Automatic programming: Difference between revisions

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{{short description|Type of computer programming}}

{{Programming paradigms}}

In [[Hazbincomputer Hotelscience]], the term '''automatic programming'''<ref>Ricardo Aler Mur, "[http://www.evannai.inf.uc3m.es/et/icml06/aiptutorial.htm Automatic Inductive Programming] {{Webarchive|url=https://web.archive.org/web/20160304073124/http://www.evannai.inf.uc3m.es/et/icml06/aiptutorial.htm |date=2016-03-04 }}", ''ICML 2006 Tutorial''. June 2006.</ref> identifiesis a type of [[computer programming]] in which some mechanism generates a [[computer program]], to allow human [[programmer]]s to write the code at a higher abstraction level.

There has been little agreement on the precise definition of automatic programming, mostly because its meaning has changed over time. [[David Parnas]], tracing the history of "automatic programming" in published research, noted that in the 1940s it described automation of the manual process of punching [[paper tape]]. Later it referred to translation of [[high-level programming language]]s like [[Fortran]] and [[ALGOL]]. In fact, one of the earliest programs identifiable as a [[compiler]] was called [[Autocode]]. [[David Parnas|Parnas]] concluded that "automatic programming has always been a [[euphemism]] for programming in a higher-level language than was then available to the programmer."<ref>D. L. Parnas. "[https://web.stanford.edu/class/cs99r/readings/parnas1.pdf Software Aspects of Strategic Defense Systems]." ''American Scientist''. November 1985.</ref>

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==Generative programming==

'''Generative programming''' and the related term [[Metaprogramming|meta-programming]]<ref>{{cite web

|quote=Generative programming, as a subdomain of meta-programming, describes the practice of writing programs that generate other programs as part of their execution.

|url=https://scala-lms.github.io/tutorials/01_overview.html

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|quote=Software that generates application programs from descriptions of the problem rather than by traditional programming. It is at a higher level and easier to use than a high-level programming language such as ...

|url=https://www.pcmag.com/encyclopedia/term/37909/application-generator

|title=Application generator |publisher=PCmag.com}}</ref> or an [[ontology (information science)|ontological]] model such as a template and is accomplished with a [[programming tool]] such as a [[template processor]] or an [[integrated development environment]] (IDE). These tools allow the generation of [[source code]] through any of various means.

Modern programming languages are well supported by tools like [https://www.json4swift.com/ Json4Swift] ([[Swift_Swift (programming_languageprogramming language)|Swift]]) and [https://www.json2kotlin.com/ Json2Kotlin] ([[Kotlin_Kotlin (programming_languageprogramming language)|Kotlin]]).

Programs that could generate [[COBOL]] code include:

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These application generators supported COBOL inserts and overrides.

A [[Macro (computer science)|macro]] processor, such as the [[C preprocessor]], which replaces patterns in source code according to relatively simple rules, is a simple form of source-code generator.{{citation needed|date=August 2017}} [[Source-to-source compiler|Source-to-source]] code generation tools also exist.<ref>Noaje, Gabriel, Christophe Jaillet, and Michaël Krajecki. "[https://www.researchgate.net/profile/Ponnuswamy_Sadayappan/publication/221302775_Automatic_C-to-CUDA_Code_Generation_for_Affine_Programs/links/09e4150e7f97085734000000/Automatic-C-to-CUDA-Code-Generation-for-Affine-Programs.pdf Source-to-source code translator: OpenMP C to CUDA]". High Performance Computing and Communications (HPCC), 2011 IEEE 13th International Conference on. IEEE, 2011.</ref><ref>Quinlan, Dan, and Chunhua Liao. "[https://www.researchgate.net/profile/Chunhua_Liao/publication/267861836_The_ROSE_Source-to-Source_Compiler_Infrastructure/links/5465a8120cf2f5eb17ff4238.pdf The ROSE source-to-source compiler infrastructure]". Cetus users and compiler infrastructure workshop, in conjunction with PACT. Vol. 2011. 2011.</ref>

[[Large language model]]s such as [[ChatGPT]] are capable of generating a program's source code from a description of the program given in a natural language.<ref name="ChatGPT can write code">{{Cite web |url=https://www.zdnet.com/article/chatgpt-can-write-code-now-researchers-say-its-good-at-fixing-bugs-too/ |title=ChatGPT can write code. Now researchers say it's good at fixing bugs, too |website=ZDNET |date=January 26, 2023 |first=Liam |last=Tung |access-date=June 22, 2023 |archive-date=February 3, 2023 |archive-url=https://web.archive.org/web/20230203051252/https://www.zdnet.com/article/chatgpt-can-write-code-now-researchers-say-its-good-at-fixing-bugs-too/ |url-status=live}}</ref>

Many [[Relational database system|relational database systems]] provide a function that will export the content of the database as [[SQL]] [[Data definition language|data definition]] queries, which may then be executed to re-import the tables and their data, or migrate them to another RDBMS.

==Low-code applications==

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* [[Comparison of code generation tools]]

* [[Feature-oriented programming]]

* [[GitHub Copilot]]

* [[AI-assisted software development]]

* [[Language-oriented programming]]

* [[Modeling language]]

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* [[Fourth-generation programming language]]

* [[Low-code development platform]]s

* [[Emergent Coding]]

==Notes==

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* [http://www.methodsandtools.com/archive/archive.php?id=86 Code Generation for Dummies]

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