Cross-project defect prediction using a credibility theory based naive bayes classifier

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Detail(s)

Original languageEnglish
Title of host publication2017 IEEE International Conference on Software Quality, Reliability and Security (QRS)
PublisherIEEE Computer Society
Pages434-441
ISBN (Print)978-1-5386-0592-9
Publication statusPublished - Jul 2017

Conference

Title17th IEEE International Conference on Software Quality, Reliability and Security, QRS 2017
PlaceCzech Republic
CityPrague
Period25 - 29 July 2017

Abstract

Several defect prediction models proposed are effective when historical datasets are available. Defect prediction becomes difficult when no historical data exist.
Cross-project defect prediction (CPDP), which uses projects from other sources/companies to predict the defects in the target projects proposed in recent studies has shown promising results. However, the performance of most CPDP approaches are still beyond satisfactory mainly due to distribution
mismatch between the source and target projects. In this study, a credibility theory based Naïve Bayes (CNB) classifier is proposed to establish a novel reweighting mechanism between the source projects and target projects so that the source data could simultaneously adapt to the target data distribution and
retain its own pattern. Our experimental results show that the feasibility of the novel algorithm design and demonstrate the significant improvement in terms of the performance metrics considered achieved by CNB over other CPDP approaches.

Research Area(s)

  • Credibility theory, Cross-project defect prediction, Naive Bayes classifier, Quality assurance, Software engineering, Transfer learning

Citation Format(s)

Cross-project defect prediction using a credibility theory based naive bayes classifier. / Poon, Wai Nam; Bennin, Kwabena Ebo; Huang, Jianglin; Phannachitta, Passakorn; Keung, Jacky Wai.

2017 IEEE International Conference on Software Quality, Reliability and Security (QRS) . IEEE Computer Society, 2017. p. 434-441 8009947.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)