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{{Short description|Programming language using strict evaluation}}
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A '''strict programming language''' is a [[programming language]]
==
A strict programming language is a [[programming language]] which employs a strict [[programming paradigm]], allowing only [[strict function]]s (functions whose parameters must be evaluated completely before they may be called) to be defined by the user. A non-strict programming language allows the user to define non-strict functions, and hence may allow [[lazy evaluation]].{{Sfn|Scott|2006|p=541}}
Non-strictness has several disadvantages which have prevented widespread adoption:{{Citation needed|date=April 2024}}▼
Some strict programming languages include features that mimic laziness. [[Raku_(programming_language)|Raku]], formerly known as Perl 6, has lazy lists.<ref>{{Cite web|title=Raku Programming/Lazy Lists and Feeds - Wikibooks, open books for an open world|url=https://en.wikibooks.org/wiki/Raku_Programming/Lazy_Lists_and_Feeds|access-date=2021-02-09|website=en.wikibooks.org}}</ref> Python has generator functions.<ref>{{cite book |last1=Lott |first1=Steven |title=Functional Python Programming. |date=2015 |publisher=Packt Publishing |___location=Birmingham, UK |isbn=978-1-78439-699-2 |page=35 |quote=a generator function is non-strict. [...] we can leverage generator functions to create lazy evaluation.}}</ref> [[Julia (programming language)|Julia]] provides a [[Macro (computer science)#Hygienic macros|macro system]] to build non-strict functions,<ref>{{Citation|last=Innes|first=Mike J.|title=MikeInnes/Lazy.jl|date=2021-02-06|url=https://github.com/MikeInnes/Lazy.jl|access-date=2021-02-09}}</ref> as does [[Scheme (programming language)|Scheme]].▼
Examples for non-strict languages are [[Haskell (programming language)|Haskell]], [[R_(programming_language)|R]], [[Miranda (programming language)|Miranda]], and [[Clean (programming language)|Clean]].{{Sfn|Cluet & Hull|1998|pp=25–26}}▼
In most non-strict languages the non-strictness extends to [[algebraic data type|data constructor]]s. This allows conceptually infinite data structures (such as the list of all [[prime number]]s) to be manipulated in the same way as ordinary finite data structures. It also allows for the use of very large but finite data structures such as the complete [[game tree]] of [[chess]].▼
▲Non-strictness has several disadvantages which have prevented widespread adoption:
* Because of the uncertainty regarding if and when expressions will be evaluated, non-strict languages generally must be [[purely functional language|purely functional]] to be useful.
* All [[computer architecture|hardware architecture]]s in common use are optimized for strict languages, so the best compilers for non-strict languages produce slower code than the best compilers for strict languages.
* [[Space complexity]] of non-strict programs is difficult to understand and predict.
* In many strict languages, some advantages of non-strict functions can be obtained through the use of [[Macro (computer science)|macros]] or [[thunk]]s.▼
Strict programming languages are often associated with [[eager evaluation]], and non-strict languages with [[lazy evaluation]], but other [[evaluation strategy|evaluation strategies]] are possible in each case.{{Citation needed|date=April 2024}} The terms "eager programming language" and "lazy programming language" are often used as synonyms for "strict programming language" and "non-strict programming language" respectively.{{Citation needed|date=April 2024}}▼
==Examples==
▲Strict programming languages are often associated with [[eager evaluation]], and non-strict languages with [[lazy evaluation]], but other [[evaluation strategy|evaluation strategies]] are possible in each case. The terms "eager programming language" and "lazy programming language" are often used as synonyms for "strict programming language" and "non-strict programming language" respectively.
▲Nearly all [[programming language]]s in common use today are strict.{{Citation needed|date=April 2024}} Examples include [[C Sharp (programming language)|C#]], [[Java (programming language)|Java]], [[Perl]] (all versions, i.e. through version 5 and version 7), [[Python (programming language)|Python]],<ref>{{cite book |last1=Lott |first1=Steven |title=Functional Python Programming. |date=2015 |publisher=Packt Publishing |___location=Birmingham, UK |isbn=978-1-78439-699-2 |page=35 |quote=Python focuses on strict evaluation}}</ref> [[Ruby (programming language)|Ruby]], [[Common Lisp]], and [[ML (programming language)|ML]]. Some strict programming languages include features that mimic laziness.{{Clarify|date=April 2024|reason=Explain what it means to "mimic laziness"}} [[Raku_(programming_language)|Raku]]
▲Examples for non-strict languages are [[Haskell (programming language)|Haskell]], [[R_(programming_language)|R]], [[Miranda (programming language)|Miranda]], and [[Clean (programming language)|Clean]].{{Sfn|Cluet & Hull|1998|pp=25–26}}
==Extension==
▲In many strict languages, some advantages of non-strict functions can be obtained through the use of [[Macro (computer science)|macros]] or [[thunk]]s.
{{unreferenced section|date=April 2024}}
▲In most non-strict languages, the non-strictness extends to [[algebraic data type|data constructor]]s. This allows conceptually infinite data structures (such as the list of all [[prime number]]s) to be manipulated in the same way as ordinary finite data structures. It also allows for the use of very large but finite data structures such as the complete [[game tree]] of [[chess]].
==Citations==
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| others =Published by Denise Penrose
| date =2006
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| title =Programming Language Pragmatics
| edition ={{Ordinal|2|sup=yes}}
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| display-editors =2
| date =1998
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| title =Database Programming Languages
| series =Lecture Notes in Computer Science
| |||