D (programming language)

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D programming language
D Programming Language logo.svg
Paradigm Multi-paradigm: functional, imperative, object-oriented
Designed by Walter Bright, Andrei Alexandrescu (since 2007)
Developer D Language Foundation
First appeared8 December 2001;22 years ago (2001-12-08) [1]
Stable release
2.108.0 [2]   OOjs UI icon edit-ltr-progressive.svg / 1 April 2024;20 days ago (1 April 2024)
Typing discipline Inferred, static, strong
OS FreeBSD, Linux, macOS, Windows
License Boost [3] [4] [5]
Filename extensions .d [6] [7]
Website dlang.org
Major implementations
DMD (reference implementation), GCC,

GDC,

LDC, SDC
Influenced by
BASIC, [8] C, C++, C#, Eiffel, [9] Java, Python
Influenced
Genie, MiniD, Qore, Swift, [10] Vala, C++11, C++14, C++17, C++20, Go, C#, and others.

D, also known as dlang, is a multi-paradigm system programming language created by Walter Bright at Digital Mars and released in 2001. Andrei Alexandrescu joined the design and development effort in 2007. Though it originated as a re-engineering of C++, D is now a very different language drawing inspiration from other high-level programming languages, notably Java, Python, Ruby, C#, and Eiffel.

Contents

The D language reference describes it as follows:

D is a general-purpose systems programming language with a C-like syntax that compiles to native code. It is statically typed and supports both automatic (garbage collected) and manual memory management. D programs are structured as modules that can be compiled separately and linked with external libraries to create native libraries or executables. [11]

Features

D is not source compatible with C and C++ source code in general. However, any code that is legal in both C and D should behave in the same way.

Like C++, D has closures, anonymous functions, compile-time function execution, ranges, built-in container iteration concepts, and type inference. Unlike C++, D also implements design by contract, modules, garbage collection, first class arrays, array slicing, nested functions and lazy evaluation. D uses Java-style single inheritance with interfaces and mixins rather than C++-style multiple inheritance. On the other hand, D's declaration, statement and expression syntax closely matches that of C++.

D is a systems programming language. Like C++, D supports low-level programming including inline assembler, which typifies the differences between D and application languages like Java and C#. Inline assembler lets programmers enter machine-specific assembly code within standard D code, a method used by system programmers to access the low-level features of the processor needed to run programs that interface directly with the underlying hardware, such as operating systems and device drivers, as well as writing high-performance code (i.e. using vector extensions, SIMD) that is hard to generate by the compiler automatically.

D supports function overloading and operator overloading. Symbols (functions, variables, classes) can be declared in any order - forward declarations are not required.

In D, text character strings are arrays of characters, and arrays in D are bounds-checked. [12] D has first class types for complex and imaginary numbers. [13]

Programming paradigms

D supports five main programming paradigms:

Imperative

Imperative programming in D is almost identical to that in C. Functions, data, statements, declarations and expressions work just as they do in C, and the C runtime library may be accessed directly. On the other hand, some notable differences between D and C in the area of imperative programming include D's foreach loop construct, which allows looping over a collection, and nested functions, which are functions that are declared inside another and may access the enclosing function's local variables.

importstd.stdio;voidmain(){intmultiplier=10;intscaled(intx){returnx*multiplier;}foreach(i;0..10){writefln("Hello, world %d! scaled = %d",i,scaled(i));}}

Object-oriented

Object-oriented programming in D is based on a single inheritance hierarchy, with all classes derived from class Object. D does not support multiple inheritance; instead, it uses Java-style interfaces, which are comparable to C++'s pure abstract classes, and mixins, which separates common functionality from the inheritance hierarchy. D also allows the defining of static and final (non-virtual) methods in interfaces.

Interfaces and inheritance in D support covariant types for return types of overridden methods.

D supports type forwarding, as well as optional custom dynamic dispatch.

Classes (and interfaces) in D can contain invariants which are automatically checked before and after entry to public methods, in accordance with the design by contract methodology.

Many aspects of classes (and structs) can be introspected automatically at compile time (a form of reflection using type traits) and at run time (RTTI / TypeInfo), to facilitate generic code or automatic code generation (usually using compile-time techniques).

Functional

D supports functional programming features such as function literals, closures, recursively-immutable objects and the use of higher-order functions. There are two syntaxes for anonymous functions, including a multiple-statement form and a "shorthand" single-expression notation: [14]

intfunction(int)g;g=(x){returnx*x;};// longhandg=(x)=>x*x;// shorthand

There are two built-in types for function literals, function, which is simply a pointer to a stack-allocated function, and delegate, which also includes a pointer to the relevant stack frame, the surrounding ‘environment’, which contains the current local variables. Type inference may be used with an anonymous function, in which case the compiler creates a delegate unless it can prove that an environment pointer is not necessary. Likewise, to implement a closure, the compiler places enclosed local variables on the heap only if necessary (for example, if a closure is returned by another function, and exits that function's scope). When using type inference, the compiler will also add attributes such as pure and nothrow to a function's type, if it can prove that they apply.

Other functional features such as currying and common higher-order functions such as map, filter, and reduce are available through the standard library modules std.functional and std.algorithm.

importstd.stdio,std.algorithm,std.range;voidmain(){int[]a1=[0,1,2,3,4,5,6,7,8,9];int[]a2=[6,7,8,9];// must be immutable to allow access from inside a pure functionimmutablepivot=5;intmySum(inta,intb)purenothrow// pure function{if(b<=pivot)// ref to enclosing-scopereturna+b;elsereturna;}// passing a delegate (closure)autoresult=reduce!mySum(chain(a1,a2));writeln("Result: ",result);// Result: 15// passing a delegate literalresult=reduce!((a,b)=>(b<=pivot)?a+b:a)(chain(a1,a2));writeln("Result: ",result);// Result: 15}

Alternatively, the above function compositions can be expressed using Uniform function call syntax (UFCS) for more natural left-to-right reading:

autoresult=a1.chain(a2).reduce!mySum();writeln("Result: ",result);result=a1.chain(a2).reduce!((a,b)=>(b<=pivot)?a+b:a)();writeln("Result: ",result);

Parallelism

Parallel programming concepts are implemented in the library, and do not require extra support from the compiler. However the D type system and compiler ensure that data sharing can be detected and managed transparently.

importstd.stdio:writeln;importstd.range:iota;importstd.parallelism:parallel;voidmain(){foreach(i;iota(11).parallel){// The body of the foreach loop is executed in parallel for each iwriteln("processing ",i);}}

iota(11).parallel is equivalent to std.parallelism.parallel(iota(11)) by using UFCS.

The same module also supports taskPool which can be used for dynamic creation of parallel tasks, as well as map-filter-reduce and fold style operations on ranges (and arrays), which is useful when combined with functional operations. std.algorithm.map returns a lazily evaluated range rather than an array. This way, the elements are computed by each worker task in parallel automatically.

importstd.stdio:writeln;importstd.algorithm:map;importstd.range:iota;importstd.parallelism:taskPool;/* On Intel i7-3930X and gdc 9.3.0: * 5140ms using std.algorithm.reduce * 888ms using std.parallelism.taskPool.reduce * * On AMD Threadripper 2950X, and gdc 9.3.0: * 2864ms using std.algorithm.reduce * 95ms using std.parallelism.taskPool.reduce */voidmain(){autonums=iota(1.0,1_000_000_000.0);autox=taskPool.reduce!"a + b"(0.0,map!"1.0 / (a * a)"(nums));writeln("Sum: ",x);}

Concurrency

Concurrency is fully implemented in the library, and it does not require support from the compiler. Alternative implementations and methodologies of writing concurrent code are possible. The use of D typing system does help ensure memory safety.

importstd.stdio,std.concurrency,std.variant;voidfoo(){boolcont=true;while(cont){receive(// Delegates are used to match the message type.(intmsg)=>writeln("int received: ",msg),(Tidsender){cont=false;sender.send(-1);},(Variantv)=>writeln("huh?")// Variant matches any type);}}voidmain(){autotid=spawn(&foo);// spawn a new thread running foo()foreach(i;0..10)tid.send(i);// send some integerstid.send(1.0f);// send a floattid.send("hello");// send a stringtid.send(thisTid);// send a struct (Tid)receive((intx)=>writeln("Main thread received message: ",x));}

Metaprogramming

Metaprogramming is supported through templates, compile-time function execution, tuples, and string mixins. The following examples demonstrate some of D's compile-time features.

Templates in D can be written in a more imperative style compared to the C++ functional style for templates. This is a regular function that calculates the factorial of a number:

ulongfactorial(ulongn){if(n<2)return1;elsereturnn*factorial(n-1);}

Here, the use of static if, D's compile-time conditional construct, is demonstrated to construct a template that performs the same calculation using code that is similar to that of the function above:

templateFactorial(ulongn){staticif(n<2)enumFactorial=1;elseenumFactorial=n*Factorial!(n-1);}

In the following two examples, the template and function defined above are used to compute factorials. The types of constants need not be specified explicitly as the compiler infers their types from the right-hand sides of assignments:

enumfact_7=Factorial!(7);

This is an example of compile-time function execution (CTFE). Ordinary functions may be used in constant, compile-time expressions provided they meet certain criteria:

enumfact_9=factorial(9);

The std.string.format function performs printf-like data formatting (also at compile-time, through CTFE), and the "msg" pragma displays the result at compile time:

importstd.string:format;pragma(msg,format("7! = %s",fact_7));pragma(msg,format("9! = %s",fact_9));

String mixins, combined with compile-time function execution, allow for the generation of D code using string operations at compile time. This can be used to parse domain-specific languages, which will be compiled as part of the program:

importFooToD;// hypothetical module which contains a function that parses Foo source code// and returns equivalent D codevoidmain(){mixin(fooToD(import("example.foo")));}

Memory management

Memory is usually managed with garbage collection, but specific objects may be finalized immediately when they go out of scope. This is what the majority of programs and libraries written in D use.

In case more control over memory layout and better performance is needed, explicit memory management is possible using the overloaded operator new, by calling C's malloc and free directly, or implementing custom allocator schemes (i.e. on stack with fallback, RAII style allocation, reference counting, shared reference counting). Garbage collection can be controlled: programmers may add and exclude memory ranges from being observed by the collector, can disable and enable the collector and force either a generational or full collection cycle. [15] The manual gives many examples of how to implement different highly optimized memory management schemes for when garbage collection is inadequate in a program. [16]

In functions, struct instances are by default allocated on the stack, while class instances by default allocated on the heap (with only reference to the class instance being on the stack). However this can be changed for classes, for example using standard library template std.typecons.scoped, or by using new for structs and assigning to a pointer instead of a value-based variable. [17]

In functions, static arrays (of known size) are allocated on the stack. For dynamic arrays, one can use the core.stdc.stdlib.alloca function (similar to alloca in C), to allocate memory on the stack. The returned pointer can be used (recast) into a (typed) dynamic array, by means of a slice (however resizing array, including appending must be avoided; and for obvious reasons they must not be returned from the function). [17]

A scope keyword can be used both to annotate parts of code, but also variables and classes/structs, to indicate they should be destroyed (destructor called) immediately on scope exit. Whatever the memory is deallocated also depends on implementation and class-vs-struct differences. [18]

std.experimental.allocator contains a modular and composable allocator templates, to create custom high performance allocators for special use cases. [19]

SafeD

SafeD [20] is the name given to the subset of D that can be guaranteed to be memory safe (no writes to memory that has not been allocated or that has been recycled). Functions marked @safe are checked at compile time to ensure that they do not use any features that could result in corruption of memory, such as pointer arithmetic and unchecked casts, and any other functions called must also be marked as @safe or @trusted. Functions can be marked @trusted for the cases where the compiler cannot distinguish between safe use of a feature that is disabled in SafeD and a potential case of memory corruption. [21]

Scope lifetime safety

Initially under the banners of DIP1000 [22] and DIP25 [23] (now part of the language specification [24] ), D provides protections against certain ill-formed constructions involving the lifetimes of data.

The current mechanisms in place primarily deal with function parameters and stack memory however it is a stated ambition of the leadership of the programming language to provide a more thorough treatment of lifetimes within the D programming language [25] (influenced by ideas from Rust programming language).

Lifetime safety of assignments

Within @safe code, the lifetime of an assignment involving a reference type is checked to ensure that the lifetime of the assignee is longer than that of the assigned.

For example:

@safevoidtest(){inttmp=0;// #1int*rad;// #2rad=&tmp;// If the order of the declarations of #1 and #2 is reversed, this fails.{intbad=45;// The lifetime of "bad" only extends to the scope in which it is defined.*rad=bad;// This is valid.rad=&bad;// The lifetime of rad is longer than bad, hence this is not valid.}}

Function parameter lifetime annotations within @safe code

When applied to function parameter which are either of pointer type or references, the keywords return and scope constrain the lifetime and use of that parameter.

The language standard dictates the following behaviour: [26]

Storage ClassBehaviour (and constraints to) of a parameter with the storage class
scopeReferences in the parameter cannot be escaped. Ignored for parameters with no references
returnParameter may be returned or copied to the first parameter, but otherwise does not escape from the function. Such copies are required not to outlive the argument(s) they were derived from. Ignored for parameters with no references

An annotated example is given below.

@safe:int*gp;voidthorin(scopeint*);voidgloin(int*);int*balin(returnscopeint*p,scopeint*q,int*r){gp=p;// Error, p escapes to global variable gp.gp=q;// Error, q escapes to global variable gp.gp=r;// OK.thorin(p);// OK, p does not escape thorin().thorin(q);// OK.thorin(r);// OK.gloin(p);// Error, p escapes gloin().gloin(q);// Error, q escapes gloin().gloin(r);// OK that r escapes gloin().returnp;// OK.returnq;// Error, cannot return 'scope' q.returnr;// OK.}

Interaction with other systems

C's application binary interface (ABI) is supported, as well as all of C's fundamental and derived types, enabling direct access to existing C code and libraries. D bindings are available for many popular C libraries. Additionally, C's standard library is part of standard D.

On Microsoft Windows, D can access Component Object Model (COM) code.

As long as memory management is properly taken care of, many other languages can be mixed with D in a single binary. For example, the GDC compiler allows to link and intermix C, C++, and other supported language codes such as Objective-C. D code (functions) can also be marked as using C, C++, Pascal ABIs, and thus be passed to the libraries written in these languages as callbacks. Similarly data can be interchanged between the codes written in these languages in both ways. This usually restricts use to primitive types, pointers, some forms of arrays, unions, structs, and only some types of function pointers.

Because many other programming languages often provide the C API for writing extensions or running the interpreter of the languages, D can interface directly with these languages as well, using standard C bindings (with a thin D interface file). For example, there are bi-directional bindings for languages like Python, [27] Lua [28] [29] and other languages, often using compile-time code generation and compile-time type reflection methods.

Interaction with C++ code

For D code marked as extern(C++), the following features are specified:

  • The name mangling conventions shall match those of C++ on the target.
  • For function calls, the ABI shall be equivalent.
  • The vtable shall be matched up to single inheritance (the only level supported by the D language specification).

C++ namespaces are used via the syntax extern(C++, namespace) where namespace is the name of the C++ namespace.

An example of C++ interoperation

The C++ side

#include<iostream>usingnamespacestd;classBase{public:virtualvoidprint3i(inta,intb,intc)=0;};classDerived:publicBase{public:intfield;Derived(intfield):field(field){}voidprint3i(inta,intb,intc){cout<<"a = "<<a<<endl;cout<<"b = "<<b<<endl;cout<<"c = "<<c<<endl;}intmul(intfactor);};intDerived::mul(intfactor){returnfield*factor;}Derived*createInstance(inti){returnnewDerived(i);}voiddeleteInstance(Derived*&d){deleted;d=0;}

The D side

extern(C++){abstractclassBase{voidprint3i(inta,intb,intc);}classDerived:Base{intfield;@disablethis();overridevoidprint3i(inta,intb,intc);finalintmul(intfactor);}DerivedcreateInstance(inti);voiddeleteInstance(refDerivedd);}voidmain(){importstd.stdio;autod1=createInstance(5);writeln(d1.field);writeln(d1.mul(4));Baseb1=d1;b1.print3i(1,2,3);deleteInstance(d1);assert(d1isnull);autod2=createInstance(42);writeln(d2.field);deleteInstance(d2);assert(d2isnull);}

Better C

The D programming language has an official subset known as "Better C". [30] This subset forbids access to D features requiring use of runtime libraries other than that of C.

Enabled via the compiler flags "-betterC" on DMD and LDC, and "-fno-druntime" on GDC, Better C may only call into D code compiled under the same flag (and linked code other than D) but code compiled without the Better C option may call into code compiled with it: this will, however, lead to slightly different behaviours due to differences in how C and D handle asserts.

Features included in Better C

  • Unrestricted use of compile-time features (for example, D's dynamic allocation features can be used at compile time to pre-allocate D data)
  • Full metaprogramming facilities
  • Nested functions, nested structs, delegates and lambdas
  • Member functions, constructors, destructors, operating overloading, etc.
  • The full module system
  • Array slicing, and array bounds checking
  • RAII
  • scope(exit)
  • Memory safety protections
  • Interfacing with C++
  • COM classes and C++ classes
  • assert failures are directed to the C runtime library
  • switch with strings
  • final switch
  • unittest blocks
  • printf format validation

Features excluded from Better C

  • Garbage collection
  • TypeInfo and ModuleInfo
  • Built-in threading (e.g. core.thread)
  • Dynamic arrays (though slices of static arrays work) and associative arrays
  • Exceptions
  • synchronized and core.sync
  • Static module constructors or destructors

History

Walter Bright started working on a new language in 1999. D was first released in December 2001 [1] and reached version 1.0 in January 2007. [31] The first version of the language (D1) concentrated on the imperative, object oriented and metaprogramming paradigms, [32] similar to C++.

Some members of the D community dissatisfied with Phobos, D's official runtime and standard library, created an alternative runtime and standard library named Tango. The first public Tango announcement came within days of D 1.0's release. [33] Tango adopted a different programming style, embracing OOP and high modularity. Being a community-led project, Tango was more open to contributions, which allowed it to progress faster than the official standard library. At that time, Tango and Phobos were incompatible due to different runtime support APIs (the garbage collector, threading support, etc.). This made it impossible to use both libraries in the same project. The existence of two libraries, both widely in use, has led to significant dispute due to some packages using Phobos and others using Tango. [34]

In June 2007, the first version of D2 was released. [35] The beginning of D2's development signaled D1's stabilization. The first version of the language has been placed in maintenance, only receiving corrections and implementation bugfixes. D2 introduced breaking changes to the language, beginning with its first experimental const system. D2 later added numerous other language features, such as closures, purity, and support for the functional and concurrent programming paradigms. D2 also solved standard library problems by separating the runtime from the standard library. The completion of a D2 Tango port was announced in February 2012. [36]

The release of Andrei Alexandrescu's book The D Programming Language on 12 June 2010, marked the stabilization of D2, which today is commonly referred to as just "D".

In January 2011, D development moved from a bugtracker / patch-submission basis to GitHub. This has led to a significant increase in contributions to the compiler, runtime and standard library. [37]

In December 2011, Andrei Alexandrescu announced that D1, the first version of the language, would be discontinued on 31 December 2012. [38] The final D1 release, D v1.076, was on 31 December 2012. [39]

Code for the official D compiler, the Digital Mars D compiler by Walter Bright, was originally released under a custom license, qualifying as source available but not conforming to the Open Source Definition. [40] In 2014, the compiler front-end was re-licensed as open source under the Boost Software License. [3] This re-licensed code excluded the back-end, which had been partially developed at Symantec. On 7 April 2017, the whole compiler was made available under the Boost license after Symantec gave permission to re-license the back-end, too. [4] [41] [42] [43] On 21 June 2017, the D Language was accepted for inclusion in GCC. [44]

Implementations

Most current D implementations compile directly into machine code.

Production ready compilers:

Toy and proof-of-concept compilers:

Using above compilers and toolchains, it is possible to compile D programs to target many different architectures, including IA-32, amd64, AArch64, PowerPC, MIPS64, DEC Alpha, Motorola m68k, SPARC, s390, WebAssembly. The primary supported operating systems are Windows and Linux, but various compilers also support Mac OS X, FreeBSD, NetBSD, AIX, Solaris/OpenSolaris and Android, either as a host or target, or both. WebAssembly target (supported via LDC and LLVM) can operate in any WebAssembly environment, like modern web browser (Google Chrome, Mozilla Firefox, Microsoft Edge, Apple Safari), or dedicated Wasm virtual machines.

Development tools

Editors and integrated development environments (IDEs) supporting syntax highlighting and partial code completion for the language include SlickEdit, Emacs, vim, SciTE, Smultron, Zeus, [56] and Geany among others. [57]

Open source D IDEs for Windows exist, some written in D, such as Poseidon, [69] D-IDE, [70] and Entice Designer. [71]

D applications can be debugged using any C/C++ debugger, like GDB or WinDbg, although support for various D-specific language features is extremely limited. On Windows, D programs can be debugged using Ddbg, or Microsoft debugging tools (WinDBG and Visual Studio), after having converted the debug information using cv2pdb. The ZeroBUGS Archived 23 December 2017 at the Wayback Machine debugger for Linux has experimental support for the D language. Ddbg can be used with various IDEs or from the command line; ZeroBUGS has its own graphical user interface (GUI).

DustMite is a tool for minimizing D source code, useful when finding compiler or tests issues. [72]

dub is a popular package and build manager for D applications and libraries, and is often integrated into IDE support. [73]

Examples

Example 1

This example program prints its command line arguments. The main function is the entry point of a D program, and args is an array of strings representing the command line arguments. A string in D is an array of characters, represented by immutable(char)[].

importstd.stdio:writefln;voidmain(string[]args){foreach(i,arg;args)writefln("args[%d] = '%s'",i,arg);}

The foreach statement can iterate over any collection. In this case, it is producing a sequence of indexes (i) and values (arg) from the array args. The index i and the value arg have their types inferred from the type of the array args.

Example 2

The following shows several D capabilities and D design trade-offs in a short program. It iterates over the lines of a text file named words.txt, which contains a different word on each line, and prints all the words that are anagrams of other words.

importstd.stdio,std.algorithm,std.range,std.string;voidmain(){dstring[][dstring]signature2words;foreach(dchar[]w;lines(File("words.txt"))){w=w.chomp().toLower();immutablesignature=w.dup.sort().release().idup;signature2words[signature]~=w.idup;}foreach(words;signature2words){if(words.length>1){writeln(words.join(" "));}}}
  1. signature2words is a built-in associative array that maps dstring (32-bit / char) keys to arrays of dstrings. It is similar to defaultdict(list) in Python.
  2. lines(File()) yields lines lazily, with the newline. It has to then be copied with idup to obtain a string to be used for the associative array values (the idup property of arrays returns an immutable duplicate of the array, which is required since the dstring type is actually immutable(dchar)[]). Built-in associative arrays require immutable keys.
  3. The ~= operator appends a new dstring to the values of the associate dynamic array.
  4. toLower, join and chomp are string functions that D allows the use of with a method syntax. The name of such functions are often similar to Python string methods. The toLower converts a string to lower case, join(" ") joins an array of strings into a single string using a single space as separator, and chomp removes a newline from the end of the string if one is present. The w.dup.sort().release().idup is more readable, but equivalent to release(sort(w.dup)).idup for example. This feature is called UFCS (Uniform Function Call Syntax), and allows extending any built-in or third party package types with method-like functionality. The style of writing code like this is often referenced as pipeline (especially when the objects used are lazily computed, for example iterators / ranges) or Fluent interface.
  5. The sort is an std.algorithm function that sorts the array in place, creating a unique signature for words that are anagrams of each other. The release() method on the return value of sort() is handy to keep the code as a single expression.
  6. The second foreach iterates on the values of the associative array, it is able to infer the type of words.
  7. signature is assigned to an immutable variable, its type is inferred.
  8. UTF-32 dchar[] is used instead of normal UTF-8 char[] otherwise sort() refuses to sort it. There are more efficient ways to write this program using just UTF-8.

Uses

Notable organisations that use the D programming language for projects include Facebook, [74] eBay, [75] and Netflix. [76]

D has been successfully used for AAA games, [77] language interpreters, virtual machines, [78] [79] an operating system kernel, [80] GPU programming, [81] web development, [82] [83] numerical analysis, [84] GUI applications, [85] [86] a passenger information system, [87] machine learning, [88] text processing, web and application servers and research.

The notorious North Korean hacking group known as Lazarus exploited CVE-2021-44228, aka "Log4Shell," to deploy three malware families written in DLang. [89]

See also

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The C and C++ programming languages are closely related but have many significant differences. C++ began as a fork of an early, pre-standardized C, and was designed to be mostly source-and-link compatible with C compilers of the time. Due to this, development tools for the two languages are often integrated into a single product, with the programmer able to specify C or C++ as their source language.

C++11 is a version of the ISO/IEC 14882 standard for the C++ programming language. C++11 replaced the prior version of the C++ standard, called C++03, and was later replaced by C++14. The name follows the tradition of naming language versions by the publication year of the specification, though it was formerly named C++0x because it was expected to be published before 2010.

In computer programming, a pure function is a function that has the following properties:

  1. the function return values are identical for identical arguments, and
  2. the function has no side effects.

In computer programming, an anonymous function is a function definition that is not bound to an identifier. Anonymous functions are often arguments being passed to higher-order functions or used for constructing the result of a higher-order function that needs to return a function. If the function is only used once, or a limited number of times, an anonymous function may be syntactically lighter than using a named function. Anonymous functions are ubiquitous in functional programming languages and other languages with first-class functions, where they fulfil the same role for the function type as literals do for other data types.

In computing, compile-time function execution is the ability of a compiler, that would normally compile a function to machine code and execute it at run time, to execute the function at compile time. This is possible if the arguments to the function are known at compile time, and the function does not make any reference to or attempt to modify any global state.

<span class="mw-page-title-main">Vala (programming language)</span> Programming language

Vala is an object-oriented programming language with a self-hosting compiler that generates C code and uses the GObject system.

Blocks are a non-standard extension added by Apple Inc. to Clang's implementations of the C, C++, and Objective-C programming languages that uses a lambda expression-like syntax to create closures within these languages. Blocks are supported for programs developed for Mac OS X 10.6+ and iOS 4.0+, although third-party runtimes allow use on Mac OS X 10.5 and iOS 2.2+ and non-Apple systems.

Objective-C is a high-level general-purpose, object-oriented programming language that adds Smalltalk-style messaging to the C programming language. Originally developed by Brad Cox and Tom Love in the early 1980s, it was selected by NeXT for its NeXTSTEP operating system. Due to Apple macOS’s direct lineage from NeXTSTEP, Objective-C was the standard programming language used, supported, and promoted by Apple for developing macOS and iOS applications until the introduction of the Swift programming language in 2014.

In computer programming, the async/await pattern is a syntactic feature of many programming languages that allows an asynchronous, non-blocking function to be structured in a way similar to an ordinary synchronous function. It is semantically related to the concept of a coroutine and is often implemented using similar techniques, and is primarily intended to provide opportunities for the program to execute other code while waiting for a long-running, asynchronous task to complete, usually represented by promises or similar data structures. The feature is found in C#, C++, Python, F#, Hack, Julia, Dart, Kotlin, Rust, Nim, JavaScript, Swift and Zig.

<span class="mw-page-title-main">Nim (programming language)</span> Programming language

Nim is a general-purpose, multi-paradigm, statically typed, compiled high-level systems programming language, designed and developed by a team around Andreas Rumpf. Nim is designed to be "efficient, expressive, and elegant", supporting metaprogramming, functional, message passing, procedural, and object-oriented programming styles by providing several features such as compile time code generation, algebraic data types, a foreign function interface (FFI) with C, C++, Objective-C, and JavaScript, and supporting compiling to those same languages as intermediate representations.

<span class="mw-page-title-main">Zig (programming language)</span> A general-purpose programming language, toolchain to build Zig/C/C++ code

Zig is an imperative, general-purpose, statically typed, compiled system programming language designed by Andrew Kelley. It is intended to be a successor to the C programming language, with the intention of being even smaller and simpler to program in while also offering more functionality.

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Further reading