A hybrid heuristic approach to optimize rule-based software quality estimation models

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dc.contributor.author Azar, D.
dc.contributor.author Harmanani, H.
dc.contributor.author Korkmaz, R.
dc.date.accessioned 2016-03-24T10:49:58Z
dc.date.available 2016-03-24T10:49:58Z
dc.date.copyright 2009
dc.date.issued 2016-03-24
dc.identifier.issn 0950-5849 en_US
dc.identifier.uri http://hdl.handle.net/10725/3405
dc.description.abstract Software quality is defined as the degree to which a software component or system meets specified requirements and specifications. Assessing software quality in the early stages of design and development is crucial as it helps reduce effort, time and money. However, the task is difficult since most software quality characteristics (such as maintainability, reliability and reusability) cannot be directly and objectively measured before the software product is deployed and used for a certain period of time. Nonetheless, these software quality characteristics can be predicted from other measurable software quality attributes such as complexity and inheritance. Many metrics have been proposed for this purpose. In this context, we speak of estimating software quality characteristics from measurable attributes. For this purpose, software quality estimation models have been widely used. These take different forms: statistical models, rule-based models and decision trees. However, data used to build such models is scarce in the domain of software quality. As a result, the accuracy of the built estimation models deteriorates when they are used to predict the quality of new software components. In this paper, we propose a search-based software engineering approach to improve the prediction accuracy of software quality estimation models by adapting them to new unseen software products. The method has been implemented and favorable result comparisons are reported in this work. en_US
dc.language.iso en en_US
dc.title A hybrid heuristic approach to optimize rule-based software quality estimation models en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 198833240 en_US
dc.author.idnumber 199490170 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 Information and Software Technology en_US
dc.journal.volume 51 en_US
dc.journal.issue 9 en_US
dc.article.pages 1365-1376 en_US
dc.keywords Software quality en_US
dc.keywords Search-based software engineering en_US
dc.keywords Soft computing en_US
dc.identifier.doi http://dx.doi.org/10.1016/j.infsof.2009.05.003 en_US
dc.identifier.ctation Azar, D., Harmanani, H., & Korkmaz, R. (2009). A hybrid heuristic approach to optimize rule-based software quality estimation models. Information and Software Technology, 51(9), 1365-1376. en_US
dc.author.email danielle.azar@lau.edu.lb
dc.author.email haidar.harmanani@lau.edu.lb
dc.identifier.url http://www.sciencedirect.com/science/article/pii/S0950584909000809

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