chance to proceed. The current thread is not blocked, so it will eventually be run again without any other thread having to do anything specific to wake it. Thus, yield() is primarily useful for waiting for an atomic to change state and for cooperative multi-threading. Usually, it is better to use sleep_for(n) than to just yield(). The argument to sleep_for() gives the scheduler a better chance to make rational choices about which threads to run when. Consider yield() a feature for optimization in very rare and specialized cases.

On all major implementations threads are preemptable; that is, the implementation can switch from one task to another to ensure that all threads progress at a reasonable rate. However, for historical and language technical reasons, preemption is only encouraged rather than required by the standard (§iso.1.10).

Usually, programmers should not mess with system clocks. But if a clock is reset (say, because it has drifted from the true time), a wait_until() would be affected, but not a wait_for(). The same applies to wait_until() and wait_for() for a timed_mutex (§42.3.1.3).

42.2.7. Killing a thread

I find one important operation missing from thread. There is no simple standard way of telling a running thread that I have lost interest in its task, so would it please stop running and release all its resources. For example, if I start a parallel find() (§42.4.7), I would often like to ask remaining tasks to stop once I have an answer. There are various historical and technical reasons for the lack of this operation (called kill, cancel, and interrupt in various languages and systems).

If needed, application programmers can write their own versions of this idea. For example, many tasks involve a request loop. In that case, a “kindly commit suicide” message would allow the receiving thread to release all resources and then terminate. If there is no request loop, a task could periodically examine a “needed” variable to see if results are still wanted.

So, a general cancel operation may be difficult to design and to implement on all systems, but I have never seen an application where a specific cancellation mechanism wasn’t relatively easy to implement.

42.2.8. thread_local Data

As indicated by its name, a thread_local variable is an object owned by a thread and not accessible from other threads unless its owner (incautiously) gives them a pointer to it. In that, a thread_local resembles a local variable, but a local variable has its lifetime and access limited by its scope within a function, whereas a thread_local is shared among all functions of a thread and “lives” for as long as the thread. A thread_local object can be extern.

For most uses, having objects local (on the stack) is preferable to having them shared; thread_local storage shares the logical problems of global variables. As usual, namespaces can be used to limit the problems with nonlocal data. However, on many systems, the amount of stack storage for a thread is rather limited, so thread_local storage becomes important for tasks that require large amounts of nonshared data.

A thread_local is said to have thread storage duration (§iso.3.7.2). Each thread has its own copy of its thread_local variables. A thread_local is initialized before its first use (§iso.3.2). If constructed, it will be destroyed on thread exit.

An important use of thread_local storage is for a thread to explicitly keep a cache of data for exclusive access. That can complicate the program logic, but on machines with shared caches it can sometimes deliver very significant performance advantages. Also, it can simplify and/or lower the cost of locking by transferring data only in larger batches.

In general, nonlocal memory is a problem for concurrent programming because it is often nontrivial to determine if it is shared and thus a possible source of data races. In particular, static class members can be a major problem because they are often hidden from the users of a class, so that potential data races are easily missed. Consider a Map design with a per-type default value:

Click here to view code image

template<typename K, typename V>
class Map {
public:
      Map();
      // ...
      static void set_default(const K&,V&);           // set default for all Maps of type Map<K,V>
private:
      static pair<const K,V> default_value;
};

Why would a user suspect a data race on two different Map objects? Obviously, a user who spotted set_default() among the members might suspect, but set_default() is an easily overlooked minor feature (§16.2.12).

One-per-class (static) values used to be popular. They include default values, use counters, caches, free lists, answers to frequently asked questions, and many obscure uses. When used in a concurrent system, we have a classic problem:

Click here to view code image

// somewhere in thread 1:
      Map<string,int>::set_default("Heraclides",1);

// somewhere in thread 2:
      Map<string,int>::set_default("Zeno",1);

This is a potential data race: which thread gets to first execute set_default()?

Adding thread_local helps:

Click here to view code image

template<typename K, typename V>
class Map {
     // ...
private:
     static thread_local pair<const K,V> default_value;
};

Now, there is no longer a potential data race. However, there is no longer a single default_value shared among all users either. In the example, thread 1 will never see the effect of a set_default() in thread 2. As often as not, that was not what was intended in the original code, so by adding thread_local, we simply exchanged one error for another. Consider static data members suspect (always, because you don’t know if your code might someday be executed as part of a concurrent system), and do not consider thread_local a panacea.

A namespace variable, a local static, and a class static member can be declared thread_local. As for local static variables, the construction of a thread_local local variable is protected by a first-time switch (§42.3.3). The order of construction of thread_locals is undefined, so keep the construction of different thread_locals independent of their order and use compile-time or link-time initialization whenever possible. Like static variables, thread_locals are by default initialized to zero (§6.3.5.1).

42.3. Avoiding Data Races

The best way to avoid data races is not to share data. Keep interesting data in local variables, in free store not shared with other threads, or in thread_local memory (§42.2.8). Do not pass pointers to such data to other threads. When such data needs to be processed by another thread (e.g., by a parallel sort), pass pointers to a specific section of the data and make sure not to touch that section of the data passed until after the termination of the task.

These simple rules are based on the idea of avoiding attempts to simultaneously access data, so they don’t require locking and lead to maximally efficient programs. Where they cannot be used, for example, because lots of data needs to be shared, use some form of locking:

• Mutexes: A mutex (a mutual exclusion variable) is an object used to represent the exclusive right to access some resource. To access the resource, acquire the mutex, access, and then release the mutex (§5.3.4, §42.3.1).

• Condition variables: A condition variable is a variable used by a thread to wait for an event generated by another thread or a timer (§5.3.4.1, §42.3.4).

Strictly speaking, condition variables do not prevent data races. Rather, they save us from having to introduce shared data that might become a source of data races.

42.3.1. Mutexes

A mutex is an object used to represent exclusive access to some resource. Thus, it can be used to protect against data races and to synchronize access to data shared between multiple threads.

The “plain” mutex is the simplest, smallest, and fastest mutex. In exchange for added functionality, recursive and timed mutexes carry a small cost, which may or may not be significant for a given application on a given machine.

Only one thread can own a mutex at any one time:

• To acquire a mutex means to gain exclusive ownership of it; an acquire operation may block the thread executing it.

• To release a mutex means relinquishing exclusive ownership; a release operation will allow another thread to eventually acquire the mutex. That is, a release operation will unblock waiting threads.

If several threads are blocked on a mutex the system scheduler could in principle select the thread to be unblocked in such a way that some unfortunate thread would never get to run. This is called starvation, and a scheduling algorithm that avoids starvation by giving each thread an equal chance to make progress is said to be fair. For example, a scheduler might always choose the thread with the highest thread::id to run next, thereby starving a thread with a low id. The standard does not guarantee fairness, but in reality schedulers are “reasonably fair.” That is, they make it extremely unlikely that a thread starves forever. For example, a scheduler may pick the next thread to run randomly among those blocked.

By itself, a mutex doesn’t do anything. Instead, we use a mutex to represent something else. We use ownership of a mutex to represent the right to manipulate a resource, such as an object, some data, or an I/O device. For example, we could define a cout_mutex to represent the right to use cout from a thread:

Click here to view code image

mutex cout_mutex; // represent the right to use cout

template<typename Arg1, typename Arg2, typename Arg3>
void write(Arg1 a1, Arg2 a2 = {}, Arg3 a3 = {})
{
     thread::id name = this_thread::get_id();
     cout_mutex.lock();
     cout << "From thread " << name << " : " << a1 << a2 << a3;
     cout_mutex.unlock();
}

If all threads use write() we should get output from different threads properly separated. The snag is that every thread has to use a mutex as intended. The correspondence between a mutex and its resource is implicit. In the cout_mutex example, a thread using cout directly (bypassing cout_mutex) can corrupt output. The standard guarantees that the cout variable is protected against corruption, but there is no protection against output from different threads becoming intermixed.

Note that I locked the mutex only for the one statement that required the lock. To minimize contention and the chances of a thread becoming blocked, we try to minimize the time a lock is held by locking only where it is essential to do so. A section of code protected by a lock is called a critical section. To keep code fast and free of problems related to locking, we minimize the size of critical sections.

The standard-library mutexes provide exclusive ownership semantics. That is, a single thread (at a time) has exclusive access to the resource. There are other kinds of mutexes. For example, multiple-reader-single-writer mutexes are popular, but the standard library does not (yet) offer one. If you need a different kind of mutex, use one offered by a specific system or write it yourself.

42.3.1.1. mutex and recursive_mutex

Class mutex offers a simple set of operations:

A mutex cannot be copied or moved. Think of a mutex as a resource, rather than a handle of a resource. In fact, a mutex is typically implemented as a handle to a system resource, but since that system resource cannot be shared, leaked, copied, or moved, it is usually a spurious complication to think of them as separate.

The basic uses of a mutex are very simple. For example:

Click here to view code image

mutex cout_mutex; // initialized to "not owned by any thread"

void hello()
{
     cout_mutex.lock();
     cout << "Hello, ";
     cout_mutex.unlock();
}
void world()
{
     cout_mutex.lock();
     cout << "World!";
     cout_mutex.unlock();
}

int main()
{
     thread t1 {hello};
     thread t2 {world};

     t1.join();
     t2.join();
}

Given that, we will get the output

Hello, World!

or

World! Hello,

We will not get cout corrupted or some mixed-up output characters.

The try_lock() operation is used when we have some other work we might usefully do if some other thread is using a resource. As an example, consider a work generator that composes work requests for other tasks and places them on a work queue:

Click here to view code image

extern mutex wqm;
extern list<Work> wq;

void composer()
{
     list<Work> requests;

     while (true) {
          for (int i=0; i!=10; ++i) {
                Work w;
                // ... compose work request ...
                requests.push_back(w);
          }
          if (wqm.try_lock()) {
               wq.splice(requests); // splice() requests into the list (§31.4.2)
               wqm.unlock();
          }
     }
}

When some server thread is examining wq, the composer() simply makes some more work instead of waiting.

When using locks, we have to beware of deadlock. That is, we must not wait for a lock that can never be released. The simplest form of deadlock requires only one lock and one thread. Consider a variant of the thread-safe output operation:

template<typename Arg, typename... Args>
void write(Arg a, Args tail...)
{
     cout_mutex.lock();
     cout << a;
     write(tail...);
     cout_mutex.unlock();
}

Now, if a thread calls write("Hello,","World!"), it will deadlock with itself when it tries the recursive call for the tail.

Recursive and mutually recursive calls are common enough for the standard to provide a solution. A recursive_mutex is just like a plain mutex, except that a single thread can acquire it repeatedly. For example:

Click here to view code image

recursive_mutex cout_mutex;    // changed to recursive_mutex to avoid deadlock

template<typename Arg, typename... Args>
void write(Arg a, Args tail...)
{
     cout_mutex.lock();
     cout << a;
     write(tail...);
     cout_mutex.unlock();
}

Now the recursive call of write() is correctly handled by cout_mutex.

42.3.1.2. mutex Errors

Trying to manipulate a mutex can fail. If so, the mutex operation throws a system_error. Some of the possible errors reflect conditions in the underlying system:

For example:

Click here to view code image

mutex mtx;
try {
    mtx.lock();
    mtx.lock();    // try to lock a second time
}
catch (system_error& e) {
    mtx.unlock();
    cout << e.what() << '\n';
    cout << e.code() << '\n';
}

I got the output

device or resource busy
generic: 16

This looks like a good argument for using a lock_guard or a unique_lock (§42.3.1.4).

42.3.1.3. timed_mutex and recursive_timed_mutex

A simple mtx.lock() is unconditional. If we don’t want to block, we can use mtx.try_lock(), but when we fail to acquire mtx, we often want to wait for a while before trying again. The timed_mutex and recursive_timed_mutex offer support for that:

The recursive_timed_mutex interface is identical to the timed_mutex interface (just as the recur-sive_mutex interface is identical to the mutex interface).

For this_thread, we can sleep_until(tp) a time_point and sleep_for(d) a duration (§42.2.6). More generally, we can m.try_lock_until(tp) or m.try_lock_for(d) for a timed_mutex m. If tp is before the current point in time or d is less than or equal to zero, the operation is equivalent to a “plain” try_lock().

As an example, consider updating an output buffer with a new image (e.g., in a video game or a visualization):

Click here to view code image

extern timed_mutex imtx;
extern Image buf;

void next()
{
    while (true) {
        Image next_image;
        // ... compute ...

        if (imtx.try_lock(milliseconds{100})) {
              buf = next_image;
              imtx.unlock();
        }
    }
}

The assumption here is that if the image cannot be updated reasonably fast (here, in 100 milliseconds), the user would prefer a newer version of the image. Further, it is assumed that missing an image in a sequence of updated images will rarely be noticed, so that a more complicated solution is not needed.

42.3.1.4. lock_guard and unique_lock

A lock is a resource, so we must not forget to release it. That is, each m.lock() operation must be matched by an m.unlock() operation. The usual opportunities for mistakes exist; for example:

Click here to view code image

void use(mutex& mtx, Vector<string>& vs, int i)
{
     mtx.lock();
     if (i<0) return;
     string s = vs[i];
     // ...
     mtx.unlock();
}

The mtx.unlock() is there, but if i<0 or if i is out of vs’s range and vs is range checked, the thread of execution never gets to the mtx.unlock() and mtx may be locked forever.

The standard library provides two RAII classes, lock_guard and unique_lock, to handle such problems.

The “plain” lock_guard is the simplest, smallest, and fastest guard. In exchange for added functionality, unique_ptr carries a small cost, which may or may not be significant for a given application on a given machine.

For example:

Click here to view code image

void use(mutex& mtx, vector<string>& vs, int i)
{
     lock_guard<mutex> g {mtx};
     if (i<0) return;
     string s = vs[i];
     // ...
}

The lock_guard’s destructor does the necessary unlock() on its argument.

As usual, we should only hold a lock for the minimal amount of time, so a lock_guard should not become an excuse for holding a lock until the end of a large scope if we only need the lock for a small section of the scope. Obviously, the checking of i does not require locking, so we could do that before acquiring the lock:

Click here to view code image

void use(mutex& mtx, vector<string>& vs, int i)
{
     if (i<0) return;
     lock_guard<mutex> g {mtx};
     string s = vs[i];
     // ...
}

Furthermore, imagine that we only needed the lock for the read of v[i]. Then, we could put the lock_guard in a small scope:

Click here to view code image

void use(mutex& mtx, vector<string>& vs, int i)
{
     if (i<0) return;
     string s;
     {
          lock_guard<mutex> g {mtx};
          s = vs[i];
     }
     // ...
}

Is such complication of the code worthwhile? Without looking at the code “hidden in the ...” we cannot tell, but we should definitely not use a lock_guard just out of unwillingness to consider where locking is needed. Minimizing the size of critical sections is in general a useful thing to do. If nothing else, it forces us to think about exactly where a lock is needed and why.

So, a lock_guard (and also a unique_lock) is a resource handle (“a guard”) for an object that you can lock to acquire ownership and unlock to release.

Such an object is called a lockable object. The obvious lockable object is of a standard-library mutex type, but users can define their own.

A lock_guard is a very simple class with no interesting operations. All it does is RAII for a mutex. To get an object that provides RAII and operations on a contained mutex, we use a unique_lock:

Obviously, the timed operations are only allowed if the contained mutex is a timed_mutex or a recur-sive_timed_mutex.

For example:

Click here to view code image

mutex mtx;
timed_mutex mtx2;

void use()
{
     unique_lock<defer_lock_t,mutex> lck {mtx};
     unique_lock<defer_lock_t,timed_mutex> lck2 {mtx2};

     lck.try_lock_for(milliseconds{2});    // error: mutex does not have member try_lock_for()

     lck2.try_lock_for(milliseconds{2});   // OK
     lck2.try_lock_until(steady_clock::now()+milliseconds{2});
     // ...
}

If you give a duration or a time_point as a second argument to a unique_lock, the constructor will execute the appropriate try operation. The owns_lock() operations allow us to check whether such an acquisition succeeded. For example:

Click here to view code image

timed_mutex mtx2;

void use2()
{
     unique_lock<timed_mutex> lck2 {mtx2,milliseconds{2}};
     if (lck2.owns_lock()) {
           // acquisition succeeded:
           // ... do something ...
     }
     else {
           // timeout:
           // ... do something else ...
     }
}

42.3.2. Multiple Locks

It is fairly common to want to acquire multiple resources to do some task. Unfortunately, acquiring two locks implies the opportunity of deadlock. For example:

Click here to view code image

mutex mtx1;    // protects one resource
mutex mtx2;    // protects another resource

void task(mutex& m1, mutex& m2)
{
     unique_lock<mutex> lck1 {m1};
     unique_lock<mutex> lck2 {m2};
     // ... use resources ...
}
thread t1 {task,ref(mtx1),ref(mtx2)};
thread t2 {task,ref(mtx2),ref(mtx1)};

The ref() is the std::ref() reference wrapper from <functional> (§33.5). It is needed to pass a reference through a variadic template (the thread constructor; §42.2.2). A mutex cannot be copied or moved, so I must pass them by reference (or use a pointer).

Change the names from mtx1 and mtx2 to something that does not indicate order and separate the definitions of t1 and t2 from each other in the source text and it will no longer be obvious that there is a good chance that the program will eventually deadlock with t1 owning mtx1, t2 owning mtx2, and each trying to acquire its second mutex forever.

The actual algorithm for try_lock() is unspecified, but one possibility would be:

Click here to view code image

template <typename M1, typename... Mx>
int try_lock(M1& mtx, Mx& tail...)
{
      if (mtx.try_lock()) {
            int n = try_lock(tail...);
            if (n == –1) return –1;    // all locks acquired
            mtx.unlock();              // back out
            return n+1;
      }
      return 1;                        // couldn't acquire mtx
}

template <typename M1>
int try_lock(M1& mtx)
{
      return (mtx.try_lock()) ? –1 : 0;
}

Given lock(), the buggy task() can be simplified and corrected:

Click here to view code image

void task(mutex& m1, mutex& m2)
{
    unique_lock lck1 {m1,defer_lock_t};
    unique_lock lck2 {m1,defer_lock_t};
    lock(lck1,lck2);
    // ... use resources ...
}

Note that applying lock() directly to the mutexes, lock(m1,m2), rather than to the unique_locks would have left the programmer with the obligation to explicitly release m1 and m2.

42.3.3. call_once()

We often want to initialize an object without getting into a race condition. The type once_flag and the function call_once() offer a low-level, efficient, and simple tool for that.

For example:

class X {
public:
     X();
     // ...
private:
     // ...
     static once_flag static_flag;
     static Y static_data_for_class_X;
     static void init();
};

X::X()
{
     call_once(static_flag,init());
}

One way to think about call_once() is as a way to simply modify preconcurrency code that relies on initialized static data.

Run-time initialization of a local static variable is implemented by call_once() or by a mechanism very similar to call_once(). Consider:

Click here to view code image

Color& default_color()    // user code
{
    static Color def { read_from_environment("background color") };
    return def;
}

This may be implemented as

Click here to view code image

Color& default_color()    // generated code
{
    static Color def;
    static_flag __def;
    call_once(__def,read_from_environment,"background color");
    return def;
}

I use the double underscore prefix (§6.3.3) to emphasize that this latter version represents compiler-generated code.

42.3.4. Condition Variables

Condition variables are used to manage communication among threads. A thread can wait (block) on a condition_variable until some event, such as reaching a specific time or another thread completing, occurs.

A condition_variable may (or may not) rely on system resources, so a constructor may fail for lack of such a resource. However, like a mutex, a condition_variable cannot be copied or moved, so it is best to think of a condition_variable as a resource in itself, rather than as a handle.

When a condition_variable is destroyed, all waiting threads (if any) must be notified (i.e., told to wake up) or they may wait forever.

The status returned by wait_until() and wait_for() is defined as:

enum class cv_status { no_timeout, timeout };

A condition_variable’s unique_lock is used by the wait functions to prevent wake-ups being lost due to contention on the unique_lock’s list of waiting threads.

The “plain” wait(lck) is a low-level operation that should be used with extra care and usually in the implementation of some higher-level abstraction. It can wake up “spuriously.” That is, the system may decide to resume wait()’s thread even though no other thread has notified it! Apparently, allowing spurious wake-up simplifies implementation of condition_variables on some systems. Always use “plain” wait() in a loop. For example:

while (queue.empty()) wait(queue_lck);

An additional reason for this loop is that some thread may have “snuck up” and invalidated the condition (here, queue.empty()) before the thread calling the unconditional wait() got to run. Such a loop basically is the implementation of a wait with a condition, so prefer those over the unconditional wait().

A thread can wait for an amount of time:

Click here to view code image

void simple_timer(int delay)
{
     condition_variable timer;
     mutex mtx;                                 // mutex protecting timer
     auto t0 = steady_clock::now();
     unique_lock<mutex> lck(mtx);               // acquire mtx
     timer.wait_for(lck,milliseconds{delay});   // release and reacquire mtx
     auto t1 = steady_clock::now();
     cout << duration_cast<milliseconds>(t1–t0).count() << "milliseconds passed\n";
} // implicitly release mtx

This basically shows the implementation of this_thread::wait_for(). The mutex protects wait_for() against data races. The wait_for() releases its mutex as it goes to sleep and reacquires it as its thread is unblocked. Finally, lck (implicitly) releases the mutex at the end of its scope.

Another simple use of a condition_variable is to control the flow of messages from a producer to a consumer:

template<typename T>
class Sync_queue {
public:
     void put(const T& val);
     void put(T&& val);
     void get(T& val);
private:
     mutex mtx;
     condition_variable cond;
     list<T> q;
};

The idea is that put() and get() will not get in each other’s way. A thread that does a get() will sleep unless there is a value on the queue for it to get.

template<typename T>
void Sync_queue::put(const T& val)
{
     lock_guard<mutex> lck(mtx);
     q.push_back(val);
     cond.notify_one();
}

That is, a producer put() acquires the queue’s mutex, adds a value at the end of the queue, calls notify_one() to wake a possibly blocked consumer, and implicitly releases the mutex. I provided an rvalue version of put() so that we can transmit objects of types that have move, but not copy, operations, such as unique_ptr (§5.2.1, §34.3.1) and packaged_task (§42.4.3).

I used notify_one() rather than notify_all() because I only added one element and wanted to keep put() simple. The possibility of multiple consumers and the possibility of consumers falling behind the producer might make me reconsider.

The get() is a bit more complicated because it should only block its thread if the mutex precludes access or if the queue is empty:

Click here to view code image

template<typename T>
void Sync_queue::get(T& val)
{
     unique_lock<mutex> lck(mtx);
     cond.wait(lck,[this]{ return !q.empty(); });
     val=q.front();
     q.pop_front();
}

A caller of get() will remain blocked until the Sync_queue is nonempty.

I used a unique_lock rather than a plain lock_guard because the lock_guard is optimized for simplicity and does not offer the operations needed to unlock and relock the mutex.

I used [this] to enable the lambda to access the Sync_queue object (§11.4.3.3).

I return the value from get() through a reference argument, rather than as a return value, to be sure that an element type with a copy constructor that can throw will not cause trouble. That is the conventional technique (e.g., the STL stack adaptor provides pop() and the containers provide front()). Writing a general get() that directly returns a value is possible, but surprisingly tricky. For an example, see future<T>::get() (§42.4.4).

A simple producer-consumer pair can be very simple:

Sync_queue<Message> mq;

void producer()
{
     while (true) {
           Message m;
           // ... fill m ...
           mq.put(m);
     }
}

void consumer()
{
     while (true) {
           Message m;
           mq.get(m);
           // ... use m ...
     }
}
     thread t1 {producer};
     thread t2 {consumer};

Using a condition_variable saves a consumer the bother of explicitly dealing with the case where it runs out of work to do. Had we simply used a mutex to control access to the Sync_queue, the consumer would have had to repeatedly wake up, look for work on the queue, and decide what to do when it found the queue empty.

I copy values into and out of the list I use to hold my queue elements. A copy of an element type may throw an exception, but if it does, the Sync_queue will remain unchanged and the put() or get() simply fails.

A Sync_queue is not itself a shared data structure, so we don’t use a separate mutex for it; only the put() and get() (updating the head and the tail of the queue, which may be the same element) need to be protected against data races.

For some applications, the simple Sync_queue has a fatal flaw: What if a consumer waits forever because a producer stopped adding values? What if a consumer has other things to do so that it cannot wait for a long time? Often there are answers, but one common technique is to add a timeout to get(), that is, to specify a maximum time to wait:

void consumer()
{
     while (true) {
           Message m;
           mq.get(m,milliseconds{200});
           // ... use m ...
     }
}

To make this work, we need to add a second get() to Sync_queue:

Click here to view code image

template<typename T>
void Sync_queue::get(T& val, steady_clock::duration d)
{
     unique_lock<mutex> lck(mtx);
     bool not_empty = cond.wait_for(lck,d,[this]{ return !q.empty(); });
     if (not_empty) {
           val=q.front();
           q.pop_front();
     }
     else
           throw system_error{"Sync_queue: get() timeout"};
}

When using a timeout, we need to consider what to do after the wait: did we get data or did we just time out? Actually, we don’t really care about the timeout, but only whether the predicate (expressed in the lambda) is true or not, so that is what wait_for() returns. I chose to report the failure of a get() with a timeout by throwing an exception. Had I thought that timing out would be a common and “nonexceptional” event, I would have returned a bool instead.

The roughly equivalent modification to put() would be to wait for the consumer to make inroads into a long queue, but not for too long a time:

Click here to view code image

template<typename T>
void Sync_queue::put(T val, steady_clock::duration d, int n)
{
     unique_lock<mutex> lck(mtx);
     bool not_full = cond.wait_for(lck,d,[this]{ return q.size()<n; });
     if (not_full) {
           q.push_back(val);
           cond.notify_one();
     }
     else {
           cond.notify_all();
           throw system_error{"Sync_queue: put() timeout"};
     }
}

For put(), the alternative of returning a bool to encourage the producer to always explicitly handle both cases seems more attractive than for get(). However, to avoid getting into a discussion of how best to handle overflow, I again chose to signal a failure by throwing an exception.

I chose to notify_all() if the queue was full. Maybe, some consumer needs a nudge to continue. The choice between notify_all() and notify_one() depends on the behavior of the application and is not always obvious. Notifying just one thread serializes access to the queue and could therefore minimize throughput when there are several potential consumers. On the other hand, notifying all waiting threads may wake up several threads, causing contention on the mutex and possibly having threads repeatedly waking up just to find the queue empty (emptied by other threads). I fall back on the old rule: Don’t trust your intuition; measure.

42.3.4.1. condition_variable_any

A condition_variable is optimized for unique_lock<mutex>. A condition_variable_any is functionally equivalent to a condition_variable but can use any lockable object for its operations:

42.4. Task-Based Concurrency

So far, this chapter focused on the mechanisms for running concurrent tasks: the focus was on threads, avoiding race conditions, and synchronizing threads. For many concurrent tasks, I find this focus on mechanisms distracting from the real task (sic!) of specifying concurrent tasks. This section focuses on specifying a simple kind of task: a task that does one thing given arguments and produces one result.

To support this task-based model of concurrency, the standard library offers:

The presentation of these facilities exposes many details that rarely need to bother an application writer. Please keep in mind the fundamental simplicity of the task model. Most of the more complicated details support rare uses, such as hiding uses of the messier threads-and-locks level.

The standard-library task support is just one example of what can be done to support task-based concurrency. Often, we would like to provide a lot of small tasks and let “the system” worry about how to map their execution onto hardware resources and how to keep them out of problems with data races, spurious wake-ups, excessive waits, etc.

The importance of these facilities is their simplicity to a programmer. In a sequential program, we usually write something like:

res = task(args);    // perform a task given arguments and get the result

The concurrent version becomes:

Click here to view code image

auto handle = async(task,args);    // perform a task given arguments
//    ... do something else ...
res = handle.get()                 // get the result

Sometimes, we lose sight of the value of simplicity as we consider alternatives, details, performance, and tradeoffs. By default, use the simplest technique and reserve the more complex solutions for where you know that they are really worthwhile.

42.4.1. future and promise

As mentioned in §5.3.5, communication between tasks is handled by a future/promise pair. A task puts its result into a promise, and a task that needs the result retrieves the result from the corresponding future:

The “value” in this diagram is technically known as the shared state (§iso.30.6.4). In addition to the return value or exception, it contains the information needed for two threads to safely exchange the information. At a minimum, a shared state must be able to hold:

• A value of the appropriate type or an exception. For a future “returning void” the value is nothing.

• A ready bit to indicate whether a value or exception is ready to be extracted by a future.

• The task to be executed when a get() is called for a future for a task launched by async() with the launch policy deferred (§42.4.6).

• A use count, so that the shared state can be destroyed when and only when its last potential user relinquishes access. In particular, if a stored value is of a class with a destructor, its destructor is called when the use count goes to zero.

• Some mutual exclusion data to enable unblocking of any thread that might be waiting (e.g., a condition_variable).

An implementation can take actions on a shared state:

• Construct: Possibly using a user-supplied allocator.

• Make ready: Set the “ready bit” and unblock any waiting threads.

• Release: Decrease the use count and destroy the shared state if this was the last user.

• Abandon: If it becomes impossible for a value or exception to be put into the shared state by a promise (e.g., because the promise is destroyed), a future_error exception with the error condition broken_promise is stored in the shared state and the shared state is made ready.

42.4.2. promise

A promise is the handle to a shared state (§42.4.1). It is where a task can deposit its result to be retrieved through a future (§42.4.4).

There are no copy operations for a promise.

A set function throws future_error if a value or exception is already set.

It is only possible to transmit a single result value through a promise. That may seem restrictive, but remember that the value is moved into and out of the shared state, rather than copied, so that we can cheaply pass a collection of objects. For example:

promise<map<string,int>> pr;
map<string,int>> m;
// ... fill m with a million <string,int> pairs ...
pr.set_value(m);

A task may then extract that map from a corresponding future at essentially zero cost.

42.4.3. packaged_task

A packaged_task holds a task and a future/promise pair.

We pass a task (a function or a function object) that we want executed to a packaged_task. When our task executes a return x, it causes a set_value(x) on the packaged_task’s promise. Similarly, a throw x causes a set_exception(px) where px is an exception_ptr for x. Basically, the packaged_task executes its task, f(args), like this:

Click here to view code image

try {
     pr.set_value(f(args));    // assume that the promise is called pr
}
catch(...) {
     pr.set_exception(current_exception());
}

A packaged_task offers a fairly conventional set of operations:

A packaged_task can be moved but not copied. A packaged_task may copy its task, and a copy of a task is assumed to yield the same result as the original. This is important because a task may be moved with its packaged_task onto the stack of a new thread.

To abandon a shared state (as is done by the destructor and the move) means making it ready. If there is no value or exception stored, a pointer to a future_error is stored (§42.4.1).

The advantage of make_ready_at_exit() is that the result is not available until destructors for thread_local variables have been executed.

There is no get_promise() operation to match get_future(). The use of the promise is completely handled by the packaged_task.

For a really simple example we don’t even need any threads. First define a simple task:

int ff(int i)
{
      if (i) return i;
      throw runtime_error("ff(0)");
}

We can now package this function into packaged_tasks and call them:

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packaged_task<int(int)> pt1 {ff};           // store ff in pt1
packaged_task<int(int)> pt2 {ff};           // store ff in pt2

pt1(1);                 // let pt1 call ff(1);
pt2(0);                 // let pt2 call ff(0);

So far, nothing appears to have happened. In particular, we don’t see the exception triggered by ff(0). In fact, pt1(1) did a set_value(1) on the promise attached to pt1, and pt1(0) did a set_exception(px) on the promise attached to pt2; that px is an exception_ptr to a runtime_error("ff(0)").

Later, we can try to retrieve the results. The get_future() operation is used to get hold of the future into which the packaged thread will deposit the result of its task.

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auto v1 = pt1.get_future();
auto v2 = pt2.get_future();

try {
     cout << v1.get() << '\n'; // will print
     cout << v2.get() << '\n'; // will throw
}
catch (exception& e) {
     cout << "exception: " << e.what() << '\n';
}

The output is:

1
exception: ff(0)

We could have gotten exactly the same effect by simply writing:

Click here to view code image

try {
      cout << ff(1) << '\n'; // will print
      cout << ff(0) << '\n'; // will throw
}
catch (exception& e) {
      cout << "exception: " << e.what() << '\n';
}

The point is that the packaged_task version works exactly like the version using ordinary function calls even when the calls of the task (here ff) and the calls of the get()s are in different threads. We can concentrate on specifying the tasks, rather than thinking about threads and locks.

We can move the future, the packaged_task, or both around. Eventually, the packaged_task is invoked and its task deposits its result in the future without having to know either which thread executed it or which thread will receive the result. This is simple and general.

Consider a thread that processes a series of requests. It could be a GUI thread, a thread owning access to a piece of specialized hardware, or indeed any server that serializes access to a resource through a queue. We can implement such a service as a queue of messages (§42.3.4), or we could pass tasks to be executed:

Click here to view code image

using Res = /* result type for server*/;
using Args = /* argument types for server */;
using PTT = Res(Args);

Sync_queue<packaged_task<PTT>> server;

Res f(Args);                                      // function: do something
struct G {
     Res operator()(Args);                        // function object: do something
     // ...
};
auto h = [=](Args a) { /* do something */ };      // lambda

packaged_task<PTT> job1(f);
packaged_task<PTT> job2(G{});
packaged_task<PTT> job3(h);

auto f1 = job1.get_future();
auto f2 = job2.get_future();
auto f3 = job3.get_future();

server.put(move(job1));
server.put(move(job2));
server.put(move(job3));

auto r1 = f1.get();
auto r2 = f2.get();
auto r3 = f3.get();

The server thread would take the packaged_tasks from the server queue and execute them in some suitable order. Typically, the tasks would carry data with them from the calling context.

The tasks are written essentially like ordinary functions, function objects, and lambdas. The server calls the tasks essentially like ordinary (callback) functions. The packaged_tasks are actually easier for the server to use than ordinary functions because the handling of their exceptions has been taken care of.

42.4.4. future

A future is a handle to a shared state (§42.4.1). It is where a task can retrieve a result deposited by a promise (§42.4.2).

A future holds a unique value and offers no copy operations.

The value, if any, is moved out of a future. So get() can only be called once. If you potentially need to read a result several times (e.g., by different tasks), use a shared_future (§42.4.5).

It is undefined what happens if you try to get() twice. In fact, it is undefined what happens if you try to do any operation except a first get(), a valid(), or a destructor on a future that is not valid(). The standard “encourages” an implementation to throw a future_error with the error condition future_errc::no_state in such cases.

If a future<T>’s value type, T, is void or a reference, special rules apply for get():

• future<void>::get() doesn’t return a value: it just returns or throws an exception.

• future<T&>::get() returns a T&. A reference isn’t an object, so the library must have transmitted something else, such as a T*, and get() converts that (back) into a T&.

The status of a future can be observed by calling wait_for() and wait_until():

The possible errors from operations on futures are:

In addition, an operation on the T value of shared_future<T>::get() could possibly throw (e.g., an unusual move operation).

Looking at the future<T> table, I find that I miss two useful functions:

• wait_for_all(args): Wait until every future in args has a value.

• wait_for_any(args): Wait until one future in args has a value.

I can easily implement a version of wait_for_all():

Click here to view code image

template<typename T>
vector<T> wait_for_all(vector<future<T>>& vf)
{
     vector<T> res;
     for (auto& fu : vf)
           res.push_back(fu.get());
     return res;
}

That’s easy enough to use, but it has a flaw: if I wait for ten futures, I risk my thread getting blocked ten times. Ideally, my thread would be blocked and unblocked at most once. However, for many uses, this wait_for_all() implementation is good enough: if some of the tasks are long-running, the extra waits will not be significant. On the other hand, if all tasks are short, they will most likely have finished after the first wait.

An implementation of wait_for_any() is trickier. First we need a way of checking if a future is ready. Surprisingly, that is done by using wait_for(). For example:

future_status s = fu.wait_for(seconds{0});

Using wait_for(seconds{0}) to get the status of a future is not obvious, but wait_for() will tell us why it resumed, and it tests for ready before suspending. It is common, but unfortunately not guaranteed, that wait_for(seconds{0}) returns immediately rather than trying to suspend for zero time.

Given wait_for(), we can write:

Click here to view code image

template<typename T>
int wait_for_any(vector<future<T>>& vf, steady_clock::duration d)
      // return index of ready future
      // if no future is ready, wait for d before trying again
{
      while(true) {
           for (int i=0; i!=vf.size(); ++i) {
                 if (!vf[i].valid()) continue;
                 switch (vf[i].wait_for(seconds{0})) {
                 case future_status::ready:
                      return i;
                 case future_status::timeout:
                      break;
                 case future_status::deferred:
                      throw runtime_error("wait_for_all(): deferred future");
                 }
           }
           this_thread::sleep_for(d);
     }
}

I decided to consider a deferred task (§42.4.6) an error for my uses.

Note the check for valid(). Trying wait_for() on an invalid future (e.g., a future on which you have already done a get()) will cause a hard-to-find error. At best, you can hope for a (probably surprising) exception being thrown.

Like the implementation of wait_for_all(), this implementation has a flaw: ideally, the caller of wait_for_any() should never have to wake up just to find that no tasks had completed and should be unblocked immediately when one does. This simple implementation only approximates that. With a large d a useless wake-up is unlikely but implies the possibility of an unnecessarily long wait.

The wait_for_all() and wait_for_any() functions are useful building blocks for concurrent algorithms. I use them in §42.4.6.

42.4.5. shared_future

The result value of a future can be read only once: it is moved. Thus, if you want to read the value repeatedly or potentially have it read by multiple readers, you must copy it, and then read the copy. That’s what a shared_future does. Every usable shared_future is directly or indirectly initialized by moving the value out of a future with the same result type.

Obviously, shared_future is very similar to future. The key difference is that a shared_future moves its value to a location where it can be repeatedly read and shared. As for future<T>, special rules apply for get() when a shared_future<T>’s value type, T, is void or a reference:

• shared_future<void>::get() doesn’t return a value: it just returns or throws an exception.

• shared_future<T&>::get() returns a T&. A reference isn’t an object, so the library must have transmitted something else, such as a T*, and get() converts that (back) into a T&.

• shared_future<T>::get() returns a const T& when T is not a reference.

Unless the returned object is a reference, it is const, so it can safely be accessed from several threads without synchronization. If the returned object is a non-const reference, you need some form of mutual exclusion to avoid data races on the referred-to object.

42.4.6. async()

Given future and promise (§42.4.1) and packaged_task (§42.4.3), we can write simple tasks without worrying too much about threads. Given those, a thread is just something you give a task to run. However, we still need to consider how many threads to use and whether a task is best run on the current thread or on another. Such decisions can be delegated to a thread launcher, that is, a function that decides whether to create a new thread, to recycle an old thread, or simply run the task on the current thread.

The async() function is basically a simple interface to a launcher of unknown sophistication. A call of async() returns a future<R> where R is the type of its task’s result. For example:

double square(int i) { return i*i; }

future<double> fd = async(square,2);
double d = fd.get();

If a thread is launched to execute square(2), we may have a record slow way of executing 2*2. The notation can be simplified by the use of auto:

double square(int i) { return i* i; }

auto fd = async(square,2);
auto d = fd.get();

In principle, a caller of async() could provide a huge variety of information to help the implementation of async() decide whether to launch a new thread, rather than simply executing the task on the current thread. For example, we can easily imagine a programmer wanting to give the launcher a hint about how long a task is likely to run. However, only two policies are currently standard:

Note the as if. The launcher has wide discretionary powers when it comes to launching a new thread or not. For example, since the default policy is async|deferred (async or deferred), it is not too fanciful to imagine an async() that decided to use deferred for async(square,2), so that the execution reduced to fd.get() calling square(2). I could even imagine an optimizer reducing that whole code fragment to

double d = 4;

However, we should not expect an implementation of async() to be optimized for such trivial examples. Implementer efforts are better spent on realistic examples where the task performs a significant amount of computation so that launching on a new or “recycled” thread could be reasonably considered.

By a “recycled thread” I mean a thread from a collection of threads (a thread pool) that async() may create once and use over and over to execute a variety of tasks. Depending on the implementation of system threads, this can drastically lower the cost of executing a task on a thread. If a thread is recycled, the launcher must take care that a task does not see leftover state from a previous task executed on the thread and that a task does not store pointers to its stack or thread_local data (§42.2.8) in nonlocal storage. Such data could conceivably be used for security violations.

A simple and realistic use of async() would be to spawn a task to collect input from a user:

Click here to view code image

void user()
{
     auto handle = async([](){ return input_interaction_manager(); });
     // ...
     auto input = handle.get();
     // ...
}

Such a task often requires some data from the caller. I used a lambda to make it obvious that I can pass arguments or allow access to local variables. When using a lambda to specify a task, beware of capturing local variables by reference. That could lead to data races or unfortunate cache access patterns by two threads accessing the same stack frame. Also, beware that capturing members of an object using [this] (§11.4.3.3) implies that the members of the object are accessed indirectly (through this), rather than copied, so that the object is subject to data races unless you make certain that it is not. If in doubt, copy (pass or capture by value, [=]).

It is often important that we can select a scheduling policy “late” and change it as needed. For example, I might use launch::deferred for initial debugging. That would eliminate errors related to concurrency until I had eliminated sequential errors. Also, I can often go back to launch::deferred to determine if an error really is related to concurrency.

Over time, more launch policies may become available, and maybe some systems offer better launch policies than others. In such cases, I might be able to improve the performance of my code by a local change of launch policy, rather than by reworking subtle details of the program logic. This, again, is an effect of the fundamental simplicity of the task-based model (§42.4).

Having launch::async|launch::deferred as the default launch policy can be a practical problem. Basically, it is not so much a default as a lacking design decision. An implementation might decide that “no concurrency” is a good idea and always use launch::deferred. If your experiments with concurrency show results surprisingly similar to single-thread execution, try being explicit about the launch policy.

42.4.7. A Parallel find() Example

A find() does a linear search of a sequence. Imagine having millions of items that are not easily sorted so that find() is the right algorithm for finding something. This could be slow, so instead of searching once starting at the beginning and going until the end, we might start 100 find()s each on a hundredth of the data.

First, we represent the data as a vector of Records:

extern vector<Record> goods; // data to be searched

An individual (sequential) task is simply a use of the standard-library find_if():

Click here to view code image

template<typename Pred>
Record*find_rec(vector<Record>& vr, int first, int last, Pred pr)
{
    vector<Record>::iterator p = std::find_if(vr.begin()+first,vr.begin()+last,pr);
    if (p == vr.begin()+last)
          return nullptr;       // at end: no record found
    return &*p;                 // found: return a pointer to the element
}

Unfortunately, we have to decide on a “grain” of parallelism. That is, we need to specify the number of records to be searched sequentially.

const int grain = 50000;      // number of records for a linear search

Picking a number like that is a very primitive way of choosing a grain size. It is hard to choose well unless a lot is known about the hardware, the library implementation, the data, and the algorithm. Experimentation is essential. Tools and frameworks that save us from having to pick a grain size or help us choose can be most useful. However, for a simple illustration of basic standard-library facilities and the most basic techniques for their use, grain is sufficient.

The pfind() (“parallel find”) function simply does the number of async() calls required by the grain and the number of Records. Then, it get()s the results:

Click here to view code image

template<typename Pred>
Record * pfind(vector<Record>& vr, Pred pr)
{
    assert(vr.size()%grain==0);

    vector<future<Record*>> res;

    for (int i = 0; i!=vr.size(); i+=grain)
          res.push_back(async(find_rec<Pred>,ref(vr),i,i+grain,pr));

    for (int i = 0; i!=res.size(); ++i)         // look for a result in the futures
          if (auto p = res[i].get())            // did the task find a match?
                return p;

    return nullptr;                             // no match found
}

Finally, we can initiate a search:

Click here to view code image

void find_cheap_red()
{
     assert(goods.size()%grain==0);

     Record* p = pfind(goods,
                        [](Record& r) { return r.price<200 && r.color==Color::red; });
     cout << "record "<< *p << '\n';
}

This first version of a parallel find() first spawns a lot of tasks and then proceeds to wait for them in order. Like std::find_if(), it reports the first element that matches the predicate; that is, it finds the element with the lowest index that matches. That may be fine, but:

• We could end up waiting for a lot of tasks that don’t find anything (maybe only the last task finds something).

• We may throw away a lot of information that could be useful (maybe a thousand items match our criteria).

The first problem may not be as bad as it sounds. Assume (somewhat recklessly) that launching a thread doesn’t cost anything and that we have as many processing units as there are tasks; then we would still get the result in roughly the time it took to process one task. That is, we would potentially get our result in the time taken to examine 50,000 records rather than millions. If we have N processing units, the results will be delivered in batches of results for N*50000 records. If no record is found until the last segment of the vector, the time will be roughly vr.size()/(N*grain) units.

Instead of waiting for each task in order, we could try to look at the results in the order the tasks completed. That is, we could use wait_for_any() (§42.4.4). For example:

Click here to view code image

template<typename Pred>
Record*pfind_any(vector<Record>& vr, Pred pr)
{
    vector<future<Record*>> res;

    for (int i = 0; i!=vr.size(); i+=grain)
          res.push_back(async(find_rec<Pred>,ref(vr),i,i+grain,pr));

    for (int count = res.size(); count; ––count) {
          int i = wait_for_any(res,microseconds{10});  // find a completed task
          if (auto p = res[i].get())                   // did the task find a match?
                return p;
    }

    return nullptr;                                    // no match found
}

A get() renders its future invalid, so we don’t get to look at a partial result twice.

I use count to make sure I don’t keep looking after all tasks have reported back. Apart from that, pfind_any() is as simple as pfind(). Whether there is a performance advantage to pfind_any() over pfind() depends on lots of things, but the key observation is that to (potentially) gain advantages of concurrency, we had to use a slightly different algorithm. Like find_if(), pfind() returns its first match, whereas pfind_any() returns whichever match it first found. Often, the best parallel algorithm for a problem is a variant of the idea for a sequential solution, rather than a simple repetition of the sequential solution.

In this case, the obvious question is “But do you really only need one match?” Given concurrency, it makes more sense to find all matches. Doing so is easy. All we need to do is to let each task return a vector of matches, rather than just a simple match:

Click here to view code image

template<typename Pred>
vector<Record*> find_all_rec(vector<Record>& vr, int first, int last, Pred pr)
{
    vector<Record*> res;
    for (int i=first; i!=last; ++i)
          if (pr(vr[i]))
                res.push_back(&vr[i]);
    return res;
}

This find_all_rec() is arguably simpler than the original find_rec().

Now we just need to launch find_all_rec() a suitable number of times and wait for the results:

Click here to view code image

template<typename Pred>
vector<Record*> pfind_all(vector<Record>& vr, Pred pr)
{

    vector<future<vector<Record*>>> res;

    for (int i = 0; i!=vr.size(); i+=grain)
          res.push_back(async(find_all_rec<Pred>,ref(vr),i,i+grain,pr));

    vector<vector<Record*>> r2 = wait_for_all(res);

    vector<Record*>r;
    for (auto& x : r2)               // merge results
          for (auto p : x)
                r.push_back(p);
    return r;
}

Had I just returned a vector<vector<Record*>> this pfind_all() would have been the simplest parallelizing function so far. However, by merging the vectors returned into a single one, pfind_all() became an example of a common and popular group of parallel algorithms:

[1] Create a number of tasks to be run.

[2] Run the tasks in parallel.

[3] Merge the results.

This is the basic idea that, when developed into a framework so that the details of concurrent execution have been completely hidden, is commonly referred to as map-reduce [Dean,2004].

The example can be run like this:

Click here to view code image

void find_all_cheap_red()
{
     assert(goods.size()%grain==0);

     auto vp = pfind_all(goods,
          [](Record& r) { return r.price<200 && r.color==Color::red; });
     for (auto p : vp)
           cout << "record "<< *p << '\n';
}

Finally, we must consider if the effort to parallelize was worthwhile. To do so, I added simple sequential versions to my test:

Click here to view code image

void just_find_cheap_red()
{
     auto p = find_if(goods.begin(),goods.end(),
          [](Record& r) { return r.price<200 && r.color==Color::red; });
     if (p!=goods.end())
               cout << "record "<< *p << '\n';
     else
               cout << "not found\n";
}

void just_find_all_cheap_red()
{
     auto vp = find_all_rec(goods,0,goods.size(),
          [](Record& r) { return r.price<200 && r.color==Color::red; });
     for (auto p : vp)
           cout << "record "<< *p << '\n';
}

For my simple test data and my (relatively) simple laptop with only four hardware threads, I did not find any consistent or significant performance differences. In this case, the cost of thread creation in the immature implementation of async() dominates the effects of concurrency. If I needed significant parallel speedup right now, I would implement my own variant of async() based on a pre-created set of threads and a work queue, along the lines of a Sync_queue (§42.3.4) of packaged_tasks (§42.4.3). Note that such a significant optimization can be done without changing my task-based parallel find() program. From the application’s point of view, replacing the standard-library async() with an optimized version is an implementation detail.

42.5. Advice

[1] A thread is a type-safe interface to a system thread; §42.2.

[2] Do not destroy a running thread; §42.2.2.

[3] Use join() to wait for a thread to complete; §42.2.4.

[4] Consider using a guarded_thread to provide RAII for threads; §42.2.4.

[5] Do not detach() a thread unless you absolutely have to; §42.2.4.

[6] Use lock_guard or unique_lock to manage mutexes; §42.3.1.4.

[7] Use lock() to acquire multiple locks; §42.3.2.

[8] Use condition_variables to manage communication among threads; §42.3.4.

[9] Think in terms of tasks that can be executed concurrently, rather than directly in terms of threads; §42.4.

[10] Value simplicity; §42.4.

[11] Return a result using a promise and get a result from a future; §42.4.1.

[12] Don’t set_value() or set_exception() to a promise twice; §42.4.2.

[13] Use packaged_tasks to handle exceptions thrown by tasks and to arrange for value return; §42.4.3.

[14] Use a packaged_task and a future to express a request to an external service and wait for its response; §42.4.3.

[15] Don’t get() twice from a future; §42.4.4.

[16] Use async() to launch simple tasks; §42.4.6.

[17] Picking a good granularity of concurrent tasks is difficult: experiment and measure; §42.4.7.

[18] Whenever possible, hide concurrency behind the interface of a parallel algorithm; §42.4.7.

[19] A parallel algorithm may be semantically different from a sequential solution to the same problem (e.g., pfind_all() vs. find()); §42.4.7.

[20] Sometimes, a sequential solution is simpler and faster than a concurrent solution; §42.4.7.

43. The C Standard Library

C is a strongly typed, weakly checked language.

– D. M. Ritchie

• Introduction

• Files

• The printf() Family

• C-Style Strings

• Memory

• Date and Time

• Etc.

• Advice

43.1. Introduction

The standard library for the C language is with very minor modifications incorporated into the C++ standard library. The C standard library provides quite a few functions that have proven useful over the years in a wide variety of contexts – especially for relatively low-level programming.

There are more C standard-library functions than are presented here; see a good C textbook, such as “Kernighan and Ritchie” [Kernighan,1988] or the ISO C standard [C,2011], if you need to know more.

43.2. Files

The <stdio> I/O system is based on files. A file (a FILE*) can refer to a file or to one of the standard input and output streams: stdin, stdout, and stderr. The standard streams are available by default; other files need to be opened:

A file opened with fopen() must be closed by fclose() or the file will remain open until the operating system closes it. If that is a problem (is considered a leak), use an fstream (§38.2.1).

A mode is a C-style string containing one or more characters specifying how a file is to be opened (and used after opening):

There may be (and usually are) more options on a specific system. For example, x is sometimes used to mean “the file must not exist before this open operation.” Some options can be combined, for example, fopen("foo","rb") tries to open a file called foo for binary reading. The I/O modes should be the same for stdio and iostreams (§38.2.1).

43.3. The printf() Family

The most popular C standard library functions are the output functions. However, I prefer iostreams because that library is type-safe and extensible. The formatted output function, printf(), is widely used (also in C++ programs) and widely imitated in other programming languages:

For each version, n is the number of characters written or a negative number if the output failed. The return value from printf() is essentially always ignored.

The declaration of printf() is:

int printf(const char* format ...);

In other words, it takes a C-style string (typically a string literal) followed by an arbitrary number of arguments of arbitrary type. The meaning of those “extra arguments” is controlled by conversion specifications, such as %c (print as character) and %d (print as decimal integer), in the format string. For example:

Click here to view code image

int x = 5;
const char* p = "Pedersen";
printf("the value of x is '%d' and the value of s is '%s'\n",x,s);

A character following a % controls the handling of an argument. The first % applies to the first “extra argument” (here, %d applies to x), the second % to the second “extra argument” (here, %s applies to s), and so on. In particular, the output of that call to printf() is

the value of x is '5' and the value of s is 'Pedersen'

followed by a newline.

In general, the correspondence between a % conversion directive and the type to which it is applied cannot be checked, and when it can, it usually is not. For example:

printf("the value of x is '%s' and the value of s is '%x'\n",x,s);     // oops

The set of conversion specifications is quite large (and growing over the years) and provides a great degree of flexibility. Various systems support options beyond the ones offered by the C standard. See also the set of options used for strftime() formatting (§43.6). Following the %, there may be:

–

an optional minus sign that specifies left-adjustment of the converted value in the field;

+

an optional plus sign that specifies that a value of a signed type will always begin with a + or – sign;

0

an optional zero that specifies that leading zeros are used for padding of a numeric value. If – or a precision is specified this 0 is ignored;

#

an optional # that specifies that floating-point values will be printed with a decimal point even if no nonzero digits follow, that trailing zeros will be printed, that octal values will be printed with an initial 0, and that hexadecimal values will be printed with an initial 0x or 0X;

d

an optional digit string specifying a field width; if the converted value has fewer characters than the field width, it will be blank-padded on the left (or right, if the left-adjustment indicator has been given) to make up the field width; if the field width begins with a zero, zero-padding will be done instead of blank-padding;

.

an optional period that serves to separate the field width from the next digit string;

d

an optional digit string specifying a precision that specifies the number of digits to appear after the decimal point, for e- and f-conversion, or the maximum number of characters to be printed from a string;

*

a field width or precision may be * instead of a digit string. In this case an integer argument supplies the field width or precision;

h

an optional character h, specifying that a following d, i, o, u, x, or X corresponds to a (signed or unsigned) short integer argument;

hh

an optional pair of characters hh, specifying that a following d, i, o, u, x, or X argument is treated as a (signed or unsigned) char argument;

l

an optional character l (ell), specifying that a following d, i, o, u, x, or X corresponds to a (signed or unsigned) long integer argument;

ll

an optional pair of characters ll (ell ell), specifying that a following d, i, o, u, x, or X corresponds to a (signed or unsigned) long long integer argument;

L

an optional character L, specifying that a following a, A, e, E, f, F, g, or G corresponds to a long double argument;

j

specifying that a following d, i, o, u, x, or X corresponds to a intmax_t or uintmax_t argument;

z

specifying that a following d, i, o, u, x, or X corresponds to a size_t argument;

t

specifying that a following d, i, o, u, x, or X corresponds to a ptrdiff_t argument;

%

indicating that the character % is to be printed; no argument is used;

c

a character that indicates the type of conversion to be applied. The conversion characters and their meanings are:

d

The integer argument is converted to decimal notation;

i

The integer argument is converted to decimal notation;

o

The integer argument is converted to octal notation;

x

The integer argument is converted to hexadecimal notation;

X

The integer argument is converted to hexadecimal notation;

f

The float or double argument is converted to decimal notation in the style [–]ddd.ddd. The number of d’s after the decimal point is equal to the precision for the argument. If necessary, the number is rounded. If the precision is missing, six digits are given; if the precision is explicitly 0 and # isn’t specified, no decimal point is printed;

F

Like %f but uses capital letters for INF, INFINITY, and NAN.

e

The float or double argument is converted to decimal notation in the scientific style [–]d.ddde+dd or [–]d.ddde–dd, where there is one digit before the decimal point and the number of digits after the decimal point is equal to the precision specification for the argument. If necessary, the number is rounded. If the precision is missing, six digits are given; if the precision is explicitly 0 and # isn’t specified, no digits and no decimal point are printed;

E

As e, but with an uppercase E used to identify the exponent;

g

The float or double argument is printed in style d, in style f, or in style e, whichever gives the greatest precision in minimum space;

G

As g, but with an uppercase E used to identify the exponent;

a

The double argument is printed in the hexadecimal format [–]0xh.hhhhp+d or [–]0xh.hhhhp+d;

A

Like %a but using X and P instead or x and p;

c

The character argument is printed. Null characters are ignored;

s

The argument is taken to be a string (character pointer), and characters from the string are printed until a null character or until the number of characters indicated by the precision specification is reached; however, if the precision is 0 or missing, all characters up to a null are printed;

p

The argument is taken to be a pointer. The representation printed is implementation-dependent;

u

The unsigned integer argument is converted to decimal notation;

n

The number of characters written so far by the call of printf(), fprintf(), or sprintf() is written to the int pointed to by the pointer to int argument.

In no case does a nonexistent or small field width cause truncation of a field; padding takes place only if the specified field width exceeds the actual width.

Here is a more elaborate example:

char* line_format = "#line %d \"%s\"\n";
int line = 13;
char* file_name = "C++/main.c";

printf("int a;\n");
printf(line_format,line,file_name);

which produces:

int a;
#line 13 "C++/main.c"

Using printf() is unsafe in the sense that type checking is not done. For example, here is a well-known way of getting unpredictable output, a segmentation fault, or worse:

Click here to view code image

char x = 'q';
printf("bad input char: %s",x);   // %s should have been %c

The printf() function does, however, provide great flexibility in a form that is familiar to C programmers.

Because C does not have user-defined types in the sense that C++ has, there are no provisions for defining output formats for user-defined types, such as complex, vector, or string. The format for strftime() (§43.6) is an example of the contortions you can get into by trying to design yet another set of format specifiers.

The C standard output, stdout, corresponds to cout. The C standard input, stdin, corresponds to cin. The C standard error output, stderr, corresponds to cerr. This correspondence between C standard I/O and C++ I/O streams is so close that C-style I/O and I/O streams can share a buffer. For example, a mix of cout and stdout operations can be used to produce a single output stream (that’s not uncommon in mixed C and C++ code). This flexibility carries a cost. For better performance, don’t mix stdio and iostream operations for a single stream. To ensure that, call ios_base::sync_with_stdio(false) before the first I/O operation (§38.4.4).

The stdio library provides a function, scanf(), that is an input operation with a style that mimics printf(). For example:

Click here to view code image

int x;
char s[buf_size];
int i = scanf("the value of x is '%d' and the value of s is '%s'\n",&x,s);

Here, scanf() tries to read an integer into x and a sequence of non-whitespace characters into s. A non-format character specifies that the input should contain that character. For example:

the value of x is '123' and the value of s is 'string '\n"

will read 123 into x and string followed by a 0 into s. If the call of scanf() succeeds, the resulting value (i in the call above) will be the number of argument pointers assigned to (hopefully 2 in the example); otherwise, EOF. This way of specifying input is error-prone (e.g., what would happen if you forgot the space after string on that input line?). All arguments to scanf() must be pointers. I strongly recommend against the use of scanf().

So what can we do for input if we are obliged to use stdio? One popular answer is “use the standard-library function gets()”:

// very dangerous code:
char s[buf_size];
char* p = gets(s);   // read a line into s

The call p=gets(s) reads characters into s until a newline or an end-of-file is encountered and a '\0' is placed after the last character written to s. If an end-of-file is encountered or if an error occurred, p is set to the nullptr; otherwise, it is set to s. Never use gets(s) or its rough equivalent (scanf("%s",s))! For years, they were the favorites of virus writers: By providing an input that overflows the input buffer (s in the example), a program can be corrupted and a computer potentially taken over by an attacker. The sprintf() function can suffer similar buffer-overflow problems. The C11 version of the C standard library offers a whole alternate set of stdio input functions that take an extra argument to defend against overflow, such as gets_s(p,n). As for iostream’s unformatted input, that leaves the user with the problem of deciding exactly which termination condition was encountered (§38.4.1.2; e.g., too many characters, a terminator character, or an end-of-file).

The stdio library also provides simple and useful character read and write functions:

The result of these operations is an int (not a char, or EOF could not be returned). For example, this is a typical C-style input loop:

Click here to view code image

int ch;   // note: not "char ch;"
while ((ch=getchar())!=EOF) { /* do something */ }

Don’t do two consecutive ungetc()s on a stream. The result of that is undefined and non-portable.

There are many more stdio functions; see a good C textbook (e.g., “K&R,”) if you need to know more.

43.4. C-Style Strings

A C-style string is a zero-terminated array of char. This notion of a string is supported by a set of functions defined in <cstring> (or <string.h>; note: not <string>) and <cstdlib>. These functions operate on C-style strings through char* pointers (const char* pointers for memory that is only read, but not unsigned char* pointers):

Note that in C++, strchr() and strstr() are duplicated to make them type-safe (they can’t turn a const char* into a char* the way the C equivalents can). See also §36.3.2, §36.3.3, and §36.3.7.

The conversions to floating-point values set errno to ERANGE (§40.3) if their result doesn’t fit into the target type. See also §36.3.5.

43.5. Memory

The memory manipulation functions operate on “raw memory” (no type known) through void* pointers (const void* pointers for memory that is only read):

Note that malloc(), etc., does not invoke constructors and free() doesn’t invoke destructors. Do not use these functions for types with constructors or destructors. Also, memset() should never be used for any type with a constructor.

Note that realloc(p,n) will reallocate (that is, copy) the data stored, from p onward, when it needs more memory than is avaliable starting from p. For example:

Click here to view code image

int max = 1024;
char* p = static_cast<char*>(malloc(max));
char* current_word = nullptr;
bool in_word = false;
int i=0;
while (cin.get(&p[i]) {
     if (isletter(p[i])) {
          if (!in_word)
                 current_word = p;
          in_word = true;
     }
     else
           in_word = false;
     if (++i==max)
           p = static_cast<char*>(realloc(p,max*=2));   // double allocation
     // ...
}

I hope you spotted the nasty bug: if realloc() was called, current_word may (may not) point to a location outside the current allocation pointed to by p.

Most uses of realloc() are better done using a vector (§31.4.1). The mem* functions are found in <cstring> and the allocation functions in <cstdlib>.

43.6. Date and Time

In <ctime>, you can find several types and functions related to date and time:

The struct tm is defined like this:

Click here to view code image

struct tm {
     int tm_sec;    // second of minute [0:61]; 60 and 61 represent leap seconds
     int tm_min;    // minute of hour [0:59]
     int tm_hour;   // hour of day [0:23]
     int tm_mday;   // day of month [1:31]
     int tm_mon;    // month of year [0:11]; 0 means January (note: not [1:12])
     int tm_year;   // year since 1900; 0 means year 1900, and 115 means 2015
     int tm_wday;   // days since Sunday [0:6]; 0 means Sunday
     int tm_yday;   // days since January 1 [0:365]; 0 means January 1
     int tm_isdst;  // hours of daylight savings time
};

A system clock is supported by the function clock() supported by a few functions giving meaning to its return type clock_t:

A example of the result of a call of asctime() is

"Sun Sep 16 01:03:52 1973\n"

Here is an example of how clock() can be used to time a function:

Click here to view code image

int main(int argc, char* argv[])
{
     int n = atoi(argv[1]);

     clock_t t1 = clock();
     if (t1 == clock_t(–1)) {         // clock_t(-1) means "clock() didn't work"
            cerr << "sorry, no clock\n";
            exit(1);
     }

     for (int i = 0; i<n; i++)
           do_something();            // timing loop
     clock_t t2 = clock();
     if (t2 == clock_t(–1)) {
            cerr << "sorry, clock overflow\n";
            exit(2);
     }
     cout << "do_something() " << n << " times took "
          << double(t2–t1)/CLOCKS_PER_SEC " seconds"
          << " (measurement granularity: " CLOCKS_PER_SEC
          << " of a second)\n";
}

The explicit conversion double(t2–t1) before dividing is necessary because clock_t might be an integer. For values t1 and t2 returned by clock(), double(t2–t1)/CLOCKS_PER_SEC is the system’s best approximation of the time in seconds between the two calls.

Compare <ctime> with the facilities provided in <chrono>; see §35.2.

If clock() isn’t provided for a processor or if a time interval is too long to measure, clock() returns clock_t(–1) .

The strftime() function uses a printf() format string to control the output of a tm. For example:

Click here to view code image

void almost_C()
{
     const int max = 80;
     char str[max];
     time_t t = time(nullptr);
     tm* pt = localtime(&t);
     strftime(str,max,"%D, %H:%M (%I:%M%p)\n",pt);
     printf(str);
}

The output is something like:

06/28/12, 15:38 (03:38PM)

The strftime() formatting characters almost constitute a small programming language:

The locale referred to is the program’s global locale.

Some conversion specifiers can be modified by an E or O modifier, indicating alternative implementation-specific and locale-specific formatting. For example:

The strftime() is used by the put_time facet (§39.4.4.1).

For C++-style time facilities, see §35.2.

43.7. Etc.

In <cstdlib> we find:

The comparison function (cmp) used by qsort() and bsort() must have the type

int (*cmp)(const void* p, const void* q);

That is, no type information is known to the sort functions that simply “see” their array arguments as sequences of bytes. The integer returned is

• Negative if *p is considered less than *q

• Zero if *p is considered equal to *q

• Positive if *p is considered greater than *q

This differs from sort(), which uses a conventional <.

Note that exit() and abort() do not invoke destructors. If you want destructors called for constructed objects, throw an exception (§13.5.1).

Similarly, longjmp() from <csetjmp> is a nonlocal goto that unravels the stack until it finds the result of a matching setjmp(). It does not invoke destructors. Its behavior is undefined if a destructor would be invoked by a throw from the same point of a program. Never use setjmp() in a C++ program.

For more C standard library functions see [Kernighan,1988] or some other reputable C language reference.

In <cstdint>, we find int_fast16_t and other standard integer aliases:

Also in <cstdint>, we find type aliases for the largest signed and unsigned integer types for an implementation. For example:

Click here to view code image

typedef long long intmax_t;           // largest signed integer type
typedef unsigned long long uintmax_t; // largest unsigned integer type

43.8. Advice

[1] Use fstreams rather than fopen()/fclose() if you worry about resource leaks; §43.2.

[2] Prefer <iostream> to <stdlib> for reasons of type safety and extensibility; §43.3.

[3] Never use gets() or scanf("%s",s); §43.3.

[4] Prefer <string> to <cstring> for reasons of ease of use and simplicity of resource management; §43.4.

[5] Use the C memory management routines, such as memcpy(), only for raw memory; §43.5.

[6] Prefer vector to uses of malloc() and realloc(); §43.5.

[7] Beware that the C standard library does not know about constructors and destructors; §43.5.

[8] Prefer <chrono> to <ctime> for timing; §43.6.

[9] For flexibility, ease of use, and performance, prefer sort() over qsort(); §43.7.

[10] Don’t use exit(); instead, throw an exception; §43.7.

[11] Don’t use longjmp(); instead, throw an exception; §43.7.

44. Compatibility

You go ahead and follow your customs, and I’ll follow mine.

– C. Napier

• Introduction

• C++11 Extensions

Language Features; Standard-Library Components; Deprecated Features; Coping with Older C++ Implementations

• C/C++ Compatibility

C and C++ Are Siblings; “Silent” Differences; C Code That Is Not C++; C++ Code That Is Not C

• Advice

44.1. Introduction

This chapter discusses the differences between Standard C++ (as defined by ISO/IEC 14882-2011) and earlier versions (such as ISO/IEC 14882-1998), Standard C (as defined by ISO/IEC 9899-2011) and earlier versions (such as Classic C). The purposes are

• To concisely list what is new in C++11

• To document differences that can cause problems for a programmer

• To point to ways of dealing with problems

Most compatibility problems surface when people try to upgrade a C program to a C++ program, try to port a C++ program from an older version of C++ to a newer one (e.g., C++98 to C++11), or try to compile C++ using modern features with an older compiler. The aim here is not to enumerate every possible compatibility problem but rather to list the most frequently occurring problems and present their standard solutions.

When you look at compatibility issues, a key question to consider is the range of implementations under which a program needs to work. For learning C++, it makes sense to use the most complete and helpful implementation. For delivering a product, a more conservative strategy might be in order to maximize the number of systems on which the product can run. In the past, this has been a reason (and more often just an excuse) to avoid C++ features deemed novel. However, implementations are converging, so the need for portability across platforms is less cause for extreme caution than it once was.

44.2. C++11 Extensions

First, I list the language features and standard-library components that have been added to C++ for the C++11 standard. Next, I discuss ways of coping with older versions (notably C++98).

44.2.1. Language Features

Looking at a list of language features can be quite bewildering. Remember that a language feature is not meant to be used in isolation. In particular, most features that are new in C++11 make no sense in isolation from the framework provided by older features. The order is roughly that of first occurrence in this book:

[1] Uniform and general initialization using {}-lists (§2.2.2, §6.3.5)

[2] Type deduction from initializer: auto (§2.2.2, §6.3.6.1)

[3] Prevention of narrowing (§2.2.2, §6.3.5)

[4] Generalized and guaranteed constant expressions: constexpr (§2.2.3, §10.4, §12.1.6)

[5] Range-for-statement (§2.2.5, §9.5.1)

[6] Null pointer keyword: nullptr (§2.2.5, §7.2.2)

[7] Scoped and strongly typed enums: enum class (§2.3.3, §8.4.1)

[8] Compile-time assertions: static_assert (§2.4.3.3, §24.4)

[9] Language mapping of {}-list to std::initializer_list (§3.2.1.3, §17.3.4)

[10] Rvalue references (enabling move semantics; §3.3.2, §7.7.2)

[11] Nested template arguments ending with >> (no space between the >s; §3.4.1)

[12] Lambdas (§3.4.3, §11.4)

[13] Variadic templates (§3.4.4, §28.6)

[14] Type and template aliases (§3.4.5, §6.5, §23.6)

[15] Unicode characters (§6.2.3.2, §7.3.2.2)

[16] long long integer type (§6.2.4)

[17] Alignment controls: alignas and alignof (§6.2.9)

[18] The ability to use the type of an expression as a type in a declaration: decltype (§6.3.6.1)

[19] Raw string literals (§7.3.2.1)

[20] Generalized POD (§8.2.6)

[21] Generalized unions (§8.3.1)

[22] Local classes as template arguments (§11.4.2, §25.2.1)

[23] Suffix return type syntax (§12.1.4)

[24] A syntax for attributes and two standard attributes: [[carries_dependency]] (§41.3) and [[noreturn]] (§12.1.7)

[25] Preventing exception propagation: the noexcept specifier (§13.5.1.1)

[26] Testing for the possibility of a throw in an expression: the noexcept operator (§13.5.1.1)

[27] C99 features: extended integral types (i.e., rules for optional longer integer types; §6.2.4); concatenation of narrow/wide strings; __func__ and __STDC_HOSTED__ (§12.6.2); _Pragma(X) (§12.6.3); vararg macros and empty macro arguments (§12.6)

[28] inline namespaces (§14.4.6)

[29] Delegating constructors (§17.4.3)

[30] In-class member initializers (§17.4.4)

[31] Control of defaults: default (§17.6) and delete (§17.6.4)

[32] Explicit conversion operators (§18.4.2)

[33] User-defined literals (§19.2.6)

[34] More explicit control of template instantiation: extern templates (§26.2.2)

[35] Default template arguments for function templates (§25.2.5.1)

[36] Inheriting constructors (§20.3.5.1)

[37] Override controls: override and final (§20.3.4)

[38] Simpler and more general SFINAE rule (§23.5.3.2)

[39] Memory model (§41.2)

[40] Thread-local storage: thread_local (§42.2.8)

I have not tried to list every minute change to C++98 in C++11. A historical perspective on these features can be found in §1.4.

44.2.2. Standard_Library Components

The C++11 additions to the standard library come in two forms: new components (such as the regular expression matching library) and improvements to C++98 components (such as move constructors for containers).

[1] initializer_list constructors for containers (§3.2.1.3, §17.3.4, §31.3.2)

[2] Move semantics for containers (§3.3.1, §17.5.2, §31.3.2)

[3] A singly-linked list: forward_list (§4.4.5, §31.4.2)

[4] Hash containers: unordered_map, unordered_multimap, unordered_set, and unordered_multiset (§4.4.5, §31.4.3)

[5] Resource management pointers: unique_ptr, shared_ptr, and weak_ptr (§5.2.1, §34.3)

[6] Concurrency support: thread (§5.3.1, §42.2), mutexes (§5.3.4, §42.3.1), locks (§5.3.4, §42.3.2), and condition variables (§5.3.4.1, §42.3.4)

[7] Higher-level concurrency support: packaged_thread, future, promise, and async() (§5.3.5, §42.4)

[8] tuples (§5.4.3, §28.5, §34.2.4.2)

[9] Regular expressions: regex (§5.5, Chapter 37)

[10] Random numbers: uniform_int_distribution, normal_distribution, random_engine, etc. (§5.6.3, §40.7)

[11] Integer type names, such as int16_t, uint32_t, and int_fast64_t (§6.2.8, §43.7)

[12] A fixed-sized contiguous sequence container: array (§8.2.4, §34.2.1)

[13] Copying and rethrowing exceptions (§30.4.1.2)

[14] Error reporting using error codes: system_error (§30.4.3)

[15] emplace() operations for containers (§31.3.6)

[16] Wide use of constexpr functions

[17] Systematic use of noexcept functions

[18] Improved function adaptors: function and bind() (§33.5)

[19] string to numeric value conversions (§36.3.5)

[20] Scoped allocators (§34.4.4)

[21] Type traits, such as is_integral and is_base_of (§35.4)

[22] Time utilities: duration and time_point (§35.2)

[23] Compile-time rational arithmetic: ratio (§35.3)

[24] Abandoning a process: quick_exit (§15.4.3)

[25] More algorithms, such as move(), copy_if(), and is_sorted() (Chapter 32)

[26] Garbage collection ABI (§34.5)

[27] Low-level concurrency support: atomics (§41.3)

More information about the standard library can be found in

• Chapter 4, Chapter 5, and Part IV

• Implementation technique examples: vector (§13.6), string (§19.3), and tuple (§28.5)

• The emerging specialized C++11 standard-library literature, such as [Williams,2012]

• A brief historical perspective can be found in §1.4.

44.2.3. Deprecated Features

By deprecating a feature, the standards committee expresses the wish that the feature will go away (§iso.D). However, the committee does not have a mandate to immediately remove a heavily used feature – however redundant or dangerous it may be. Thus, a deprecation is a strong hint to avoid the feature. It may disappear in the future. Compilers are likely to issue warnings for uses of deprecated features.

• Generation of the copy constructor and the copy assignment is deprecated for a class with a destructor.

• It is no longer allowed to assign a string literal to a char* (§7.3.2).

• C++98 exception specifications are deprecated:

     void f() throw(X,Y); // C++98; now deprecated

The support facilities for exception specifications, unexcepted_handler, set_unexpected(), get_unexpected(), and unexpected(), are similarly deprecated. Instead, use noexcept (§13.5.1.1).

• Some C++ standard-library function objects and associated functions are deprecated: unary_function, binary_function, pointer_to_unary_function, pointer_to_binary_function, ptr_fun(), mem_fun_t, mem_fun1_t, mem_fun_ref_t, mem_fun_ref1_t, mem_fun(), const_mem_fun_t, const_mem_fun1_t, const_mem_fun_ref_t, const_mem_fun_ref1_t, binder1st, bind1st(), binder2nd, bind2nd(). Instead, use function and bind() (§33.5).

• The auto_ptr is deprecated. Instead, use unique_ptr (§5.2.1, §34.3.1).

In addition, the committee did remove the essentially unused export feature, because it was complex and not shipped by the major vendors.

C-style casts should have been deprecated when the named casts (§11.5.2) were introduced. Programmers should seriously consider banning C-style casts from their own programs. Where explicit type conversion is necessary, static_cast, reinterpret_cast, const_cast, or a combination of these can do what a C-style cast can. The named casts should be preferred because they are more explicit and more visible.

44.2.4. Coping with Older C++ Implementations

C++ has been in constant use since 1983 (§1.4). Since then, several versions have been defined, and many separately developed implementations have emerged. The fundamental aim of the standards effort was to ensure that implementers and users would have a single definition of C++ to work from. From 1998, programmers could rely on the ISO C++98 standard, and now we have the ISO C++11 standard.

Unfortunately, it is not uncommon for people to take their first serious look at C++ using a five-year-old implementation. The typical reason is that such implementations are widely available and free. Given a choice, no self-respecting professional would touch such an antique. Also, many modern quality implementations are available for free. For a novice, older implementations come with serious hidden costs. The lack of language features and library support means that the novice must struggle with problems that have been eliminated in newer implementations. Using a feature-poor older implementation, especially if guided by an antique tutorial, warps the novice’s programming style and gives a biased view of what C++ is. The best subset of C++ to initially learn is not the set of low-level facilities (and not the common C and C++ subset; see §1.3). In particular, to ease learning and to get a good initial impression of what C++ programming can be, I recommend relying on the standard library, and to heavily use classes, templates, and exceptions.

There are still places, where for political reasons or lack of suitable tool chains, C is preferred over C++. If you must use C, write in the common subset of C and C++. That way, you gain some type safety, increase portability, and will be ready when C++ features become available to you. See also §1.3.3.

Use an implementation that conforms to the standard wherever possible, and minimize the reliance on implementation-defined and undefined aspects of the language. Design as if the full language were available, and only use workarounds when necessary. This leads to better organized and more maintainable programs than designing for a lowest-common-denominator subset of C++. Also, use implementation-specific language extensions only when necessary. See also §1.3.2.

44.3. C/C++ Compatibility

With minor exceptions, C++ is a superset of C (meaning C11, defined by ISO/IEC 9899:2011(E)). Most differences stem from C++’s greater emphasis on type checking. Well-written C programs tend to be C++ programs as well. A compiler can diagnose every difference between C++ and C. The C99/C++11 incompatibilities are listed in §iso.C. At the time of writing, C11 is still very new and most C code is Classic C or C99.

44.3.1. C and C++ Are Siblings

Classic C has two main descendants: ISO C and ISO C++. Over the years, these languages have evolved at different paces and in different directions. One result of this is that each language provides support for traditional C-style programming in slightly different ways. The resulting incompatibilities can make life miserable for people who use both C and C++, for people who write in one language using libraries implemented in the other, and for implementers of libraries and tools for C and C++.

How can I call C and C++ siblings? Clearly, C++ is a descendant of C. However, look at a simplified family tree:

A solid line means a massive inheritance of features, a dashed line a borrowing of major features, and a dotted line a borrowing of minor features. From this, ISO C and ISO C++ emerge as the two major descendants of K&R C, and as siblings. Each carries with it the key aspects of Classic C, and neither is 100% compatible with Classic C. I picked the term “Classic C” from a sticker that used to be affixed to Dennis Ritchie’s terminal. It is K&R C plus enumerations and struct assignment.

Incompatibilities are nasty for programmers in part because they create a combinatorial explosion of alternatives. Consider a simple Venn diagram:

The areas are not to scale. Both C++11 and C11 have most of K&R C as a subset. C++11 has most of C11 as a subset. There are features belonging to most of the distinct areas. For example:

Note that differences between C and C++ are not necessarily the result of changes to C made in C++. In several cases, the incompatibilities arise from features adopted incompatibly into C long after they were common in C++. Examples are the ability to assign a T* to a void* and the linkage of global consts [Stroustrup,2002]. Sometimes, a feature was even incompatibly adopted into C after it was part of the ISO C++ standard, such as details of the meaning of inline.

44.3.2. “Silent” Differences

With a few exceptions, programs that are both C++ and C have the same meaning in both languages. Fortunately, these exceptions (often referred to as silent differences) are rather obscure:

• In C, the size of a character constant and of an enumeration equals sizeof(int). In C++, sizeof('a') equals sizeof(char).

• In C, an enumerator is an int, whereas a C++ implementation is allowed to choose whatever size is most appropriate for an enumeration (§8.4.2).

• In C++, the name of a struct is entered into the scope in which it is declared; in C, it is not. Thus, the name of a C++ struct declared in an inner scope can hide the name in an outer scope. For example:

Click here to view code image

     int x[99];
     void f()
     {
          struct x { int a; };
          sizeof(x);             /* size of the array in C, size of the struct in C++ */
          sizeof(struct x);      /* size of the struct */
     }

44.3.3. C Code That Is Not C++

The C/C++ incompatibilities that cause most real problems are not subtle. Most are easily caught by compilers. This section gives examples of C code that is not C++. Most are deemed poor style or even obsolete in modern C. A comprehensive list of incompatibilities can be found in §iso.C.

• In C, most functions can be called without a previous declaration. For example:

Click here to view code image

     int main()     // not C++; poor style in C
     {
          double sq2 = sqrt(2);                       /* call undeclared function */
          printf("the square root of 2 is %g\n",sq2); /* call undeclared function */
     }

Complete and consistent use of function declarations (function prototypes) is generally recommended for C. Where that sensible advice is followed, and especially where C compilers provide options to enforce it, C code conforms to the C++ rule. Where undeclared functions are called, you have to know the functions and the rules for C pretty well to know whether you have made a mistake or introduced a portability problem. For example, the previous main() contains at least two errors as a C program.

• In C, a function declared without specifying any argument types can take any number of arguments of any type at all.

Click here to view code image

     void f();   /* argument types not mentioned */

     void g()
     {
          f(2);     /* poor style in C; not C++ */
     }

Such use is deemed obsolete in ISO C.

• In C, functions can be defined using a syntax that optionally specifies argument types after the list of arguments:

     void f(a,p,c) char *p; char c; { /* ... */ }          /* C; not C++ */

Such definitions must be rewritten:

     void f(int a, char* p, char c) { /* ... */ }

• In C, structs can be defined in return type and argument type declarations. For example:

Click here to view code image

     struct S { int x,y; } f();         /* C; not C++ */
     void g(struct S { int x,y; } y);   /* C; not C++ */

The C++ rules for defining types make such declarations useless, and they are not allowed.

• In C, integers can be assigned to variables of enumeration type:

Click here to view code image

     enum Direction { up, down };
     enum Direction d = 1;             /* error: int assigned to Direction; OK in C */

• C++ provides many more keywords than C does. If one of these appears as an identifier in a C program, that program must be modified to make it a C++ program:

In addition, the word export is reserved for future use. C99 adopted inline.

• In C, some of the C++ keywords are macros defined in standard headers:

This implies that in C they can be tested using #ifdef, redefined, etc.

• In C, a global data object may be declared several times in a single translation unit without using the extern specifier. As long as at most one such declaration provides an initializer, the object is considered defined only once. For example:

Click here to view code image

     int i;
     int i; /* just another declaration of a single integer "i"; not C++ */

In C++, an entity must be defined exactly once; §15.2.3.

• In C, a void* may be used as the right-hand operand of an assignment to or initialization of a variable of any pointer type; in C++ it may not (§7.2.1). For example:

Click here to view code image

     void f(int n)
     {
          int* p = malloc(n*sizeof(int)); /* not C++; in C++, allocate using "new" */
     }

This is probably the single most difficult incompatibility to deal with. Note that the implicit conversion of a void* to a different pointer type is not in general harmless:

Click here to view code image

     char ch;
     void* pv = &ch;
     int* pi = pv;         // not C++
     *pi = 666;            // overwrite ch and other bytes near ch

If you use both languages, cast the result of malloc() to the right type. If you use only C++, avoid malloc().

• In C, the type of a string literal is “array of char,” but in C++ it is “array of const char,” so:

Click here to view code image

     char* p = "a string literal is not mutable";      // error in C++; OK in C
     p[7] = 'd';

• C allows transfer of control to a labeled statement (a switch or a goto; §9.6) to bypass an initialization; C++ does not. For example:

     goto foo;                // OK in C; not C++
     // ...
     {
          int x = 1;
     foo:
          if (x!=1) abort();
          /* ... */
     }

• In C, a global const by default has external linkage; in C++ it does not and must be initialized, unless explicitly declared extern (§7.5). For example:

     const int ci;     // OK in C; const not initialized error in C++

• In C, names of nested structures are placed in the same scope as the structure in which they are nested. For example:

Click here to view code image

     struct S {
          struct T { /* ... */ } t;
          // ...
     };

     struct T x;      // OK in C, meaning "S::T x;"; not C++

• In C++, the name of a class is entered into the scope in which it is declared; thus it cannot have the same name as another type declared in that scope. For example:

Click here to view code image

     struct X { /* ... */ };
     typedef int X;          // OK in C; not C++

• In C, an array can be initialized by an initializer that has more elements than the array requires. For example:

Click here to view code image

     char v[5] = "Oscar";     // OK in C, the terminating 0 is not used; not C++
     printf("%s",v);          // likely disaster

44.3.3.1. “Classic C” Problems

Should you need to upgrade Classic C programs (“K&R C”) or C89 programs, a few more problems will emerge:

• C89 does not have the // comments (though most C89 compilers added them):

     int x;   // not C89

• In C89, the type specifier defaults to int (known as “implicit int”). For example:

Click here to view code image

     const a = 7;   /* in C89, type int assumed; not C++ or C99 */

     f() /* f()'s return type is int by default; not C++ or C99 */
     {
         /* .. */
     }

44.3.3.2. C Features Not Adopted by C++

A few additions to C99 (compared with C89) were deliberately not adopted in C++:

[1] Variable-length arrays (VLAs); use vector or some form of dynamic array

[2] Designated initializers; use constructors

The C11 features are too new to have been considered for C++, except for features such as the memory model and atomics (§41.3) that came from C++.

44.3.4. C++ Code That Is Not C

This section lists facilities offered by C++ but not by C (or adopted by C years after their introduction in C++, as marked, so that they may be missing in old C compilers). The features are sorted by purpose. However, many classifications are possible, and most features serve multiple purposes, so this classification should not be taken too seriously.

• Features primarily for notational convenience:

[1] // comments (§2.2.1, §9.7); added to C99

[2] Support for restricted character sets (§iso.2.4); partially added to C99

[3] Support for extended character sets (§6.2.3); added to C99

[4] Non-constant initializers for objects in static storage (§15.4.1)

[5] const in constant expressions (§2.2.3, §10.4.2)

[6] Declarations as statements (§9.3); added to C99

[7] Declarations in for-statement initializers (§9.5); added to C99

[8] Declarations in conditions (§9.4.3)

[9] Structure names need not be prefixed by struct (§8.2.2)

[10] Anonymous unions (§8.3.2); added to C11

• Features primarily for strengthening the type system:

[1] Function argument type checking (§12.1); partially added to C (§44.3.3)

[2] Type-safe linkage (§15.2, §15.2.3)

[3] Free-store management using new and delete (§11.2)

[4] const (§7.5, §7.5); partially added to C

[5] The Boolean type bool (§6.2.2); partially added to C99

[6] Named casts (§11.5.2)

• Facilities for user-defined types:

[1] Classes (Chapter 16)

[2] Member functions (§16.2.1) and member classes (§16.2.13)

[3] Constructors and destructors (§16.2.5, Chapter 17)

[4] Derived classes (Chapter 20, Chapter 21)

[5] virtual functions and abstract classes (§20.3.2, §20.4)

[6] Public/protected/private access control (§16.2.3, §20.5)

[7] friends (§19.4)

[8] Pointers to members (§20.6)

[9] static members (§16.2.12)

[10] mutable members (§16.2.9.3)

[11] Operator overloading (Chapter 18)

[12] References (§7.7)

• Features primarily for program organization (in addition to classes):

[1] Templates (Chapter 23)

[2] Inline functions (§12.1.3); added to C99

[3] Default arguments (§12.2.5)

[4] Function overloading (§12.3)

[5] Namespaces (§14.3.1)

[6] Explicit scope qualification (operator ::; §6.3.4)

[7] Exceptions (§2.4.3.1, Chapter 13)

[8] Run-Time Type Identification (Chapter 22)

[9] Generalized constant expressions (constexpr; §2.2.3, §10.4, §12.1.6)

The C++11 features listed in §44.2 are not in C.

The keywords added by C++ (§44.3.3) can be used to spot most C++-specific facilities. However, some facilities, such as function overloading and consts in constant expressions, are not identified by a keyword.

C++’s linking for functions is type-safe, whereas C’s rules do not require type safety when linking functions. This implies that on some (most?) implementations, a C++ function must be declared extern "C" to be compiled as C++ and also conform to C calling conventions (§15.2.5).

For example:

Click here to view code image

double sin(double);              // may not link to C code
extern "C" double cos(double);   // will link to C code

The __cplusplus macro can be used to determine whether a program is being processed by a C or a C++ compiler (§15.2.5).

In addition to the features listed, the C++ library (§30.1.1, §30.2) is mostly C++-specific. The C standard library offers type-generic macros in <tgmath.h> and _Complex number support in <complex.h>, approximating <complex>.

C also offers <stdbool.h>, offering _Bool and the alias bool to approximate C++’s bool.

44.4. Advice

[1] Before using a new feature in production code, try it out by writing small programs to test the standards conformance and performance of the implementations you plan to use; §44.1.

[2] For learning C++, use the most up-to-date and complete implementation of Standard C++ that you can get access to; §44.2.4.

[3] The common subset of C and C++ is not the best initial subset of C++ to learn; §1.2.3, §44.2.4.

[4] Prefer standard facilities to nonstandard ones; §36.1, §44.2.4.

[5] Avoid deprecated features such as throw-specifications; §44.2.3, §13.5.1.3.

[6] Avoid C-style casts; §44.2.3, §11.5.

[7] “Implicit int” has been banned, so explicitly specify the type of every function, variable, const, etc.; §44.3.3.

[8] When converting a C program to C++, first make sure that function declarations (prototypes) and standard headers are used consistently; §44.3.3.

[9] When converting a C program to C++, rename variables that are C++ keywords; §44.3.3.

[10] For portability and type safety, if you must use C, write in the common subset of C and C++; §44.2.4.

[11] When converting a C program to C++, cast the result of malloc() to the proper type or change all uses of malloc() to uses of new; §44.3.3.

[12] When converting from malloc() and free() to new and delete, consider using vector, push_back(), and reserve() instead of realloc(); §3.4.2, §43.5.

[13] When converting a C program to C++, remember that there are no implicit conversions from ints to enumerations; use explicit type conversion where necessary; §44.3.3, §8.4.

[14] A facility defined in namespace std is defined in a header without a suffix (e.g., std::cout is declared in <iostream>); §30.2.

[15] Use <string> to get std::string (<string.h> holds the C-style string functions); §15.2.4.

[16] For each standard C header <X.h> that places names in the global namespace, the header <cX> places the names in namespace std; §15.2.2.

[17] Use extern "C" when declaring C functions; §15.2.5.

Index

Knowledge is of two kinds. We know a subject ourselves, or we know where we can find information on it.

– Samuel Johnson

Token

!

logical not operator 274

logical_not 966

not 258

valarray 1170

!=

bitset 980

container 902

duration 1012

error_category 877

error_code 875

iterator 959

match_results 1060

not-equal operator 41

not_eq 258

not_equal_to 966

pair 984

regex_iterator 1067

regex_token_iterator 1068

rel_ops 1029

shared_ptr 992

string 1040

sub_match 1058

time_point 1014

tuple 985

unique_ptr 987

valarray 1170

″″

empty string 177

operator 558

″

double quote 176

prefix 147

string literal 39, 176

## 338

# 338

,

and [] 183

no order 531

operator 260

predefined 531

prohibiting 531

$

character 155

regex 1052

$$ the $ character 1061

$& match 1061

$’ suffix 1061

$‘ prefix 1061

$1 first submatch 1061

%

duration 1012

format character 1255

modulus 966

modulus operator 40

remainder operator 40

valarray 1170

%=

duration 1011

operator 42

valarray 1167

&

address-of operator 45, 172

and 258

bitset 979

bitwise and operator 274

predefined 531

prohibiting 531

reference to 45, 190

valarray 1170

&&

bitand 258

logical and operator 260, 274

logical_and 966

no order 531

rvalue reference 75, 194

valarray 1170

&=

and_eq 258

atomic<T> 1203

bitset 979

valarray 1167

’

character literal 143

prefix 147

single quote 143

(, regex 1052

()

and initializer 162

argument list 307

call operator 80, 550

function call 315

initialization problem 492

Matrix 833, 846

packaged_task 1238

vs. {} initialization 160

(? lazy match 1056

), regex 1052

*

and [], -> and 553

contents-of operator 45

dereferencing operator 172

duration 1012

for pointer 181

indirection operator 172

iterator 959

Matrix 839

multiplies 966

multiply operator 40

pointer to 44

regex 1052

shared_ptr 992

unary 172

unique_ptr 987

valarray 1170

**, exponentiation 529

*=

duration 1011

scaling operator 42

valarray 1167

+

duration 1011–1012

for pointer 181

iterator

Matrix 836–837

plus 966

plus operator 40

pointer 182

regex 1052

string 1041

time_point 1014

user-defined operator 532, 575

valarray 1170

++

atomic<T> 1203

duration 1011

for pointer 181

increment operator 42, 276

iterator 959

regex_iterator 1067

regex_token_iterator 1068

user-defined operator 531, 554

+=

atomic<T> 1203

duration 1011

iterator 959

Matrix 836

operator 42, 244

string 1041

time_point 1014

user-defined operator 531, 536, 575

valarray 1167

-

duration 1011–1012

for pointer 181

iterator 959

minus 966

minus operator 40

negate 966

pointer 182

time_point 1014

valarray 1170

--

atomic<T> 1203

decrement operator 42, 276

duration 1011

for pointer 181

iterator 959

user-defined operator 554

-=

atomic<T> 1203

duration 1011

iterator

operator 244

time_point 1014

valarray 1167

->

dereference operator 552

iterator 959

member access operator 202

operator 466

regex_iterator 1067

regex_token_iterator 1068

required 758

return type 308

unique_ptr 987

user-defined operator 552

->*

operator 609

pointer to member 607

->~ 487

-1 142

.

floating-point 146

infix 147

member access 48

member access operator 202

operator 466

regex 1052

.*

operator 609

pointer to member 607

...

class 812

ellipsis 321

exception 369

typename 812

/

divide operator 40

divides 966

duration 1012

valarray 1170

/* comment 239, 338

// comment 39, 238

/=

duration 1011

scaling operator 42

valarray 1167

:

arithmetic-if ? 275

bit-field 212

derived class 579

for and 233

label 226

private 605

protected 605

public 66, 605

::

and virtual function, operator 589

namespace and 392

operator 466, 582

scope resolution operator 158, 468

using 403

::*, pointer to member 607

;, semicolon 153, 202, 226

<<=

bitset 979

valarray 1167

<<

bitset 979

error_code 875

example, Season 1121, 1152

exception and 1132

money_put and 1138

num_put and 1131

output operator 39

output ostream 91

resolution 533

shared_ptr 992

string 1042

tuple 817

valarray 1170

<=

container 902

duration 1012

less-than-or-equal operator 41

less_equal 966

pair 984

rel_ops 1029

shared_ptr 992

string 1040

sub_match 1058

time_point 1014

tuple 985

unique_ptr 987

valarray 1170

<

comparison 891

container 902

duration 1012

error_category 877

error_code 875

iterator 959

less 966

less-than operator 41

pair 984

shared_ptr 992

string 1040

sub_match 1058

time_point 1014

tuple 985

unique_ptr 987

valarray 1170

<>

specialization 682

template 731, 737

=

0 65, 598

and == 41

and ==, equivalence 510

atomic<T> 1200

auto 42

container 896

default 518, 524

delete 524

delete vs. missing 525

duration 1010

future 1241

independence 510

initialization problem 492

initializer 41

match_results 1060

Matrix 832

nested_exception 871

packaged_task 1238

pair 983

predefined 531

prohibiting 531

promise 1237

regex 1057

regex_iterator 1067

regex_token_iterator 1068

semantics 510

string 1039

sub_match 1058

time_point 1013

tuple 985

user-defined operator 575

valarray 1167, 1174

weak_ptr 994

=*

regex_iterator 1067

regex_token_iterator 1068

==

= and 41

bitset 980

container 902

duration 1012

equal operator 41

equal_to 966

equality without 892

equivalence = and 510

error_category 877

error_code 875

iterator 959

match_results 1060

pair 984

pointer 177

regex_iterator 1067

regex_token_iterator 1068

shared_ptr 992

string 1040

sub_match 1058

time_point 1014

tuple 985

unique_ptr 987

valarray 1170

>

container 902

duration 1012

greater 966

greater-than operator 41

iterator 959

pair 984

parentheses and 788

rel_ops 1029

shared_ptr 992

string 1040

sub_match 1058

time_point 1014

tuple 985

unique_ptr 987

valarray 1170

>=

container 902

duration 1012

greater-than-or-equal operator 41

greater_equal 966

iterator 959

pair 984

rel_ops 1029

shared_ptr 992

string 1040

sub_match 1058

time_point 1014

tuple 985

valarray 1170

>>

bitset 979

example, Season 1121, 1152

input cin 247

input istream 93

money_get and 1139

num_get and 1133

string 1042

valarray 1170

>>=

bitset 979

valarray 1167

?

:, arithmetic-if 275

regex 1052

?:

conditional expression 264, 275

operator 275

[, regex 1052

[&], lambda 294

[=], lambda 294

[]

, and 183

-> and * and 553

array 976

array of 44

bitset 979

container 900

design of 562

iterator

lambda 294

map 910

match_results 1060

Matrix 833

string 1041

subscript operator 50

subscript operator 174

valarray 1168

\”, double quote 143

\

backslash 39, 143

escape character 143

string literal 177

\’, single quote 143

-> and * and [] 553

, regex 1052

bit_xor 966

bitset 979

bitwise exclusive or operator 274

regex 1052

valarray 1170

xor 258

^=

atomic<T> 1203

bitset 979

valarray 1167

xor_eq 258

_

and suffix 823

underscore character 155

_1, placeholders 967

_2, placeholders 967

{, regex 1052

{}

ambiguity 286

and auto 289

block 157

construction 299

grouping 39

initialization 456, 489, 492

initialization, () vs. 160

initialization, Matrix 843

initializer 41, 175, 202

list 162, 286

list argument 319

Matrix 832

qualified 287

type of 289

unqualified 288

use of 159

|

bit_or 966

bitset 979

bitwise or operator 274

or 258

regex 1052

valarray 1170

|=

atomic<T> 1203

bitset 979

or_eq 258

valarray 1167

||

bitor 258

logical or operator 260, 274

logical_or 966

no order 531

valarray 1170

regex 1052

bitset 979

bitwise complement operator 274

compl 258

destructor 63, 485

valarray 1170

0

= 65, 598

constant-expression 269

false and 139

null pointer 269

nullptr NULL 46

octal 145

octal digit 144

prefix 147

zero null 174

0X

hexadecimal 145

hexadecimal digit 144

0x prefix 147

1, true and 139

A

\a, alert 143

a, file mode 1254

%a format 1256

%A format 1256

ABA problem 1202

ABI and layout 211

abort() 372, 443

abs() 1163–1164

<cstdlib> 865

valarray 1170

absence of initializer 161

abstract

base class 598

class 598

class 65

class and design 617

class constructor 598

class destructor 598

class, use of 622

type 65

abstraction

data 11

elegant and efficient 9

mechanisms 5

access 571

., member 48

control 453, 600

control and base class 605

control and multiple inheritance 606

control, using-declaration and 606

function 216

Matrix 846

member 466

namespace 403

operator, design of 562

range 964

time, memory 1195

to facet 1119

accessor 541

accumulate() 701, 1177

acos(), valarray 1170

acquire

mutex 1220

operation 1199

acquisition

RAII, resource 112

resource 354

ad hoc concept 708

adaptor

container 887

function 967

iterator 960

adaptors

container 920

sequence 920

add_const 1023

adding

facet to locale 1117

to container 963

to sequence 963

to standard library 866

addition, pointer 182

add_lvalue_reference 1023

Add_reference 816

address 172

constant expression 267

addressing, unit of 172

address-of operator & 45, 172

add_rvalue_reference 1023

add_volatile 1023

adjacent_difference() 1179

adjacent_find() 933

ADL 754

– see argument-dependent lookup

and template 754

overaggressive 754

surprise 397

adopt_lock_t 1225, 1227

advance(), iterator 959

advice 31

aggregate

array 202

struct 202

aggregate() 701

aims

C++ design 12

C++11 27

alert \a 143

algorithm 102, 700

and iterator 927

and string 1044

complexity 931

container 103, 109, 411, 928

container, iterator 953

generalized numeric 1176

lifting and 701

modifying 935

nonmodifying 932

set 947

standard library 109

STL 927

<algorithm> 863, 927

alias

namespace 406

reopen, namespace 398

template 694

template member 676

trait 788

type 167, 784

typedef 168

using 83, 167

alignas, alignment 151

aligned_storage 1025

aligned_union 1025

alignment 151, 203

alignas 151

alignof 151

alignment_of 1022

alignof, alignment 151

all, catch 370

allocate array 281

allocate()

allocator 997

allocator_traits 998

allocateshared(), shared_ptr 992

allocation 63

and deallocation 277, 556

unit of 172

allocator 995

scoped 1000

allocator

allocate() 997

construct() 997

constructor 997

deallocate() 997

destroy() 997

max_size() 997

rebind 997

allocator_arg_t, tuple 985

allocator_traits

allocate() 998

construct() 998

deallocate() 998

destroy() 998

difference_type 998

propagate_on_* 998

allocator_type 896

all_of() 932

almost container 973

alnum, regex 1054

alpha, regex 1054

[[:alpha:]] letter 1054

alternative

implementation 620, 734

to macro 338

alternatives, lambda 291

always_noconv(), codecvt 1148

ambiguity

{} 286

point-of-instantiation 752

resolution, multiple inheritance 627

template 691

ambiguous type conversion 546

amortized complexity 895

analysis, requirements 704

and

& 258

operator &, bitwise 274

operator &&, logical 260, 274

and_eq, &= 258

Annemarie 180

anonymous

union 213, 216

union example 564

ANSI C++ 25

any(), bitset 980

Anya 500

any_of() 932

append(), string 1044

application operator 550

apply()

Matrix 837

valarray 1169

archetype 717

argc, main() argv 253

argument

{} list 319

array 318–319

array function 184

capture and 295

command-line 253

deducing template 685, 687

default 324

dependency on template 746

explicit template 686

formal 315

function 315

function template 686

int template 685

lambda template 727

list () 307

passing, function 315, 482

reference 191, 316

rvalue reference 317

template 722

template literal type 724

template operation as 725

template pointer 724

template string 724

template type 722

template value 724

to main() 253

type check, function 315

type conversion, function 315

type, difference from C 1274

types, virtual function 586

unnamed 308

value, example of default 457

variable number of 321

argument-dependent lookup 395, 754

arguments

constexpr function 266

overload resolution for multiple 329

reference 266

argv argc, main() 253

arithmetic

conversions, usual 258, 271

Matrix 836

mixed-mode 536

operation 966

operator 40

pointer 181, 276

ratio compile-time 1017

type 139

vector 131, 1166

arithmetic-if ?: 275

ARM 25

array 174

aggregate 202

allocate 281

argument 318–319

array of 183

array vs. 976

assignment 180

associative 550

by string, initialization of 176

deallocate 281

fixed-length 174

function argument 184

initializer 175

initializer, difference from C 1276

layout 183, 1172

multidimensional 1172, 1175

numeric 1166

of [] 44

of array 183

of reference 190

passing multidimensional 185

pointer and 179, 318

T[n] built-in 887

unique_ptr 988

valarray and 1166

zero-terminated 175

array 208, 974

[] 976

contiguous 887

data() 976

fill() 974

initialize 975

operation 974

representation 890

size() 976

swap() 974

tuple_element 977

tuple_size 977

vs. array 976

vs. vector 976

<array> 863

arrow operator 552

ASCII 137

character set 143

UTF-8 and 179

asin() 1163

valarray 1170

assembler 14, 23

Assert example 361

assert() 360

<cassert> 873

NDBUG 873

Assert::dynamic() 361

<assert.h> 864

assertion 360

static_assert 57

assign, regex 1057

assign()

char_traits 1035

container 896

error_code 875

string 1044

Assignable 716

assignment

and exception 381

and slicing 513

and template, copy 679

array 180

copy 73, 381, 482, 508

function call and 192

move 75, 482, 515

must be member 531

of class object 507

operator 244, 536

to self 382, 508

valarray 1167, 1174

Assoc example 550

associative

array 550

array – see map

container 886, 909

container, ordered 909

container, unordered 887, 913

associativity of operator 257

asymptotic complexity 895

async()

launch 122

launch::async 1245

launch::deferred 1245

task launcher 1245

throws system_error 868

asynchronous event 348

at() 97

container 900

map 910

string 1041

atan() 1163

valarray 1170

atan2() 1163

valarray 1170

atexit()

and destructor 444

and exception 352

atomic operation 1196, 1198

atomic type 1200

<atomic> 865

atomic_compare_exchange_weak() 1204

atomic_flag

ATOMIC_FLAG_INIT 1205

clear() 1205

test_and_set() 1205

ATOMIC_FLAG_INIT, atomic_flag 1205

atomic_init() 1204

atomic_is_lock_free( 1204

atomic_load() 1204

atomic_signal_fence(), fence 1206

atomic_store() 1204

atomic<T* > 1204

atomic<T>

|= 1203

^= 1203

= 1200

-= 1203

-- 1203

+= 1203

++ 1203

&= 1203

compare_exchange_strong() 1200

compare_exchange_weak() 1200

constructor 1200

exchange() 1200

fetch_add() 1203

fetch_and() 1203

fetch_or() 1203

fetch_sub() 1203

fetch_xor() 1203

is_lock_free() 1200

load() 1200

store() 1200

atomic_thread_fence(), fence 1206

AT&T Bell Laboratories 25

atto 1018

attribute 314

auto 163

= 42

{} and 289

decltype 163

use of 160, 163

automatic

object 167

storage 167

auto_ptr, deprecated 1270

avoiding data race 1197

awk, regex 1057

axiom 713

B

\b, backspace 143

b, file mode 1254

\B, regex 1055

\b, regex 1055

back()

container 900

of queue 922

string 1041

back_inserter() 103, 963

back_insert_iterator 963

backslash \ 39, 143

backspace \b 143

bad_alloc 283

new throws 868

bad_cast 1119

dynamic_cast throws 868

bad_typeid, typeid() throws 868

base

and derived class 66

and member destructor 486

class 578–579

class, abstract 598

class, access control and 605

class lookup 756

class, override from virtual 638

class, private member of 581

class, repeated 630

class, template 756

class, virtual 632

conversion, derived to 580

copy of 509

copy of virtual 510

initializer 502

layout, virtual 633

optimization, empty 804

overloading and 693

private 605

protected 605, 618

replicated vs. virtual 636

type 153

Bases... example 813

basic

guarantee 353

guarantee, standard library 868

language facilities 4

basic, regex 1057

basic_regex 1056–1057

basic_string 1036

contiguously 887

generic conversion 1044

basic_string<char>, string 887

basic_string<char16_t>, u16string 887

basic_string<char32_t>, u32string 887

basic_string<wchar_t>, wstring 887

before/after 483

begin() 99, 103, 954

iterator 899

match_results 1060

nonmember 964

string 1044

unordered_map 920

valarray 1170

beginner, book for 37

behavior, undefined 136

Bell Laboratories, AT&T 25

benefits, template 721

Bernoulli distributions 1187

bernoulli_distribution 1187

Bessel 1164

beta() 1164

bibliography 32

bidirectional iterator 955

Bidirectional_iterator 716

bidirectional_iterator_tag 956

big-O notation 894

binary operator, user-defined 530

binary_search() 945

bind() 967

and overloading 968

bind1st() deprecated 967

binder 967

binding

name 746

strength, operator 257

binomial_distribution 1187

bit

field and bitwise logical operators 275

fields and concurrency 1194

order, bitset 978

order, vector<bool> 982

pattern 145

position 978

reference to 978

vector 274

bitand, && 258

bit_and &y 966

bit-field

: 212

bitset and 977

promotion 267

bit_or | 966

bitor, || 258

bits

in char 1161

in float 1161

in int 1161

bitset 887, 977

~ 979

<< 979

& 979

<<= 979

[] 979

&= 979

== 980

^ 979

>>= 979

>> 979

|= 979

^= 979

| 979

!= 980

and bit-field 977

and enum 977

and set 977

and vector<bool> 977

any() 980

bit order 978

constructor 978

count() 980

flip() 979

hash of 915, 980

input 979

none() 980

operation 979

output 979

reset() 979

set() 979

size() 980

test() 980

throws invalid_argument 868

throws out_of_range 868

throws overflow\rror 868

to_string() 980

to_ullong() 980

to_ulong() 980

<bitset> 863

bitwise

and operator & 274

complement operator ~ 274

exclusive or operator ^ 274

logical operators 274

logical operators, bit field and 275

or operator | 274

bit_xor ^ 966

blank, regex 1054

BLAS 1172

Blixen, Karen 2

block 227, 1210

{} 157

as function body, try 98, 371

try 55, 344

body

function 39, 307

loop 233

book

for beginner 37

organization of 4

structure of 4

_Bool 1278

bool 40, 139

conversion to 269

error_code to 875

hash of 915

nullptr 140

promotion 267

shared_ptr conversion to 992

unique_lock 1227

unique_ptr conversion to 987

bottom-up construction 486

branch, declaration on 229

break 231, 236, 244, 252

case and 230

statement 252

broken_promise 883

bucket

load 919

unordered_map 920

bucket(), unordered_map 920

bucket_count(), unordered_map 920

bucket_size(), unordered_map 920

buffer memory 1005

Buffer example 685, 724

built-in

array, T[n] 887

feature vs. technique 17

type 47, 139

type, constructor for 301, 494

type, move of 516

type, user-defined operator and 532

by value, return 517

_byname facet 1124

byte 150

C

C 23

and C++ 9, 19

and C++ compatibility 1271

and C++ global locale 1154

and C++, learning 18

and exception 350

argument type, difference from 1274

array initializer, difference from 1276

compatibility 14

concepts in 708

const linkage, difference from 1276

declaration and definition, difference from 1275

difference from 1271

enum, difference from 1275

function and exception 352

function call, difference from 1274

function definition, difference from 1274

headers 416

initialization and goto, difference from 1276

int implicit, difference from 1277

jump past initialization, difference from 1276

linkage to 428

locale 1114

macro, difference from 1275

programmer 19

sizeof, difference from 1273

struct name, difference from 1276

struct scope, difference from 1273, 1276

void * assignment, difference from 1275

with Classes 22

with Classes language features 23

with Classes standard library 25

C# programmer 20

.c file 425

.C file 425

%c format 1256

C++

and embedded systems 31

and infrastructure 10, 30

and libraries 31

and operating systems 30

and science 31

and Web 30

ANSI 25

C and 9, 19

compatibility, C and 1271

design aims 12

design of 9

earliest 12

feature summary 1277

general-purpose language 9

history 21

ideals 9

ISO 25, 135

large program and 16

learning 17, 1271

learning C and 18

meaning 23

programmer 19

pronunciation 23

pure 8

standardization 25

teaching and 17

timeline 22

tour of 37

use of 9, 30

C++-style thread support, C-style vs. 1192

C++03 25

C++0x, C++11 23, 27

C++11

aims 27

C++0x 23, 27

C++98 28

facilities, use of 8

language features 28

standard library 29

C++98 25

C++11 28

language features 26

standard library 26

C11 1271

C89 and C99 14, 1271

C99, C89 and 14, 1271

cache memory 1193

cache example 462

calculator example 242, 399–400, 431

call

(), function 315

by reference 191, 316

by value 316

function 315

of constructor 487

of destructor 487

of destructor, explicit 285

operator () 80, 550

callback 290, 615, 971

callC() example 350

call_from_C() example 350

call_once()

once_flag 1230

throws system_error 868

can’t use exception 349

capacity()

container 898

string 1040

capture

and argument 295

lambda 293

list 81

list, lambda 293

carriage return \r 143

[[carries_dependency]] 1200

CAS, compare-and-swap 1202

case, declaration in 232

case and break 230

<cassert> 864

assert() 873

cast

C-style 302

deprecated C-style 1271

function-style 303

named 301

catalog, message 1149

catch all 369

catch 367

all 370

clause 55, 344

every exception 98

throw and 344

catch(...) 98

category, facet 1124–1125

category, facet 1113

cauchy_distribution 1188

cbegin()

iterator 899

match_results 1060

string 1044

unordered_map 920

.cc file 425

<ccomplex> 866

<cctype> 864, 1034

ceil() 1163

cend()

iterator 899

match_results 1060

string 1044

unordered_map 920

centi 1018

cerr 91

<cerrno> 864

POSIX 880

<cfenv> floating-point environment 866

<cfloat> 865, 1163

change, incremental 1179

char 40, 140, 144, 150

bits in 1161

character type 141

range of 141

signed 140, 142

sizeof 150

char*, specialization and 736

char, unsigned 140, 142

char16t 140

char32t 140

character

$ 155

\, escape 143

%, format 1255

_ underscore 155

classification 1033, 1142, 1154

code conversion 1146

encoding, multibyte 1146

in name 155

integer value 141

literal ’ 143

mask 1142

name U’, universal 144

name \u, universal 179

promotion 267

representation, converting 1146

set 137

set, ASCII 143

set, large 144

set, larger 178

special 143

string 864

thousands_sep() separator 1129

traits 1035

type 140, 1035

type char 141

CHAR_BIT 1162

char_traits 1035

assign() 1035

char_type 1035

compare() 1035

copy() 1035

eof() 1035

eq() 1035

eq_int_type() 1035

find() 1035

get_state() 1035

int_type() 1035

length() 1035

lt() 1035

move() 1035

not_eof() 1035

off_type 1035

pos_type 1035

state_type 1035

to_char_type() 1035

to_int_type() 1035

char_traits<char> 1035

char_type, char_traits 1035

check

sanity 363

template definition 717

checked pointer 555

checking

concept 709

range 174, 543

type 13

unit 818

chi_squared_distribution 1188

choice of default value 495

choosing

default operation 523

name 155

chrono 123

namespace 1009

<chrono> 118, 123, 863, 1009

cin 93

>>, input 247

value of 544

<cinttypes> 866

circular structures, shared_ptr 991

Circular_buffer example 603

clash, name 390

class 60

:, derived 579

abstract 598

and design, abstract 617

base 578–579

concept and 577

concrete 60

constructor, abstract 598

conversion of pointer to 580

derived 578

design questions 523

destructor, abstract 598

forward reference to 571

friend 572

hierarchy 583

hierarchy design 613

invariant 484

layout 579

member, constructor for 500

member of derived 581

member, private 453

member, public 453

member, template argument 748

object, assignment of 507

operations, set of 471

override from virtual base 638

pointer to 580

private member of base 581

repeated base 630

scope 157

storage 167

template 78, 670

template member 675

use of abstract 622

class 31, 48

... 812

abstract 65

abstract base 598

and concept 449

and struct 454

base and derived 66

concrete 470, 478

declaration 454

definition 454

facet 1118

final 592

hierarchy 68

interface 48

invariant 454

lambda and local 291

locale 1112

member 48

nested 469

recursion 794

string 561

struct and 206, 454

typename and 668

union and 215

user-defined type 450

vs. function requirement 706

classes, multiple implementation 624

classic C, locale 1114

classification, character 1033, 1142, 1154

class-oriented programming 11

cleanup, initialization and 354

clear()

atomic_flag 1205

container 898, 901

error_code 875

string 1040

<climits> 865, 1162

<clocale> 864

clock 1015

from_time_t() 1015

is_steady() 1015

now 1015

to_time_t() 1015

Clock example 635

clock timing 118

clone 596

close(), messages 1150

closure 854

lambda 291

type 297

cmatch 1060

<cmath> 128, 865, 1163

cntrl, regex 1054

code

bloat, curbing 732

complexity, function and 306

exception-safe 378

flexible composition of 741

code() system_error 878

codecvt

always_noconv() 1148

encoding() 1148

facet 1146

in() 1147

length() 1148

max_length() 1148

out() 1148

unshift() 1148

<codecvt> 864

codecvt_base result 1146

coercion 535

collate

compare() 1126–1127

do_compare() 1126

do_hash() 1126

do_transform() 1126

facet 1126

hash() 1126

regex 1057

transform() 1126–1127

collate_byname 1128

collating

order 1128

sequence 726

column(), Matrix 833, 846

combine() 1112

comma and subscripting 183

command-line argument 253

comment 238

// 39, 238

/* 239, 338

nesting 240

Common 716

commonality 577

common_type 1025

communication, task 120

compactly stored, vector<bool> 887

compare()

char_traits 1035

collate 1126–1127

string 1048

sub_match 1058

compare-and-swap CAS 1202

compare_exchange_strong(), atomic<T> 1200

compare_exchange_weak(), atomic<T> 1200

comparison

< 891

container 902

criteria 726

default 891

locale used for string 1118

operator 41

requirement 891

string 1126

user-supplied 891

compatibility

C 14

C and C++ 1271

compilation

of template, separate 26

separate 52, 420

unit of 419

compile time, header and 435

compiler 38

compile-time

arithmetic, ratio 1017

computation 124, 781

control structure 789

evaluation 43

if 790

IF 794

iteration 793

programming 780

recursion 793

selection 789

switch 791

type checking 13

type safety 264

vs. run-time 790

compl, ~ 258

complement operator ~, bitwise 274

complete

encapsulation 482

specialization 731

complex 61, 129, 535

_Complex 1278

complex example 542

<complex> 128–129, 865

complexity

algorithm 931

amortized 895

asymptotic 895

function and code 306

guarantee 894

operation 894

composite operator 536

composition

namespace 407, 409

of code, flexible 741

compositor 855

compound statement 227

computation

compile-time 124, 781

conditional 339

numerical 128

concept 704

ad hoc 708

and class 577

and predicate 672

and requirement 672

checking 709

class and 449

constraint 708

constraints check 715

discovering a 704

locale 1109

multi-argument 714

Range 929

semantics and 709

value 715

concepts 708

Enable_if and 799

history 29

in C 708

static_assert and 709

concrete

class 470, 478

class 60

type 60, 470

type, reuse of 478

concurrency 114, 1191, 1209

bit fields and 1194

initialization and 443

task-based 1235

condition 226

declaration in 232

pointer as 228

variable, mutex and 1219

conditional

computation 339

definition 795–796

evaluation 313

expression, ?: 264, 275

Conditional if 790

conditional 1025

condition_variable 119

constructor 1231

destructor 1231

native_handle() 1231

native_handle_type 1231

notify_all() 1231

notify_one() 1231

throws system_error 868

wait() 1231

wait_for() 1231

wait_until() 1231

<condition_variable> 119, 865

condition_variable_any 1235

consistency, sequential 1196

consistent specialization 735

*const 154, 187

const 186

and linkage 422

constexpr 262

C-style string and 176

function 307

function argument 307

immutability 42

in constant expression 264

linkage, difference from C 1276

member 506

member function 461

physical and logical 462

pointer 187

pointer to 187

reference 190

Tuple example 807

variable 461

constant 186

enumerator as in-class 506

expression 43, 262

expression, address 267

expression, const in 264

in-class definition of 506

member 506

symbolic 264

time 894

constant-expression 0 269

const_cast 298, 302

constexpr

and reference 312

const 262

function 43, 264, 307, 311

function arguments 266

immutability 42

type function 786

const_iterator 106, 896

const_local_iterator 896

const_pointer 896

const_pointer_cast(), shared_ptr 992

constraint 708

concept 708

constraints

check 709

check concept 715

const_reference const_value_type& 896

const_reverse_iterator 896

construct()

allocator 997

allocator_traits 998

construction

{} 299

bottom-up 486

explicit 487

order 487

partial 357

constructor 49, 455, 484

abstract class 598

allocator 997

and copy, default 509

and destructor 24, 483, 485, 500, 582

and template, copy 679

and type conversion 538, 543

and virtual base 634

atomic<T> 1200

bitset 978

call of 487

condition_variable 1231

container 896

copy 73, 482, 508

default 61, 493

delegating 502–503

destructor, RAII 486

disambiguation, {}-list 496

duration 1010

exception and 356–357

explicit 457, 499

for built-in type 301, 494

for class member 500

forwarding 503

future 1241

inheriting 594

initialization without 489

initialize by 492

initializer-list 64, 495

invariant and 56

{}-list 495

locale 1116

map 910

match_results 1060

move 75, 482, 515

mutex 1221

packaged_task 1238

pair 983

POD and 212

pointer to 597

promise 1237

protected 1119

regex_iterator 1067

regex_token_iterator 1068

return type 484

shared_ptr 992

simplifies implementation 473

string 1039

thread 1210, 1212

timed_mutex 1224

time_point 1013

tuple 984

unique_lock 1227

unique_ptr 987

unordered_map 915

virtual 597, 623

weak_ptr 994

constructors, initialization using 491

const_value_type&, const_reference 896

consume operation 1199

container 62, 78, 95

!= 902

<= 902

< 902

== 902

= 896

>= 902

> 902

[] 900

adaptor 887

adaptors 920

adding to 963

algorithm 103, 109, 411, 928

almost 973

assign() 896

associative 886, 909

at() 900

back() 900

capacity() 898

clear() 898, 901

comparison 902

constructor 896

destructor 896

emplace() 901

emplace_back() 900

empty() 898

erase() 901

front() 900

hash 887

implementation of 888

insert() 901

iterator algorithm 953

maxsize() 898

member types 896

object in 97

operation 893

operation overview 893

ordered 909

ordered associative 909

overview 101, 885

pop_back() 900

push_back() 900

representation of 888

reserve() 898

resize() 898

return 104

sequence 886

shrinktofit() 898

size() 898

sort() 124

standard library 101

subscripting 900

swap() 902

unordered 909

unordered associative 887, 913

containers

almost 887

list of 863

contents-of operator * 45

context

of template definition 746

of template instantiation 746

contextual

keyword final 593

keyword override 590

contiguous

array 887

vector 886

contiguously, basic_string 887

continue 237, 252

statement 252

contravariance 610

control

override 589

structure, compile-time 789

controlled statement 233

convenience

and orthogonality 862

vs. safety 405

convention

not-found 928

::type 784

::value 786

conversion

ambiguous type 546

basic_string generic 1044

character code 1146

constructor and type 538, 543

delete 524

derived to base 580

explicit 457

explicit type 298

floating-point 269

implicit 457

implicit type 150, 267, 544, 575

integer 268

narrowing 41, 267

of operand 539

of pointer to class 580

operator, explicit 545

operator, type 543

pointer 269

signed unsigned integer 268

string numeric 1042

template and 673

to() 730

to bool 269

to floating-point 270

to integer type 270

to integral 270

type 543

undefined enum 223

undefined enum class 221

user-defined type 535, 575, 678

conversions, usual arithmetic 258, 271

Convertible 716

converting character representation 1146

copy 72, 452, 507

and exception 364

and hierarchy 77

and move 507

and throw 364, 507

assignment 73, 381, 482, 508

assignment and template 679

constructor 73, 482, 508

constructor and template 679

cost of 74

deep 511

default constructor and 509

destructor and 486

elimination of 853

initialization 458

initialization, initializer_list and 498

memberwise 453, 482, 519

move by 516

of base 509

of exception 368

of virtual base 510

on write 512

pointer and 510

requirement 890

semantics 510

shallow 511

shared_ptr and 511

strcpy() string 277

swap() and 514

union 215

_copy suffix 938

copy() 936

char_traits 1035

string 1041

copyable type, trivially 211

Copyable 716

copy_backward() 936

copy_if() 936

copy_n() 936

core language, ISO 38

cos() 1163

valarray 1170

cosh() 1163

valarray 1170

cost

of copy 74

of exception 351

count() 933

bitset 980

count_if() 108, 933

Courtney 500

cout 91

output 39

covariant return 596

Cowboy example 629

__cplusplus 340, 429

.cpp file 425

crbegin()

iterator 899

string 1044

creation, localization of object 623

cref() 968

cregex_iterator 1067

cregex_token_iterator 1068

crend()

iterator 899

string 1044

criteria, standard library 861

critique, design 616, 622

Crowl, Lawrence 1200

<csetjmp> 865, 1264

cshift() 1169

<csignal> 865

<cstdalign> 866

<cstdarg> 865

<cstdbool> 866

<cstddef> 150

<cstdint> 865

<cstdio> 416, 428, 864

<cstdlib> 444, 863–865, 1164

abs() 865

div() 865

c_str(), string 1041

<cstring> 864

C-style

cast 302

cast, deprecated 1271

error handling 1163

string 46, 175

string and const 176

string, hash of 915

vs. C++-style thread support 1192

<ctgmath>

<ctime> 863, 865

ctype

facet 1143

is() 1143

narrow() 1145

scan_is() 1144

scan_not() 1144

tolower() 1144

toupper() 1144

widen() 1144

ctype_base 1142

<ctype.h> 864

<cuchar> 864

cultural preference, locale 1109

curbing code bloat 732

currency

symbol, international 1136

symbol, local 1136

symbol, standard 1136

current_exception() 374, 870

curr_symbol(), moneypunct 1136

Currying 967

customization point 737

cv_status::notimeout 1231

cv_status::timeout 1231

Cvt_to_upper example 1148

<cwchar> 864, 1124

<cwctype> 864

.cxx file 425

D

%d format 1256

\D, regex 1054

d, regex 1054

\d, regex 1054

daemon 1215

Darwin, Charles 858

data

abstraction 11

member, template 675

race 115, 1197

race, avoiding 1197

race, initialization and 443

race, static variable 314

struct 454

data()

array 976

string 1041

Date example 470

__DATE__ 340

DBL_MINEXP 1162

d.count(), duration 1010

D&E 10, 22

deadlock 118

mutex and 1223

deallocate array 281

deallocate()

allocator 997

allocator_traits 998

deallocation 63

allocation and 277, 556

debugging 454

deca 1018

decay 1023

deci 1018

decimal 145

decimal_point() 1129

moneypunct 1136

declaration 40, 151, 153

and definition, difference from C 1275

and definition, namespace member 400

class 454

enum class 221

function 305, 307

in case 232

in condition 232

in for statement 235

interface 51

on branch 229

point of 158

statement 227

struct name 205

using 393

declarations, keeping consistent 424

declarator operator 46, 154

decltype 165

auto 163

declval 1027

decrement

increment and 554

operator -- 42, 276

deducing template argument 685, 687

deduction

reference 688

rvalue-reference 688

deep copy 511

default

argument 324

argument value, example of 457

comparison 891

constructor 61, 493

constructor and copy 509

initialization 161

initialization union 216

initializer 159

member initialization 501

memberwise 519

operation, choosing 523

operation, generate 517

operation, invariant and 520

operations, using 520

operator, meaning of 519

template argument 728

underlying type 219, 223

value 473, 490

value, choice of 495

default 231, 244

= 518, 524

default_error_condition()

error_category 877

error_code 875

default_random_engine 1183

defer_lock_t 1227, 1229

#define 336

defining a template 669

definition 152

check, template 717

class 454

conditional 795–796

context of template 746

difference from C declaration and 1275

function 307

implementation 51

in-class 460

namespace member declaration and 400

of constant, in-class 506

of virtual function 586

point of 204, 748

using directive and 408

degrees of exception safety 375

delayed

checking, ::type 784

type checking 784

Delayed 785

delays, shared_ptr 991

delegating constructor 502–503

delegation 554

delete element from sequence 938

delete

= 524

a function 524

an operation 77

and operator delete() 556

conversion 524

destructor and 488

double 279

free-store allocation 525

naked 64

nothrow 285

nullptr 279

operator 63, 277

placement 283

premature 279

stack allocation 525

vs. missing, = 525

delete(), operator 282

delete[] 281

nullptr 282

delete()[], operator 282

deleter 987

denorm_min() 1161

dependency

hardware 136

on template argument 746

dependent

name 746

name, template and 748

name, typename and 747

deprecated

auto_ptr 1270

bind1st() 967

C-style cast 1271

exception specification 1270

feature 1270

mem_fun() 967

mem_fun_ref() 967

deque

double-ended queue 886

operation 893

<deque> 863

dereference operator -> 552

dereferencing operator * 172

derivation, overloading and 693

derived

class 578

class : 579

class, base and 66

class, member of 581

to base conversion 580

design

abstract class and 617

aims, C++ 12

class hierarchy 613

criteria, locale 1111

critique 616, 622

ideals 10

of [] 562

of access operator 562

of C++ 9

questions, class 523

standard library 860–861

destroy()

allocator 997

allocator_traits 998

destruction

explicit 487

order 487

top-down 486

destructive read 194

destructor 63, 482

~ 63, 485

abstract class 598

and copy 486

and delete 488

and join(), thread 1215

and resource 485

and scope 488

and throw 354

atexit() and 444

base and member 486

call of 487

condition_variable 1231

constructor and 24, 483, 485, 500, 582

container 896

exception and 356

explicit call of 285

future 1241

match_results 1060

mutex 1221

packaged_task 1238

pair 983

promise 1237

RAII constructor 486

shared_ptr 992

string 1039

thread 1210, 1213

timed_mutex 1224

tuple 985

unique_lock 1227

unique_ptr 987

virtual 70, 488, 598, 619

weak_ptr 994

detach(), thread 1210, 1215

diagnostics 864

dictionary – see map

difference

from C 1271

from C argument type 1274

from C array initializer 1276

from C const linkage 1276

from C declaration and definition 1275

from C enum 1275

from C function call 1274

from C function definition 1274

from C initialization and goto 1276

from C int implicit 1277

from C jump past initialization 1276

from C macro 1275

from C sizeof 1273

from C struct name 1276

from C struct scope 1273, 1276

from C void * assignment 1275

silent 1273

difference_type 896

allocator_traits 998

iterator_traits 957

of pointer 788

digit

0, octal 144

0X, hexadecimal 144

[[:digit:]] 1054

digit, regex 1054

[[:digit:]] digit 1054

digits 1161

digits10 1161

direct

initialization 458

initialization, initializer_list and 498

directed acyclic graph 583

directive, template instantiation 744

disambiguation

{}-list constructor 496

name 205

discard_block_engine 1184

discovering a concept 704

discrete_distribution 1188

discriminated union 217

dispatch, tag 124, 957

distance(), iterator 959

distribution, random 129

distributions

Bernoulli 1187

normal 1188

Poisson 1187

sampling 1188

uniform 1186

div() 1164

<cstdlib> 865

divide operator / 40

divides / 966

div_t 1164

do statement 236, 250

do_compare(), collate 1126

do_hash(), collate 1126

domain error 1163

dominance 638

dot product 1179

do_transform(), collate 1126

double

delete 279

quote ” 176

quote \” 143

double 40, 146

sizeof 150

double-checked locking 1203

double-ended queue, deque 886

doubly-linked, list 886

do/undo 483

duck typing 700

duration 123

%= 1011

% 1012

< 1012

<= 1012

*= 1011

/ 1012

++ 1011

* 1012

/= 1011

+ 1011–1012

- 1011–1012

-= 1011

-- 1011

= 1010

>= 1012

> 1012

+= 1011

== 1012

!= 1012

constructor 1010

d.count() 1010

duration_cast() 1012

hours 1012

max() 1012

microseconds 1012

milliseconds 1012

min() 1012

minutes 1012

nanoseconds 1012

seconds 1012

time_point 1013

zero() 1012

duration_cast 123

duration_cast(), duration 1012

dynamic

memory 277

store 63

dynamic_cast 298

throws bad_cast 868

dynamic_pointer_cast(), shared_ptr 992

E

E infix 147

e, floating-point 146

%e format 1256

e infix 147

earliest C++ 12

ec.category() error_code 875

ECMAScript rules, format_default 1062

ECMAScript, regex 1057

EDOM 1163

efficiency and generality 862

efficient abstraction, elegant and 9

egrep, regex 1057

elegant and efficient abstraction 9

element

access, Tuple 806

from sequence, delete 938

requirements 97, 890

eliminate_duplicates() example 938

elimination

of copy 853

of temporary 853

ellipsis ... 321

elliptic 1164

else 228

embedded systems, C++ and 31

emphasis, examples and 7

emplace()

container 901

map 910

emplace_after(), forward_list 908

emplace_back(), container 900

emplace_front(), list 907

emplace_hint(), map 910

Employee example 578

empty

base optimization 804

sequence 954

statement 226

string ”” 177

empty()

container 898

match_results 1060

string 1040

Enable_if

and concepts 799

and overloading 801

implementation of 799

enable_if 795, 1025

notation 797

use 797

encapsulation, complete 482

encoding(), codecvt 1148

end() 99, 103, 954

iterator 899

match_results 1060

nonmember 964

string 1044

unordered_map 920

valarray 1170

#endif 339

enforcing invariant 359

engine, random 129

entanglement 511

and garbage collection 512

enum 201, 218

and enum class 218

and integer 223

bitset and 977

class 201

class and integer 221

class conversion, undefined 221

class declaration 221

class, enum and 218

class enumeration 50, 219

class, sizeof 222

class underlying type 219

conversion, undefined 223

difference from C 1275

enumeration 50

member 506

plain 222

range of 223

sizeof 223

switch and 231

underlying type 223

unnamed 224

user-defined operator 220

user-defined operator and 532

user-defined type 220

enumeration 218

enum 50

enum class 50, 219

switch on 219

enumerator 218

as in-class constant 506

scope 218

environment, <cfenv> floating-point 866

eof(), char_traits 1035

epsilon() 1161

eq(), char_traits 1035

eq_int_type(), char_traits 1035

equal operator == 41

equal() 934

equality without == 892

Equality_comparable 714, 716

equal_range() 126, 945

equal_to 887

== 966

equation, Matrix linear 849

equivalence

= and == 510

type 210, 673

equivalent() error_category 877

ERANGE 1163

erase() 99

container 901

string 1044

erase_after(), forward_list 908

erasure, type 733

errc

POSIX 880

systemcategory() 880

errno 350, 1163

<errno.h> 864

error

detection, template 674

domain 1163

exception and 345, 348

function size and 306

handling 54, 251

handling, C-style 1163

handling, hierarchical 350

handling, multilevel 350

handling, traditional 345

library and 344

linkage 421

mutex 1223

name lookup 674

range 1163

run-time 55, 344

state 346

syntax 674

type 674

value, return an 346

error_category 877

== 877

!= 877

< 877

default_error_condition() 877

equivalent() 877

message() 877

name() 877

value() 877

error_code 875

<< 875

!= 875

< 875

== 875

assign() 875

clear() 875

default_error_condition() 875

ec.category() 875

hash of 915

mapping 879

message() 875

=n() 875

to bool 875

value() 875

error_condition 878

error-handler function 346

escape character \ 143

essential operations 482, 517, 561

Estd sort() 411

evaluation

compile-time 43

conditional 313

order of 259

partial 967

short-circuit 229, 260

event, asynchronous 348

exa 1018

example

anonymous union 564

Assert 361

Assoc 550

Bases... 813

Buffer 685, 724

cache 462

calculator 242, 399–400, 431

callC() 350

call_from_C() 350

Circular_buffer 603

Clock 635

complex 542

const Tuple 807

Cowboy 629

Cvt_to_upper 1148

Date 470

eliminate_duplicates() 938

Employee 578

Expr 596

File_ptr 357

find_all() 104

find_last() 962

getNth 806

guarded_thread 1214

Has_f 799

Hello, World! 39

Ival_box 614

Matrix 827

Matrix_ref 842

Money 1134

My_messages 1150

My_money_io 1137

My_punct 1129

of default argument value 457

of input 250

of operator overloading 561

of user-defined memory management 561

parallel find() 1246

printf() 809

Rand_int 130

Satellite 625

Season 1120

Season << 1121, 1152

Season >> 1121, 1152

SI units 818

Slice_iter 1173

sort() 333, 684

split() 394

Storable 632

String 668

String I/O 568

String_numput 1131

Sync_queue 1232

Tic_tac_toe 522

Tiny 543

Token 243

Token_stream 247

Tracer 483

Tuple 802

Tuple get() 806

Vec 97

Vector 730

Window 635

examples and emphasis 7

exception 55, 344, 347

... 369

and << 1132

and constructor 356–357

and destructor 356

and error 345, 348

and main() 98

and member 357

and member initialization 371

and new 357

and old code 349

and recursive function 348

and subobject 357

and thread 374

and time critical 349

assignment and 381

atexit() and 352

C and 350

C function and 352

can’t use 349

catch every 98

copy and 364

copy of 368

cost of 351

goto and 238

guarantee 353

packaged_task and 1238

propagation 870

qsort() and 352

runtime_error 1116

safe 353

safety, degrees of 375

safety, techniques for 375

specification 26, 367

specification, deprecated 1270

standard library 868

transparency 378

uncaught 372

exception hierarchy 870

<exception> 372, 864–865

exception_ptr 870

exceptions() 1132

exception-safe code 378

exchange(), atomic<T> 1200

exclusive or operator ^, bitwise 274

exercises – see www.stroustrup.com

exhaustion, free store 283

exit

from function 310

loop 236

exit() 443

exp(), valarray 1170

expired(), weak_ptr 994

explicit

call of destructor 285

construction 487

conversion 457

destruction 487

qualification 588

specialization 693

template argument 686

template instantiation 744

type conversion 298

explicit

constructor 457, 499

conversion operator 545

exponent, size of 1161

exponential_distribution 129, 1187

exponentiation

** 529

vector 1170

export 26, 156

removed 1270

Expr example 596

expr() 1163

expression

?: conditional 264, 275

address constant 267

const in constant 264

constant 43, 262

full 261

lambda 81, 290

statement and 225

extended integer 145

extended, regex 1057

extent 1022

extern 428

extern 421

external linkage 421

externally imposed layout 212

extreme_value_distribution 1187

F

F suffix 147

%F format 1256

%f format 1256

\f, formfeed 143

f suffix 147

fabs() 1163

facet

access to 1119

_byname 1124

category 1124–1125

category 1113

class 1118

codecvt 1146

collate 1126

ctype 1143

identifier id 1119

lifetime of 1119

locale and 1109, 1113

messages 1150

money_get 1138

moneypunct 1135

money_put 1137

numpunct 1129

num_put 1130

put() iterator 1130

Season_io, user-defined 1120

standard 1124

to locale, adding 1117

use of 1119

user-defined 1123

facilities

basic language 4

standard library 88, 860

use of C++11 8

factory 623

failed() 1132

failure

output 1132

precondition 359

false

and 0 139

false_type and 800

falsename() 1130

false_type and false 800

fault tolerance 350

feature

deprecated 1270

summary, C++ 1277

vs. technique, built-in 17

features

C with Classes language 23

C++11 language 28

C++98 language 26

portability and 1267

femto 1018

fence

atomic_signal_fence() 1206

atomic_thread_fence() 1206

fetch_add(), atomic<T> 1203

fetch_and(), atomic<T> 1203

fetch_or(), atomic<T> 1203

fetch_sub(), atomic<T> 1203

fetch_xor(), atomic<T> 1203

file

.C 425

.c 425

.cc 425

.cpp 425

.cxx 425

.h 424

header 52, 424

.hh 425

mode a 1254

mode b 1254

mode r 1254

mode w 1254

mode x 1254

source 419

__FILE__ 340

File_ptr example 357

fill() 941

array 974

fill_n() 941

final 591

and performance 592

class 592

contextual keyword 593

function 307

finally() 358

find() 103, 933

char_traits 1035

example, parallel 1246

map 910

string 1046

find_all() example 104

find_end() 933

find_first_not_of(), string 1047

find_first_of() 933

string 1047

find_if() 108, 933

find_if_not() 933

find_last() example 962

find_last_not_of(), string 1047

find_last_of(), string 1047

firewall 350

first submatch, $1 1061

first, pair member 127, 983

fisher_f_distribution 1188

fixed-length array 174

flags, match 1062

flags(), regex 1057

flexible composition of code 741

flip() bitset 979

float 146

bits in 1161

sizeof 150

float_denorm_style 1161

<float.h> 865

floating-point

. 146

conversion 269

conversion to 270

e 146

environment, <cfenv> 866

hash of 915

literal 146

promotion 267

to int 270

type 139, 146

float_round_style 1161

floor() 1163

FLT_RADIX 1162

fmod() 1163

fold() 701

for

and : 233

<iterator> range 868

loop, lambda and 292

statement 45, 235

statement, declaration in 235

statement, range 45, 233, 965

for(;;) forever 235, 244

for_each() 932

forever, for(;;) 235, 244

formal argument 315

format

%A 1256

%a 1256

%c 1256

character % 1255

%d 1256

%e 1256

%F 1256

%f 1256

%G 1256

%g 1256

%i 1256

%n 1256

number 1129

%o 1256

of monetary amount 1134–1135

%p 1256

%s 1256

string 1255

substitution 1061

%u 1256

%X 1256

%x 1256

format()

options 1062

regex 1061

format_default ECMAScript rules 1062

format_first_only 1062

format_no_copy 1062

format_sed 1062

formfeed \f 143

Fortran 16

forward

iterator 955

reference to class 571

forward() 1028

forward_as_tuple(), tuple 985

forwarding constructor 503

Forward_iterator 716

forward_iterator_tag 956

forward_list 906

emplace_after() 908

erase_after() 908

insert_after() 908

operation 893, 907–908

representation 889

singly-linked list 886

size() 907

splice_after() 908

<forward_list> 863

frac_digits()

monetary 1137

money_punct 1135

free

storage 167

store 63, 167, 277

store exhaustion 283

freestanding implementation 137

free-store allocation, delete 525

frexp() 1163

friend 571

and member 532, 574

class 572

function 572

lookup 573

template and 682

from_time_t(), clock 1015

front()

container 900

of queue 922

string 1041

front_inserter() 963

front_insert_iterator 963

<fstream> 864

full expression 261

__FUNC__ 340

function 39

access 216

adaptor 967

and code complexity 306

and exception, C 352

argument 315

argument, array 184

argument const 307

argument names 308

argument passing 315, 482

argument type check 315

argument type conversion 315

argument types, virtual 586

argument unused 308

arguments, constexpr 266

body 39, 307

body, try block as 98, 371

call 315

call () 315

call and assignment 192

call, difference from C 1274

const 307

const member 461

constexpr 43, 264, 307, 311

constexpr type 786

declaration 305, 307

definition 307

definition, difference from C 1274

definition of virtual 586

definition, old-style 1274

delete a 524

error-handler 346

exit from 310

final 307

friend 572

get 541

helper 542

implementation of virtual 67

init() 455

inline 307, 310

inline member 460

long 306

mathematical 128

mathematical special 1164

member 451, 473

name, overloaded 326

noexcept 307, 365

[[noreturn]] 307, 314

object 80, 551

object, lambda and 291

only, instantiate used 743

operator :: and virtual 589

override 307

parameter 315

parameter pack 812

pointer to 332

pointer to member 607

pure virtual 598

requirement, class vs. 706

selection 787

set 541

size and error 306

specialization 736

static 307

static member 467, 571

template 79, 670, 684

template argument 686

template member 676

template overloading 689

type 124, 781

type of overriding 596

value return 308

value return 482

virtual 307, 585, 625

virtual template 679

function 969

and nullptr 969

functional programming, pure 780

<functional> 863

functions, list of operator 529

function-style cast 303

fundamental type 40, 138

fused operation 853

future

= 1241

and promise 120, 1236

and promise, packaged_task and 1238

constructor 1241

destructor 1241

get() 1241

member get() 120

share() 1241

throws future_error 868

valid() 1241

wait() 1241

wait_for() 1241

wait_until() 1241

<future> 120, 865

future_already_retrieved 883

future_category() 877

future_errc 883

future_errc 1242

future_category() 883

future_error

future throws 868

promise throws 868

future_status::deferred 1242

future_status::ready 1242

future_status::timeout 1242

G

%g format 1256

%G format 1256

game 1180

gamma_distribution 1187

garbage

collection, entanglement and 512

collection, pointers and 512

collection, shared_ptr 991

collector 278

Gaussian elimination, Matrix 850

Gavin 500

generality

and iterator 929

efficiency and 862

generalized

numeric algorithm 1176

slice 1175

general-purpose language, C++ 9

generate default operation 517

generate() 941

generated specialization 742

generative programming 779

generic

conversion, basic_string 1044

programming 11, 78, 699

programming, template and 665

generic_category() 877

geometric_distribution 1187

get function 541

get, pair 984

get<>() 127

get()

and set() 216

future 1241

future member 120

messages 1150

money_get 1138

num_get 1133

shared_ptr 992

tuple 985

unique_ptr 987

get_allocator()

match_results 1060

string 1040

getdeleter(), shared_ptr 992

get_deleter(), unique_ptr 987

get_future()

packaged_task 1238

promise 1237

get_id(), this_thread 1217

getid(), thread 1210

getline() 93

string 1042

getloc()

regex 1057

regex_traits 1070

getNth example 806

get_state(), char_traits 1035

get_temporary_buffer() 1005

get_terminate() 872

giga 1018

global

initialization of 442

locale, C and C++ 1154

name, lambda and 295

namespace 393

scope 157, 393

variable 423, 467

glvalue 166

goto

and exception 238

and initializer 238

difference from C initialization and 1276

statement 237

grain of parallelism 1247

graph, directed acyclic 583

graph, regex 1054

greater > 966

greater_equal >= 966

greater-than operator > 41

greater-than-or-equal operator >= 41

greedy match 1053, 1056

grep, regex 1057

grouping, {} 39

grouping() 1129

moneypunct 1136

gslice 1175

gslice_array 1175

guarantee

basic 353

complexity 894

exception 353

nothrow 353

standard 135

strong 353

guard, scope 358

guarded_thread example 1214

H

.h file 424

half-open range 954

handle 49, 64, 280

resource 73, 113

handle_ioexception() 1132

handler, unexpected 367

hardware 149

dependency 136

hardware_concurrency(), thread 1210

has identity 166, 171

has_denorm 1161

has_denorm_loss 1161

Has_f example 799

has_facet() 1119

hash

container 887

policy 919

table 100, 887

hash 887

of bitset 915, 980

of bool 915

of C-style string 915

of error_code 915

of floating-point 915

of integer 915

of pointer 915

of shared_ptr 915

of string 915

of thread::id 915

of typeindex 915

of u16string 915

of unique_ptr 915

of wstring 915

specialization 915

user-defined 916

hash(), collate 1126

hashed

unordered_map 887

unordered_multimap 887

unordered_multiset 887

unordered_set 887

hasher 896

hash_function(), unordered_map 919

has_infinity 1161

has_quiet_NaN 1161

has_signaling_NaN 1161

has_virtual_destructor 1022

header 253, 424

and compile time 435

file 52, 424

language support 866

single 431

standard library 89, 428, 863

headers

C 416

multiple 435

use of 439

heap 63

operation 948

store 277

heap, priority_queue and 924

heartbeat 1215

hecto 1018

Heisenbug 1216

Hello, World! example 39

helper

function 542

function and namespace 475

Hermite polynomials 1164

hexadecimal

0X 145

digit 0X 144

.hh file 425

hiding, name 157

hierarchical error handling 350

hierarchy 578

class 68

class 583

copy and 77

design, class 613

exception 870

traditional 614

high-level language 15

high_resolution_clock 1016

history

C++ 21

concepts 29

homemade, standard vs. 859

HOPL 22

horizontal tab \t 143

hosted implementation 137

hours, duration 1012

Hume, David 134

hybrid language 12

I

%i format 1256

\i, regex 1055

$i submatch 1061

icase, regex 1057

id

facet identifier 1119

thread 1210–1211

ideal library 111

ideals

C++ 9

design 10

programming 10

identifier 155

id, facet 1119

identity

has 166, 171

thread 1211

IEC-559, is_iec559 1161

IF, compile-time 794

if

compile-time 790

Conditional 790

statement 43, 228

_if suffix 930

if, switch and 230

#ifdef 339

#ifndef 339, 441

$ii submatch 1061

imbue()

iostream locale 1111

regex 1057

regex_traits 1070

immutability

const 42

constexpr 42

immutable 461

locale is 1118

state 512

string literal 176

implementation

alternative 620, 734

and interface 616

classes, multiple 624

definition 51

dependency type of integer literal 146

freestanding 137

hosted 137

inheritance 70, 578, 599, 637

interface and 419, 450, 599, 636

iterator 105

lambda 290

Matrix 840

namespace, interface 404

of container 888

of Enable_if 799

of virtual function 67

pre-standard 1271

priority_queue 923

shared 624

specialization 734

stack 920, 922

implementation-defined 135

_impl.h 435

implicit

conversion 457

invariant 520

type conversion 150, 267, 544, 575

in(), codecvt 1147

in-class

constant, enumerator as 506

definition 460

definition of constant 506

initializer 504, 506

member initializer 459

include directory, standard 424

#include 52, 253, 416, 424

guard 440

includes() 947

inclusion, template 695

incomplete type 205

increment

and decrement 554

operator ++ 42, 276

incremental change 1179

indentation 238

independence = 510

independent_bits_engine 1184

index, Tuple 806

indirection 554

mutability by 463

operator * 172

infinity() 1161

infix

. 147

e 147

E 147

infrastructure, C++ and 10, 30

inheritance 66, 579, 583

access control and multiple 606

ambiguity resolution, multiple 627

implementation 70, 578, 599, 637

interface 70, 578, 599, 617, 637

multiple 24, 583, 624

repeated 630

template and 673

inheriting constructor 594

init() function 455

initialization 153, 455

{} 456, 489, 492

() vs. {} 160

and cleanup 354

and concurrency 443

and data race 443

and goto, difference from C 1276

and slicing 513

copy 458

default 161

default member 501

difference from C jump past 1276

direct 458

initializer_list and copy 498

initializer_list and direct 498

main() and 442

Matrix {} 843

memberwise 489

of array by string 176

of global 442

of local variable 314

of reference 191

of structure 202

of variable 227

order 487

order of member 501

problem, = 492

problem, () 492

reference member 495

resource acquisition is 356

run-time 442

static member 506

syntax 159

uniform 492

union, default 216

universal 492

using constructors 491

without constructor 489

initialize 64

array 975

by constructor 492

initializer

= 41

{} 41, 175, 202

() and 162

absence of 161

array 175

base 502

default 159

goto and 238

in-class 504, 506

in-class member 459

lack of 490

list 162

member 500–501

struct 202

initializer-list constructor 64, 495

initializer_list 64, 495

and copy initialization 498

and direct initialization 498

<initializer_list> 867

use of 497

<initializer_list> initializer_list 867

inline

and linkage 422

function 307, 310

member function 460

namespace 412

inlining template arguments 671

inner product 1179

inner_product() 1178

inplace_merge() 946

input

and output 864

bitset 979

cin >> 247

example of 250

istream >> 93

iterator 955

of monetary amount 1138

of numeric value 1133

of user-defined type 94

string 93

Input_iterator 716

input_iterator_tag 956

insert() 99

container 901

map 910

string 1044

insert_after(), forward_list 908

inserter() 963

insertion, overwriting vs. 963

insert_iterator 963

instantiate used function only 743

instantiation

context of template 746

directive, template 744

explicit template 744

member 744

multiple 744

multiple point of 752

needed 743

point of 749

template 671, 742

instruction reordering 1195

int 40, 144, 150

and pointer 150

bits in 1161

floating-point to 270

implicit, difference from C 1277

largest 1161

output bits of 981

sizeof 150

smallest 1161

template argument 685

int32t 168

integer

conversion 268

conversion, signed unsigned 268

enum and 223

enum class and 221

extended 145

hash of 915

literal 145, 218

literal, implementation dependency type of 146

literal, type of 146

type 139, 144

type, conversion to 270

value character 141

integral

conversion to 270

promotion 267

type 139

interface

and implementation 419, 450, 599, 636

class 48

declaration 51

implementation and 616

implementation namespace 404

inheritance 70, 578, 599, 617, 637

module and 399

multiple 624

shared 624

specialization 733

internal linkage 421

international currency symbol 1136

internationalization, approaches to 1110

interoperability 16

INT_MAX 1162

introducer, lambda 293

int_type(), char_traits 1035

invalid_argument, bitset throws 868

invalidate iterator 898

invariant 56

and constructor 56

and default operation 520

class 484

class 454

enforcing 359

implicit 520

partially specified 522

rationale 485

resource 521

I/O 91

example, String 568

iterator and 106

I/O, string 1042

io_errc iostream_category() 883

<iomanip> 864

<ios> 864

ios_base::failure, iostream throws 868

<iosfwd> 864

iostream 91

locale and 1114, 1123

locale, imbue() 1111

throws ios_base::failure 868

<iostream> 39, 864

iostream_category() 877

io_errc 883

is(), ctype 1143

is_abstract 1020

isalnum() 1034

locale 1154

isalpha() 249, 1034

locale 1154

is_arithmetic 1019

is_array 1018

is_assignable 1020

is_base_of 1022

isblank() locale 1154

is_bounded 1161

is_class 1018

iscntrl() 1034

locale 1154

is_compound 1019

is_const 1020

is_constructible 1020

is_convertible 1022

is_copy_assignable 1020

is_copy_constructible 1020

isctype(), regex_traits 1070

is_default_constructible 1020

is_destructible

isdigit() 1034

locale 1154

is_empty 1020

is_enum 1018

is_exact 1161

is_floating_point 1018

is_function 1018

is_fundamental 1019

isgraph() 1034

locale 1154

is_heap() 948

is_heap_until() 948

is_iec559 IEC-559 1161

is_integer 1161

is_integral 1018

is_literal_type 1020

is_lock_free(), atomic<T> 1200

islower() 1034

locale 1154

is_lvalue_reference 1018

is_member_functionpointer 1018

is_member_objectpointer 1018

is_memberpointer 1019

is_modulo 1161

is_move_assignable 1020

is_move_constructible 1020

is_nothrow_assignable 1022

is_nothrow_constructible 1022

is_nothrow_copy_assignable 1022

is_nothrow_copy_constructible 1022

is_nothrow_default_constructible 1022

is_nothrow_destructible 1022

is_nothrow_move_assignable 1022

is_nothrow_move_constructible 1022

ISO

C++ 25, 135

core language 38

standard 135

standard library 38

ISO-14882 25

ISO-4217 1136

ISO-646 137

is_object 1019

is_partitioned() 940

is_permutation() 940

is_pod 1020

is_pointer 1018

is_polymorphic 1020

isprint() 1034

locale 1154

ispunct() 1034

locale 1154

is_reference 1019

is_rvalue_reference 1018

is_same 1022

is_scalar 1019

is_signed 1020, 1161

is_sorted() 942

isspace locale 1154

isspace() 1034

whitespace 250

is_specialized 1161

is_standard_layout 1020

is_steady(), clock 1015

istream >>, input 93

<istream> 864

istream_iterator 106

is_trivial 1020

is_trivially_assignable 1021

is_trivially_constructible 1021

is_trivially_copyable 1020

is_trivially_copy_assignable 1021

is_trivially_copy_constructible 1021

is_trivially_default_constructible 1021

is_trivially_destructible 1021

is_trivially_move_assignable 1021

is_trivially_move_constructible 1021

is_union 1018

is_unsigned 1020

isupper() 1034

locale 1154

is_void 1018

is_volatile 1020

isxdigit() 1034

locale 1154

iteration

compile-time 793

statement 233

iterator 103

* 959

+

-- 959

-> 959

-=

!= 959

< 959

[]

== 959

- 959

+= 959

>= 959

++ 959

> 959

adaptor 960

advance() 959

algorithm and 927

algorithm container 953

and I/O 106

begin() 899

bidirectional 955

cbegin() 899

cend() 899

crbegin() 899

crend() 899

distance() 959

end() 899

facet put() 1130

forward 955

generality and 929

implementation 105

input 955

invalidate 898

move 964

next() 959

operation 959

output 955

prev() 959

random-access 955

rbegin() 899

rend() 899

STL 954

string 1044

valarray 1173

iterator 99, 106, 896, 958

<iterator> 125, 956

range for 868

iterator_category 125

iterator_traits 957

iterator_traits 124–125, 788, 956

difference_type 957

iterator_category 957

pointer 957

reference 957

value_type 957

iterator_type 125

iter_swap() 942

itoa() 322

Ival_box example 614

Ival_slider 636

J

Java programmer 20

JIS 1146

join() 115

thread 1210, 1214

thread destructor and 1215

joinable(), thread 1210

jump past initialization, difference from C 1276

K

keeping consistent declarations 424

key and value 100

key_comp(), map 910

key_compare 896

key_eq(), unordered_map 919

key_equal 896

key_type 896

keyword 156

final, contextual 593

override, contextual 590

kilo 1018

knuth_b 1184

L

L” prefix 147

L’ prefix 147

L suffix 147

L’, wide-character literal 144

\L, regex 1054

\l, regex 1054

l suffix 147

label

: 226

scope of 238

labs() 1164

lack

of initializer 490

of modularity 585

Laguerre polynomials 1164

lambda

[=] 294

[] 294

[&] 294

alternatives 291

and for loop 292

and function object 291

and global name 295

and local class 291

and member name 296

and namespace name 295

capture 293

capture list 293

closure 291

expression 81, 290

implementation 290

introducer 293

lifetime 295

mutable 296

named 297

operator()() 296

recursive 297

state 296

template argument 727

this 296

type of 297

language

and library 87

C++ general-purpose 9

facilities, basic 4

features, C with Classes 23

features, C++11 28

features, C++98 26

high-level 15

hybrid 12

library system 15

low-level 15

people and machines 9

programming style 17

scripting 16

support 865–866

support header 866

large

character set 144

program 435, 437

program and C++ 16

larger character set 178

largest int 1161

launch, async() 122

launch::async, async() 1245

launch::deferred, async() 1245

launcher, async() task 1245

layout

ABI and 211

array 183, 1172

class 579

externally imposed 212

object 151

struct 203

Tuple 804

type, standard 211

virtual base 633

lazy

match 1053, 1056

match, (? 1056

ldexp() 1163

ldiv() 1164

ldiv_t 1164

leak, resource 76, 112

leaked object 279

learning

C++ 17, 1271

C and C++ 18

Legendre polynomials 1164

length

of name 155

valarray 1169

length()

char_traits 1035

codecvt 1148

match_results 1060

regex_traits 1070

string 1040

sub_match 1058

length_error, string throws 868

less 887

< 966

less_equal <= 966

less-than operator < 41

less-than-or-equal operator <= 41

letter, [[:alpha:]] 1054

lexical token 258

lexicographical order 949

lexicographical_compare() 949

libraries, C++ and 31

library 9

algorithm, standard 109

and error 344

C with Classes standard 25

C++11 standard 29

C++98 standard 26

container, standard 101

facilities, standard 88, 860

ideal 111

language and 87

non-standard 88

standard 6, 88, 111, 416

standard – see standard library

system, language 15

life cycle, object 481

lifetime 482

lambda 295

of facet 1119

of locale 1130

of object 166

of temporary 261

lifting and algorithm 701

limits, numeric 1160

<limits> 124, 131, 865, 1160

<limits.h> 865, 1162

__LINE__ 340

linear

equation, Matrix 849

time 894

linear_congruential_engine 1183

linkage

and namespace 430

and pointer to function 430

const and 422

error 421

external 421

inline and 422

internal 421

no 422

template 697

to C 428

type-safe 420

linker 38, 420

list

{} 162, 286

(), argument 307

argument, {} 319

capture 81

forward_list singly-linked 886

initializer 162

of containers 863

of operator functions 529

operation 893, 901

Tuple 802

list 98, 906

{}-list

constructor 495

constructor disambiguation 496

list

doubly-linked 886

emplace_front() 907

merge() 907

operation 893, 907

pop_front() 907

push_front() 907

remove() 907

remove_if() 907

representation 889

reverse() 907

sort() 907

splice() 907

unique() 907

<list> 863

literal

’, character 143

”, string 39, 176

floating-point 146

immutable, string 176

implementation dependency type of integer 146

integer 145, 218

L’, wide-character 144

of user-defined type 540

operator 558

operator, template 560

prefix 147

raw string 128, 177

suffix 147, 558

type 264–265

type argument, template 724

type of integer 146

type of string 176

Unicode 179

Unit 822

user-defined 822

literals, user-defined 558

LL suffix 147

ll suffix 147

llabs() 1164

lldiv() 1164

load bucket 919

load(), atomic<T> 1200

loader 420

load_factor(), unordered_map 919

local

class, lambda and 291

currency symbol 1136

name, template argument 748

scope 157

static 314

variable 314

variable, initialization of 314

locale

adding facet to 1117

and facet 1109, 1113

and iostream 1114, 1123

C 1114

C and C++ global 1154

class 1112

classic C 1114

concept 1109

constructor 1116

cultural preference 1109

design criteria 1111

imbue() iostream 1111

is immutable 1118

isalnum() 1154

isalpha() 1154

isblank() 1154

iscntrl() 1154

isdigit() 1154

isgraph() 1154

islower() 1154

isprint() 1154

ispunct() 1154

isspace 1154

isupper() 1154

isxdigit() 1154

lifetime of 1130

modify 1118

name 1114–1115

name string 1116

preferred 1114

string 1127

used for string comparison 1118

<locale> 864, 1124

<locale.h> 864

locale-sensitive message 1149

local_iterator 896

locality 437

localization of object creation 623

location, memory 1193

lock 1192

lock() 118, 1229

and RAII 118

mutex 1221

timed_mutex 1224

unique_lock 1227

weak_ptr 994

lockable object 1227

lock_guard and unique_lock 1225

lock_guard<M> 1225

locking 357

double-checked 1203

locks, multiple 1228

log() 1163

valarray 1170

log10() 1163

valarray 1170

logarithmic time 894

logical

and operator && 260, 274

const, physical and 462

not operator ! 274

operators, bitwise 274

or operator || 260, 274

program structure 420

logical_and && 966

logical_not ! 966

logical_or || 966

lognormal_distribution 1188

long

function 306

namespace name 406

long 144

double 146

double, sizeof 150

long long 144

long

long, sizeof 150

sizeof 150

longjmp() 865, 1264

lookup

argument-dependent 395, 754

base class 756

error, name 674

friend 573

namespace name 395, 533

lookup_classname(), regex_traits 1070

lookup_collatename(), regex_traits 1070

loop 233

body 233

exit 236

lambda and for 292

merging 853

statement 252

lower, regex 1054

lower_bound() 945

map 910

low-level language 15

lt(), char_traits 1035

lvalue 165–166, 575

modifiable 165

reference 190

M

m, _m vs. 823

->m, shared_ptr 992

_m vs. m 823

Machiavelli, Niccolò 448

machines, language people and 9

macro 336

alternative to 338

difference from C 1275

predefined 340

template and 750

magnitude ratio, SI 1018

main() 39, 252, 441, 443

and initialization 442

argument to 253

argv argc 253

exception and 98

maintenance 437

make_error_code() 875

make_exception_ptr() 870

make_heap() 948

make_move_iterator() 964

make_pair() 127

makepair(), pair 984

make_ready_at_exit(), packaged_task 1238

makeshared(), shared_ptr 992

make_signed 1024

make_tuple 817

make_tuple() 127, 808

maketuple(), tuple 985

make_unsigned 1024

management, resource 13, 76, 112

manager object 280

mantissa, size of 1161

manual

overload resolution 330

tutorial and 3

map 100, 909

[] 910

at() 910

constructor 910

emplace() 910

emplace_hint() 910

find() 910

insert() 910

key_comp() 910

lower_bound() 910

operation 893, 910

ordered 886

representation 889

subscripting 910

upper_bound() 910

value_comp() 910

<map> 863

mapped type, value 100

mapped_type 896

mapping error_code 879

map-reduce 1249

Marian 153

markcount(), regex 1057

mask, character 1142

match

$& 1061

(? lazy 1056

flags 1062

greedy 1053, 1056

lazy 1053, 1056

match_any 1062

match_continuous 1062

matches and submatches 1060

match_flag_type, regex_constants 1062

match_not_bol 1062

match_not_bow 1062

match_not_eol 1062

match_not_eow 1062

match_not_null 1062

match_prev_avail 1062

match_results 1059

!= 1060

[] 1060

== 1060

= 1060

begin() 1060

cbegin() 1060

cend() 1060

constructor 1060

destructor 1060

empty() 1060

end() 1060

get_allocator() 1060

length() 1060

maxsize() 1060

position() 1060

prefix() 1060

ready() 1060

size() 1060

str() 1060

subscript 1060

suffix() 1060

swap() 1060

mathematical

function 128

functions, standard 1163

functions, valarray 1170

functions, vector 1170

special function 1164

<math.h> 865, 1163

Matrix 846

{} 832

[] 833

* 839

+ 836–837

+= 836

() 833, 846

= 832

{} initialization 843

access 846

and Vector 682

apply() 837

arithmetic 836

column() 833, 846

example 827

Gaussian elimination 850

implementation 840

linear equation 849

pivot 851

requirements 830

row() 833, 846

slice() 833, 841, 846

subscript 833

template 831

uses 828

zero-dimensional 848

Matrix_ref example 842

Max Munch 258

max() 950, 1161

duration 1012

time_point 1014

valarray 1169

maxbucket_count(), unordered_map 920

max_element() 950

max_exponent 1161

max_exponent10 1161

max_length(), codecvt 1148

max_load_factor(), unordered_map 919

max_size(), allocator 997

maxsize()

container 898

match_results 1060

max_size(), string 1040

mbstate_t 1124

state_type 1035

meaning

C++ 23

for operator, predefined 531

of default operator 519

mechanisms, abstraction 5

mega 1018

member

->*, pointer to 607

::*, pointer to 607

.*, pointer to 607

access 466

access . 48

access operator . 202

access operator -> 202

alias, template 676

and nonmember operators 535

assignment must be 531

class 48

class 469

class template 675

const 506

constant 506

constructor for class 500

destructor, base and 486

enum 506

exception and 357

friend and 532, 574

function 451, 473

function, const 461

function, inline 460

function, pointer to 607

function, static 467, 571

function, template 676

initialization, default 501

initialization, exception and 371

initialization, order of 501

initialization, reference 495

initialization, static 506

initializer 500–501

initializer, in-class 459

instantiation 744

name, lambda and 296

nullptr, pointer to 607

of base class, private 581

of derived class 581

operator delete() 557

operator() must be 531

operator-> must be 531

operator= must be 531

operator[] must be 531

operator new() 557

pointer to 607, 609

private class 453

protected 603–604

public class 453

static 467, 557

struct 202

template 670

template data 675

template static 676

template, template 678

type 469

type, template 677

typedef, template 676

types, container 896

union 215

using and 593

using, template 676

void *, pointer to 607

memberwise

copy 453, 482, 519

default 519

initialization 489

move 519

memcpy() 210

mem_fn() 969

mem_fun() deprecated 967

mem_fun_ref() deprecated 967

memory

access time 1195

buffer 1005

cache 1193

dynamic 277

location 1193

management, example of user-defined 561

model 1193

model, relaxed 1199

order 1195

representing 379

uninitialized 1005

<memory> 112, 863, 1005

unique_ptr 987

memory_order 1199

merge() 946

list 907

mersenne_twister_engine 1183

message

catalog 1149

locale-sensitive 1149

queue 922

message()

error_category 877

error_code 875

messages

close() 1150

facet 1150

get() 1150

open() 1150

messages_base 1149

metaprogramming 779

and programming 781

template 779

when to use 794

method 586

micro 1018

microseconds, duration 1012

milli 1018

milliseconds, duration 1012

min() 950, 1161

duration 1012

time_point 1014

valarray 1169

min_element() 950

min_exponent 1161

min_exponent10 1161

minmax() 950

minmax_element() 950

minstd_rand 1184

minstd_rand0 1184

minus operator - 40

minus - 966

minutes, duration 1012

mismatch() 934

missing, = delete vs. 525

mixed-mode arithmetic 536

mixin 639

MKS units 819

model, memory 1193

modf() 1163

modifiable lvalue 165

modify locale 1118

modifying algorithm 935

modularity 51, 389, 587

lack of 585

module and interface 399

modulus operator % 40

modulus % 966

monetary

amount, format of 1134–1135

amount, input of 1138

amount, output of 1137

amount, punctuation of 1135

monetary frac_digits() 1137

Money example 1134

money_base 1135

money_get

and >> 1139

facet 1138

get() 1138

moneypunct

curr_symbol() 1136

decimal_point() 1136

facet 1135

money_punct frac_digits() 1135

moneypunct

grouping() 1136

negative_sign() 1136

neg_format() 1136

pattern 1136

pos_format() 1136

positive_sign() 1136

thousands_sep() 1136

money_put

and << 1138

facet 1137

put() 1138

movable 166

Movable 716

move 75, 514

and throw 507

assignment 75, 482, 515

by copy 516

by swap() 515

constructor 75, 482, 515

copy and 507

iterator 964

memberwise 519

of built-in type 516

swap() and 516

move() 76, 195, 516, 936, 1028

char_traits 1035

static_cast and 194

swap() and 516

move_backward() 936

moved-from state 507

move_if_noexcept() 1028

mt19937 1184

mt19937_64 1184

muddling through 347

multi-argument concept 714

multibyte character encoding 1146

multidimensional

array 1172, 1175

array, passing 185

multilevel

error handling 350

programming 779

multi_map operation 893

multimap ordered 886

multiple

arguments, overload resolution for 329

headers 435

implementation classes 624

inheritance 24, 583, 624

inheritance, access control and 606

inheritance ambiguity resolution 627

instantiation 744

interface 624

locks 1228

point of instantiation 752

multiplies * 966

multiply operator * 40

multi_set operation 893

multiset ordered 886

must include, standard header 866

mutability 461

by indirection 463

mutable 463

lambda 296

mutex

acquire 1220

and condition variable 1219

release 1220

mutex 117

and deadlock 1223

and recursive_mutex 1221

constructor 1221

destructor 1221

error 1223

lock() 1221

native_handle() 1221

throws system_error 868

try_lock() 1221

unlock() 1221

mutex(), unique_lock 1227

<mutex> 117, 865

mutual reference 571

My_messages example 1150

My_money_io example 1137

My_punct example 1129

N

\n 39

%n format 1256

\n, newline 143

=n() error_code 875

naked

delete 64

new 64

name 155

binding 746

binding, template 745

character in 155

choosing 155

clash 390

declaration, struct 205

dependent 746

disambiguation 205

hiding 157

length of 155

locale 1114–1115

long namespace 406

lookup error 674

lookup, namespace 395, 533

namespace qualified 392

of template, template and 748

of type, typename and 747

qualified 589

shadowing 158

short namespace 406

string, locale 1116

template and dependent 748

template argument local 748

typename and dependent 747

name() error_category 877

named

cast 301

lambda 297

names

function argument 308

reserved 155

namespace

and specialization 736

interface implementation 404

name, lambda and 295

pollution 223

scope 157

struct 205

namespace 54, 391, 400

access 403

alias 406

alias reopen 398

and :: 392

and overloading 410

and scope 393

and versioning 412

chrono 1009

composition 407, 409

global 393

helper function and 475

inline 412

is open 398

linkage and 430

member declaration and definition 400

name, long 406

name lookup 395, 533

name, short 406

nested 414

operators and 533

placeholders 967

purpose of 408

qualified name 392

std 89

template and 753

unnamed 415, 423

using 416

nano 1018

nanoseconds, duration 1012

narrow(), ctype 1145

narrowing conversion 41, 267

n-ary operators 853

native_handle()

condition_variable 1231

mutex 1221

thread 1210

timed_mutex 1224

native_handle_type

condition_variable 1231

thread 1210

timed_mutex 1224

NDBUG 360

assert() 873

NDEBUG 340

needed, instantiation 743

negate - 966

negative_binomial_distribution 1187

negative_sign(), moneypunct 1136

neg_format(), moneypunct 1136

nested

class 469

namespace 414

template, template 678

nested_exception 871

= 871

nested_ptr() 871

rethrow() 871

nested_ptr() nested_exception 871

nesting

comment 240

template and 680

Neumann 1164

new

and operator new() 556

exception and 357

naked 64

nothrow 285

operator 63, 277

overload 283

placement 283, 487

throws bad_alloc 868

new(), operator 282

new()[], operator 282

<new> 865

newline

\n 143

raw string 178

next(), iterator 959

next_permutation() 940

Nicholas 90

no

linkage 422

order, , 531

order, && 531

order, || 531

Nocase 891

noexcept

function 307, 365

operator 366

non-C++ program 442

non-deduced parameter 693

none(), bitset 980

none_of() 932

nonintrusive 600

nonlocal object 488

nonmember

begin() 964

end() 964

operators, member and 535

nonmodifying algorithm 932

non-standard library 88

non-type template parameter 724

Norah 500

[[noreturn]] function 307, 314

normal distributions 1188

normal_distribution 129, 1188

no_state 883

nosubs, regex 1057

not

! 258

operator !, logical 274

not1() 967

not2() 967

notation

enable_if 797

regular expression 1052

value of 527

not_eof(), char_traits 1035

not_eq, != 258

not-equal operator != 41

not_equal_to != 966

not-found 954

convention 928

nothrow guarantee 353

nothrow

delete 285

new 285

nothrow_t 285

notify_all(), condition_variable 1231

notifyone() 119

notify_one(), condition_variable 1231

now, clock 1015

nth_element() 942, 944

null

0 zero 174

pointer 0 269

reference 198

NULL 174, 865

0, nullptr 46

nullptr 46, 173, 198

bool 140

delete 279

delete[] 282

function and 969

NULL 0 46

pointer to member 607

shared_ptr 992

unique_ptr 987

number

format 1129

pseudo-random 1180

punctuation 1129

random 129

size of 149

numeric

algorithm, generalized 1176

array 1166

conversion, string 1042

limits 1160

value, input of 1133

value, output of 1130

<numeric> 128, 865, 1176

numerical

computation 128

valarray 887

numeric_limits 131, 1160

num_get

and >> 1133

get() 1133

numpunct facet 1129

num_put

and << 1131

facet 1130

put() 1130

O

O notation 894

%o format 1256

object 40, 165

automatic 167

creation, localization of 623

function 80, 551

in container 97

lambda and function 291

layout 151

leaked 279

life cycle 481

lifetime of 166

lockable 1227

manager 280

nonlocal 488

placement of 283

reference and 190

state and value 510

static 161

temporary 167, 261

value and 510

object-oriented programming 11, 68, 577

octal

0 145

digit 0 144

ODR, the one-definition rule 425

offset, pointer to member and 608

off_type

char_traits 1035

streamoff 1035

old code, exception and 349

old-style function definition 1274

once_flag call_once() 1230

one-definition rule, ODR, the 425

open, namespace is 398

open(), messages 1150

operand

conversion of 539

passing 532

operating systems, C++ and 30

operation

acquire 1199

arithmetic 966

array 974

as argument, template 725

atomic 1196, 1198

bitset 979

choosing default 523

complexity 894

consume 1199

container 893

delete an 77

deque 893

forward_list 893, 907–908

fused 853

generate default 517

heap 948

invariant and default 520

iterator 959

list 893, 907

list 893, 901

map 893, 910

multi_map 893

multi_set 893

overview, container 893

release 1199

set 893

stack 900

unordered_map 893

unordered_multimap 893

unordered_multiset 893

unordered_set 893

vector 893

operations

essential 482, 517, 561

on references 190

on structure 203

set of class 471

typical 471

using default 520

valarray 1169–1170

vector 1170

operator

%= 42

+= 42, 244

.* 609

. 466

:: 466, 582

-> 466

, 260

?: 275

-= 244

->* 609

&, address-of 45, 172

:: and virtual function 589

&, bitwise and 274

~, bitwise complement 274

^, bitwise exclusive or 274

|, bitwise or 274

(), call 80, 550

*, contents-of 45

--, decrement 42, 276

->, dereference 552

*, dereferencing 172

/, divide 40

==, equal 41

>, greater-than 41

>=, greater-than-or-equal 41

++, increment 42, 276

*, indirection 172

<, less-than 41

<=, less-than-or-equal 41

&&, logical and 260, 274

!, logical not 274

||, logical or 260, 274

->, member access 202

., member access 202

-, minus 40

%, modulus 40

*, multiply 40

!=, not-equal 41

<<, output 39

+, plus 40

%, remainder 40

*=, scaling 42

/=, scaling 42

::, scope resolution 158, 468

[], subscript 174

++, user-defined 531, 554

->, user-defined 552

=, user-defined 575

+=, user-defined 531, 536, 575

+, user-defined 532, 575

--, user-defined 554

and built-in type, user-defined 532

and enum, user-defined 532

application 550

arithmetic 40

arrow 552

assignment 244, 536

associativity of 257

binding strength 257

comparison 41

composite 536

declarator 46, 154

delete 63, 277

design of access 562

enum user-defined 220

explicit conversion 545

literal 558

meaning of default 519

new 63, 277

noexcept 366

overloaded 62, 477

overloading, example of 561

precedence 255

predefined meaning for 531

return from 532

special 549

summary 255

symmetric 539

template literal 560

type conversion 543

user-defined 62, 529

user-defined binary 530

user-defined unary 530

operator

”” 558

[], subscript 50

delete()[] 282

delete() 282

delete and size 557

delete(), delete and 556

delete(), member 557

functions, list of 529

operator-> must be member 531

operator= must be member 531

operator

new() 282

new()[] 282

new and size 556

new(), member 557

new(), new and 556

operator=, vector 382

operator() 80, 550

operator()(), lambda 296

operator() must be member 531

operator[] 550

must be member 531

operators

and namespace 533

bitwise logical 274

member and nonmember 535

n-ary 853

optimization 853

empty base 804

short string 561, 563–564

optimize, regex 1057

options, format() 1062

or

| 258

operator |, bitwise 274

operator ||, logical 260, 274

order 891

bitset bit 978

collating 1128

construction 487

destruction 487

initialization 487

lexicographical 949

memory 1195

of evaluation 259

of member initialization 501

of specialization 736

strict weak 891

string 1128

total 892

vector<bool> bit 982

ordered

associative container 909

container 909

map 886

multimap 886

multiset 886

set 886

type 707

Ordered 707, 709, 716

or_eq, |= 258

organization

of book 4

standard library 863

orthogonality, convenience and 862

ostream <<, output 91

<ostream> 864

ostream_iterator 106

out(), codecvt 1148

out_of_range 97

bitset throws 868

string throws 868

vector throws 868

output 91

bits of int 981

bitset 979

cout 39

failure 1132

input and 864

iterator 955

of monetary amount 1137

of numeric value 1130

of user-defined type 94

operator << 39

ostream << 91

sequence 955

string 93

Output_iterator 716

output_iterator_tag 956

overabstraction 10

overaggressive ADL 754

overflow, stack 922

overflow\rror, bitset throws 868

overload

new 283

resolution 327

resolution for multiple arguments 329

resolution, manual 330

return type and 328

scope and 328

overloaded

function name 326

operator 62, 477

overloading

and base 693

and derivation 693

bind() and 968

Enable_if and 801

example of operator 561

function template 689

namespace and 410

specialization and 737–738

override 66, 587, 598, 631

control 589

from virtual base class 638

override 590

contextual keyword 590

function 307

overriding function, type of 596

overuse of traits 789

overview

container 101, 885

container operation 893

overwriting vs. insertion 963

owner, unique_ptr 987

owner_before()

shared_ptr 992

weak_ptr 994

ownership 112

pointers and 188

shared_ptr shared 990

owns_lock(), unique_lock 1227

P

%p format 1256

packaged_task

() 1238

= 1238

and exception 1238

and future and promise 1238

constructor 1238

destructor 1238

get_future() 1238

make_ready_at_exit() 1238

reset() 1238

swap() 1238

thread 121

throws system_error 868

uses_allocator 1238

valid() 1238

pair 126

> 984

!= 984

<= 984

< 984

== 984

>= 984

= 983

constructor 983

destructor 983

get 984

makepair() 984

member first 127, 983

member second 127, 983

piecewiseconstruct 983

swap() 983

tuple\lement 984

tuplesize 984

<utility> 983

paradigm, programming 10

parallel find() example 1246

parallelism, grain of 1247

parameter

function 315

non-deduced 693

non-type template 724

pack 811

pack, function 812

pack, template 812

template 722

typename and template 747

parameterized type 78

parentheses

and > 788

uses of 260

parser, recursive descent 243

partial

construction 357

evaluation 967

specialization 732

specification 708

partially specified invariant 522

partial_sort() 942

partial_sort_copy() 942

partial_sum() 1179

partition() 940

partition_copy() 940

partitioning of program 431, 435

partition_point() 940

pass-by-lvalue-reference 317

pass-by-rvalue-reference 317

passing

data to task 116

multidimensional array 185

operand 532

result 532

pattern, specialization 732

pattern, moneypunct 1136

people and machines, language 9

perfection 17

performance

final and 592

template 780

permutation 940

peta 1018

phone_book example 95

physical

and logical const 462

program structure 419–420

pico 1018

piecewise_constant_distribution 1188

piecewiseconstruct, pair 983

piecewise_linear_distribution 1188

p=is_sorted_until() 942

pivot, Matrix 851

placeholders

_1 967

_2 967

namespace 967

placement

delete 283

new 283, 487

of object 283

plain

enum 222

old data, POD 210

plus operator + 40

plus + 966

POD

and constructor 212

plain old data 210

point

of declaration 158

of definition 204, 748

of instantiation 749

of instantiation, multiple 752

pointer 172

- 182

+ 182

== 177

* for 181

++ for 181

+ for 181

-- for 181

- for 181

0, null 269

addition 182

and array 179, 318

and copy 510

argument, template 724

arithmetic 181, 276

as condition 228

checked 555

const 187

conversion 269

difference_type of 788

hash of 915

int and 150

reference and 189, 196

semantics 562

size of 149

smart 112, 552, 554

subtraction 182

to * 44

to class 580

to class, conversion of 580

to const 187

to constructor 597

to function 332

to function, linkage and 430

to member 607, 609

to member ->* 607

to member .* 607

to member ::* 607

to member and offset 608

to member function 607

to member nullptr 607

to member void * 607

to void 173

valid 140, 228

value_type of 788

pointer 896

iterator_traits 957

pointers

and garbage collection 512

and ownership 188

pointer_traits 999

point-of-instantiation ambiguity 752

Poisson distributions 1187

poisson_distribution 1187

policy, hash 919

pollution, namespace 223

polymorphic type 66, 587

polymorphism 578

– see virtual function

runtime 587

polynomials

Hermite 1164

Laguerre 1164

Legendre 1164

pop()

of priority_queue 923

of queue 922

of stack 920

pop_back()

container 900

string 1041

pop_front(), list 907

pop_heap() 948

portability 16, 136

and features 1267

pos_format(), moneypunct 1136

position, bit 978

position(), match_results 1060

positive_sign(), moneypunct 1136

POSIX

<cerrno> 880

errc 880

thread support 1192

postcondition 330

pos_type

char_traits 1035

streampos 1035

pow() 1163

valarray 1170

#pragma 341

precedence, operator 255

precondition 56, 330

failure 359

testing 359

predefined

, 531

= 531

& 531

macro 340

meaning for operator 531

predicate 81, 108, 966

concept and 672

type 785

Predicate 716

preempt, thread 1217

preferred locale 1114

prefix

’ 147

$‘ 1061

” 147

0 147

0x 147

L’ 147

L” 147

literal 147

R” 147

return type 308

u’ 147

u” 147

U” 147

U’ 147

u8” 147

prefix(), match_results 1060

premature delete 279

pre-standard implementation 1271

prev(), iterator 959

prev_permutation() 940

primary template 735

principle, zero-overhead 10

print, regex 1054

printf() example 809

priority queue 923

priorityqueue 887

priority_queue

and heap 924

implementation 923

pop() of 923

push() of 923

top() of 923

private member of base class 581

private

: 454, 600

base 605

class member 453

problem

= initialization 492

() initialization 492

procedural programming 11

process 1192

product

dot 1179

inner 1179

program 39

and C++, large 16

large 435, 437

non-C++ 442

partitioning of 431, 435

start 441

structure, logical 420

structure, physical 419–420

termination 443

programmer

C# 20

C++ 19

C 19

Java 20

programming 31

class-oriented 11

compile-time 780

generative 779

generic 11, 78, 699

ideals 10

meta 779

metaprogramming and 781

multilevel 779

object-oriented 11, 68, 577

paradigm 10

procedural 11

pure functional 780

style 10

style language 17

systems 10, 16

template and generic 665

two-level 779

type-rich 13

value-oriented 478

prohibiting

= 531

, 531

& 531

promise

= 1237

constructor 1237

destructor 1237

future and 120, 1236

get_future() 1237

member set_exception() 120

member set_value() 120

packaged_task and future and 1238

set_exception() 1237

set_exception_at_thread_exit() 1237

set_value()

set_value_at_thread_exit() 1237

swap() 1237

throws future_error 868

promise_already_satisfied 883

promotion

bit-field 267

bool 267

character 267

floating-point 267

integral 267

standard 267

pronunciation, C++ 23

propagate_on_*, allocator_traits 998

propagation, exception 870

protected

: 600

base 605, 618

constructor 1119

member 603–604

protection 454

prvalue 166

pseudo-random number 1180

ptrdiff_t 150, 259, 865

public

: 453–454, 600

class member 453

punct, regex 1054

punctuation

number 1129

of monetary amount 1135

pure

C++ 8

functional programming 780

virtual 65

virtual function 598

purpose

of namespace 408

template 699

push()

of priority_queue 923

of queue 922

of stack 920

push_back() 64, 99

container 900

string 1041

pushback(), vector 385

push_front() 99

list 907

push_heap() 948

put()

iterator, facet 1130

money_put 1138

num_put 1130

Q

qsort() 334

and exception 352

quadratic time 894

qualification, explicit 588

qualified

{} 287

name 589

name, namespace 392

Quantity 820

queue

deque double-ended 886

priority 923

queue 887

back() of 922

front() of 922

message 922

pop() of 922

push() of 922

<queue> 863

quick_exit() 443

quiet_NaN() 1161

quote

”, double 176

\”, double 143

’, single 143

\’, single 143

quotient 1164

R

R” 128, 177

prefix 147

\r, carriage return 143

r, file mode 1254

race, data 115, 1197

RAII 356

constructor destructor 486

lock() and 118

resource acquisition 112

RAII 64

rand(), random number 1189

Rand_int example 130

RAND_MAX 1189

random

number 939, 1180

number 129

number rand() 1189

number, truly 1185

random

distribution 129

engine 129

<random> 129, 865

random-access iterator 955

Random_access_iterator 716

random_access_iterator_tag 956

random_device 1185

random_shuffle() 939

range

access 964

checking 174, 543

checking Vec 97

error 1163

for, <iterator> 868

for statement 45, 233, 965

half-open 954

of char 141

of enum 223

Range concept 929

rank 1022

ranlux24 1184

ranlux24_base 1184

ranlux48 1184

ranlux48_base 1184

ratio

compile-time arithmetic 1017

SI magnitude 1018

<ratio> 863, 1017

ratio_add 1017

ratio_divide 1017

ratio_equal 1017

ratio_greater 1017

ratio_less 1017

ratio_multiply 1017

rationale, invariant 485

ratio_subtract 1017

raw

storage 1005

string literal 128, 177

string newline 178

raw_storage_iterator 1005

rbegin()

iterator 899

string 1044

read, destructive 194

ready(), match_results 1060

rebind, allocator 997

recompilation 697

recursion 309

class 794

compile-time 793

recursive

descent parser 243

function, exception and 348

lambda 297

recursive_mutex 1223

mutex and 1221

recursive_timed_mutex, timed_mutex and 1224

reduce 1178

reduce() 701

reduction 1178

ref() 968

reference 189

&&, rvalue 75, 194

and object 190

and pointer 189, 196

and template 688

and temporary 191

argument 191, 316

arguments 266

array of 190

call by 191, 316

const 190

constexpr and 312

deduction 688

initialization of 191

lvalue 190

member initialization 495

mutual 571

null 198

return by 310

rvalue 190, 193

to & 45, 190

to class, forward 571

reference

iterator_traits 957

to bit 978

value_type& 896

references, operations on 190

reference_wrapper 968

regex

} 1052

{ 1052

$ 1052

( 1052

) 1052

* 1052

| 1052

+ 1052

] 1052

[ 1052

^ 1052

? 1052

= 1057

. 1052

alnum 1054

alpha 1054

assign 1057

awk 1057

\b 1055

\B 1055

basic 1057

blank 1054

cntrl 1054

collate 1057

\D 1054

d 1054

\d 1054

digit 1054

ECMAScript 1057

egrep 1057

extended 1057

flags() 1057

format() 1061

getloc() 1057

graph 1054

grep 1057

\i 1055

icase 1057

imbue() 1057

\l 1054

\L 1054

lower 1054

markcount() 1057

nosubs 1057

optimize 1057

print 1054

punct 1054

regular expression 127

repetition 1053

s 1054

\S 1054

\s 1054

space 1054

throws regex_error 868

\U 1054

\u 1054

upper 1054

\W 1054

w 1054

\w 1054

xdigit 1054

<regex> 127, 864

regular expression 1051

regex_constants match_flag_type 1062

regex_error, regex throws 868

regex_iterator 1067

= 1067

== 1067

=* 1067

-> 1067

++ 1067

!= 1067

constructor 1067

regex_match() 1062

regex_replace() 1065

regex_search 128

regex_search() 1064

regex_token_iterator 1068

!= 1068

++ 1068

-> 1068

= 1068

== 1068

=* 1068

constructor 1068

regex_traits

getloc() 1070

imbue() 1070

isctype() 1070

length() 1070

lookup_classname() 1070

lookup_collatename() 1070

transform() 1070

transformprimary() 1070

translate() 1070

translate_nocase() 1070

value() 1070

regular

expression notation 1052

expression regex 127

expression <regex> 1051

type 706

Regular 706, 716

rehash(), unordered_map 919

reinterpret_cast 214, 298, 301

relaxation of return type 596

relaxed memory model 1199

release

mutex 1220

operation 1199

resource 354

release()

unique_lock 1227

unique_ptr 987

reliability 350

rel_ops

>= 1029

> 1029

<= 1029

!= 1029

remainder 1164

operator % 40

remove() 938

list 907

remove_all_extents 1024

remove_const 1023

remove_copy() 938

remove_copy_if() 938

remove_cv 1023

removed, export 1270

remove_extent 1024

remove_if(), list 907

remove_reference 1023

remove_volatile 1023

rend()

iterator 899

string 1044

reopen, namespace alias 398

reordering, instruction 1195

repeated

base class 630

inheritance 630

repetition, regex 1053

replace() 938

string 1045

replace_copy() 938

replace_copy_if() 938

replace_if() 938

replicated vs. virtual base 636

representation

array 890

converting character 1146

forward_list 889

list 889

map 889

of container 888

string 890

String 563

unordered_map 889

vector 888

representing memory 379

required

-> 758

this-> 758

requirement

class vs. function 706

comparison 891

concept and 672

copy 890

template 704

requirements

analysis 704

element 97, 890

Matrix 830

template 672

reserve()

container 898

string 1040

unordered_map 919

reserved names 155

reset()

bitset 979

packaged_task 1238

shared_ptr 992

unique_ptr 987

weak_ptr 994

resize()

container 898

string 1040

valarray 1169

resolution, << 533

resource

acquisition 354

acquisition is initialization 356

acquisition RAII 112

destructor and 485

handle 73, 113

invariant 521

leak 76, 112

leak, standard library 868

management 13, 76, 112

release 354

safety 76

restriction 13

result

of sizeof 259

passing 532

type 258

result, codecvt_base 1146

result_of 1025

rethrow 369

rethrow() nested_exception 871

rethrow_exception() 870

rethrow_if_nested() 871

return

an error value 346

by value 517

covariant 596

function value 482

\r, carriage 143

type 307–308

type, -> 308

type and overload 328

type, constructor 484

type of, virtual 596

type, prefix 308

type, relaxation of 596

type, suffix 308

value type check 309

value type conversion 309

return; 308

return

by reference 310

by value 310

container 104

from operator 532

function value 308

of void expression 310

type, void 40

returning results from task 116

return_temporary_buffer() 1005

reuse of concrete type 478

reverse() 938

list 907

reverse_copy() 938

reverse_iterator 896, 960

rfind(), string 1046

Riemann zeta 1164

rotate() 939

rotate_copy() 939

round() 300

round_error() 1161

row(), Matrix 833, 846

rule, ODR, the one-definition 425

run-time

compile-time vs. 790

error 55, 344

initialization 442

runtime polymorphism 587

run-time support 15

runtime_error exception 1116

rvalue 166

reference 190, 193

reference && 75, 194

reference argument 317

rvalue-reference deduction 688

S

%s format 1256

\s, regex 1054

s, regex 1054

\S, regex 1054

s, _s vs. 823

_s vs. s 823

safe_assign() 383

safety

convenience vs. 405

resource 76

sampling distributions 1188

sanity check 363

Satellite example 625

saving space 213

scale 437

scaling 1171

operator /= 42

operator *= 42

scan_is(), ctype 1144

scan_not(), ctype 1144

SCARY 682

science, C++ and 31

scope 157, 571

and overload 328

class 157

destructor and 488

enumerator 218

global 157, 393

guard 358

local 157

namespace 157

namespace and 393

of label 238

resolution operator :: 158, 468

statement 157

scoped allocator 1000

<scoped_allocator> 863

scoped_allocator_adaptor 1000

scripting language 16

search() 935

search_n() 935

Season

>> example 1121, 1152

<< example 1121, 1152

example 1120

Season_io, user-defined facet 1120

second, pair member 127, 983

seconds, duration 1012

Select 791

selection

compile-time 789

function 787

statement 228

self, assignment to 382, 508

self-reference this 464

semantics 713

= 510

and concept 709

copy 510

pointer 562

value 562

semicolon ; 153, 202, 226

Semiregular 711, 716

separate

compilation 52, 420

compilation of template 26

separator character, thousands_sep() 1129

sequence 102, 927

adaptors 920

adding to 963

container 886

delete element from 938

empty 954

output 955

STL 954

sequential consistency 1196

set 274

algorithm 947

function 541

of class operations 471

set

bitset and 977

operation 893

ordered 886

set()

bitset 979

get() and 216

<set> 863

set_difference() 947

set_exception()

promise 1237

promise member 120

set_exception_at_thread_exit(), promise 1237

set_intersection() 947

setjmp() 865, 1264

<setjmp.h> 865

set_symmetric_difference() 947

set_terminate() 372, 872

set_union() 947

set_value()

promise

promise member 120

set_value_at_thread_exit(), promise 1237

SFINAE 691

shadowing, name 158

shallow copy 511

share(), future 1241

shared

implementation 624

interface 624

ownership, shared_ptr 990

state 511

shared_future 1244

shared_ptr 112

<< 992

<= 992

< 992

== 992

>= 992

> 992

* 992

!= 992

allocateshared() 992

and copy 511

circular structures 991

const_pointer_cast() 992

constructor 992

conversion to bool 992

delays 991

destructor 992

dynamic_pointer_cast() 992

garbage collection 991

get() 992

getdeleter() 992

hash of 915

->m 992

makeshared() 992

nullptr 992

owner_before() 992

reset() 992

shared ownership 990

swap() 992

unpredictable 991

weaknesses 991

sharing data task 117

shift state 1146

shift() 1169

short

namespace name 406

string optimization 561, 563–564

short 144

sizeof 150

short-circuit evaluation 229, 260

shrinktofit(), container 898

shrink_to_fit(), string 1040

shuffle() 939

shuffle_order_engine 1184

SI

magnitude ratio 1018

units example 818

sign extension 142

signal 348

<signal.h> 865

signaling_NaN() 1161

signed

char 140, 142

type 144

unsigned integer conversion 268

silent difference 1273

simplifies implementation, constructor 473

Simula 21

simulation 1180

sin() 1163

valarray 1170

single

header 431

quote ’ 143

quote \’ 143

singly-linked list, forward_list 886

sinh() 1163

valarray 1170

size

of exponent 1161

of mantissa 1161

of number 149

of pointer 149

of string 318

of structure 203

of type 40

operator delete and 557

operator new and 556

size()

array 976

bitset 980

container 898

forward_list 907

match_results 1060

string 1040

valarray 1169

sizeof 40, 149

sizeof... 813

sizeof

char 150

difference from C 1273

double 150

enum 223

enum class 222

float 150

int 150

long 150

long double 150

long long 150

result of 259

short 150

sizeof() 124

size_t 83, 150, 259, 865

size_type 896

sleep 1210

sleep_for(), this_thread 1217

sleep_until(), this_thread 1217

slice, generalized 1175

slice 1172

slice(), Matrix 833, 841, 846

slice_array 1174

Slice_iter example 1173

slicing 513

assignment and 513

initialization and 513

smallest int 1161

smart pointer 112, 552, 554

smatch 1060

sort, stable 943

sort() 102, 942

container 124

Estd 411

example 333, 684

list 907

sort_heap() 948

source

code, template 695

file 419

space, saving 213

space, regex 1054

special

character 143

function, mathematical 1164

operator 549

specialization 742

<> 682

and char* 736

and overloading 737–738

and void* 730

complete 731

consistent 735

explicit 693

function 736

generated 742

hash 915

implementation 734

interface 733

namespace and 736

order of 736

partial 732

pattern 732

template 671, 730

use of 743

user 742

user-defined 730

specialized, more 736

specification

partial 708

throw 367

specifier 153

splice(), list 907

splice_after(), forward_list 908

split() example 394

sqrt() 1163

valarray 1170

srand() 1189

sregex_iterator 1067

sregex_token_iterator 1068

<sstream> 254, 864

stable sort 943

stable_partition() 940

stable_sort() 942

stack

allocation, delete 525

frame 167

operation 900

Tuple and 804

unwinding 364, 865

stack 887

implementation 920, 922

overflow 922

pop() of 920

push() of 920

top() of 920

underflow 922

<stack> 863

standard

currency symbol 1136

facet 1124

guarantee 135

header must include 866

include directory 424

ISO 135

layout type 211

library 6, 88, 111, 416

library, adding to 866

library algorithm 109

library basic guarantee 868

library, C with Classes 25

library, C++11 29

library, C++98 26

library container 101

library criteria 861

library design 860–861

library exception 868

library facilities 88, 860

library header 89, 428, 863

library, ISO 38

library organization 863

library resource leak 868

library std 89, 863

mathematical functions 1163

promotion 267

vs. homemade 859

standardization, C++ 25

start, program 441

start/stop 483

state

immutable 512

lambda 296

moved-from 507

shared 511

valid 353

value and 510

statement

and expression 225

break 252

compound 227

continue 252

controlled 233

declaration 227

do 236, 250

empty 226

for 45, 235

goto 237

if 43, 228

iteration 233

loop 252

range for 45, 233, 965

scope 157

selection 228

summary 226

switch 43, 230

while 44, 236

state_type

char_traits 1035

mbstate_t 1035

static

object 161

storage 167

type checking 13

static 423

function 307

local 314

member 467, 557

member function 467, 571

member initialization 506

member, template 676

variable data race 314

static_assert 131, 360

and concepts 709

assertion 57

static_assert() 873

static_cast 298, 301, 334

and move() 194

std 39

namespace 89

standard library 89, 863

<stdarg.h> 322, 865

<stdbool.h> 1278

__STDC__ 340

__STDC_HOSTED__ 340

__STDC_MB_MIGHT_NEQ_WC__ 340

__STDCPP_STRICT_POINTER_SAFETY__ 340

__STDCPP_THREADS__ 340

<stddef> 865

<stddef.h> 865

<stdexcept> 864

<stdio.h> 416, 428, 864

<stdlib.h> 863–865, 1164

steady_clock 1016

STL 26

algorithm 927

iterator 954

sequence 954

stod(), string 1042

stof(), string 1042

stoi(), string 1042

stol(), string 1042

stold(), string 1042

stoll(), string 1042

Storable example 632

storage

automatic 167

class 167

free 167

raw 1005

static 167

temporary 167

store

dynamic 63

free 63, 167, 277

heap 277

store(), atomic<T> 1200

stoul(), string 1042

stoull(), string 1042

str()

match_results 1060

sub_match 1058

strcpy() string copy 277

stream 864

stream 883

Streamable 716

<streambuf> 864

streamoff, off_type 1035

streampos, pos_type 1035

strict weak order 891

stride() 1172

string

””, empty 177

and const, C-style 176

argument, template 724

character 864

comparison 1126

comparison, locale used for 1118

copy, strcpy() 277

C-style 46, 175

format 1255

initialization of array by 176

literal, \ 177

literal ” 39, 176

literal immutable 176

literal, raw 128, 177

literal, type of 176

locale name 1116

newline, raw 178

optimization, short 561, 563–564

order 1128

size of 318

String

example 668

I/O example 568

representation 563

string 90, 1037

> 1040

>> 1042

>= 1040

[] 1041

= 1039

== 1040

< 1040

<= 1040

<< 1042

+ 1041

+= 1041

!= 1040

algorithm and 1044

append() 1044

assign() 1044

at() 1041

back() 1041

basic_string<char> 887

begin() 1044

capacity() 1040

cbegin() 1044

cend() 1044

class 561

clear() 1040

compare() 1048

constructor 1039

copy() 1041

crbegin() 1044

crend() 1044

c_str() 1041

data() 1041

destructor 1039

empty() 1040

end() 1044

erase() 1044

find() 1046

find_first_not_of() 1047

find_first_of() 1047

find_last_not_of() 1047

find_last_of() 1047

front() 1041

get_allocator() 1040

getline() 1042

hash of 915

input 93

insert() 1044

I/O 1042

iterator 1044

length() 1040

locale 1127

max_size() 1040

numeric conversion 1042

output 93

pop_back() 1041

push_back() 1041

rbegin() 1044

rend() 1044

replace() 1045

representation 890

reserve() 1040

resize() 1040

rfind() 1046

shrink_to_fit() 1040

size() 1040

stod() 1042

stof() 1042

stoi() 1042

stol() 1042

stold() 1042

stoll() 1042

stoul() 1042

stoull() 1042

subscripting 1041

substr() 1048

swap() 1041

throws length_error 868

throws out_of_range 868

to_string() 1042

to_wstring()

<string> 90, 864, 1035–1036

<string.h> 864

String_numput example 1131

strong guarantee 353

Strovstrup 1065

struct 47, 201

aggregate 202

and class 206, 454

array 207

class and 454

data 454

initializer 202

layout 203

member 202

name declaration 205

name, difference from C 1276

namespace 205

scope, difference from C 1273, 1276

union and 213

structure 202

initialization of 202

logical program 420

of book 4

operations on 203

physical program 419–420

size of 203

student_t_distribution 1188

style, programming 10

subarray 1168, 1172, 1174–1175

subclass 578–579

superclass and 66

submatch

$i 1061

$ii 1061

sub_match

> 1058

>= 1058

= 1058

== 1058

< 1058

<= 1058

!= 1058

compare() 1058

length() 1058

str() 1058

submatches, matches and 1060

subobject, exception and 357

subscript

match_results 1060

Matrix 833

operator [] 174

operator [] 50

subscripting

comma and 183

container 900

map 910

user-defined 550

valarray 1168

subscripting, string 1041

subset of valarray 1168

substitution

failure 691

format 1061

substitution_failure 800

substr(), string 1048

subtraction, pointer 182

subtract_with_carry_engine 1183

suffix

$’ 1061

_ and 823

_copy 938

F 147

f 147

_if 930

l 147

L 147

literal 147, 558

LL 147

ll 147

return type 308

u 147

U 147

suffix(), match_results 1060

sum() 701

valarray 1169

superclass 578–579

and subclass 66

support, run-time 15

surprise, ADL 397

swap() 195, 382, 738, 942, 1029

and copy 514

and move 516

and move() 516

array 974

container 902

match_results 1060

move by 515

packaged_task 1238

pair 983

promise 1237

shared_ptr 992

string 1041

thread 1210

tuple 985

unique_lock 1227

unique_ptr 987

weak_ptr 994

swap_ranges() 942

switch 244

and enum 231

and if 230

compile-time 791

on enumeration 219

statement 43, 230

symbolic constant 264

symmetric operator 539

synchronization, volatile and 1207

Sync_queue example 1232

synonym

– see typedef

– see using

syntax

error 674

initialization 159

system, language library 15

system_category() 877

systemcategory(), errc 880

system_clock 1016

system_error 877

async() throws 868

call_once() throws 868

code() 878

condition_variable throws 868

mutex throws 868

packaged_task throws 868

what() 878

<system_error> 864

<system\rror> 874

systems programming 10, 16

T

\t, horizontal tab 143

tab

\t, horizontal 143

\v, vertical 143

table, hash 100, 887

tag

dispatch 124, 957

type 217

tagged union 217

tan(), valarray 1170

tanh() 1163

valarray 1170

task 1191, 1209

and thread 115

communication 120

launcher, async() 1245

passing data to 116

returning results from 116

sharing data 117

task-based concurrency 1235

teaching and C++ 17

technique, built-in feature vs. 17

techniques for exception safety 375

template

literal operator 560

parameter, template and 748

separate compilation of 26

variadic 82

template 31, 78, 668

<> 731, 737

ADL and 754

alias 694

ambiguity 691

and conversion 673

and dependent name 748

and friend 682

and generic programming 665

and inheritance 673

and macro 750

and name of template 748

and namespace 753

and nesting 680

and template parameter 748

and typedef 694

and using 694

argument 722

argument class member 748

argument, deducing 685, 687

argument, default 728

argument, dependency on 746

argument, explicit 686

argument, function 686

argument, int 685

argument, lambda 727

argument local name 748

arguments, inlining 671

as template parameter 727

base class 756

benefits 721

class 78, 670

copy assignment and 679

copy constructor and 679

data member 675

defining a 669

definition check 717

definition, context of 746

error detection 674

function 79, 670, 684

function, virtual 679

inclusion 695

instantiation 671, 742

instantiation, context of 746

instantiation directive 744

instantiation, explicit 744

linkage 697

literal type argument 724

Matrix 831

member 670

member alias 676

member, class 675

member function 676

member template 678

member type 677

member typedef 676

member using 676

metaprogramming 779

name binding 745

nested template 678

operation as argument 725

overloading, function 689

parameter 722

parameter, non-type 724

parameter pack 812

parameter, template as 727

parameter, typename and 747

performance 780

pointer argument 724

primary 735

purpose 699

reference and 688

requirement 704

requirements 672

source code 695

specialization 671, 730

static member 676

string argument 724

this and 466

Turing complete 780

type argument 722

type checking 672

type safe 666

type safety 780

value argument 724

variadic 809, 812

temporary 191

elimination of 853

lifetime of 261

object 167, 261

reference and 191

storage 167

value 261

variable 261

tera 1018

terminate program 346

terminate() 372, 872

terminate_handler 372

termination 347

program 443

test(), bitset 980

test_and_set(), atomic_flag 1205

testing 1180

precondition 359

<tgmath> 1278

the $ character, $$ 1061

this 571

and template 466

lambda 296

this-> required 758

this, self-reference 464

this_thread

get_id() 1217

sleep_for() 1217

sleep_until() 1217

yield() 1217

thousands_sep()

moneypunct 1136

separator character 1129

thread 1191, 1209

support, C-style vs. C++-style 1192

support, POSIX 1192

thread 1210

constructor 1210, 1212

destructor 1210, 1213

destructor and join() 1215

detach() 1210, 1215

exception and 374

getid() 1210

hardware_concurrency() 1210

id 1210–1211

identity 1211

join() 1210, 1214

joinable() 1210

native_handle() 1210

native_handle_type 1210

packaged_task 121

preempt 1217

swap() 1210

task and 115

<thread> 115, 865

thread::id, hash of 915

thread_local 1218

thread-support, type-safe 1192

throw 363, 369

and catch 344

copy and 364, 507

destructor and 354

move and 507

specification 367

throw_withnested() 871

Tic_tac_toe example 522

tie(), tuple 985

time 123

constant 894

critical, exception and 349

linear 894

logarithmic 894

memory access 1195

quadratic 894

traits 1016

__TIME__ 340

timed_mutex

and recursive_timed_mutex 1224

constructor 1224

destructor 1224

lock() 1224

native_handle() 1224

native_handle_type 1224

trylock() 1224

trylock_for() 1224

trylock_until() 1224

unlock() 1224

<time.h> 863, 865

timeline, C++ 22

time_point 123

!= 1014

+= 1014

> 1014

>= 1014

= 1013

== 1014

-= 1014

- 1014

< 1014

<= 1014

+ 1014

constructor 1013

duration 1013

max() 1014

min() 1014

time_point_cast() 1014

time_since_epoch() 1013

time_point_cast(), time_point 1014

time_since_epoch(), time_point 1013

timing, clock 118

Tiny example 543

tinyness_before 1161

T[n] built-in array 887

to() conversion 730

to_char_type(), char_traits 1035

to_int_type(), char_traits 1035

token, lexical 258

Token example 243

Token_stream example 247

tolower() 1034

ctype 1144

top()

of priority_queue 923

of stack 920

top-down destruction 486

to_string()

bitset 980

string 1042

total order 892

Totally_ordered 710, 716

to_time_t(), clock 1015

to_ullong(), bitset 980

to_ulong(), bitset 980

toupper() 1034

ctype 1144

tour of C++ 37

to_wstring(), string

Tracer example 483

traditional hierarchy 614

trait 788

alias 788

type function 788

traits

character 1035

overuse of 789

time 1016

transform() 935

collate 1126–1127

regex_traits 1070

transformprimary(), regex_traits 1070

transition and using directive 416

translate(), regex_traits 1070

translate_nocase(), regex_traits 1070

translation unit 420

transparency, exception 378

traps 1161

treat_as_floating_point 1016

trivial type 211

trivially copyable type 211

true

and 1 139

true_type and 800

truename() 1130

true_type and true 800

truly random number 1185

truncate 270

truncation 270

try

block 55, 344

block as function body 98, 371

try-block 378

try_lock() 1229

mutex 1221

trylock(), timed_mutex 1224

try_lock(), unique_lock 1227

trylock_for(), timed_mutex 1224

try_lock_for(), unique_lock 1227

trylock_until(), timed_mutex 1224

try_lock_until(), unique_lock 1227

try_to_lock_t 1227

Tuple

and stack 804

element access 806

example 802

get() example 806

index 806

layout 804

list 802

use 804

tuple 127, 815, 984

!= 985

> 985

>= 985

= 985

== 985

< 985

<= 985

<< 817

allocator_arg_t 985

constructor 984

destructor 985

forward_as_tuple() 985

get() 985

maketuple() 985

swap() 985

tie() 985

tuple_cat 985

tuple_elements 985

tuple_size 985

uses_allocator 985

<tuple> 863

tuple_cat, tuple 985

tuple_element, array 977

tuple_elements, tuple 985

tuple\lement, pair 984

tuple_size, array 977

tuplesize, pair 984

tuple_size, tuple 985

Turing complete, template 780

tutorial and manual 3

two-level programming 779

type 40, 138

abstract 65

alias 167, 784

argument, template 722

arithmetic 139

atomic 1200

base 153

built-in 47, 139

char, character 141

character 140, 1035

check, function argument 315

check, return value 309

checking 13

checking, compile-time 13

checking, delayed 784

checking, static 13

checking, template 672

class user-defined 450

closure 297

concrete 60, 470

constructor for built-in 301, 494

conversion 543

conversion, ambiguous 546

conversion, constructor and 538, 543

conversion, explicit 298

conversion, function argument 315

conversion, implicit 150, 267, 544, 575

conversion operator 543

conversion, return value 309

conversion, unions and 214

conversion, user-defined 535, 575, 678

default underlying 219, 223

enum class underlying 219

enum underlying 223

enum user-defined 220

equivalence 210, 673

erasure 733

error 674

floating-point 139, 146

function 124, 781

function, constexpr 786

function, trait 788

function, using 784

fundamental 40, 138

incomplete 205

input of user-defined 94

integer 139, 144

integral 139

literal 264–265

literal of user-defined 540

member 469

move of built-in 516

of {} 289

of integer literal 146

of integer literal, implementation dependency 146

of lambda 297

of overriding function 596

of string literal 176

ordered 707

output of user-defined 94

parameterized 78

polymorphic 66, 587

predicate 785

regular 706

result 258

return 307–308

reuse of concrete 478

safe, template 666

safety, compile-time 264

safety, template 780

signed 144

size of 40

standard layout 211

tag 217

template member 677

trivial 211

trivially copyable 211

typename and name of 747

unsigned 144

user-defined 139, 201

user-defined operator and built-in 532

value 478

::type

convention 784

delayed checking 784

typedef

alias 168

template and 694

template member 676

type-field 583

typeid() throws bad_typeid 868

type_index and type_info 1030

typeindex, hash of 915

<typeindex> 863

type_info, type_index and 1030

<typeinfo> 865

typename 78, 105

... 812

and class 668

and dependent name 747

and name of type 747

and template parameter 747

type-rich programming 13

types

container member 896

user-defined 47

type-safe

linkage 420

thread-support 1192

<type_traits> 126, 863

typical operations 471

typing, duck 700

U

U’ prefix 147

U” prefix 147

U suffix 147

U’, universal character name 144

%u format 1256

u’ prefix 147

u” prefix 147

\U, regex 1054

\u, regex 1054

u suffix 147

\u, universal character name 179

u16string 1037

basic_string<char16_t> 887

hash of 915

u32string 1037

basic_string<char32_t> 887

u8” prefix 147

unary

* 172

operator, user-defined 530

uncaught exception 372

uncaught_exception() 872

#undef 339

undefined

behavior 136

enum class conversion 221

enum conversion 223

underflow, stack 922

underlying

type, default 219, 223

type, enum 223

type, enum class 219

underlying_type 1025

underscore character, _ 155

unexpected handler 367

Unicode 1146

literal 179

uniform

distributions 1186

initialization 492

uniform_int_distribution 129, 1186

uniform_real_distribution 1186

uninitialized 41

memory 1005

variable 161, 490

uninitialized_copy() 941

uninitialized_copy_n() 941

uninitialized_fill() 377, 941

uninitialized_fill_n() 941

union example, anonymous 564

union 201, 213

and class 215

and struct 213

anonymous 213, 216

copy 215

default initialization 216

discriminated 217

member 215

tagged 217

unnamed 213

unions and type conversion 214

unique() 937

list 907

unique_copy() 102, 937

unique_lock 117, 119

bool 1227

constructor 1227

destructor 1227

lock() 1227

lock_guard and 1225

mutex() 1227

owns_lock() 1227

release() 1227

swap() 1227

try_lock() 1227

try_lock_for() 1227

try_lock_until() 1227

unlock() 1227

unique_ptr 71, 112

< 987

<= 987

-> 987

* 987

!= 987

> 987

== 987

array 988

constructor 987

conversion to bool 987

destructor 987

get() 987

get_deleter() 987

hash of 915

<memory> 987

nullptr 987

owner 987

release() 987

reset() 987

swap() 987

unit

checking 818

of addressing 172

of allocation 172

of compilation 419

translation 420

Unit 819

literal 822

universal

character name \u 179

character name U’ 144

initialization 492

UNIX 15

unlock()

mutex 1221

timed_mutex 1224

unique_lock 1227

unnamed

argument 308

enum 224

namespace 415, 423

union 213

unordered

associative container 887, 913

container 909

unordered_map 100, 914

begin() 920

bucket() 920

bucket 920

bucket_count() 920

bucket_size() 920

cbegin() 920

cend() 920

constructor 915

end() 920

hashed 887

hash_function() 919

key_eq() 919

load_factor() 919

maxbucket_count() 920

max_load_factor() 919

operation 893

rehash() 919

representation 889

reserve() 919

<unordered_map> 863

unordered_multimap

hashed 887

operation 893

unordered_multiset

hashed 887

operation 893

unordered_set

hashed 887

operation 893

<unordered_set> 863

unpredictable, shared_ptr 991

unqualified {} 288

unshift(), codecvt 1148

unsigned

char 140, 142

integer conversion, signed 268

type 144

unspecified 136

unused, function argument 308

unwinding, stack 364, 865

upper, regex 1054

upper_bound() 945

map 910

use

enable_if 797

of {} 159

of abstract class 622

of auto 160, 163

of C++ 9, 30

of C++11 facilities 8

of facet 1119

of headers 439

of initializer_list 497

of specialization 743

Tuple 804

use_count(), weak_ptr 994

used function only, instantiate 743

use_facet() 1119

user specialization 742

user-defined

binary operator 530

facet 1123

facet Season_io 1120

hash 916

literal 822

literals 558

memory management, example of 561

operator 62, 529

operator = 575

operator + 532, 575

operator ++ 531, 554

operator += 531, 536, 575

operator -- 554

operator -> 552

operator and built-in type 532

operator and enum 532

operator, enum 220

specialization 730

subscripting 550

type 139, 201

type, class 450

type conversion 535, 575, 678

type, enum 220

type, input of 94

type, literal of 540

type, output of 94

types 47

unary operator 530

user-supplied comparison 891

uses

Matrix 828

of parentheses 260

uses_allocator

packaged_task 1238

tuple 985

using

:: 403

default operations 520

using 403

using

alias 83, 167

and member 593

declaration 393

declaration vs. using directive 405

directive 394

directive and definition 408

directive, transition and 416

directive, using declaration vs. 405

namespace 416

namespace, using vs. 405

template and 694

template member 676

type function 784

using 403

vs. using namespace 405

using-declaration and access control 606

usual arithmetic conversions 258, 271

UTF-16 179

UTF-32 179

UTF-8 179

and ASCII 179

utilities 863

<utility> 127, 863

pair 983

V

\v, vertical tab 143

va_arg() 323

valarray 131, 1166

<< 1170

<<= 1167

/ 1170

/= 1167

- 1170

-= 1167

+ 1170

+= 1167

* 1170

*= 1167

& 1170

&= 1167

&& 1170

!= 1170

! 1170

%= 1167

% 1170

~ 1170

[] 1168

^ 1170

^= 1167

> 1170

>> 1170

>>= 1167

>= 1170

= 1167, 1174

== 1170

< 1170

<= 1170

|| 1170

| 1170

|= 1167

abs() 1170

acos() 1170

and array 1166

apply() 1169

asin() 1170

assignment 1167, 1174

atan() 1170

atan2() 1170

begin() 1170

cos() 1170

cosh() 1170

end() 1170

exp() 1170

iterator 1173

length 1169

log() 1170

log10() 1170

mathematical functions 1170

max() 1169

min() 1169

numerical 887

operations 1169–1170

pow() 1170

resize() 1169

sin() 1170

sinh() 1170

size() 1169

sqrt() 1170

subscripting 1168

subset of 1168

sum() 1169

tan() 1170

tanh() 1170

<valarray> 131, 865, 1166

valid

pointer 140, 228

state 353

valid()

future 1241

packaged_task 1238

value 40

and object 510

and state 510

argument, template 724

call by 316

choice of default 495

concept 715

default 473, 490

key and 100

mapped type 100

object state and 510

of cin 544

of notation 527

return by 310

return, function 482

return, function 308

semantics 562

temporary 261

type 478

::value convention 786

value()

error_category 877

error_code 875

regex_traits 1070

value_comp(), map 910

value-oriented programming 478

value_type 83, 896

iterator_traits 957

of pointer 788

value_type&, reference 896

variable 40

const 461

data race, static 314

global 423, 467

initialization of 227

initialization of local 314

local 314

number of argument 321

temporary 261

uninitialized 161, 490

variadic

template 809, 812

template 82

Vec

example 97

range checking 97

vector

arithmetic 131, 1166

bit 274

exponentiation 1170

mathematical functions 1170

operations 1170

Vector

example 730

Matrix and 682

vector 95

array vs. 976

contiguous 886

operation 893

operator= 382

pushback() 385

representation 888

throws out_of_range 868

<vector> 863

vector_base 379

vector<bool> 981

bit order 982

bitset and 977

compactly stored 887

versioning, namespace and 412

vertical tab \v 143

virtual 65

base class 632

base class, override from 638

base, constructor and 634

base, copy of 510

base layout 633

base, replicated vs. 636

constructor 597, 623

destructor 70, 488, 598, 619

function 307, 585, 625

function argument types 586

function, definition of 586

function, implementation of 67

function, operator :: and 589

function, pure 598

function table vtbl 67, 587

pure 65

return type of 596

template function 679

void 148

* 173

* assignment, difference from C 1275

*, pointer to member 607

*, specialization and 730

expression, return of 310

pointer to 173

return type 40

*volatile 154

volatile 1206

and synchronization 1207

vtbl, virtual function table 67, 587

W

w, file mode 1254

\w, regex 1054

\W, regex 1054

w, regex 1054

wait() 119

condition_variable 1231

future 1241

wait_for()

condition_variable 1231

future 1241

wait_until()

condition_variable 1231

future 1241

<wchar.h> 864, 1124

wchart 140

wchar_t 144, 1146

wcmatch 1060

wcregex_iterator 1067

wcregex_token_iterator 1068

weak order, strict 891

weaknesses, shared_ptr 991

weak_ptr 993

= 994

constructor 994

destructor 994

expired() 994

lock() 994

owner_before() 994

reset() 994

swap() 994

use_count() 994

Web, C++ and 30

weibull_distribution 1187

WG21 22

what() system_error 878

when to use metaprogramming 794

while statement 44, 236

whitespace, isspace() 250

wide-character literal L’ 144

widen(), ctype 1144

Window example 635

word 150

wsmatch 1060

wsregex_iterator 1067

wsregex_token_iterator 1068

wstring 1037

basic_string<wchar_t> 887

hash of 915

<wtype.h> 864

www.stroustrup.com, exercises – see

X

x, file mode 1254

%x format 1256

%X format 1256

X3J16 25

xdigit, regex 1054

xor, ^ 258

xor_eq, ^= 258

xvalue 166

Y

&y, bit_and 966

yield(), this_thread 1217

yocto 1018

yotta 1018

Z

zepto 1018

zero null, 0 174

zero(), duration 1012

zero-dimensional, Matrix 848

zero-overhead principle 10

zero-terminated array 175

zeta, Riemann 1164

zetta 1018

Preparation for Programming in the Real World

ISBN-13: 978-0-321-54372-1

From Bjarne Stroustrup, the inventor of C++, comes Programming: Principles and Practice Using C++, a general introduction to programming, including object-oriented programming and generic programming, and a solid introduction to the C++ programming language. Stroustrup presents modern C++ programming techniques from the start, introducing the C++ standard library to simplify programming tasks.

The book is primarily designed for people who have never programmed before, and it has been tested with more than ten thousand first-year students and thousands of self-study learners. However, practitioners and advanced students also will gain new insight and guidance by seeing how a recognized master approaches the elements of his art.

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