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Universal Programmability - How AI Can Help

Universal Programmability - How AI Can Help
Tagung:

Technischer Artikel 

Jahr:

2013 

Autoren:

Walter F. Tichy
Mathias Landhäußer
Sven J. Körner

Links:PDFPDFLink zur Bibliothek

Summary

Everyone should be able to program. Programming in informal, but precise natural language would enable anyone to program and help eliminate the worldwide software backlog. Highly trained software engineers would still be needed for complex and demanding applications, but not for routine programming tasks. Programming in natural language is a monumental challenge and will require AI and software researchers to join forces. Early results, however, appear promising. Combining natural language understanding and ontological reasoning helps remove defects from requirements statements, transforms requirements into UML models, and might even enable scriptlike programming in specific, narrow domains. An important precondition for rapid progress in this area are benchmarks that help compare different approaches and stimulate competition among researchers.

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Bibtex

@techreport{,
author={Walter F. Tichy, Mathias Landh{\"a}u{\ss}er, Sven J. K{\"o}rner},
title={Universal Programmability - How AI Can Help},
year=2013,
month=May,
booktitle={2nd International NSF sponsored Workshop on Realizing Artificial Intelligence Synergies in Software Engineering},
editor={Karlsruhe Institute of Technology, Faculty of Informatics},
institution={Fakultät für Informatik (INFORMATIK), Institut für Programmstrukturen und Datenorganisation (IPD)},
series={Karlsruhe Reports in Informatics ; 2013,15},
url={https://ps.ipd.kit.edu/downloads/},
abstract={Everyone should be able to program. Programming in informal, but precise natural language would enable anyone to program and help eliminate the worldwide software backlog. Highly trained software engineers would still be needed for complex and demanding applications, but not for routine programming tasks. Programming in natural language is a monumental challenge and will require AI and software researchers to join forces. Early results, however, appear promising. Combining natural language understanding and ontological reasoning helps remove defects from requirements statements, transforms requirements into UML models, and might even enable scriptlike programming in specific, narrow domains. An important precondition for rapid progress in this area are benchmarks that help compare different approaches and stimulate competition among researchers.},
pptUrl={https://ps.ipd.kit.edu/downloads/},
note={
http://digbib.ubka.uni-karlsruhe.de/volltexte/1000037684
URN: urn:nbn:de:swb:90-376842

 

},
}