Two-Stage Cost-Sensitive Learning for Software Defect Prediction

Software defect prediction (SDP), which classifies software modules into defect-prone and not-defect-prone categories, provides an effective way to maintain high quality software systems. Most existing SDP models attempt to attain lower classification error rates other than lower misclassification c...

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Veröffentlicht in:	IEEE transactions on reliability 2014-06, Vol.63 (2), p.676-686
Hauptverfasser:	Liu, Mingxia, Miao, Linsong, Zhang, Daoqiang
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Cost-sensitive learning Defects feature selection Methods Neural networks Prediction algorithms Software algorithms software defect prediction Software metrics Software packages Software systems
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