Transferring Research Into the Real World - How to Improve RE with AI in the Automotive Industry

  • Tagung:

    Konferenzartikel 

  • Autoren:

    Sven J . Körner
    Mathias Landhäußer
    Walter F. Tichy

  • Summary

    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.
  • Jahr:

    2014 

  • Links:
Beteiligte Mitarbeiter (zufällige Reihenfolge)
Titel Vorname Nachname
Dr. Mathias Landhäußer
Dr. Sven J. Körner
Prof. em. Dr. Walter F. Tichy

Bibtex

@inproceedings{,
author={Sven J . K{\"o}rner, Mathias Landh{\"a}u{\ss}er and Walter F. Tichy},
title={Transferring Research Into the Real World - How to Improve RE with AI in the Automotive Industry},
year=2014,
month=Aug,
booktitle={First International Workshop on Artificial Intelligence for Requirements Engineering},
url={https://ps.ipd.kit.edu/downloads/},
doi={10.1109/AIRE.2014.6894851},
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.},
}