A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models

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dc.contributor.author Azar, Danielle
dc.date.accessioned 2016-03-24T11:46:30Z
dc.date.available 2016-03-24T11:46:30Z
dc.date.copyright 2010
dc.date.issued 2016-03-24
dc.identifier.issn 1469-0268 en_US
dc.identifier.uri http://hdl.handle.net/10725/3406
dc.description.abstract In this work, we present a genetic algorithm to optimize predictive models used to estimate software quality characteristics. Software quality assessment is crucial in the software development field since it helps reduce cost, time and effort. However, software quality characteristics cannot be directly measured but they can be estimated based on other measurable software attributes (such as coupling, size and complexity). Software quality estimation models establish a relationship between the unmeasurable characteristics and the measurable attributes. However, these models are hard to generalize and reuse on new, unseen software as their accuracy deteriorates significantly. In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess. en_US
dc.language.iso en en_US
dc.title A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models en_US
dc.type Article en_US
dc.description.version Published en_US
dc.title.subtitle A Search-Based Software Engineering Approach en_US
dc.author.school SAS en_US
dc.author.idnumber 198833240 en_US
dc.author.woa N/A en_US
dc.author.department Computer Science and Mathematics en_US
dc.description.embargo N/A en_US
dc.relation.journal International Journal of Computational Intelligence and Applications en_US
dc.journal.volume 9 en_US
dc.journal.issue 2 en_US
dc.article.pages 125-136
dc.keywords Classification models en_US
dc.keywords Genetic algorithms en_US
dc.keywords Search-based software engineering en_US
dc.keywords Software quality en_US
dc.identifier.doi http://dx.doi.org/10.1142/S1469026810002811 en_US
dc.identifier.ctation Azar, D. (2010). A genetic algorithm for improving accuracy of software quality predictive models: a search-based software engineering approach. International Journal of Computational Intelligence and Applications, 9(02), 125-136. en_US
dc.author.email danielle.azar@lau.edu.lb
dc.identifier.url http://www.worldscientific.com/doi/abs/10.1142/S1469026810002811?journalCode=ijcia

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