automatic programming

In computer science, automatic programmingRicardo 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. is a type of computer programming in which some mechanism generates a computer program, to allow human programmers 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 languages like Fortran and ALGOL. In fact, one of the earliest programs identifiable as a compiler was called Autocode. Parnas concluded that "automatic programming has always been a euphemism for programming in a higher-level language than was then available to the programmer."D. L. Parnas. "[https://web.stanford.edu/class/cs99r/readings/parnas1.pdf Software Aspects of Strategic Defense Systems]." American Scientist. November 1985.

Program synthesis is one type of automatic programming where a procedure is created from scratch, based on mathematical requirements.

Origin

Mildred Koss, an early UNIVAC programmer, explains: "Writing machine code involved several tedious steps—breaking down a process into discrete instructions, assigning specific memory locations to all the commands, and managing the I/O buffers. After following these steps to implement mathematical routines, a sub-routine library, and sorting programs, our task was to look at the larger programming process. We needed to understand how we might reuse tested code and have the machine help in programming. As we programmed, we examined the process and tried to think of ways to abstract these steps to incorporate them into higher-level language. This led to the development of interpreters, assemblers, compilers, and generators—programs designed to operate on or produce other programs, that is, automatic programming."Chun, Wendy. "On Software, or the Persistence of Visual Knowledge." Grey Room 18. Boston: 2004, pg. 30.

Generative programming

Generative programming and the related term meta-programming{{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

|title=About Generative Programming}} are concepts whereby programs can be written "to manufacture software components in an automated way"{{cite book

|quote=Generative Programming (GP) is an attempt to manufacture software components in an automated way by developing programs that synthesize other programs.

|author=P. Cointe |title=Unconventional Programming Paradigms

|volume=3566 |pages=315–325 |date=2005|doi=10.1007/11527800_24

|series=Lecture Notes in Computer Science |isbn=978-3-540-27884-9 |chapter=Towards Generative Programming }} just as automation has improved "production of traditional commodities such as garments, automobiles, chemicals, and electronics."{{cite web

|title=Generative Programming: Concepts and Experiences (GPCE)

|url=http://www.sigplan.org/Conferences/GPCE}}A conference of SIGPLAN on

this topic is planned for November 2018. Earlier/1970s attempts in this area included Yacc

and the related Lex programs.

The goal is to improve programmer productivity.James Wilcox, "[http://edgewatertech.wordpress.com/2011/03/11/paying-too-much-for-custom-application-implementation-code-generation/ Paying Too Much for Custom Application Development]", March 2011. It is often related to code-reuse topics such as component-based software engineering.

Source-code generation

Source-code generation is the process of generating source code based on a description of the problem{{cite web

|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}} or an 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) and [https://www.json2kotlin.com/ Json2Kotlin] (Kotlin).

Programs that could generate COBOL code include:

the DYL250/DYL260/DYL270/DYL280 series{{cite web

|url=http://www.sysed.com/DnLoads/RefCards/DYL280.pdf

|title=DYL-280 Command Syntax

|access-date=2018-09-03

|archive-url=https://web.archive.org/web/20180730111004/http://www.sysed.com/DnLoads/RefCards/DYL280.pdf

|archive-date=2018-07-30

|url-status=dead

}}

Business Controls Corporation's SB-5
Peat Marwick Mitchell's PMM2170 application-program-generator package

These application generators supported COBOL inserts and overrides.

A 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. Source-to-source code generation tools also exist.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.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.

Large language models such as ChatGPT are capable of generating a program's source code from a description of the program given in a natural language.{{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}}

Many relational database systems provide a function that will export the content of the database as SQL 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

A low-code development platform (LCDP) is software that provides an environment programmers use to create application software through graphical user interfaces and configuration instead of traditional computer programming.

Notes

References

Generative Programming: Methods, Tools, and Applications by Krzysztof Czarnecki and Ulrich W. Eisenecker, Addison Wesley, 2000.

External links

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

Category:Programming paradigms

Category:Source code generation