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ASE 2002

Combining and Adapting Software Quality Predictive Models by Genetic Algorithms

Danielle Azar, Doina Precup, Salah Bouktif, Balázs Kégl, Houari A. Sahraoui

DOI 10.1109/ase.2002.1115031dblp

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.

BibTeX
@inproceedings{Azar-al:ASE02,
  author    = {Danielle Azar and
               Doina Precup and
               Salah Bouktif and
               Bal{\'{a}}zs K{\'{e}}gl and
               Houari A. Sahraoui},
  title     = {Combining and Adapting Software Quality Predictive Models by Genetic Algorithms},
  booktitle = {ASE},
  pages     = {285--288},
  publisher = {{IEEE} Computer Society},
  year      = {2002},
}

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