A novel kernel to predict software defectiveness

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dc.authorid0000-0001-6664-515X
dc.authorid0000-0001-5838-4615
dc.contributor.authorOkutan, Ahmeten_US
dc.contributor.authorYıldız, Olcay Taneren_US
dc.date.accessioned2016-10-24T16:50:54Z
dc.date.available2016-10-24T16:50:54Z
dc.date.issued2016-09
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Computer Engineeringen_US
dc.description.abstractAlthough the software defect prediction problem has been researched for a long time, the results achieved are not so bright. In this paper, we propose to use novel kernels for defect prediction that are based on the plagiarized source code, software clones and textual similarity. We generate precomputed kernel matrices and compare their performance on different data sets to model the relationship between source code similarity and defectiveness. Each value in a kernel matrix shows how much parallelism exists between the corresponding files of a software system chosen. Our experiments on 10 real world datasets indicate that support vector machines (SVM) with a precomputed kernel matrix performs better than the SVM with the usual linear kernel in terms of F-measure. Similarly, when used with a precomputed kernel, the k-nearest neighbor classifier (KNN) achieves comparable performance with respect to KNN classifier. The results from this preliminary study indicate that source code similarity can be used to predict defect proneness.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationOkutan, A. & Yıldız, O. T. (2016). A novel kernel to predict software defectiveness. The Journal of Systems and Software, 119, 109-121. doi:10.1016/j.jss.2016.06.006en_US
dc.identifier.doi10.1016/j.jss.2016.06.006
dc.identifier.endpage121
dc.identifier.issn0164-1212
dc.identifier.issn1873-1228
dc.identifier.scopus2-s2.0-84975270426
dc.identifier.scopusqualityQ1
dc.identifier.startpage109
dc.identifier.urihttps://hdl.handle.net/11729/1126
dc.identifier.urihttp://dx.doi.org/10.1016/j.jss.2016.06.006
dc.identifier.volume119
dc.identifier.wosWOS:000381232600007
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorYıldız, Olcay Taneren_US
dc.institutionauthorid0000-0001-5838-4615
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherElsevier Science Incen_US
dc.relation.ispartofJournal of Systems and Softwareen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDefect predictionen_US
dc.subjectSVMen_US
dc.subjectKernel methodsen_US
dc.subjectObject-oriented designen_US
dc.subjectReliabilityen_US
dc.subjectQualityen_US
dc.subjectModelsen_US
dc.titleA novel kernel to predict software defectivenessen_US
dc.typeArticleen_US
dspace.entity.typePublication

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