Master data

Title: Acquiring Empirical Knowledge to Support Intelligent Analysis of Quality-Related Issues in Software Development
Subtitle:
Abstract: The paper describes the current state of the initial part of the ongoing project aimed at the intelligent support for dealing with quality-related information in the software process. We describe the empirical qualitative studies aimed at acquiring the knowledge on stakeholder perception of quality and quality-related stakeholder interactions. This knowledge is supposed to be incorporated into a common ontology serving as a conceptual foundation for the prospective intelligent issue monitoring and analysis system based on the semantic repository. This system can be used to support prediction of the quality-related behavior of the stakeholders and facilitate reuse of the relevant knowledge.
Keywords:
Publication type: Article in compilation (Authorship)
Publication date: 09.2012 (Print)
Published by: 8th International Conference on the Quality of Information and Communications Technology - QUATIC 2012
8th International Conference on the Quality of Information and Communications Technology - QUATIC 2012
to publication
 ( IEEE Computer Society Press; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 153 - 156

Versionen

Keine Version vorhanden
Publication date:
ISBN (e-book): -
eISSN: -
DOI: http://dx.doi.org/10.1109/QUATIC.2012.19
Homepage: -
Open access
  • No open access
Publication date: 09.2012
ISBN: -
ISSN: -
Homepage: -

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Artificial Intelligence und Cybersecurity
Universitätsstr. 65-67
A-9020 Klagenfurt
Austria
  -993705
   aics-office@aau.at
https://www.aau.at/en/aics/
To organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

Categorisation

Subject areas
  • 1108 - Informatics
  • 1140 - Software engineering
Research Cluster
  • Human centered computing and design
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: II)
Classification raster of the assigned organisational units:
working groups No working group selected

Cooperations

No partner organisations selected

Articles of the publication

No related publications