Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSong, Q-
dc.contributor.authorGuo, Y-
dc.contributor.authorShepperd, M-
dc.identifier.citationSong, Q., Guo, Y. and Shepperd, M. (2018) 'A Comprehensive Investigation of the Role of Imbalanced Learning for Software Defect Prediction', IEEE Transactions on Software Engineering, 45(12): 1253-1269. doi: 10.1109/TSE.2018.2836442.en_US
dc.description.sponsorshipNational Natural Science Foundation of Chinaen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectsoftware defect prediction-
dc.subjectbug prediction-
dc.subjectimbalanced learning-
dc.subjectimbalance ratio-
dc.subjecteffect size-
dc.titleA Comprehensive Investigation of the Role of Imbalanced Learning for Software Defect Predictionen_US
dc.relation.isPartOfIEEE Transactions on Software Engineering-
Appears in Collections:Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdf1.98 MBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.