Combining and adapting software quality predictive models by genetic algorithms

D. Azar, D. Precup, S. Bouktif, B. Kégl, H. Sahraoui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

The goal of quality models is to predict a quality factor starting from a set of direct measures. Selecting an appropriate quality model for a particular software is a difficult, non-trivial decision. In this paper, we propose an approach to combine and/or adapt existing models (experts) in such way that the combined/adapted model works well on the particular system. Test results indicate that the models perform significantly better than individual experts in the pool.

Original languageEnglish
Title of host publicationProceedings - ASE 2002: 17th IEEE International Conference on Automated Software Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages285-288
Number of pages4
ISBN (Electronic)0769517366, 9780769517360
DOIs
Publication statusPublished - 2002
Externally publishedYes
Event17th IEEE International Conference on Automated Software Engineering, ASE 2002 - Edinburgh, United Kingdom
Duration: Sep 23 2002Sep 27 2002

Other

Other17th IEEE International Conference on Automated Software Engineering, ASE 2002
Country/TerritoryUnited Kingdom
CityEdinburgh
Period9/23/029/27/02

ASJC Scopus subject areas

  • Software

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