DocumentCode
230802
Title
Transferring research into the real world: How to improve RE with AI in the automotive industry
Author
Korner, Sven J. ; Landhausser, Mathias ; Tichy, Walter F.
Author_Institution
Karlsruhe Inst. of Technol., Karlsruhe, Germany
fYear
2014
fDate
26-26 Aug. 2014
Firstpage
13
Lastpage
18
Abstract
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.
Keywords
artificial intelligence; automobile industry; natural language processing; ontologies (artificial intelligence); software engineering; traffic engineering computing; AI; RE process; artificial intelligence; automotive industry; computer systems; embedded software; intelligent deduction; intelligent reasoning; natural language processing; ontologies; requirement texts; requirements engineering; semantic knowledge; software engineering domain; software tools; Lighting; Natural languages; Ontologies; Semantics; Software; Software engineering; Unified modeling language;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence for Requirements Engineering (AIRE), 2014 IEEE 1st International Workshop on
Conference_Location
Karlskrona
Type
conf
DOI
10.1109/AIRE.2014.6894851
Filename
6894851
Link To Document