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Transferring research into the real world: How to improve RE with AI in the automotive industry

Körner, Sven J. 1; Landhäußer, Mathias 1; Tichy, Walter F. ORCID iD icon 1
1 Karlsruher Institut für Technologie (KIT)


For specifications, people use natural language. We show that processing natural language and combining this with intelligent deduction and reasoning with ontologies can possibly replace some manual processes associated with requirements engineering (RE). Our prior research shows that the software tools we developed can indeed solve problems in the RE process. This paper shows this does not only work in the software engineering domain, but also for embedded software in the automotive industry. We use artificial intelligence in the sense of combining semantic knowledge from ontologies and natural language processing. This enables computer systems to “understand” requirement texts and process these with “common sense”. Our specification improver RESI detects flaws in texts such as ambiguous words, incomplete process words, and erroneous quantifiers and determiners.

DOI: 10.1109/AIRE.2014.6894851
Zitationen: 7
Zitationen: 6
Zugehörige Institution(en) am KIT Institut für Programmstrukturen und Datenorganisation (IPD)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2014
Sprache Englisch
Identifikator ISBN: 978-1-4799-6356-0
KITopen-ID: 1000046117
Erschienen in IEEE 1st International Workshop on Artificial Intelligence for Requirements Engineering (AIRE'14), Karlskrona, Sweden, August 26, 2014
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 13-18
Nachgewiesen in Scopus
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