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dc.contributor.authorÇatal, Çağatay
dc.date.accessioned2018-07-19T13:07:44Z
dc.date.available2018-07-19T13:07:44Z
dc.date.issued2016
dc.identifier.issn1300-0632
dc.identifier.other1303-6203
dc.identifier.urihttps://doi.org/10.3906/elk-1409-137
dc.identifier.urihttps://hdl.handle.net/11413/2208
dc.description.abstractWe investigated how to use cross-company (CC) data in software fault prediction and in predicting the fault labels of software modules when there are not enough fault data. This paper involves case studies of NASA projects that can be accessed from the PROMISE repository. Case studies show that CC data help build high-performance fault predictors in the absence of fault labels and remarkable results are achieved. We suggest that companies use CC data if they do not have any historical fault data when they decide to build their fault prediction models.tr_TR
dc.language.isoen_UStr_TR
dc.publisherTUBİTAK Scientific & Technical Research Council Turkey, Ataturk Bulvarı No 221, Kavaklıdere, Ankara, 00000, Turkeytr_TR
dc.relationTurkish Journal of Electrical Engineering and Computer Sciencestr_TR
dc.subjectMetrics valuestr_TR
dc.subjectdefect predictiontr_TR
dc.subjectcross-company datatr_TR
dc.subjectRoc Curvestr_TR
dc.subjectClassificationtr_TR
dc.subjectModulestr_TR
dc.subjectMetricstr_TR
dc.titleThe use of cross-company fault data for the software fault prediction problemtr_TR
dc.typeArticletr_TR
dc.contributor.authorID108363tr_TR
dc.identifier.wos378097800030
dc.identifier.scopus2-s2.0-84978238268


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