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{{Short description|Style of computer programming}}
{{Use dmy dates|date=November 2020}}
{{Distinguish|Genetic programming|Pseudocode}}

'''Generic programming''' is a style of [[computer programming]] in which [[algorithm]]s are written in terms of [[data type]]s ''to-be-specified-later'' that are then ''instantiated'' when needed for specific types provided as [[Parameter (computer programming)|parameters]]. This approach, pioneered in the [[programming language]] [[ML (programming language)|ML]] in 1973,<ref name="Lee2008">
{{cite book
| last1=Lee
| first1=Kent D.
| date=15 December 2008
| title=Programming Languages: An Active Learning Approach
| url=https://books.google.com/books?id=OuW5dC2O99AC&pg=PA9
| publisher=Springer Science & Business Media
| isbn=978-0-387-79422-8
| pages=9–10}}</ref><ref>{{cite conference |last1=Milner |first1=R. |author1-link=Robin Milner |last2=Morris |first2=L. |last3=Newey |first3=M. |year=1975 |title=A Logic for Computable Functions with Reflexive and Polymorphic Types |book-title=Proceedings of the Conference on Proving and Improving Programs}}</ref> permits writing common [[Function (computer science)|functions]] or [[data type]]s that differ only in the [[Set (mathematics)|set]] of types on which they operate when used, thus reducing [[duplicate code]].

Generic programming was introduced to the mainstream with [[Ada (programming language)|Ada]] in 1977. With [[Template (C++)|templates]] in [[C++]], generic programming became part of the repertoire of professional [[Library (computing)|library]] design. The techniques were further improved and ''parameterized types'' were introduced in the influential 1994 book ''[[Design Patterns]]''.<ref name="GoF">
{{cite book |last1=Gamma
 |first1=Erich
 |last2=Helm
 |first2=Richard
 |last3=Johnson
 |first3=Ralph
 |last4=Vlissides
 |first4=John
 |date=1994
 |title=Design Patterns
 |publisher=Addison-Wesley
 |isbn=0-201-63361-2
 |url-access=registration
 |url=https://archive.org/details/designpatternsel00gamm
}}</ref>

New techniques were introduced by [[Andrei Alexandrescu]] in his 2001 book ''[[Modern C++ Design]]: Generic Programming and Design Patterns Applied''. Subsequently, [[D (programming language)|D]] implemented the same ideas.

Such software entities are known as ''generics'' in [[Ada (programming language)|Ada]], [[C Sharp (programming language)|C#]], [[Delphi (software)|Delphi]], [[Eiffel (programming language)|Eiffel]], [[F Sharp (programming language)|F#]], [[Java (programming language)|Java]], [[Nim (programming language)|Nim]], [[Python (programming language)|Python]], [[Go (programming language)|Go]], [[Rust (programming language)|Rust]], [[Swift (programming language)|Swift]], [[TypeScript]], and [[Visual Basic (.NET)]]. They are known as ''[[parametric polymorphism]]'' in [[ML (programming language)|ML]], [[Scala (programming language)|Scala]], [[Julia (programming language)|Julia]], and [[Haskell]]. (Haskell terminology also uses the term ''generic'' for a related but somewhat different concept.)

The term ''generic programming'' was originally coined by [[David Musser]] and [[Alexander Stepanov]]{{sfn|Musser|Stepanov|1989}} in a more specific sense than the above, to describe a programming paradigm in which fundamental requirements on data types are abstracted from across concrete examples of algorithms and [[data structure]]s and formalized as [[Concept (generic programming)|concepts]], with [[generic function]]s implemented in terms of these concepts, typically using language genericity mechanisms as described above.

== Stepanov–Musser and other generic programming paradigms ==
Generic programming is defined in {{harvtxt|Musser|Stepanov|1989}} as follows,
{{Blockquote
| text = Generic programming centers around the idea of abstracting from concrete, efficient algorithms to obtain generic algorithms that can be combined with different data representations to produce a wide variety of useful software.
| author = Musser, David R.; Stepanov, Alexander A.
| source = Generic Programming<ref>{{cite book |url=https://stepanovpapers.com/genprog.pdf |title=Generic Programming |author1=Musser, David R. |author2=Stepanov, Alexander A.}}</ref>}}

The "generic programming" paradigm is an approach to software decomposition whereby fundamental requirements on types are abstracted from across concrete examples of algorithms and data structures and formalized as [[Concept (generic programming)|concepts]], analogously to the abstraction of algebraic theories in [[abstract algebra]].<ref>{{cite book|author1 =Alexander Stepanov |author2 =Paul McJones|title=Elements of Programming|publisher=Addison-Wesley Professional |date=19 June 2009|isbn=978-0-321-63537-2}}</ref> Early examples of this programming approach were implemented in Scheme and Ada,<ref>{{cite book |doi=10.1145/317500.317529 |author1=Musser, David R. |author2=Stepanov, Alexander A. |title=Proceedings of the 1987 annual ACM SIGAda international conference on Ada - SIGAda '87 |chapter=A library of generic algorithms in Ada |pages=216–225| year=1987 |isbn=0897912438 |citeseerx=10.1.1.588.7431 |s2cid=795406}}</ref> although the best known example is the [[Standard Template Library]] (STL),<ref>Alexander Stepanov and Meng Lee: The Standard Template Library. HP Laboratories Technical Report 95-11(R.1), 14 November 1995</ref><ref>Matthew H. Austern: Generic programming and the STL: using and extending the C++ Standard Template Library. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA 1998</ref> which developed a theory of [[iterator]]s that is used to decouple sequence data structures and the algorithms operating on them.

For example, given ''N'' sequence data structures, e.g. singly linked list, vector etc., and ''M'' algorithms to operate on them, e.g. <code>find</code>, <code>sort</code> etc., a direct approach would implement each algorithm specifically for each data structure, giving {{nowrap|''N'' × ''M''}} combinations to implement. However, in the generic programming approach, each data structure returns a model of an iterator concept (a simple value type that can be dereferenced to retrieve the current value, or changed to point to another value in the sequence) and each algorithm is instead written generically with arguments of such iterators, e.g. a pair of iterators pointing to the beginning and end of the subsequence or ''range'' to process. Thus, only {{nowrap|''N'' + ''M''}} data structure-algorithm combinations need be implemented. Several iterator concepts are specified in the STL, each a refinement of more restrictive concepts e.g. forward iterators only provide movement to the next value in a sequence (e.g. suitable for a singly linked list or a stream of input data), whereas a random-access iterator also provides direct constant-time access to any element of the sequence (e.g. suitable for a vector). An important point is that a data structure will return a model of the most general concept that can be implemented efficiently—[[Analysis of algorithms|computational complexity]] requirements are explicitly part of the concept definition. This limits the data structures a given algorithm can be applied to and such complexity requirements are a major determinant of data structure choice. Generic programming similarly has been applied in other domains, e.g. graph algorithms.<ref>Jeremy G. Siek, Lie-Quan Lee, Andrew Lumsdaine: The Boost Graph Library: User Guide and Reference Manual. Addison-Wesley 2001</ref>

Although this approach often uses language features of [[compile-time]] genericity and templates, it is independent of particular language-technical details. Generic programming pioneer Alexander Stepanov wrote,
{{Blockquote
| text = Generic programming is about abstracting and classifying algorithms and data structures. It gets its inspiration from [[Donald Knuth|Knuth]] and not from type theory. Its goal is the incremental construction of systematic catalogs of useful, efficient and abstract algorithms and data structures. Such an undertaking is still a dream.
| author = Alexander Stepanov
| source = Short History of STL<ref>{{cite book |last=Stepanov |first=Alexander |url=https://stepanovpapers.com/history%20of%20STL.pdf |title=Short History of STL}}</ref><ref name="stroustrup2007">{{cite book |last=Stroustrup |first=Bjarne |url=https://www.stroustrup.com/hopl-almost-final.pdf |title=Evolving a language in and for the real world: C++ 1991-2006 |doi=10.1145/1238844.1238848 |s2cid=7518369}}</ref>}}

{{Blockquote
| text = I believe that iterator theories are as central to Computer Science as theories of [[Ring (mathematics)|rings]] or [[Banach space]]s are central to Mathematics.
| author = Alexander Stepanov
| source = An Interview with A. Stepanov<ref name=stepanov2011>{{cite web |url =https://www.stlport.org/resources/StepanovUSA.html |title=An Interview with A. Stepanov |last=Lo Russo |first=Graziano}}</ref>}}

[[Bjarne Stroustrup]] noted,
{{Blockquote
| text = Following Stepanov, we can define generic programming without mentioning language features: Lift algorithms and data structures from concrete examples to their most general and abstract form.
| author = Bjarne Stroustrup
| source = Evolving a language in and for the real world: C++ 1991-2006<ref name="stroustrup2007"/>}}

Other programming paradigms that have been described as generic programming include ''Datatype generic programming'' as described in  "Generic Programming – an Introduction".<ref>{{cite book |last1=Backhouse |first1=Roland |last2=Jansson |first2=Patrik |last3=Jeuring |first3=Johan |last4=Meertens |first4=Lambert |author4-link=Lambert Meertens |year=1999 |url=https://www.cse.chalmers.se/~patrikj/poly/afp98/genprogintro.pdf |title=Generic Programming – an Introduction}}</ref> The {{em | Scrap your [[Boilerplate code|boilerplate]]}} approach is a lightweight generic programming approach for Haskell.<ref>{{cite web |url=https://www.microsoft.com/en-us/research/wp-content/uploads/2003/01/hmap.pdf |title=Scrap Your Boilerplate: A Practical Design Pattern for Generic Programming |last1=Lämmel |first1=Ralf |last2=Peyton Jones |first2=Simon |author2-link=Simon Peyton Jones |date=January 2003 |publisher=Microsoft |access-date=16 October 2016}}</ref>

In this article we distinguish the high-level [[programming paradigm]]s of ''generic programming'', above, from the lower-level programming language ''genericity mechanisms'' used to implement them (see [[#Programming language support for genericity|Programming language support for genericity]]). For further discussion and comparison of generic programming paradigms, see.<ref>{{cite web |url=https://lcsd05.cs.tamu.edu/papers/dos_reis_et_al.pdf |title=What is Generic Programming? (preprint LCSD'05) |last1=Dos Reis |first1=Gabriel |last2=Ja ̈rvi |first2=Jaakko |year=2005 |url-status=dead |archive-url=https://web.archive.org/web/20051225114849/https://lcsd05.cs.tamu.edu/papers/dos_reis_et_al.pdf |archive-date=25 December 2005}}</ref>

==Programming language support for genericity==
Genericity facilities have existed in high-level languages since at least the 1970s in languages such as [[ML (programming language)|ML]], [[CLU (programming language)|CLU]] and [[Ada (programming language)|Ada]], and were subsequently adopted by many [[object-based]] and [[object-oriented]] languages, including [[BETA (programming language)|BETA]], [[C++]], [[D (programming language)|D]], [[Eiffel (programming language)|Eiffel]], [[Java (programming language)|Java]], and [[Digital Equipment Corporation|DEC]]'s now defunct [[Trellis-Owl]].

Genericity is implemented and supported differently in various programming languages; the term "generic" has also been used differently in various programming contexts. For example, in [[Forth (programming language)|Forth]] the [[compiler]] can execute code while compiling and one can create new ''compiler keywords'' and new implementations for those words on the fly. It has few ''words'' that expose the compiler behaviour and therefore naturally offers ''genericity'' capacities that, however, are not referred to as such in most Forth texts. Similarly, dynamically typed languages, especially interpreted ones, usually offer ''genericity'' by default as both passing values to functions and value assignment are type-indifferent and such behavior is often used for abstraction or code terseness, however this is not typically labeled ''genericity'' as it's a direct consequence of the dynamic typing system employed by the language.{{citation needed|date=August 2015}} The term has been used in [[functional programming]], specifically in [[Haskell]]-like languages, which use a [[structural type system]] where types are always parametric and the actual code on those types is generic. These uses still serve a similar purpose of code-saving and rendering an abstraction.

[[Array data type|Arrays]] and [[struct (C programming language)|structs]] can be viewed as predefined generic types. Every usage of an array or struct type instantiates a new concrete type, or reuses a previous instantiated type. Array element types and struct element types are parameterized types, which are used to instantiate the corresponding generic type. All this is usually built-in in the [[compiler]] and the syntax differs from other generic constructs. Some [[extensible programming|extensible programming languages]] try to unify built-in and user defined generic types.

A broad survey of genericity mechanisms in programming languages follows. For a specific survey comparing suitability of mechanisms for generic programming, see.<ref>{{Cite CiteSeerX |title=An extended comparative study of language support for generic programming (preprint) |author1=R. Garcia |author2=J. Ja ̈rvi |author3=A. Lumsdaine |author4=J. Siek |author5=J. Willcock |year=2005 |citeseerx=10.1.1.110.122}}</ref>

===In object-oriented languages===
When creating container classes in statically typed languages, it is inconvenient to write specific implementations for each datatype contained, especially if the code for each datatype is virtually identical. For example, in C++, this duplication of code can be circumvented by defining a class template:
<syntaxhighlight lang="Cpp">
template<typename T>
class List {
  // Class contents.
};

List<Animal> list_of_animals;
List<Car> list_of_cars;
</syntaxhighlight>
Above, <code>T</code> is a placeholder for whatever type is specified when the list is created. These "containers-of-type-T", commonly called [[template (programming)|templates]], allow a class to be reused with different datatypes as long as certain contracts such as [[Subtyping|subtype]]s and [[Type signature|signature]] are kept. This genericity mechanism should not be confused with ''[[polymorphism (computer science)|inclusion polymorphism]]'', which is the [[algorithm]]ic usage of exchangeable sub-classes: for instance, a list of objects of type <code>Moving_Object</code> containing objects of type <code>Animal</code> and <code>Car</code>. Templates can also be used for type-independent functions as in the <code>Swap</code> example below:

<syntaxhighlight lang="Cpp">
// "&" denotes a reference
template<typename T>
void Swap(T& a, T& b) { // A similar, but safer and potentially faster function 
                        // is defined in the standard library header <utility>
  T temp = b;
  b = a;
  a = temp;
}

std::string world = "World!";
std::string hello = "Hello, ";
Swap(world, hello);
std::cout << world << hello << ‘\n’;  // Output is "Hello, World!".
</syntaxhighlight>

The C++ <code>template</code> construct used above is widely cited{{Citation needed|date=May 2010}} as the genericity construct that popularized the notion among programmers and [[List of programming language researchers|language designers]] and supports many generic programming idioms. The D language also offers fully generic-capable templates based on the C++ precedent but with a simplified syntax. The Java language has provided genericity facilities syntactically based on C++'s since the introduction of [[Java Platform, Standard Edition]] (J2SE) 5.0.

[[C Sharp (programming language)|C#]] 2.0, [[Oxygene (programming language)|Oxygene]] 1.5 (formerly Chrome) and [[Visual Basic (.NET)]] 2005 have constructs that exploit the support for generics present in Microsoft [[.NET Framework]] since version 2.0.

====Generics in Ada====
{{unreferenced|section|date=January 2024}}
[[Ada (programming language)|Ada]] has had generics since it was first designed in 1977–1980. The [[standard library]] uses generics to provide many services. Ada 2005 adds a comprehensive generic container library to the standard library, which was inspired by C++'s [[Standard Template Library]].

A ''generic unit'' is a package or a subprogram that takes one or more ''generic formal parameters''.<ref>{{Cite web |title=Generic Units |url=https://www.adaic.org/resources/add_content/standards/05rm/html/RM-12.html |access-date=2024-04-25 |website=www.adaic.org}}</ref>

A ''generic formal parameter'' is a value, a variable, a constant, a type, a subprogram, or even an instance of another, designated, generic unit. For generic formal types, the syntax distinguishes between discrete, floating-point, fixed-point, access (pointer) types, etc. Some formal parameters can have default values.

To ''instantiate'' a generic unit, the programmer passes ''actual'' parameters for each formal. The generic instance then behaves just like any other unit. It is possible to instantiate generic units at [[Run time (program lifecycle phase)|run-time]], for example inside a loop.

=====Example=====
The specification of a generic package:

<syntaxhighlight lang="ada">
 generic
    Max_Size : Natural; -- a generic formal value
    type Element_Type is private; -- a generic formal type; accepts any nonlimited type
 package Stacks is
    type Size_Type is range 0 .. Max_Size;
    type Stack is limited private;
    procedure Create (S : out Stack;
                      Initial_Size : in Size_Type := Max_Size);
    procedure Push (Into : in out Stack; Element : in Element_Type);
    procedure Pop (From : in out Stack; Element : out Element_Type);
    Overflow : exception;
    Underflow : exception;
 private
    subtype Index_Type is Size_Type range 1 .. Max_Size;
    type Vector is array (Index_Type range <>) of Element_Type;
    type Stack (Allocated_Size : Size_Type := 0) is record
       Top : Index_Type;
       Storage : Vector (1 .. Allocated_Size);
    end record;
 end Stacks;
</syntaxhighlight>

Instantiating the generic package:

<syntaxhighlight lang="ADA">
 type Bookmark_Type is new Natural;
 -- records a location in the text document we are editing

 package Bookmark_Stacks is new Stacks (Max_Size => 20,
                                        Element_Type => Bookmark_Type);
 -- Allows the user to jump between recorded locations in a document
</syntaxhighlight>

Using an instance of a generic package:

<syntaxhighlight lang="ada">
 type Document_Type is record
    Contents : Ada.Strings.Unbounded.Unbounded_String;
    Bookmarks : Bookmark_Stacks.Stack;
 end record;

 procedure Edit (Document_Name : in String) is
   Document : Document_Type;
 begin
   -- Initialise the stack of bookmarks:
   Bookmark_Stacks.Create (S => Document.Bookmarks, Initial_Size => 10);
   -- Now, open the file Document_Name and read it in...
 end Edit;
</syntaxhighlight>

=====Advantages and limits=====
The language syntax allows precise specification of constraints on generic formal parameters. For example, it is possible to specify that a generic formal type will only accept a modular type as the actual. It is also possible to express constraints ''between'' generic formal parameters; for example:

<syntaxhighlight lang="ada">
 generic
    type Index_Type is (<>); -- must be a discrete type
    type Element_Type is private; -- can be any nonlimited type
    type Array_Type is array (Index_Type range <>) of Element_Type;
</syntaxhighlight>

In this example, Array_Type is constrained by both Index_Type and Element_Type. When instantiating the unit, the programmer must pass an actual array type that satisfies these constraints.

The disadvantage of this fine-grained control is a complicated syntax, but, because all generic formal parameters are completely defined in the specification, the [[compiler]] can instantiate generics without looking at the body of the generic.

Unlike C++, Ada does not allow specialised generic instances, and requires that all generics be instantiated explicitly. These rules have several consequences:
* the compiler can implement ''shared generics'': the object code for a generic unit can be shared between all instances (unless the programmer requests inlining of subprograms, of course). As further consequences:
** there is no possibility of code bloat (code bloat is common in C++ and requires special care, as explained below).
** it is possible to instantiate generics at run-time, and at compile time, since no new object code is required for a new instance.
** actual objects corresponding to a generic formal object are always considered to be non-static inside the generic; see [[wikibooks:Ada Programming/Generics#Generic formal objects|Generic formal objects]] in the Wikibook for details and consequences.
* all instances of a generic being exactly the same, it is easier to review and understand programs written by others; there are no "special cases" to take into account.
* all instantiations being explicit, there are no hidden instantiations that might make it difficult to understand the program.
* Ada does not permit arbitrary computation at compile time, because operations on generic arguments are performed at runtime.

====Templates in C++====
{{Main|Template (C++)}}

C++ uses templates to enable generic programming techniques. The C++ Standard Library includes the [[Standard Template Library]] or STL that provides a framework of templates for common data structures and algorithms. Templates in C++ may also be used for [[template metaprogramming]], which is a way of pre-evaluating some of the code at compile-time rather than [[Run time (program lifecycle phase)|run-time]]. Using template specialization, C++ Templates are [[Turing complete]].

=====Technical overview=====
There are many kinds of templates, the most common being function templates and class templates. A ''function template'' is a pattern for creating ordinary functions based upon the parameterizing types supplied when instantiated. For example, the C++ Standard Template Library contains the function template <code>max(x, y)</code> that creates functions that return either ''x'' or ''y,'' whichever is larger.  <code>max()</code> could be defined like this:

<syntaxhighlight lang="cpp">
template<typename T>
T max(T x, T y) {
  return x < y ? y : x;
}
</syntaxhighlight>

''Specializations'' of this function template, instantiations with specific types, can be called just like an ordinary function:

<syntaxhighlight lang="cpp">
std::cout << max(3, 7);  // Outputs 7.
</syntaxhighlight>

The compiler examines the arguments used to call <code>max</code> and determines that this is a call to <code>max(int, int)</code>. It then instantiates a version of the function where the parameterizing type <code>T</code> is <code>int</code>, making the equivalent of the following function:

<syntaxhighlight lang="cpp">
int max(int x, int y) {
  return x < y ? y : x;
}
</syntaxhighlight>

This works whether the arguments <code>x</code> and <code>y</code> are integers, strings, or any other type for which the expression <code>x &lt; y</code> is sensible, or more specifically, for any type for which <code>operator&lt;</code> is defined. Common inheritance is not needed for the set of types that can be used, and so it is very similar to [[Duck typing#Templates or generic types|duck typing]]. A program defining a custom data type can use [[operator overloading]] to define the meaning of <code>&lt;</code> for that type, thus allowing its use with the <code>max()</code> function template. While this may seem a minor benefit in this isolated example, in the context of a comprehensive library like the STL it allows the programmer to get extensive functionality for a new data type, just by defining a few operators for it. Merely defining <code>&lt;</code> allows a type to be used with the standard <code>sort()</code>, <code>stable_sort()</code>, and <code>binary_search()</code> algorithms or to be put inside data structures such as <code>set</code>s, [[heap (programming)|heap]]s, and [[associative array]]s.

C++ templates are completely [[type safe]] at compile time. As a demonstration, the standard type <code>complex</code> does not define the <code>&lt;</code> operator, because there is no strict order on [[complex number]]s. Therefore, <code>max(x, y)</code> will fail with a compile error, if ''x'' and ''y'' are <code>complex</code> values. Likewise, other templates that rely on <code>&lt;</code> cannot be applied to <code>complex</code> data unless a comparison (in the form of a functor or function) is provided. E.g.: A <code>complex</code> cannot be used as key for a <code>map</code> unless a comparison is provided. Unfortunately, compilers historically generate somewhat esoteric, long, and unhelpful error messages for this sort of error. Ensuring that a certain object adheres to a [[protocol (computer science)|method protocol]] can alleviate this issue. Languages which use <code>compare</code> instead of <code>&lt;</code> can also use <code>complex</code> values as keys.

Another kind of template, a ''class template,'' extends the same concept to classes. A class template specialization is a class. Class templates are often used to make generic containers. For example, the STL has a [[linked list]] container. To make a linked list of integers, one writes <code>list&lt;int&gt;</code>. A list of strings is denoted <code>list&lt;string&gt;</code>. A <code>list</code> has a set of standard functions associated with it, that work for any compatible parameterizing types.

=====Template specialization=====
A powerful feature of C++'s templates is ''template specialization''. This allows alternative implementations to be provided based on certain characteristics of the parameterized type that is being instantiated. Template specialization has two purposes: to allow certain forms of optimization, and to reduce code bloat.

For example, consider a <code>sort()</code> template function. One of the primary activities that such a function does is to swap or exchange the values in two of the container's positions. If the values are large (in terms of the number of bytes it takes to store each of them), then it is often quicker to first build a separate list of pointers to the objects, sort those pointers, and then build the final sorted sequence. If the values are quite small however it is usually fastest to just swap the values in-place as needed. Furthermore, if the parameterized type is already of some pointer-type, then there is no need to build a separate pointer array. Template specialization allows the template creator to write different implementations and to specify the characteristics that the parameterized type(s) must have for each implementation to be used.

Unlike function templates, class templates can be [[Partial template specialization|partially specialized]]. That means that an alternate version of the class template code can be provided when some of the template parameters are known, while leaving other template parameters generic. This can be used, for example, to create a default implementation (the ''primary specialization'') that assumes that copying a parameterizing type is expensive and then create partial specializations for types that are cheap to copy, thus increasing overall efficiency. Clients of such a class template just use specializations of it without needing to know whether the compiler used the primary specialization or some partial specialization in each case. Class templates can also be ''fully specialized,'' which means that an alternate implementation can be provided when all of the parameterizing types are known.

=====Advantages and disadvantages=====
Some uses of templates, such as the <code>max()</code> function, were formerly filled by function-like [[preprocessor]] [[Macro (computer science)|macros]] (a legacy of the [[C (programming language)|C]] language). For example, here is a possible implementation of such macro:

<syntaxhighlight lang="cpp">
#define max(a,b) ((a) < (b) ? (b) : (a))
</syntaxhighlight>

Macros are expanded (copy pasted) by the [[preprocessor]], before program compiling; templates are actual real functions. Macros are always expanded inline; templates can also be [[inline function]]s when the compiler deems it appropriate.

However, templates are generally considered an improvement over macros for these purposes. Templates are type-safe. Templates avoid some of the common errors found in code that makes heavy use of function-like macros, such as evaluating parameters with side effects twice. Perhaps most importantly, templates were designed to be applicable to much larger problems than macros.

There are four primary drawbacks to the use of templates: supported features, compiler support, poor error messages (usually with pre C++20 ''substitution failure is not an error'' ([[SFINAE]])), and [[code bloat]]:
# Templates in C++ lack many features, which makes implementing them and using them in a straightforward way often impossible. Instead programmers have to rely on complex tricks which leads to bloated, hard to understand and hard to maintain code. Current developments in the C++ standards exacerbate this problem by making heavy use of these tricks and building a lot of new features for templates on them or with them intended.
# Many compilers historically had poor support for templates, thus the use of templates could make code somewhat less portable. Support may also be poor when a C++ compiler is being used with a [[Linker (computing)|linker]] that is not C++-aware, or when attempting to use templates across [[Library (computer science)#Shared libraries|shared library]] boundaries.
# Compilers can produce confusing, long, and sometimes unhelpful error messages when errors are detected in code that uses SFINAE.<ref>[https://www.stroustrup.com/N1522-concept-criteria.pdf Stroustrup, Dos Reis (2003): Concepts - Design choices for template argument checking]</ref> This can make templates difficult to develop with.
# Finally, the use of templates requires the compiler to generate a separate ''instance'' of the templated class or function for every type parameters used with it. (This is necessary because types in C++ are not all the same size, and the sizes of data fields are important to how classes work.) So the indiscriminate use of templates can lead to [[code bloat]], resulting in excessively large executables. However, judicious use of template specialization and derivation can dramatically reduce such code bloat in some cases:{{Blockquote|So, can derivation be used to reduce the problem of code replicated because templates are used? This would involve deriving a template from an ordinary class. This technique proved successful in curbing code bloat in real use. People who do not use a technique like this have found that replicated code can cost megabytes of code space even in moderate size programs.|[[Bjarne Stroustrup]]|The Design and Evolution of C++, 1994<ref name="Stroustrup94Design">{{cite book |last1=Stroustrup |first1=Bjarne |author1-link=Bjarne Stroustrup |year=1994 |title=The Design and Evolution of C++ |publisher=Addison-Wesley |location=Reading, Massachusetts |isbn=978-81-317-1608-3 |pages=346–348 |chapter=15.5 Avoiding Code Replication |bibcode=1994dec..book.....S}}</ref>}}
# Templated classes or functions may require an ''explicit specialization'' of the template class which would require rewriting of an entire class for a specific template parameters used by it.
The extra instantiations generated by templates can also cause some debuggers to have difficulty working gracefully with templates. For example, setting a debug breakpoint within a template from a source file may either miss setting the breakpoint in the actual instantiation desired or may set a breakpoint in every place the template is instantiated.

Also, the implementation source code for the template must be completely available (e.g. included in a header) to the translation unit (source file) using it. Templates, including much of the Standard Library, if not included in header files, cannot be compiled. (This is in contrast to non-templated code, which may be compiled to binary, providing only a declarations header file for code using it.) This may be a disadvantage by exposing the implementing code, which removes some abstractions, and could restrict its use in closed-source projects.{{Citation needed|date=March 2009}}

====Templates in D====
The [[D (programming language)|D]] language supports templates based in design on C++. Most C++ template idioms work in D without alteration, but D adds some functionality:
* Template parameters in D are not restricted to just types and primitive values (as it was in C++ before C++20), but also allow arbitrary compile-time values (such as strings and struct literals), and aliases to arbitrary identifiers, including other templates or template instantiations.
* Template constraints and the <code>static if</code> statement provide an alternative to respectively C++'s [[C++ concepts]] and <code>if constexpr</code>.
* The <code>is(...)</code> expression allows speculative instantiation to verify an object's traits at compile time.
* The <code>auto</code> keyword and the <code>[[typeof]]</code> expression allow [[type inference]] for variable declarations and function return values, which in turn allows "Voldemort types" (types that do not have a global name).<ref>{{cite web |last=Bright |first=Walter |title=Voldemort Types in D |url =https://www.drdobbs.com/cpp/voldemort-types-in-d/232901591 |website=Dr. Dobbs |access-date=3 June 2015}}</ref>

Templates in D use a different syntax than in C++: whereas in C++ template parameters are wrapped in angular brackets (<code>Template<param1, param2></code>),
D uses an exclamation sign and parentheses: <code>Template!(param1, param2)</code>.
This avoids the [[Template (C++)#Advantages and disadvantages|C++ parsing difficulties]] due to ambiguity with comparison operators.
If there is only one parameter, the parentheses can be omitted.

Conventionally, D combines the above features to provide [[compile-time polymorphism]] using trait-based generic programming.
For example, an input [[Range (computer programming)#Range as an alternative to iterator|range]] is defined as any type that satisfies the checks performed by <code>isInputRange</code>, which is defined as follows:

<syntaxhighlight lang="d">
template isInputRange(R)
{
    enum bool isInputRange = is(typeof(
    (inout int = 0)
    {
        R r = R.init;     // can define a range object
        if (r.empty) {}   // can test for empty
        r.popFront();     // can invoke popFront()
        auto h = r.front; // can get the front of the range
    }));
}
</syntaxhighlight>

A function that accepts only input ranges can then use the above template in a template constraint:

<syntaxhighlight lang="d">
auto fun(Range)(Range range)
    if (isInputRange!Range)
{
    // ...
}
</syntaxhighlight>

=====Code generation=====
In addition to template metaprogramming, D also provides several features to enable compile-time code generation:
* The <code>import</code> expression allows reading a file from disk and using its contents as a string expression.
* Compile-time reflection allows enumerating and inspecting declarations and their members during compiling.
* User-defined [[Attribute (computing)|attributes]] allow users to attach arbitrary identifiers to declarations, which can then be enumerated using compile-time reflection.
* [[Compile-time function execution]] (CTFE) allows a subset of D (restricted to safe operations) to be interpreted during compiling.
* String mixins allow evaluating and compiling the contents of a string expression as D code that becomes part of the program.

Combining the above allows generating code based on existing declarations.
For example, D serialization frameworks can enumerate a type's members and generate specialized functions for each serialized type
to perform serialization and deserialization.
User-defined attributes could further indicate serialization rules.

The <code>import</code> expression and compile-time function execution also allow efficiently implementing [[domain-specific language]]s.
For example, given a function that takes a string containing an HTML template and returns equivalent D source code, it is possible to use it in the following way:

<syntaxhighlight lang="d">
// Import the contents of example.htt as a string manifest constant.
enum htmlTemplate = import("example.htt");

// Transpile the HTML template to D code.
enum htmlDCode = htmlTemplateToD(htmlTemplate);

// Paste the contents of htmlDCode as D code.
mixin(htmlDCode);
</syntaxhighlight>

====Genericity in Eiffel====
Generic classes have been a part of [[Eiffel (programming language)|Eiffel]] since the original method and language design. The foundation publications of Eiffel,<ref>''Object-Oriented Software Construction,'' Prentice Hall, 1988, and ''Object-Oriented Software Construction, second edition,'' Prentice Hall, 1997.</ref><ref>''Eiffel: The Language,'' Prentice Hall, 1991.</ref> use the term ''genericity'' to describe creating and using generic classes.

=====Basic, unconstrained genericity=====
Generic classes are declared with their class name and a list of one or more ''formal generic parameters''. In the following code, class <code lang=Eiffel>LIST</code> has one formal generic parameter <code lang=Eiffel>G</code>

<syntaxhighlight lang="eiffel">
class
    LIST [G]
            ...
feature   -- Access
    item: G
            -- The item currently pointed to by cursor
            ...
feature   -- Element change
    put (new_item: G)
            -- Add `new_item' at the end of the list
            ...
</syntaxhighlight>

The formal generic parameters are placeholders for arbitrary class names that will be supplied when a declaration of the generic class is made, as shown in the two ''generic derivations'' below, where <code lang=Eiffel>ACCOUNT</code> and <code lang=Eiffel>DEPOSIT</code> are other class names. <code lang=Eiffel>ACCOUNT</code> and <code lang=Eiffel>DEPOSIT</code> are considered ''actual generic parameters'' as they provide real class names to substitute for <code lang=Eiffel>G</code> in actual use.

<syntaxhighlight lang="eiffel">
    list_of_accounts: LIST [ACCOUNT]
            -- Account list

    list_of_deposits: LIST [DEPOSIT]
            -- Deposit list
</syntaxhighlight>

Within the Eiffel type system, although class <code lang=Eiffel>LIST [G]</code> is considered a class, it is not considered a type. However, a generic derivation of <code lang=Eiffel>LIST [G]</code> such as <code lang=Eiffel>LIST [ACCOUNT]</code> is considered a type.

=====Constrained genericity=====

For the list class shown above, an actual generic parameter substituting for <code lang=Eiffel>G</code> can be any other available class. To constrain the set of classes from which valid actual generic parameters can be chosen, a ''generic constraint'' can be specified. In the declaration of class <code lang=Eiffel>SORTED_LIST</code> below, the generic constraint dictates that any valid actual generic parameter will be a class that inherits from class <code lang=Eiffel>COMPARABLE</code>. The generic constraint ensures that elements of a <code lang=Eiffel>SORTED_LIST</code> can in fact be sorted.

<syntaxhighlight lang="eiffel">
class
    SORTED_LIST [G -> COMPARABLE]
</syntaxhighlight>

====Generics in Java====<!-- This section is linked from [[Comparison of Java and C++]] -->
{{Main|Generics in Java}}

Support for the ''generics'', or "containers-of-type-T" was added to the [[Java programming language]] in 2004 as part of J2SE 5.0. In Java, generics are only checked at compile time for type correctness. The generic type information is then removed via a process called [[type erasure]], to maintain compatibility with old [[JVM]] implementations, making it unavailable at runtime.{{sfn|Bloch|2018|loc=§Item 28: Prefer lists to arrays|p=126}} For example, a <code>List&lt;String&gt;</code> is converted to the raw type <code>List</code>. The compiler inserts [[Type conversion|type casts]] to convert the elements to the <code>String</code> type when they are retrieved from the list, reducing performance compared to other implementations such as C++ templates.

====Genericity in .NET [C#, VB.NET]====
Generics were added as part of [[.NET Framework#.NET Framework 2.0|.NET Framework 2.0]] in November 2005, based on a research prototype from Microsoft Research started in 1999.<ref>[https://docs.microsoft.com/en-us/archive/blogs/dsyme/netc-generics-history-some-photos-from-feb-1999 .NET/C# Generics History: Some Photos From Feb 1999]</ref> Although similar to generics in Java, .NET generics do not apply [[type erasure]],{{sfn|Albahari|2022}}{{rp|208–209}} but implement generics as a first class mechanism in the runtime using [[Reification (computer science)|reification]]. This design choice provides additional functionality, such as allowing [[Reflective programming|reflection]] with preservation of generic types, and alleviating some of the limits of erasure (such as being unable to create generic arrays).<ref>[https://www.ondotnet.com/pub/a/dotnet/2005/10/17/interview-with-anders-hejlsberg.html C#: Yesterday, Today, and Tomorrow: An Interview with Anders Hejlsberg]</ref><ref>[https://www.artima.com/intv/generics2.html Generics in C#, Java, and C++]</ref> This also means that there is no performance hit from runtime [[Type conversion|casts]] and normally expensive [[Boxing (computer science)|boxing conversions]]. When primitive and value types are used as generic arguments, they get specialized implementations, allowing for efficient generic [[Collection class|collections]] and methods. As in C++ and Java, nested generic types such as Dictionary<string, List<int>> are valid types, however are advised against for member signatures in code analysis design rules.<ref>[https://msdn.microsoft.com/en-us/library/ms182144.aspx Code Analysis CA1006: Do not nest generic types in member signatures]</ref>

.NET allows six varieties of generic type constraints using the <code>where</code> keyword including restricting generic types to be value types, to be classes, to have constructors, and to implement interfaces.<ref>[https://msdn2.microsoft.com/en-us/library/d5x73970.aspx Constraints on Type Parameters (C# Programming Guide)]</ref> Below is an example with an interface constraint:

<syntaxhighlight lang="csharp" line="1">
using System;

class Sample
{
    static void Main()
    {
        int[] array = { 0, 1, 2, 3 };
        MakeAtLeast<int>(array, 2); // Change array to { 2, 2, 2, 3 }
        foreach (int i in array)
            Console.WriteLine(i); // Print results.
        Console.ReadKey(true);
    }

    static void MakeAtLeast<T>(T[] list, T lowest) where T : IComparable<T>
    {
        for (int i = 0; i < list.Length; i++)
            if (list[i].CompareTo(lowest) < 0)
                list[i] = lowest;
    }
}
</syntaxhighlight>

The <code>MakeAtLeast()</code> method allows operation on arrays, with elements of generic type <code>T</code>. The method's type constraint indicates that the method is applicable to any type <code>T</code> that implements the generic <code>IComparable&lt;T></code> interface. This ensures a [[compile time]] error, if the method is called if the type does not support comparison. The interface provides the generic method <code>CompareTo(T)</code>.

The above method could also be written without generic types, simply using the non-generic <code>Array</code> type. However, since arrays are [[Covariance and contravariance (computer science)|contravariant]], the casting would not be [[type safe]], and the compiler would be unable to find certain possible errors that would otherwise be caught when using generic types. In addition, the method would need to access the array items as <code>object</code>s instead, and would require [[Type conversion|casting]] to compare two elements. (For value types like types such as <code>int</code> this requires a [[Boxing (computer science)|boxing]] conversion, although this can be worked around using the <code>Comparer&lt;T&gt;</code> class, as is done in the standard collection classes.)

A notable behavior of static members in a generic .NET class is static member instantiation per run-time type (see example below).

<syntaxhighlight lang="csharp">
    // A generic class
    public class GenTest<T>
    {
        // A static variable - will be created for each type on reflection
        static CountedInstances OnePerType = new CountedInstances();

        // a data member
        private T _t;

        // simple constructor
        public GenTest(T t)
        {
            _t = t;
        }
    }

    // a class
    public class CountedInstances
    {
        //Static variable - this will be incremented once per instance
        public static int Counter;

        //simple constructor
        public CountedInstances()
        {
            //increase counter by one during object instantiation
            CountedInstances.Counter++;
        }
    }

// main code entry point
// at the end of execution, CountedInstances.Counter = 2
GenTest<int> g1 = new GenTest<int>(1);
GenTest<int> g11 = new GenTest<int>(11);
GenTest<int> g111 = new GenTest<int>(111);
GenTest<double> g2 = new GenTest<double>(1.0);
</syntaxhighlight>

====Genericity in Pascal====
For [[Pascal (programming language)|Pascal]], generics were first implemented in 2006, in the implementation [[#In Free Pascal|Free Pascal]].

=====In Delphi=====
The [[Object Pascal]] dialect [[Delphi (software)|Delphi]] acquired generics in the 2007 Delphi 11 release by [[CodeGear]], initially only with the .NET compiler (since discontinued) before being added to the native code in the 2009 Delphi 12 release. The semantics and abilities of Delphi generics are largely modelled on those of generics in .NET 2.0, though the implementation is by necessity quite different. Here is a more or less direct translation of the first C# example shown above:

<syntaxhighlight lang="delphi">
program Sample;

{$APPTYPE CONSOLE}

uses
  Generics.Defaults; //for IComparer<>

type
  TUtils = class
    class procedure MakeAtLeast<T>(Arr: TArray<T>; const Lowest: T;
      Comparer: IComparer<T>); overload;
    class procedure MakeAtLeast<T>(Arr: TArray<T>; const Lowest: T); overload;
  end;

class procedure TUtils.MakeAtLeast<T>(Arr: TArray<T>; const Lowest: T;
  Comparer: IComparer<T>);
var
  I: Integer;
begin
  if Comparer = nil then Comparer := TComparer<T>.Default;
  for I := Low(Arr) to High(Arr) do
    if Comparer.Compare(Arr[I], Lowest) < 0 then
      Arr[I] := Lowest;
end;

class procedure TUtils.MakeAtLeast<T>(Arr: TArray<T>; const Lowest: T);
begin
  MakeAtLeast<T>(Arr, Lowest, nil);
end;

var
  Ints: TArray<Integer>;
  Value: Integer;
begin
  Ints := TArray<Integer>.Create(0, 1, 2, 3);
  TUtils.MakeAtLeast<Integer>(Ints, 2);
  for Value in Ints do
    WriteLn(Value);
  ReadLn;
end.
</syntaxhighlight>

As with C#, methods and whole types can have one or more type parameters. In the example, TArray is a generic type (defined by the language) and MakeAtLeast a generic method. The available constraints are very similar to the available constraints in C#: any value type, any class, a specific class or interface, and a class with a parameterless constructor. Multiple constraints act as an additive union.

=====In Free Pascal=====
[[Free Pascal]] implemented generics in 2006 in [[Free Pascal#Version 2.2.x|version 2.2.0]], before Delphi and with different syntax and semantics. However, since FPC version 2.6.0, the Delphi-style syntax is available when using the language mode <code>{$mode Delphi}</code>. Thus, Free Pascal code supports generics in either style.

Delphi and Free Pascal example:
<syntaxhighlight lang="delphi">
// Delphi style
unit A;

{$ifdef fpc}
  {$mode delphi}
{$endif}

interface

type
  TGenericClass<T> = class
    function Foo(const AValue: T): T;
  end;

implementation

function TGenericClass<T>.Foo(const AValue: T): T;
begin
  Result := AValue + AValue;
end;

end.

// Free Pascal's ObjFPC style
unit B;

{$ifdef fpc}
  {$mode objfpc}
{$endif}

interface

type
  generic TGenericClass<T> = class
    function Foo(const AValue: T): T;
  end;

implementation

function TGenericClass.Foo(const AValue: T): T;
begin
  Result := AValue + AValue;
end;

end.

// example usage, Delphi style
program TestGenDelphi;

{$ifdef fpc}
  {$mode delphi}
{$endif}

uses
  A,B;

var
  GC1: A.TGenericClass<Integer>;
  GC2: B.TGenericClass<String>;
begin
  GC1 := A.TGenericClass<Integer>.Create;
  GC2 := B.TGenericClass<String>.Create;
  WriteLn(GC1.Foo(100)); // 200
  WriteLn(GC2.Foo('hello')); // hellohello
  GC1.Free;
  GC2.Free;
end.

// example usage, ObjFPC style
program TestGenDelphi;

{$ifdef fpc}
  {$mode objfpc}
{$endif}

uses
  A,B;

// required in ObjFPC
type
  TAGenericClassInt = specialize A.TGenericClass<Integer>;
  TBGenericClassString = specialize B.TGenericClass<String>;
var
  GC1: TAGenericClassInt;
  GC2: TBGenericClassString;
begin
  GC1 := TAGenericClassInt.Create;
  GC2 := TBGenericClassString.Create;
  WriteLn(GC1.Foo(100)); // 200
  WriteLn(GC2.Foo('hello')); // hellohello
  GC1.Free;
  GC2.Free;
end.
</syntaxhighlight>

===Functional languages===
====Genericity in Haskell====
The [[type class]] mechanism of [[Haskell]] supports generic programming. Six of the predefined type classes in Haskell (including <code>Eq</code>, the types that can be compared for equality, and <code>Show</code>, the types whose values can be rendered as strings) have the special property of supporting ''derived instances.'' This means that a programmer defining a new type can state that this type is to be an instance of one of these special type classes, without providing implementations of the class methods as is usually necessary when declaring class instances. All the necessary methods will be "derived" – that is, constructed automatically – based on the structure of the type. For example, the following declaration of a type of [[binary tree]]s states that it is to be an instance of the classes <code>Eq</code> and <code>Show</code>:

<syntaxhighlight lang="haskell">
data BinTree a = Leaf a | Node (BinTree a) a (BinTree a)
      deriving (Eq, Show)
</syntaxhighlight>

This results in an equality function (<code>==</code>) and a string representation function (<code>show</code>) being automatically defined for any type of the form <code>BinTree T</code> provided that <code>T</code> itself supports those operations.

The support for derived instances of <code>Eq</code> and <code>Show</code> makes their methods <code>==</code> and <code>show</code> generic in a qualitatively different way from parametrically polymorphic functions: these "functions" (more accurately, type-indexed families of functions) can be applied to values of various types, and although they behave differently for every argument type, little work is needed to add support for a new type. Ralf Hinze (2004) has shown that a similar effect can be achieved for user-defined type classes by certain programming techniques. Other researchers have proposed approaches to this and other kinds of genericity in the context of Haskell and extensions to Haskell (discussed below).

===== PolyP =====
PolyP was the first generic programming language extension to [[Haskell]]. In PolyP, generic functions are called ''polytypic''. The language introduces a special construct in which such polytypic functions can be defined via structural induction over the structure of the pattern functor of a regular datatype. Regular datatypes in PolyP are a subset of Haskell datatypes. A regular datatype t must be of [[Kind (type theory)|kind]] ''* → *'', and if ''a'' is the formal type argument in the definition, then all recursive calls to ''t'' must have the form ''t a''. These restrictions rule out higher-kinded datatypes and nested datatypes, where the recursive calls are of a different form.
The flatten function in PolyP is here provided as an example:

<syntaxhighlight lang="haskell">
   flatten :: Regular d => d a -> [a]
   flatten = cata fl

   polytypic fl :: f a [a] -> [a]
     case f of
       g+h -> either fl fl
       g*h -> \(x,y) -> fl x ++ fl y
       () -> \x -> []
       Par -> \x -> [x]
       Rec -> \x -> x
       d@g -> concat . flatten . pmap fl
       Con t -> \x -> []

   cata :: Regular d => (FunctorOf d a b -> b) -> d a -> b
</syntaxhighlight>

=====Generic Haskell=====
Generic Haskell is another extension to [[Haskell]], developed at [[Utrecht University]] in the [[Netherlands]]. The extensions it provides are:
*''Type-indexed values'' are defined as a value indexed over the various Haskell type constructors (unit, primitive types, sums, products, and user-defined type constructors). In addition, we can also specify the behaviour of a type-indexed values for a specific constructor using ''constructor cases'', and reuse one generic definition in another using ''default cases''.
The resulting type-indexed value can be specialized to any type.
*''Kind-indexed types'' are types indexed over kinds, defined by giving a case for both ''*'' and ''k → k'''. Instances are obtained by applying the kind-indexed type to a kind.
*Generic definitions can be used by applying them to a type or kind. This is called ''generic application''. The result is a type or value, depending on which sort of generic definition is applied.
*''Generic abstraction'' enables generic definitions be defined by abstracting a type parameter (of a given kind).
*''Type-indexed types'' are types that are indexed over the type constructors. These can be used to give types to more involved generic values. The resulting type-indexed types can be specialized to any type.

As an example, the equality function in Generic Haskell:<ref>[https://www.cs.uu.nl/research/projects/generic-haskell/compiler/diamond/GHUsersGuide.pdf The Generic Haskell User's Guide]</ref>

<syntaxhighlight lang="haskell">
   type Eq {[ * ]} t1 t2 = t1 -> t2 -> Bool
   type Eq {[ k -> l ]} t1 t2 = forall u1 u2. Eq {[ k ]} u1 u2 -> Eq {[ l ]} (t1 u1) (t2 u2)

   eq {| t :: k |} :: Eq {[ k ]} t t
   eq {| Unit |} _ _ = True
   eq {| :+: |} eqA eqB (Inl a1) (Inl a2) = eqA a1 a2
   eq {| :+: |} eqA eqB (Inr b1) (Inr b2) = eqB b1 b2
   eq {| :+: |} eqA eqB _ _ = False
   eq {| :*: |} eqA eqB (a1 :*: b1) (a2 :*: b2) = eqA a1 a2 && eqB b1 b2
   eq {| Int |} = (==)
   eq {| Char |} = (==)
   eq {| Bool |} = (==)
</syntaxhighlight>

====Clean====
[[Clean (programming language)|Clean]] offers generic programming based [[#PolyP|PolyP]] and the [[#Generic Haskell|Generic Haskell]] as supported by the GHC ≥ 6.0. It parametrizes by kind as those but offers overloading.

===Other languages===
Languages in the [[ML (programming language)|ML]] family support generic programming through [[parametric polymorphism]] and generic [[Modular programming|modules]] called ''functors.'' Both [[Standard ML]] and [[OCaml]] provide functors, which are similar to class templates and to Ada's generic packages. [[Scheme (programming language)|Scheme]] syntactic abstractions also have a connection to genericity – these are in fact a superset of C++ templates.

A [[Verilog]] module may take one or more parameters, to which their actual values are assigned upon the instantiation of the module. One example is a generic [[Hardware register|register]] array where the array width is given via a parameter. Such an array, combined with a generic wire vector, can make a generic buffer or memory module with an arbitrary bit width out of a single module implementation.<ref>Verilog by Example, Section ''The Rest for Reference''. Blaine C. Readler, Full Arc Press, 2011. {{ISBN|978-0-9834973-0-1}}</ref>

[[VHDL]], being derived from Ada, also has generic abilities.<ref>https://www.ics.uci.edu/~jmoorkan/vhdlref/generics.html VHDL Reference</ref>

[[C (programming language)|C]] has a feature called "type-generic expressions" using the {{c-lang|_Generic}} keyword:<ref name="N1516">[https://www.open-std.org/jtc1/sc22/wg14/www/docs/n1516.pdf WG14 N1516 Committee Draft — October 4, 2010]</ref> This feature gives c [[function overloading]] capabilities, but is not related to generic programming. Generic programming can be achieve by using the proprocessor to define the generic code, with macro expansion taking the role of ''instantiation''. Sometimes the non-standard extention "statement expressions" is used to simulate function like behaviour for generic code:
<syntaxhighlight lang="c">
#define max(a,b) \
        ({ typeof (a) _a = (a); \
           typeof (b) _b = (b); \
           _a > _b ? _a : _b; })</syntaxhighlight>

==See also==
* [[Concept (generic programming)]]
* [[Partial evaluation]]
* [[Template metaprogramming]]
* [[Type polymorphism]]

== References ==
{{Reflist}}

== Sources ==
{{refbegin}}
* {{cite book |last=Albahari |first=Joseph |title= C# 10 in a Nutshell |publisher= O'Reilly |isbn= 978-1-098-12195-2|edition=First|year=2022}}
*{{cite book |title= "Effective Java: Programming Language Guide" |last=Bloch| first=Joshua| publisher=Addison-Wesley |edition=third |isbn=978-0134685991| year=2018}}
* {{Cite book |last1=Musser |first1=D. R. |author-link1=David Musser |last2=Stepanov |first2=A. A. |author-link2=Alexander Stepanov| chapter=Generic programming |doi=10.1007/3-540-51084-2_2 |title=Symbolic and Algebraic Computation: International symposium ISSAC 1988 |editor=P. Gianni |editor-link=Patrizia Gianni |series=Lecture Notes in Computer Science |volume=358 |pages=13–25 |year=1989 |isbn=978-3-540-51084-0}}
* {{cite conference  |url =https://www.research.att.com/~bs/hopl-almost-final.pdf |title=Evolving a language in and for the real world: C++ 1991-2006 |author-link=Bjarne Stroustrup |last=Stroustrup |first=Bjarne |conference=ACM HOPL 2007 |year=2007}}
* {{cite book |title=Design Patterns: Elements of Reusable Object-Oriented Software |first1=Erich |last1=Gamma |first2=Richard |last2=Helm |first3=Ralph |last3=Johnson |first4=John |last4=Vlissides |year=1994 |publisher=Addison-Wesley |isbn=0-201-63361-2 |bibcode=1995dper.book.....G |url-access=registration |url=https://archive.org/details/designpatternsel00gamm}}
{{refend}}

== Further reading ==
* Gabriel Dos Reis and Jaakko Järvi, ''[https://www.elegantcoding.com/2012/04/what-is-generic-programming.html What is Generic Programming?],'' [https://lcsd05.cs.tamu.edu LCSD 2005] {{Webarchive|url=https://web.archive.org/web/20190828045251/https://lcsd05.cs.tamu.edu/ |date=28 August 2019}}.
* {{cite conference |first=Jeremy |last=Gibbons |author-link=Jeremy Gibbons |citeseerx=10.1.1.159.1228 |title=Datatype-generic programming
  |editor1-last=Backhouse |editor1-first=R. |editor2-last=Gibbons |editor2-first=J. |editor3-last=Hinze |editor3-first=R.
  |editor4-last=Jeuring |editor4-first=J.
  |conference=Spring School on Datatype-Generic Programming 2006 |series=Lecture Notes in Computer Science |volume=4719 |pages=1–71
  |publisher=Springer |location=Heidelberg |year=2007}}
* {{cite book|doi=10.1145/28697.28738|chapter=Genericity versus inheritance|title=Conference proceedings on Object-oriented programming systems, languages and applications - OOPSLA '86|pages=391–405|year=1986|last1=Meyer|first1=Bertrand|isbn=0897912047|s2cid=285030|author-link1=Bertrand Meyer}}

==External links==
* [https://www.generic-programming.org generic-programming.org]
* Alexander A. Stepanov, [https://www.stepanovpapers.com/ Collected Papers of Alexander A. Stepanov] (creator of the [[Standard Template Library|STL]])

;C++, D
* Walter Bright, ''[https://www.digitalmars.com/d/templates-revisited.html Templates Revisited].''
* David Vandevoorde, Nicolai M Josuttis, ''C++ Templates: The Complete Guide'', 2003 Addison-Wesley. {{ISBN|0-201-73484-2}}

;C#, .NET
* Jason Clark, "[https://msdn.microsoft.com/msdnmag/issues/03/09/NET/ Introducing Generics in the Microsoft CLR]," September 2003, ''MSDN Magazine'', Microsoft.
* Jason Clark, "[https://msdn.microsoft.com/msdnmag/issues/03/10/NET/ More on Generics in the Microsoft CLR]," October 2003, ''MSDN Magazine'', Microsoft.
* M. Aamir Maniar, [https://codeplex.com/Wiki/View.aspx?ProjectName=genericsnet Generics.Net]. An open source generics library for C#.

;Delphi, Object Pascal
* Nick Hodges, "[https://edn.embarcadero.com/article/38757 Delphi 2009 Reviewers Guide]," October 2008, ''Embarcadero Developer Network'', Embarcadero.
* Craig Stuntz, "[https://web.archive.org/web/20090131211440/https://blogs.teamb.com/craigstuntz/2008/08/29/37832/ Delphi 2009 Generics and Type Constraints]," October 2008
* Dr. Bob, "[https://www.drbob42.com/examines/examinA4.htm Delphi 2009 Generics]"
* [[Free Pascal]]: [https://www.freepascal.org/docs-html/ref/refch8.html Free Pascal Reference guide Chapter 8: Generics], Michaël Van Canneyt, 2007
* Delphi for Win32: [https://sjrd.developpez.com/delphi/tutoriel/generics/ Generics with Delphi 2009 Win32], Sébastien DOERAENE, 2008
* Delphi for .NET: [https://www.felix-colibri.com/papers/oop_components/delphi_generics_tutorial/delphi_generics_tutorial.html Delphi Generics], Felix COLIBRI, 2008

;Eiffel
* [https://www.ecma-international.org/publications/standards/Ecma-367.htm Eiffel ISO/ECMA specification document]

;Haskell
* Johan Jeuring, Sean Leather, José Pedro Magalhães, and Alexey Rodriguez Yakushev. [https://www.cs.uu.nl/wiki/pub/GP/CourseLiterature/afp08.pdf ''Libraries for Generic Programming in Haskell'']. Utrecht University.
* Dæv Clarke, Johan Jeuring and Andres Löh, [https://www.cs.uu.nl/research/projects/generic-haskell/compiler/diamond/GHUsersGuide.pdf The Generic Haskell user's guide]
* Ralf Hinze, "[https://www.cs.ox.ac.uk/ralf.hinze/publications/Masses.pdf Generics for the Masses]," In ''Proceedings of the [[Association for Computing Machinery|ACM]] [[SIGPLAN]] [[International Conference on Functional Programming]] (ICFP),'' 2004.
* [[Simon Peyton Jones]], editor, ''[https://haskell.org/onlinereport/index.html The Haskell 98 Language Report],'' Revised 2002.
* [[Ralf Lämmel]] and [[Simon Peyton Jones]], "Scrap Your Boilerplate: A Practical Design Pattern for Generic Programming," In ''Proceedings of the [[Association for Computing Machinery|ACM]] [[SIGPLAN]] International Workshop on Types in Language Design and Implementation (TLDI'03),'' 2003. (Also see the website [https://web.archive.org/web/20041207211740/https://www.cs.vu.nl/boilerplate/ devoted to this research])
* Andres Löh, ''[https://web.archive.org/web/20050404015900/https://www.cs.uu.nl/~andres/ExploringGH.pdf Exploring Generic Haskell],'' PhD thesis, 2004 [[Utrecht University]]. {{ISBN|90-393-3765-9}}
* [https://www.generic-haskell.org/ Generic Haskell: a language for generic programming]

;Java
* Gilad Bracha, ''[https://www.oracle.com/technetwork/java/javase/generics-tutorial-159168.pdf Generics in the Java Programming Language],'' 2004.
* Maurice Naftalin and Philip Wadler, ''Java Generics and Collections,'' 2006, O'Reilly Media, Inc. {{ISBN|0-596-52775-6}}
* Peter Sestoft, ''Java Precisely, Second Edition,'' 2005 MIT Press. {{ISBN|0-262-69325-9}}
* {{Javadoc:SE-guide|language/generics.html|Generic Programming in Java}}, 2004 Sun Microsystems, Inc.
* Angelika Langer, [https://www.angelikalanger.com/GenericsFAQ/JavaGenericsFAQ.html Java Generics FAQs]

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