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Friday, April 28, 2023

C++

https://en.wikipedia.org/wiki/C%2B%2B
Not to be confused with C++/CLI, a variant of C++, modified for the Common Language Infrastructure.
ISO C++ Logo.svg
Logo endorsed by the C++ standards committee

ParadigmsMulti-paradigm: procedural, imperative, functional, object-oriented, generic, modular
FamilyC
Designed byBjarne Stroustrup
DeveloperISO/IEC JTC 1 (Joint Technical Committee 1) / SC 22 (Subcommittee 22) / WG 21 (Working Group 21)
First appeared1985; 38 years ago

Stable release
C++20 (ISO/IEC 14882:2020) / 15 December 2020; 2 years ago
Preview release
C++23 / 18 December 2022; 4 months ago
Typing disciplineStatic, strong, nominative, partially inferred
OSCross-platform
Filename extensions.C, .cc, .cpp, .cxx, .c++, .h, .H, .hh, .hpp, .hxx, .h++
Websiteisocpp.org
Major implementations
GCC, LLVM Clang, Microsoft Visual C++, Embarcadero C++Builder, Intel C++ Compiler, IBM XL C++, EDG
Influenced by
Ada, ALGOL 68, BCPL, C, CLU, F#, ML, Mesa, Modula-2, Simula, Smalltalk
Influenced
Ada 95, C#, C99, Carbon, Chapel, Clojure, D, Java, JS++, Lua, Nim, Objective-C++, Perl, PHP, Python, Rust, Seed7
  • C++ Programming at Wikibooks

C++ (/ˈsiː plʌs plʌs/, pronounced "C plus plus") is a high-level, general-purpose programming language created by Danish computer scientist Bjarne Stroustrup. First released in 1985 as an extension of the C programming language, it has since expanded significantly over time; modern C++ currently has object-oriented, generic, and functional features, in addition to facilities for low-level memory manipulation. It is almost always implemented as a compiled language, and many vendors provide C++ compilers, including the Free Software Foundation, LLVM, Microsoft, Intel, Embarcadero, Oracle, and IBM.

C++ was designed with systems programming and embedded, resource-constrained software and large systems in mind, with performance, efficiency, and flexibility of use as its design highlights. C++ has also been found useful in many other contexts, with key strengths being software infrastructure and resource-constrained applications, including desktop applications, video games, servers (e.g. e-commerce, web search, or databases), and performance-critical applications (e.g. telephone switches or space probes).

C++ is standardized by the International Organization for Standardization (ISO), with the latest standard version ratified and published by ISO in December 2020 as ISO/IEC 14882:2020 (informally known as C++20). The C++ programming language was initially standardized in 1998 as ISO/IEC 14882:1998, which was then amended by the C++03, C++11, C++14, and C++17 standards. The current C++20 standard supersedes these with new features and an enlarged standard library. Before the initial standardization in 1998, C++ was developed by Stroustrup at Bell Labs since 1979 as an extension of the C language; he wanted an efficient and flexible language similar to C that also provided high-level features for program organization. Since 2012, C++ has been on a three-year release schedule with C++23 as the next planned standard.

History

Bjarne Stroustrup, the creator of C++, in his AT&T New Jersey office, c. 2000

In 1979, Bjarne Stroustrup, a Danish computer scientist, began work on "C with Classes", the predecessor to C++. The motivation for creating a new language originated from Stroustrup's experience in programming for his PhD thesis. Stroustrup found that Simula had features that were very helpful for large software development, but the language was too slow for practical use, while BCPL was fast but too low-level to be suitable for large software development. When Stroustrup started working in AT&T Bell Labs, he had the problem of analyzing the UNIX kernel with respect to distributed computing. Remembering his PhD experience, Stroustrup set out to enhance the C language with Simula-like features. C was chosen because it was general-purpose, fast, portable and widely used. As well as C and Simula's influences, other languages also influenced this new language, including ALGOL 68, Ada, CLU and ML.

Initially, Stroustrup's "C with Classes" added features to the C compiler, Cpre, including classes, derived classes, strong typing, inlining and default arguments.

A quiz on C++11 features being given in Paris in 2015

In 1982, Stroustrup started to develop a successor to C with Classes, which he named "C++" (++ being the increment operator in C) after going through several other names. New features were added, including virtual functions, function name and operator overloading, references, constants, type-safe free-store memory allocation (new/delete), improved type checking, and BCPL style single-line comments with two forward slashes (//). Furthermore, Stroustrup developed a new, standalone compiler for C++, Cfront.

In 1984, Stroustrup implemented the first stream input/output library. The idea of providing an output operator rather than a named output function was suggested by Doug McIlroy (who had previously suggested Unix pipes).

In 1985, the first edition of The C++ Programming Language was released, which became the definitive reference for the language, as there was not yet an official standard. The first commercial implementation of C++ was released in October of the same year.

In 1989, C++ 2.0 was released, followed by the updated second edition of The C++ Programming Language in 1991. New features in 2.0 included multiple inheritance, abstract classes, static member functions, const member functions, and protected members. In 1990, The Annotated C++ Reference Manual was published. This work became the basis for the future standard. Later feature additions included templates, exceptions, namespaces, new casts, and a Boolean type.

In 1998, C++98 was released, standardizing the language, and a minor update (C++03) was released in 2003.

After C++98, C++ evolved relatively slowly until, in 2011, the C++11 standard was released, adding numerous new features, enlarging the standard library further, and providing more facilities to C++ programmers. After a minor C++14 update released in December 2014, various new additions were introduced in C++17. After becoming finalized in February 2020, a draft of the C++20 standard was approved on 4 September 2020 and officially published on 15 December 2020.

On January 3, 2018, Stroustrup was announced as the 2018 winner of the Charles Stark Draper Prize for Engineering, "for conceptualizing and developing the C++ programming language".

As of December 2022 C++ ranked third on the TIOBE index, surpassing Java for the first time in the history of the index. It ranks 3rd, after Python and C.

Etymology

According to Stroustrup, "the name signifies the evolutionary nature of the changes from C". This name is credited to Rick Mascitti (mid-1983) and was first used in December 1983. When Mascitti was questioned informally in 1992 about the naming, he indicated that it was given in a tongue-in-cheek spirit. The name comes from C's ++ operator (which increments the value of a variable) and a common naming convention of using "+" to indicate an enhanced computer program.

During C++'s development period, the language had been referred to as "new C" and "C with Classes" before acquiring its final name.

Philosophy

Throughout C++'s life, its development and evolution has been guided by a set of principles:

  • It must be driven by actual problems and its features should be immediately useful in real world programs.
  • Every feature should be implementable (with a reasonably obvious way to do so).
  • Programmers should be free to pick their own programming style, and that style should be fully supported by C++.
  • Allowing a useful feature is more important than preventing every possible misuse of C++.
  • It should provide facilities for organising programs into separate, well-defined parts, and provide facilities for combining separately developed parts.
  • No implicit violations of the type system (but allow explicit violations; that is, those explicitly requested by the programmer).
  • User-created types need to have the same support and performance as built-in types.
  • Unused features should not negatively impact created executables (e.g. in lower performance).
  • There should be no language beneath C++ (except assembly language).
  • C++ should work alongside other existing programming languages, rather than fostering its own separate and incompatible programming environment.
  • If the programmer's intent is unknown, allow the programmer to specify it by providing manual control.

Standardization

Scene during the C++ standards committee meeting in Stockholm in 1996
C++ standards
Year C++ Standard Informal name
1998 ISO/IEC 14882:1998 C++98
2003 ISO/IEC 14882:2003 C++03
2011 ISO/IEC 14882:2011 C++11, C++0x
2014 ISO/IEC 14882:2014 C++14, C++1y
2017 ISO/IEC 14882:2017 C++17, C++1z
2020 ISO/IEC 14882:2020 C++20, C++2a
2023
C++23

C++ is standardized by an ISO working group known as JTC1/SC22/WG21. So far, it has published six revisions of the C++ standard and is currently working on the next revision, C++23.

In 1998, the ISO working group standardized C++ for the first time as ISO/IEC 14882:1998, which is informally known as C++98. In 2003, it published a new version of the C++ standard called ISO/IEC 14882:2003, which fixed problems identified in C++98.

The next major revision of the standard was informally referred to as "C++0x", but it was not released until 2011. C++11 (14882:2011) included many additions to both the core language and the standard library.

In 2014, C++14 (also known as C++1y) was released as a small extension to C++11, featuring mainly bug fixes and small improvements. The Draft International Standard ballot procedures completed in mid-August 2014.

After C++14, a major revision C++17, informally known as C++1z, was completed by the ISO C++ committee in mid July 2017 and was approved and published in December 2017.

As part of the standardization process, ISO also publishes technical reports and specifications:

  • ISO/IEC TR 18015:2006 on the use of C++ in embedded systems and on performance implications of C++ language and library features,
  • ISO/IEC TR 19768:2007 (also known as the C++ Technical Report 1) on library extensions mostly integrated into C++11,
  • ISO/IEC TR 29124:2010 on special mathematical functions, integrated into C++17
  • ISO/IEC TR 24733:2011 on decimal floating-point arithmetic,
  • ISO/IEC TS 18822:2015 on the standard filesystem library, integrated into C++17
  • ISO/IEC TS 19570:2015 on parallel versions of the standard library algorithms, integrated into C++17
  • ISO/IEC TS 19841:2015 on software transactional memory,
  • ISO/IEC TS 19568:2015 on a new set of library extensions, some of which are already integrated into C++17,
  • ISO/IEC TS 19217:2015 on the C++ concepts, integrated into C++20
  • ISO/IEC TS 19571:2016 on the library extensions for concurrency, some of which are already integrated into C++20
  • ISO/IEC TS 19568:2017 on a new set of general-purpose library extensions
  • ISO/IEC TS 21425:2017 on the library extensions for ranges, integrated into C++20
  • ISO/IEC TS 22277:2017 on coroutines, integrated into C++20
  • ISO/IEC TS 19216:2018 on the networking library
  • ISO/IEC TS 21544:2018 on modules, integrated into C++20
  • ISO/IEC TS 19570:2018 on a new set of library extensions for parallelism
  • ISO/IEC TS 23619:2021 on new extensions for reflection

More technical specifications are in development and pending approval, including new set of concurrency extensions.

Language

The C++ language has two main components: a direct mapping of hardware features provided primarily by the C subset, and zero-overhead abstractions based on those mappings. Stroustrup describes C++ as "a light-weight abstraction programming language [designed] for building and using efficient and elegant abstractions"; and "offering both hardware access and abstraction is the basis of C++. Doing it efficiently is what distinguishes it from other languages."

C++ inherits most of C's syntax. The following is Bjarne Stroustrup's version of the Hello world program that uses the C++ Standard Library stream facility to write a message to standard output:

#include <iostream>

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

Object storage

As in C, C++ supports four types of memory management: static storage duration objects, thread storage duration objects, automatic storage duration objects, and dynamic storage duration objects.

Static storage duration objects

Static storage duration objects are created before main() is entered (see exceptions below) and destroyed in reverse order of creation after main() exits. The exact order of creation is not specified by the standard (though there are some rules defined below) to allow implementations some freedom in how to organize their implementation. More formally, objects of this type have a lifespan that "shall last for the duration of the program".

Static storage duration objects are initialized in two phases. First, "static initialization" is performed, and only after all static initialization is performed, "dynamic initialization" is performed. In static initialization, all objects are first initialized with zeros; after that, all objects that have a constant initialization phase are initialized with the constant expression (i.e. variables initialized with a literal or constexpr). Though it is not specified in the standard, the static initialization phase can be completed at compile time and saved in the data partition of the executable. Dynamic initialization involves all object initialization done via a constructor or function call (unless the function is marked with constexpr, in C++11). The dynamic initialization order is defined as the order of declaration within the compilation unit (i.e. the same file). No guarantees are provided about the order of initialization between compilation units.

Thread storage duration objects

Variables of this type are very similar to static storage duration objects. The main difference is the creation time is just prior to thread creation and destruction is done after the thread has been joined.

Automatic storage duration objects

The most common variable types in C++ are local variables inside a function or block, and temporary variables. The common feature about automatic variables is that they have a lifetime that is limited to the scope of the variable. They are created and potentially initialized at the point of declaration (see below for details) and destroyed in the reverse order of creation when the scope is left. This is implemented by allocation on the stack.

Local variables are created as the point of execution passes the declaration point. If the variable has a constructor or initializer this is used to define the initial state of the object. Local variables are destroyed when the local block or function that they are declared in is closed. C++ destructors for local variables are called at the end of the object lifetime, allowing a discipline for automatic resource management termed RAII, which is widely used in C++.

Member variables are created when the parent object is created. Array members are initialized from 0 to the last member of the array in order. Member variables are destroyed when the parent object is destroyed in the reverse order of creation. i.e. If the parent is an "automatic object" then it will be destroyed when it goes out of scope which triggers the destruction of all its members.

Temporary variables are created as the result of expression evaluation and are destroyed when the statement containing the expression has been fully evaluated (usually at the ; at the end of a statement).

Dynamic storage duration objects

Main article: new and delete (C++)

These objects have a dynamic lifespan and can be created directly with a call to new and destroyed explicitly with a call to delete. C++ also supports malloc and free, from C, but these are not compatible with new and delete. Use of new returns an address to the allocated memory. The C++ Core Guidelines advise against using new directly for creating dynamic objects in favor of smart pointers through make_unique<T> for single ownership and make_shared<T> for reference-counted multiple ownership, which were introduced in C++11.

Templates

See also: Template metaprogramming and Generic programming

C++ templates enable generic programming. C++ supports function, class, alias, and variable templates. Templates may be parameterized by types, compile-time constants, and other templates. Templates are implemented by instantiation at compile-time. To instantiate a template, compilers substitute specific arguments for a template's parameters to generate a concrete function or class instance. Some substitutions are not possible; these are eliminated by an overload resolution policy described by the phrase "Substitution failure is not an error" (SFINAE). Templates are a powerful tool that can be used for generic programming, template metaprogramming, and code optimization, but this power implies a cost. Template use may increase code size, because each template instantiation produces a copy of the template code: one for each set of template arguments, however, this is the same or smaller amount of code that would be generated if the code was written by hand. This is in contrast to run-time generics seen in other languages (e.g., Java) where at compile-time the type is erased and a single template body is preserved.

Templates are different from macros: while both of these compile-time language features enable conditional compilation, templates are not restricted to lexical substitution. Templates are aware of the semantics and type system of their companion language, as well as all compile-time type definitions, and can perform high-level operations including programmatic flow control based on evaluation of strictly type-checked parameters. Macros are capable of conditional control over compilation based on predetermined criteria, but cannot instantiate new types, recurse, or perform type evaluation and in effect are limited to pre-compilation text-substitution and text-inclusion/exclusion. In other words, macros can control compilation flow based on pre-defined symbols but cannot, unlike templates, independently instantiate new symbols. Templates are a tool for static polymorphism (see below) and generic programming.

In addition, templates are a compile-time mechanism in C++ that is Turing-complete, meaning that any computation expressible by a computer program can be computed, in some form, by a template metaprogram prior to runtime.

In summary, a template is a compile-time parameterized function or class written without knowledge of the specific arguments used to instantiate it. After instantiation, the resulting code is equivalent to code written specifically for the passed arguments. In this manner, templates provide a way to decouple generic, broadly applicable aspects of functions and classes (encoded in templates) from specific aspects (encoded in template parameters) without sacrificing performance due to abstraction.

Objects

Main article: C++ classes

C++ introduces object-oriented programming (OOP) features to C. It offers classes, which provide the four features commonly present in OOP (and some non-OOP) languages: abstraction, encapsulation, inheritance, and polymorphism. One distinguishing feature of C++ classes compared to classes in other programming languages is support for deterministic destructors, which in turn provide support for the Resource Acquisition is Initialization (RAII) concept.

Encapsulation

Encapsulation is the hiding of information to ensure that data structures and operators are used as intended and to make the usage model more obvious to the developer. C++ provides the ability to define classes and functions as its primary encapsulation mechanisms. Within a class, members can be declared as either public, protected, or private to explicitly enforce encapsulation. A public member of the class is accessible to any function. A private member is accessible only to functions that are members of that class and to functions and classes explicitly granted access permission by the class ("friends"). A protected member is accessible to members of classes that inherit from the class in addition to the class itself and any friends.

The object-oriented principle ensures the encapsulation of all and only the functions that access the internal representation of a type. C++ supports this principle via member functions and friend functions, but it does not enforce it. Programmers can declare parts or all of the representation of a type to be public, and they are allowed to make public entities not part of the representation of a type. Therefore, C++ supports not just object-oriented programming, but other decomposition paradigms such as modular programming.

It is generally considered good practice to make all data private or protected, and to make public only those functions that are part of a minimal interface for users of the class. This can hide the details of data implementation, allowing the designer to later fundamentally change the implementation without changing the interface in any way.

Inheritance

Inheritance allows one data type to acquire properties of other data types. Inheritance from a base class may be declared as public, protected, or private. This access specifier determines whether unrelated and derived classes can access the inherited public and protected members of the base class. Only public inheritance corresponds to what is usually meant by "inheritance". The other two forms are much less frequently used. If the access specifier is omitted, a "class" inherits privately, while a "struct" inherits publicly. Base classes may be declared as virtual; this is called virtual inheritance. Virtual inheritance ensures that only one instance of a base class exists in the inheritance graph, avoiding some of the ambiguity problems of multiple inheritance.

Multiple inheritance is a C++ feature allowing a class to be derived from more than one base class; this allows for more elaborate inheritance relationships. For example, a "Flying Cat" class can inherit from both "Cat" and "Flying Mammal". Some other languages, such as C# or Java, accomplish something similar (although more limited) by allowing inheritance of multiple interfaces while restricting the number of base classes to one (interfaces, unlike classes, provide only declarations of member functions, no implementation or member data). An interface as in C# and Java can be defined in C++ as a class containing only pure virtual functions, often known as an abstract base class or "ABC". The member functions of such an abstract base class are normally explicitly defined in the derived class, not inherited implicitly. C++ virtual inheritance exhibits an ambiguity resolution feature called dominance.

Operators and operator overloading

Operators that cannot be overloaded
Operator Symbol
Scope resolution operator ::
Conditional operator ?:
dot operator .
Member selection operator .*
"sizeof" operator sizeof
"typeid" operator typeid
Main article: Operators in C and C++

C++ provides more than 35 operators, covering basic arithmetic, bit manipulation, indirection, comparisons, logical operations and others. Almost all operators can be overloaded for user-defined types, with a few notable exceptions such as member access (. and .*) as well as the conditional operator. The rich set of overloadable operators is central to making user-defined types in C++ seem like built-in types.

Overloadable operators are also an essential part of many advanced C++ programming techniques, such as smart pointers. Overloading an operator does not change the precedence of calculations involving the operator, nor does it change the number of operands that the operator uses (any operand may however be ignored by the operator, though it will be evaluated prior to execution). Overloaded "&&" and "||" operators lose their short-circuit evaluation property.

Polymorphism

See also: Polymorphism (computer science)

Polymorphism enables one common interface for many implementations, and for objects to act differently under different circumstances.

C++ supports several kinds of static (resolved at compile-time) and dynamic (resolved at run-time) polymorphisms, supported by the language features described above. Compile-time polymorphism does not allow for certain run-time decisions, while runtime polymorphism typically incurs a performance penalty.

Static polymorphism

See also: Parametric polymorphism and ad hoc polymorphism

Function overloading allows programs to declare multiple functions having the same name but with different arguments (i.e. ad hoc polymorphism). The functions are distinguished by the number or types of their formal parameters. Thus, the same function name can refer to different functions depending on the context in which it is used. The type returned by the function is not used to distinguish overloaded functions and differing return types would result in a compile-time error message.

When declaring a function, a programmer can specify for one or more parameters a default value. Doing so allows the parameters with defaults to optionally be omitted when the function is called, in which case the default arguments will be used. When a function is called with fewer arguments than there are declared parameters, explicit arguments are matched to parameters in left-to-right order, with any unmatched parameters at the end of the parameter list being assigned their default arguments. In many cases, specifying default arguments in a single function declaration is preferable to providing overloaded function definitions with different numbers of parameters.

Templates in C++ provide a sophisticated mechanism for writing generic, polymorphic code (i.e. parametric polymorphism). In particular, through the curiously recurring template pattern, it's possible to implement a form of static polymorphism that closely mimics the syntax for overriding virtual functions. Because C++ templates are type-aware and Turing-complete, they can also be used to let the compiler resolve recursive conditionals and generate substantial programs through template metaprogramming. Contrary to some opinion, template code will not generate a bulk code after compilation with the proper compiler settings.

Dynamic polymorphism

Inheritance
See also: Subtyping

Variable pointers and references to a base class type in C++ can also refer to objects of any derived classes of that type. This allows arrays and other kinds of containers to hold pointers to objects of differing types (references cannot be directly held in containers). This enables dynamic (run-time) polymorphism, where the referred objects can behave differently, depending on their (actual, derived) types.

C++ also provides the dynamic_cast operator, which allows code to safely attempt conversion of an object, via a base reference/pointer, to a more derived type: downcasting. The attempt is necessary as often one does not know which derived type is referenced. (Upcasting, conversion to a more general type, can always be checked/performed at compile-time via static_cast, as ancestral classes are specified in the derived class's interface, visible to all callers.) dynamic_cast relies on run-time type information (RTTI), metadata in the program that enables differentiating types and their relationships. If a dynamic_cast to a pointer fails, the result is the nullptr constant, whereas if the destination is a reference (which cannot be null), the cast throws an exception. Objects known to be of a certain derived type can be cast to that with static_cast, bypassing RTTI and the safe runtime type-checking of dynamic_cast, so this should be used only if the programmer is very confident the cast is, and will always be, valid.

Virtual member functions

Ordinarily, when a function in a derived class overrides a function in a base class, the function to call is determined by the type of the object. A given function is overridden when there exists no difference in the number or type of parameters between two or more definitions of that function. Hence, at compile time, it may not be possible to determine the type of the object and therefore the correct function to call, given only a base class pointer; the decision is therefore put off until runtime. This is called dynamic dispatch. Virtual member functions or methods allow the most specific implementation of the function to be called, according to the actual run-time type of the object. In C++ implementations, this is commonly done using virtual function tables. If the object type is known, this may be bypassed by prepending a fully qualified class name before the function call, but in general calls to virtual functions are resolved at run time.

In addition to standard member functions, operator overloads and destructors can be virtual. An inexact rule based on practical experience states that if any function in the class is virtual, the destructor should be as well. As the type of an object at its creation is known at compile time, constructors, and by extension copy constructors, cannot be virtual. Nonetheless, a situation may arise where a copy of an object needs to be created when a pointer to a derived object is passed as a pointer to a base object. In such a case, a common solution is to create a clone() (or similar) virtual function that creates and returns a copy of the derived class when called.

A member function can also be made "pure virtual" by appending it with = 0 after the closing parenthesis and before the semicolon. A class containing a pure virtual function is called an abstract class. Objects cannot be created from an abstract class; they can only be derived from. Any derived class inherits the virtual function as pure and must provide a non-pure definition of it (and all other pure virtual functions) before objects of the derived class can be created. A program that attempts to create an object of a class with a pure virtual member function or inherited pure virtual member function is ill-formed.

Lambda expressions

C++ provides support for anonymous functions, also known as lambda expressions, with the following form:

[capture](parameters) -> return_type { function_body }

Since C++20, the keyword template is optional for template parameters of lambda expressions:

[capture]<template_parameters>(parameters) -> return_type { function_body }

If the lambda takes no parameters, and no return type or other specifiers are used, the () can be omitted, that is,

[capture] { function_body }

The return type of a lambda expression can be automatically inferred, if possible, e.g.:

[](int x, int y) { return x + y; } // inferred
[](int x, int y) -> int { return x + y; } // explicit

The [capture] list supports the definition of closures. Such lambda expressions are defined in the standard as syntactic sugar for an unnamed function object.

Exception handling

Exception handling is used to communicate the existence of a runtime problem or error from where it was detected to where the issue can be handled. It permits this to be done in a uniform manner and separately from the main code, while detecting all errors. Should an error occur, an exception is thrown (raised), which is then caught by the nearest suitable exception handler. The exception causes the current scope to be exited, and also each outer scope (propagation) until a suitable handler is found, calling in turn the destructors of any objects in these exited scopes. At the same time, an exception is presented as an object carrying the data about the detected problem.

Some C++ style guides, such as Google's, LLVM's, and Qt's forbid the usage of exceptions.

The exception-causing code is placed inside a try block. The exceptions are handled in separate catch blocks (the handlers); each try block can have multiple exception handlers, as it is visible in the example below.

#include <iostream>
#include <vector>
#include <stdexcept>

int main() {
    try {
        std::vector<int> vec{3, 4, 3, 1};
        int i{vec.at(4)}; // Throws an exception, std::out_of_range (indexing for vec is from 0-3 not 1-4)
    }
    // An exception handler, catches std::out_of_range, which is thrown by vec.at(4)
    catch (const std::out_of_range &e) {
        std::cerr << "Accessing a non-existent element: " << e.what() << '\n';
    }
    // To catch any other standard library exceptions (they derive from std::exception)
    catch (const std::exception &e) {
        std::cerr << "Exception thrown: " << e.what() << '\n';
    }
    // Catch any unrecognised exceptions (i.e. those which don't derive from std::exception)
    catch (...) {
        std::cerr << "Some fatal error\n";
    }
}

It is also possible to raise exceptions purposefully, using the throw keyword; these exceptions are handled in the usual way. In some cases, exceptions cannot be used due to technical reasons. One such example is a critical component of an embedded system, where every operation must be guaranteed to complete within a specified amount of time. This cannot be determined with exceptions as no tools exist to determine the maximum time required for an exception to be handled.

Unlike signal handling, in which the handling function is called from the point of failure, exception handling exits the current scope before the catch block is entered, which may be located in the current function or any of the previous function calls currently on the stack.

Enumerated types

C++ has enumeration types that are directly inherited from C's and work mostly like these, except that an enumeration is a real type in C++, giving added compile-time checking. Also (as with structs), the C++ enum keyword is combined with a typedef, so that instead of naming the type enum name, simply name it name. This can be simulated in C using a typedef: typedef enum {Value1, Value2} name;

C++11 also provides a second kind of enumeration, called a scoped enumeration. These are type-safe: the enumerators are not implicitly converted to an integer type. Among other things, this allows I/O streaming to be defined for the enumeration type. Another feature of scoped enumerations is that the enumerators do not leak, so usage requires prefixing with the name of the enumeration (e.g., Color::Red for the first enumerator in the example below), unless a using enum declaration (introduced in C++20) has been used to bring the enumerators into the current scope. A scoped enumeration is specified by the phrase enum class (or enum struct). For example:

enum class Color {Red, Green, Blue};

The underlying type of an enumeration is an implementation-defined integral type that is large enough to hold all enumerated values; it does not have to be the smallest possible type. The underlying type can be specified directly, which allows "forward declarations" of enumerations:

enum class Color : long {Red, Green, Blue};  // must fit in size and memory layout the type 'long'
enum class Shapes : char;  // forward declaration. If later there are values defined that don't fit in 'char' it is an error.

Standard library

The draft "Working Paper" standard that became approved as C++98; half of its size was devoted to the C++ Standard Library.
 
Main article: C++ Standard Library

The C++ standard consists of two parts: the core language and the standard library. C++ programmers expect the latter on every major implementation of C++; it includes aggregate types (vectors, lists, maps, sets, queues, stacks, arrays, tuples), algorithms (find, for_each, binary_search, random_shuffle, etc.), input/output facilities (iostream, for reading from and writing to the console and files), filesystem library, localisation support, smart pointers for automatic memory management, regular expression support, multi-threading library, atomics support (allowing a variable to be read or written to by at most one thread at a time without any external synchronisation), time utilities (measurement, getting current time, etc.), a system for converting error reporting that doesn't use C++ exceptions into C++ exceptions, a random number generator and a slightly modified version of the C standard library (to make it comply with the C++ type system).

A large part of the C++ library is based on the Standard Template Library (STL). Useful tools provided by the STL include containers as the collections of objects (such as vectors and lists), iterators that provide array-like access to containers, and algorithms that perform operations such as searching and sorting.

Furthermore, (multi)maps (associative arrays) and (multi)sets are provided, all of which export compatible interfaces. Therefore, using templates it is possible to write generic algorithms that work with any container or on any sequence defined by iterators. As in C, the features of the library are accessed by using the #include directive to include a standard header. The C++ Standard Library provides 105 standard headers, of which 27 are deprecated.

The standard incorporates the STL that was originally designed by Alexander Stepanov, who experimented with generic algorithms and containers for many years. When he started with C++, he finally found a language where it was possible to create generic algorithms (e.g., STL sort) that perform even better than, for example, the C standard library qsort, thanks to C++ features like using inlining and compile-time binding instead of function pointers. The standard does not refer to it as "STL", as it is merely a part of the standard library, but the term is still widely used to distinguish it from the rest of the standard library (input/output streams, internationalization, diagnostics, the C library subset, etc.).

Most C++ compilers, and all major ones, provide a standards-conforming implementation of the C++ standard library.

C++ Core Guidelines

The C++ Core Guidelines are an initiative led by Bjarne Stroustrup, the inventor of C++, and Herb Sutter, the convener and chair of the C++ ISO Working Group, to help programmers write 'Modern C++' by using best practices for the language standards C++11 and newer, and to help developers of compilers and static checking tools to create rules for catching bad programming practices.

The main aim is to efficiently and consistently write type and resource safe C++.

The Core Guidelines were announced in the opening keynote at CPPCon 2015.

The Guidelines are accompanied by the Guideline Support Library (GSL), a header only library of types and functions to implement the Core Guidelines and static checker tools for enforcing Guideline rules.

Compatibility

To give compiler vendors greater freedom, the C++ standards committee decided not to dictate the implementation of name mangling, exception handling, and other implementation-specific features. The downside of this decision is that object code produced by different compilers is expected to be incompatible. There were, however, attempts to standardize compilers for particular machines or operating systems (for example C++ ABI), though they seem to be largely abandoned now.

With C

Further information: Compatibility of C and C++

C++ is often considered to be a superset of C but this is not strictly true. Most C code can easily be made to compile correctly in C++ but there are a few differences that cause some valid C code to be invalid or behave differently in C++. For example, C allows implicit conversion from void* to other pointer types but C++ does not (for type safety reasons). Also, C++ defines many new keywords, such as new and class, which may be used as identifiers (for example, variable names) in a C program.

Some incompatibilities have been removed by the 1999 revision of the C standard (C99), which now supports C++ features such as line comments (//) and declarations mixed with code. On the other hand, C99 introduced a number of new features that C++ did not support that were incompatible or redundant in C++, such as variable-length arrays, native complex-number types (however, the std::complex class in the C++ standard library provides similar functionality, although not code-compatible), designated initializers, compound literals, and the restrict keyword. Some of the C99-introduced features were included in the subsequent version of the C++ standard, C++11 (out of those which were not redundant). However, the C++11 standard introduces new incompatibilities, such as disallowing assignment of a string literal to a character pointer, which remains valid C.

To intermix C and C++ code, any function declaration or definition that is to be called from/used both in C and C++ must be declared with C linkage by placing it within an extern "C" {/*...*/} block. Such a function may not rely on features depending on name mangling (i.e., function overloading).

Criticism

Main article: Criticism of C++

Despite its widespread adoption, some notable programmers have criticized the C++ language, including Linus Torvalds, Richard Stallman, Joshua Bloch, Ken Thompson and Donald Knuth.

One of the most often criticised points of C++ is its perceived complexity as a language, with the criticism that a large number of non-orthogonal features in practice necessitates restricting code to a subset of C++, thus eschewing the readability benefits of common style and idioms. As expressed by Joshua Bloch:

I think C++ was pushed well beyond its complexity threshold, and yet there are a lot of people programming it. But what you do is you force people to subset it. So almost every shop that I know of that uses C++ says, "Yes, we're using C++ but we're not doing multiple-implementation inheritance and we're not using operator overloading.” There are just a bunch of features that you're not going to use because the complexity of the resulting code is too high. And I don't think it's good when you have to start doing that. You lose this programmer portability where everyone can read everyone else's code, which I think is such a good thing.

Donald Knuth (1993, commenting on pre-standardized C++), who said of Edsger Dijkstra that "to think of programming in C++" "would make him physically ill":

The problem that I have with them today is that... C++ is too complicated. At the moment, it's impossible for me to write portable code that I believe would work on lots of different systems, unless I avoid all exotic features. Whenever the C++ language designers had two competing ideas as to how they should solve some problem, they said "OK, we'll do them both". So the language is too baroque for my taste.

Ken Thompson, who was a colleague of Stroustrup at Bell Labs, gives his assessment:

It certainly has its good points. But by and large I think it's a bad language. It does a lot of things half well and it's just a garbage heap of ideas that are mutually exclusive. Everybody I know, whether it's personal or corporate, selects a subset and these subsets are different. So it's not a good language to transport an algorithm—to say, "I wrote it; here, take it." It's way too big, way too complex. And it's obviously built by a committee. Stroustrup campaigned for years and years and years, way beyond any sort of technical contributions he made to the language, to get it adopted and used. And he sort of ran all the standards committees with a whip and a chair. And he said "no" to no one. He put every feature in that language that ever existed. It wasn't cleanly designed—it was just the union of everything that came along. And I think it suffered drastically from that.

However Brian Kernighan, also a colleague at Bell Labs, disputes this assessment:

C++ has been enormously influential. ... Lots of people say C++ is too big and too complicated etc. etc. but in fact it is a very powerful language and pretty much everything that is in there is there for a really sound reason: it is not somebody doing random invention, it is actually people trying to solve real world problems. Now a lot of the programs that we take for granted today, that we just use, are C++ programs.

Stroustrup himself comments that C++ semantics are much cleaner than its syntax: "within C++, there is a much smaller and cleaner language struggling to get out".

Other complaints may include a lack of reflection or garbage collection, long compilation times, perceived feature creep, and verbose error messages, particularly from template metaprogramming.

at April 28, 2023
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History of compiler construction

https://en.wikipedia.org/wiki/History_of_compiler_construction

History of computing
Eniac.jpg

In computing, a compiler is a computer program that transforms source code written in a programming language or computer language (the source language), into another computer language (the target language, often having a binary form known as object code or machine code). The most common reason for transforming source code is to create an executable program.

Any program written in a high-level programming language must be translated to object code before it can be executed, so all programmers using such a language use a compiler or an interpreter. Thus, compilers are very important to programmers. Improvements to a compiler may lead to a large number of improved features in executable programs.

The Production Quality Compiler-Compiler, in the late 1970s, introduced the principles of compiler organization that are still widely used today (e.g., a front-end handling syntax and semantics and a back-end generating machine code).

First compilers

Software for early computers was primarily written in assembly language, and before that directly in machine code. It is usually more productive for a programmer to use a high-level language, and programs written in a high-level language can be reused on different kinds of computers. Even so, it took a while for compilers to become established, because they generated code that did not perform as well as hand-written assembler, they were daunting development projects in their own right, and the very limited memory capacity of early computers created many technical problems for practical compiler implementations.

The first practical compiler was written by Corrado Böhm in 1951 for his PhD thesis, one of the first computer science doctorates awarded anywhere in the world.

The first implemented compiler was written by Grace Hopper, who also coined the term "compiler", referring to her A-0 system which functioned as a loader or linker, not the modern notion of a compiler. The first Autocode and compiler in the modern sense were developed by Alick Glennie in 1952 at the University of Manchester for the Mark 1 computer. The FORTRAN team led by John W. Backus at IBM introduced the first commercially available compiler, in 1957, which took 18 person-years to create.

The first ALGOL 58 compiler was completed by the end of 1958 by Friedrich L. Bauer, Hermann Bottenbruch, Heinz Rutishauser, and Klaus Samelson for the Z22 computer. Bauer et al. had been working on compiler technology for the Sequentielle Formelübersetzung (i.e. sequential formula translation) in the previous years.

By 1960, an extended Fortran compiler, ALTAC, was available on the Philco 2000, so it is probable that a Fortran program was compiled for both IBM and Philco computer architectures in mid-1960. The first known demonstrated cross-platform high-level language was COBOL. In a demonstration in December 1960, a COBOL program was compiled and executed on both the UNIVAC II and the RCA 501.

Self-hosting compilers

Not to be confused with Compiler-compiler.

Like any other software, there are benefits from implementing a compiler in a high-level language. In particular, a compiler can be self-hosted – that is, written in the programming language it compiles. Building a self-hosting compiler is a bootstrapping problem, i.e. the first such compiler for a language must be either hand written machine code, compiled by a compiler written in another language, or compiled by running the compiler's source on itself in an interpreter.

Corrado Böhm PhD dissertation

Corrado Böhm developed a language, a machine, and a translation method for compiling that language on the machine in his PhD dissertation dated 1951. He not only described a complete compiler, but also defined for the first time that compiler in its own language. The language was interesting in itself, because every statement (including input statements, output statements and control statements) was a special case of an assignment statement.

NELIAC

The Navy Electronics Laboratory International ALGOL Compiler or NELIAC was a dialect and compiler implementation of the ALGOL 58 programming language developed by the Naval Electronics Laboratory in 1958.

NELIAC was the brainchild of Harry Huskey – then Chairman of the ACM and a well known computer scientist (and later academic supervisor of Niklaus Wirth), and supported by Maury Halstead, the head of the computational center at NEL. The earliest version was implemented on the prototype USQ-17 computer (called the Countess) at the laboratory. It was the world's first self-compiling compiler – the compiler was first coded in simplified form in assembly language (the bootstrap), then re-written in its own language and compiled by the bootstrap, and finally re-compiled by itself, making the bootstrap obsolete.

Lisp

Another early self-hosting compiler was written for Lisp by Tim Hart and Mike Levin at MIT in 1962. They wrote a Lisp compiler in Lisp, testing it inside an existing Lisp interpreter. Once they had improved the compiler to the point where it could compile its own source code, it was self-hosting.

The compiler as it exists on the standard compiler tape is a machine language program that was obtained by having the S-expression definition of the compiler work on itself through the interpreter. (AI Memo 39)

This technique is only possible when an interpreter already exists for the very same language that is to be compiled. It borrows directly from the notion of running a program on itself as input, which is also used in various proofs in theoretical computer science, such as the proof that the halting problem is undecidable.

Forth

Forth is an example of a self-hosting compiler. The self compilation and cross compilation features of Forth are synonymous with metacompilation and metacompilers. Like Lisp, Forth is an extensible programming language. It is the extensible programming language features of Forth and Lisp that enable them to generate new versions of themselves or port themselves to new environments.

Context-free grammars and parsers

A parser is an important component of a compiler. It parses the source code of a computer programming language to create some form of internal representation. Programming languages tend to be specified in terms of a context-free grammar because fast and efficient parsers can be written for them. Parsers can be written by hand or generated by a parser generator. A context-free grammar provides a simple and precise mechanism for describing how programming language constructs are built from smaller blocks. The formalism of context-free grammars was developed in the mid-1950s by Noam Chomsky.

Block structure was introduced into computer programming languages by the ALGOL project (1957–1960), which, as a consequence, also featured a context-free grammar to describe the resulting ALGOL syntax.

Context-free grammars are simple enough to allow the construction of efficient parsing algorithms which, for a given string, determine whether and how it can be generated from the grammar. If a programming language designer is willing to work within some limited subsets of context-free grammars, more efficient parsers are possible.

LR parsing

Main article: LR parser

The LR parser (left to right) was invented by Donald Knuth in 1965 in a paper, "On the Translation of Languages from Left to Right". An LR parser is a parser that reads input from Left to right (as it would appear if visually displayed) and produces a Rightmost derivation. The term LR(k) parser is also used, where k refers to the number of unconsumed lookahead input symbols that are used in making parsing decisions.

Knuth proved that LR(k) grammars can be parsed with an execution time essentially proportional to the length of the program, and that every LR(k) grammar for k > 1 can be mechanically transformed into an LR(1) grammar for the same language. In other words, it is only necessary to have one symbol lookahead to parse any deterministic context-free grammar (DCFG).

Korenjak (1969) was the first to show parsers for programming languages could be produced using these techniques. Frank DeRemer devised the more practical Simple LR (SLR) and Look-ahead LR (LALR) techniques, published in his PhD dissertation at MIT in 1969. This was an important breakthrough, because LR(k) translators, as defined by Donald Knuth, were much too large for implementation on computer systems in the 1960s and 1970s.

In practice, LALR offers a good solution; the added power of LALR(1) parsers over SLR(1) parsers (that is, LALR(1) can parse more complex grammars than SLR(1)) is useful, and, though LALR(1) is not comparable with LL(1)(See below) (LALR(1) cannot parse all LL(1) grammars), most LL(1) grammars encountered in practice can be parsed by LALR(1). LR(1) grammars are more powerful again than LALR(1); however, an LR(1) grammar requires a canonical LR parser which would be extremely large in size and is not considered practical. The syntax of many programming languages are defined by grammars that can be parsed with an LALR(1) parser, and for this reason LALR parsers are often used by compilers to perform syntax analysis of source code.

A recursive ascent parser implements an LALR parser using mutually-recursive functions rather than tables. Thus, the parser is directly encoded in the host language similar to recursive descent. Direct encoding usually yields a parser which is faster than its table-driven equivalent for the same reason that compilation is faster than interpretation. It is also (in principle) possible to hand edit a recursive ascent parser, whereas a tabular implementation is nigh unreadable to the average human.

Recursive ascent was first described by Thomas Pennello in his article "Very fast LR parsing" in 1986. The technique was later expounded upon by G.H. Roberts in 1988 as well as in an article by Leermakers, Augusteijn, Kruseman Aretz in 1992 in the journal Theoretical Computer Science.

LL parsing

Main article: LL parser

An LL parser parses the input from Left to right, and constructs a Leftmost derivation of the sentence (hence LL, as opposed to LR). The class of grammars which are parsable in this way is known as the LL grammars. LL grammars are an even more restricted class of context-free grammars than LR grammars. Nevertheless, they are of great interest to compiler writers, because such a parser is simple and efficient to implement.

LL(k) grammars can be parsed by a recursive descent parser which is usually coded by hand, although a notation such as META II might alternatively be used.

The design of ALGOL sparked investigation of recursive descent, since the ALGOL language itself is recursive. The concept of recursive descent parsing was discussed in the January 1961 issue of Communications of the ACM in separate papers by A.A. Grau and Edgar T. "Ned" Irons. Richard Waychoff and colleagues also implemented recursive descent in the Burroughs ALGOL compiler in March 1961, the two groups used different approaches but were in at least informal contact.

The idea of LL(1) grammars was introduced by Lewis and Stearns (1968).

Recursive descent was popularised by Niklaus Wirth with PL/0, an educational programming language used to teach compiler construction in the 1970s.

LR parsing can handle a larger range of languages than LL parsing, and is also better at error reporting (This is disputable, REFERENCE is required), i.e. it detects syntactic errors when the input does not conform to the grammar as soon as possible.

Earley parser

In 1970, Jay Earley invented what came to be known as the Earley parser. Earley parsers are appealing because they can parse all context-free languages reasonably efficiently.

Grammar description languages

John Backus proposed "metalinguistic formulas" to describe the syntax of the new programming language IAL, known today as ALGOL 58 (1959). Backus's work was based on the Post canonical system devised by Emil Post.

Further development of ALGOL led to ALGOL 60; in its report (1963), Peter Naur named Backus's notation Backus normal form (BNF), and simplified it to minimize the character set used. However, Donald Knuth argued that BNF should rather be read as Backus–Naur form, and that has become the commonly accepted usage.

Niklaus Wirth defined extended Backus–Naur form (EBNF), a refined version of BNF, in the early 1970s for PL/0. Augmented Backus–Naur form (ABNF) is another variant. Both EBNF and ABNF are widely used to specify the grammar of programming languages, as the inputs to parser generators, and in other fields such as defining communication protocols.

Parser generators

For a more complete list, which also includes LL, SLR, GLR and LR parser generators, see Comparison of parser generators

A parser generator generates the lexical-analyser portion of a compiler. It is a program that takes a description of a formal grammar of a specific programming language and produces a parser for that language. That parser can be used in a compiler for that specific language. The parser detects and identifies the reserved words and symbols of the specific language from a stream of text and returns these as tokens to the code which implements the syntactic validation and translation into object code. This second part of the compiler can also be created by a compiler-compiler using a formal rules-of-precedence syntax-description as input.

The first compiler-compiler to use that name was written by Tony Brooker in 1960 and was used to create compilers for the Atlas computer at the University of Manchester, including the Atlas Autocode compiler. However it was rather different from modern compiler-compilers, and today would probably be described as being somewhere between a highly customisable generic compiler and an extensible-syntax language. The name "compiler-compiler" was far more appropriate for Brooker's system than it is for most modern compiler-compilers, which are more accurately described as parser generators. It is almost certain that the "Compiler-Compiler" name has entered common use due to Yacc rather than Brooker's work being remembered.

In the early 1960s, Robert McClure at Texas Instruments invented a compiler-compiler called TMG, the name taken from "transmogrification". In the following years TMG was ported to several UNIVAC and IBM mainframe computers.

The Multics project, a joint venture between MIT and Bell Labs, was one of the first to develop an operating system in a high-level language. PL/I was chosen as the language, but an external supplier could not supply a working compiler. The Multics team developed their own subset dialect of PL/I known as Early PL/I (EPL) as their implementation language in 1964. TMG was ported to GE-600 series and used to develop EPL by Douglas McIlroy, Robert Morris, and others.

Not long after Ken Thompson wrote the first version of Unix for the PDP-7 in 1969, Douglas McIlroy created the new system's first higher-level language: an implementation of McClure's TMG. TMG was also the compiler definition tool used by Ken Thompson to write the compiler for the B language on his PDP-7 in 1970. B was the immediate ancestor of C.

An early LALR parser generator was called "TWS", created by Frank DeRemer and Tom Pennello.

XPL

XPL is a dialect of the PL/I programming language, used for the development of compilers for computer languages. It was designed and implemented in 1967 by a team with William M. McKeeman, James J. Horning, and David B. Wortman at Stanford University and the University of California, Santa Cruz. It was first announced at the 1968 Fall Joint Computer Conference in San Francisco.

XPL featured a relatively simple translator writing system dubbed ANALYZER, based upon a bottom-up compiler precedence parsing technique called MSP (mixed strategy precedence). XPL was bootstrapped through Burroughs Algol onto the IBM System/360 computer. (Some subsequent versions of XPL used on University of Toronto internal projects utilized an SLR(1) parser, but those implementations have never been distributed).

Yacc

Yacc is a parser generator (loosely, compiler-compiler), not to be confused with lex, which is a lexical analyzer frequently used as a first stage by Yacc. Yacc was developed by Stephen C. Johnson at AT&T for the Unix operating system. The name is an acronym for "Yet Another Compiler Compiler." It generates an LALR(1) compiler based on a grammar written in a notation similar to Backus–Naur form.

Johnson worked on Yacc in the early 1970s at Bell Labs. He was familiar with TMG and its influence can be seen in Yacc and the design of the C programming language. Because Yacc was the default compiler generator on most Unix systems, it was widely distributed and used. Derivatives such as GNU Bison are still in use.

The compiler generated by Yacc requires a lexical analyzer. Lexical analyzer generators, such as lex or flex are widely available. The IEEE POSIX P1003.2 standard defines the functionality and requirements for both Lex and Yacc.

Coco/R

Coco/R is a parser generator that generates LL(1) parsers in Modula-2 (with plug-ins for other languages) from input grammars written in a variant of EBNF. It was developed by Hanspeter Mössenböck at the Swiss Federal Institute of Technology in Zurich (ETHZ) in 1985.

ANTLR

ANTLR is a parser generator that generates LL(*) parsers in Java from input grammars written in a variant of EBNF. It was developed by Terence Parr at the University of San Francisco in the early 1990s as a successor of an earlier generator called PCCTS.

Metacompilers

Main article: metacompiler

Metacompilers differ from parser generators, taking as input a program written in a metalanguage. Their input consists grammar analyzing formula combined with embedded transform operations that construct abstract syntax trees, or simply output reformatted text strings that may be stack machine code.

Many can be programmed in their own metalanguage enabling them to compile themselves, making them self-hosting extensible language compilers.

Many metacompilers build on the work of Dewey Val Schorre. His META II compiler, first released in 1964, was the first documented metacompiler. Able to define its own language and others, META II accepted syntax formula having imbedded output (code production). It also translated to one of the earliest instances of a virtual machine. Lexical analysis was performed by built token recognizing functions: .ID, .STRING, and .NUMBER. Quoted strings in syntax formula recognize lexemes that are not kept.

TREE-META, a second generation Schorre metacompiler, appeared around 1968. It extended the capabilities of META II, adding unparse rules separating code production from the grammar analysis. Tree transform operations in the syntax formula produce abstract syntax trees that the unparse rules operate on. The unparse tree pattern matching provided peephole optimization ability.

CWIC, described in a 1970 ACM publication is a third generation Schorre metacompiler that added lexing rules and backtracking operators to the grammar analysis. LISP 2 was married with the unparse rules of TREEMETA in the CWIC generator language. With LISP 2 processing, CWIC can generate fully optimized code. CWIC also provided binary code generation into named code sections. Single and multipass compiles could be implemented using CWIC.

CWIC compiled to 8-bit byte-addressable machine code instructions primarily designed to produce IBM System/360 code.

Later generations are not publicly documented. One important feature would be the abstraction of the target processor instruction set, generating to a pseudo machine instruction set, macros, that could be separately defined or mapped to a real machine's instructions. Optimizations applying to sequential instructions could then be applied to the pseudo instruction before their expansion to target machine code.

Cross compilation

A cross compiler runs in one environment but produces object code for another. Cross compilers are used for embedded development, where the target computer has limited capabilities.

An early example of cross compilation was AIMICO, where a FLOW-MATIC program on a UNIVAC II was used to generate assembly language for the IBM 705, which was then assembled on the IBM computer.

The ALGOL 68C compiler generated ZCODE output, that could then be either compiled into the local machine code by a ZCODE translator or run interpreted. ZCODE is a register-based intermediate language. This ability to interpret or compile ZCODE encouraged the porting of ALGOL 68C to numerous different computer platforms.

Optimizing compilers

Compiler optimization is the process of improving the quality of object code without changing the results it produces.

The developers of the first FORTRAN compiler aimed to generate code that was better than the average hand-coded assembler, so that customers would actually use their product. In one of the first real compilers, they often succeeded.

Later compilers, like IBM's Fortran IV compiler, placed more priority on good diagnostics and executing more quickly, at the expense of object code optimization. It wasn't until the IBM System/360 series that IBM provided two separate compilers—a fast-executing code checker, and a slower, optimizing one.

Frances E. Allen, working alone and jointly with John Cocke, introduced many of the concepts for optimization. Allen's 1966 paper, Program Optimization, introduced the use of graph data structures to encode program content for optimization. Her 1970 papers, Control Flow Analysis and A Basis for Program Optimization established intervals as the context for efficient and effective data flow analysis and optimization. Her 1971 paper with Cocke, A Catalogue of Optimizing Transformations, provided the first description and systematization of optimizing transformations. Her 1973 and 1974 papers on interprocedural data flow analysis extended the analysis to whole programs. Her 1976 paper with Cocke describes one of the two main analysis strategies used in optimizing compilers today.

Allen developed and implemented her methods as part of compilers for the IBM 7030 Stretch-Harvest and the experimental Advanced Computing System. This work established the feasibility and structure of modern machine- and language-independent optimizers. She went on to establish and lead the PTRAN project on the automatic parallel execution of FORTRAN programs. Her PTRAN team developed new parallelism detection schemes and created the concept of the program dependence graph, the primary structuring method used by most parallelizing compilers.

Programming Languages and their Compilers by John Cocke and Jacob T. Schwartz, published early in 1970, devoted more than 200 pages to optimization algorithms. It included many of the now familiar techniques such as redundant code elimination and strength reduction.

Peephole optimization

Peephole optimization is a simple but effective optimization technique. It was invented by William M. McKeeman and published in 1965 in CACM. It was used in the XPL compiler that McKeeman helped develop.

Capex COBOL optimizer

Capex Corporation developed the "COBOL Optimizer" in the mid-1970s for COBOL. This type of optimizer depended, in this case, upon knowledge of "weaknesses" in the standard IBM COBOL compiler, and actually replaced (or patched) sections of the object code with more efficient code. The replacement code might replace a linear table lookup with a binary search for example or sometimes simply replace a relatively "slow" instruction with a known faster one that was otherwise functionally equivalent within its context. This technique is now known as "Strength reduction". For example, on the IBM System/360 hardware the CLI instruction was, depending on the particular model, between twice and 5 times as fast as a CLC instruction for single byte comparisons.

Modern compilers typically provide optimization options to allow programmers to choose whether or not to execute an optimization pass.

Diagnostics

When a compiler is given a syntactically incorrect program, a good, clear error message is helpful. From the perspective of the compiler writer, it is often difficult to achieve.

The WATFIV Fortran compiler was developed at the University of Waterloo, Canada in the late 1960s. It was designed to give better error messages than IBM's Fortran compilers of the time. In addition, WATFIV was far more usable, because it combined compiling, linking and execution into one step, whereas IBM's compilers had three separate components to run.

PL/C

PL/C was a computer programming language developed at Cornell University in the early 1970s. While PL/C was a subset of IBM's PL/I language, it was designed with the specific goal of being used for teaching programming. The two researchers and academic teachers who designed PL/C were Richard W. Conway and Thomas R. Wilcox. They submitted the famous article "Design and implementation of a diagnostic compiler for PL/I" published in the Communications of ACM in March 1973.

PL/C eliminated some of the more complex features of PL/I, and added extensive debugging and error recovery facilities. The PL/C compiler had the unusual capability of never failing to compile any program, through the use of extensive automatic correction of many syntax errors and by converting any remaining syntax errors to output statements.

Just-in-time compilation

Main article: Just-in-time compilation

Just-in-time (JIT) compilation is the generation of executable code on-the-fly or as close as possible to its actual execution, to take advantage of runtime metrics or other performance-enhancing options.

Intermediate representation

Main article: Intermediate representation

Most modern compilers have a lexer and parser that produce an intermediate representation of the program. The intermediate representation is a simple sequence of operations which can be used by an optimizer and a code generator which produces instructions in the machine language of the target processor. Because the code generator uses an intermediate representation, the same code generator can be used for many different high-level languages.

There are many possibilities for the intermediate representation. Three-address code, also known as a quadruple or quad is a common form, where there is an operator, two operands, and a result. Two-address code or triples have a stack to which results are written, in contrast to the explicit variables of three-address code.

Static Single Assignment (SSA) was developed by Ron Cytron, Jeanne Ferrante, Barry K. Rosen, Mark N. Wegman, and F. Kenneth Zadeck, researchers at IBM in the 1980s. In SSA, a variable is given a value only once. A new variable is created rather than modifying an existing one. SSA simplifies optimization and code generation.

Code generation

Main article: Code generation (compiler)

A code generator generates machine language instructions for the target processor.

Register allocation

Sethi–Ullman algorithm or Sethi–Ullman numbering is a method to minimise the number of registers needed to hold variables.

Notable compilers

See also: ALGOL 60: ALGOL 60 implementations timeline and List of compilers
  • Amsterdam Compiler Kit by Andrew Tanenbaum and Ceriel Jacobs
  • Berkeley Pascal, written by Ken Thompson in 1975. Bill Joy and others at University of California, Berkeley added improvements
  • GNU Compiler Collection, formerly the GNU C Compiler. Originally authored by Richard Stallman in 1987, GCC is a major modern compiler which is used to compile many free software projects, notably Linux.
  • LLVM, formerly known as the Low Level Virtual Machine
  • Small-C by Ron Cain and James E Hendrix
  • Turbo Pascal, created by Anders Hejlsberg, first released in 1983.
  • WATFOR, created at the University of Waterloo. One of the first popular educational compilers, although now largely obsolete.
at April 28, 2023
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