LEADER 04885nam 22003853 450 001 9910805580003321 005 20240121090240.0 010 $a981-9928-42-7 035 $a(MiAaPQ)EBC31072041 035 $a(Au-PeEL)EBL31072041 035 $a(EXLCZ)9929958294300041 100 $a20240121d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIntelligent Software Defect Prediction 205 $a1st ed. 210 1$aSingapore :$cSpringer Singapore Pte. Limited,$d2024. 210 4$dİ2023. 215 $a1 online resource (210 pages) 311 08$aPrint version: Jing, Xiao-Yuan Intelligent Software Defect Prediction Singapore : Springer Singapore Pte. Limited,c2024 9789819928415 327 $aIntro -- Preface -- Acknowledgments -- Contents -- 1 Introduction -- 1.1 Software Quality Assurance -- 1.2 Software Defect Prediction -- 1.3 Research Directions of SDP -- 1.3.1 Within-Project Defect Prediction (WPDP) -- 1.3.2 Cross-Project Defect Prediction (CPDP) -- 1.3.3 Heterogeneous Defect Prediction (HDP) -- 1.3.4 Other Research Questions of SDP -- 1.3.4.1 Cross-Version Defect Prediction -- 1.3.4.2 Just-in-Time Defect Prediction -- 1.3.4.3 Effort-Aware Defect Prediction -- 1.4 Notations and Corresponding Descriptions -- 1.5 Structure of This Book -- References -- 2 Machine Learning Techniques for Intelligent SDP -- 2.1 Transfer Learning -- 2.2 Deep Learning -- 2.3 Other Techniques -- 2.3.1 Dictionary Learning -- 2.3.2 Semi-Supervised Learning -- 2.3.3 Multi-View Learning -- References -- 3 Within-Project Defect Prediction -- 3.1 Basic WPDP -- 3.1.1 Dictionary Learning Based Software Defect Prediction -- 3.1.1.1 Methodology -- 3.1.1.2 Experiments -- 3.1.1.3 Discussions -- 3.1.2 Collaborative Representation Classification Based Software Defect Prediction -- 3.1.2.1 Methodology -- 3.1.2.2 Experiments -- 3.1.2.3 Discussions -- 3.2 Semi-supervised WPDP -- 3.2.1 Sample-Based Software Defect Prediction with Active and Semi-supervised Learning -- 3.2.1.1 Methodology -- 3.2.1.2 Experiments -- 3.2.1.3 Discussions -- References -- 4 Cross-Project Defect Prediction -- 4.1 Basic CPDP -- 4.1.1 Manifold Embedded Distribution Adaptation -- 4.1.1.1 Methodology -- 4.1.1.2 Experiments -- 4.1.1.3 Discussions -- 4.2 Class Imbalance Problem in CPDP -- 4.2.1 An Improved SDA Based Defect Prediction Framework -- 4.2.1.1 Methodology -- 4.2.1.2 Experiments -- 4.2.1.3 Discussions -- 4.3 Semi-Supervised CPDP -- 4.3.1 Cost-Sensitive Kernelized Semi-supervised Dictionary Learning -- 4.3.1.1 Methodology -- 4.3.1.2 Experiments -- 4.3.1.3 Discussion -- References. 327 $a5 Heterogeneous Defect Prediction -- 5.1 Basic HDP -- 5.1.1 Unified Metric Representation and CCA-Based Transfer Learning -- 5.1.1.1 Methodology -- 5.1.1.2 Experiments -- 5.1.1.3 Discussions -- 5.2 Class Imbalance Problem in HDP -- 5.2.1 Cost-Sensitive Transfer Kernel Canonical Correlation Analysis -- 5.2.1.1 Methodology -- 5.2.1.2 Experiments -- 5.2.1.3 Discussions -- 5.2.2 Other Solutions -- 5.3 Multiple Sources and Privacy Preservation Problems in HDP -- 5.3.1 Multi-Source Selection Based Manifold Discriminant Alignment -- 5.3.1.1 Methodology -- 5.3.1.2 Experiments -- 5.3.1.3 Discussions -- 5.3.2 Sparse Representation Based Double Obfuscation Algorithm -- 5.3.2.1 Methodology -- 5.3.2.2 Experiments -- 5.3.2.3 Discussions -- References -- 6 An Empirical Study on HDP Approaches -- 6.1 Goal Question Metric (GQM) Based Research Methodology -- 6.1.1 Major Challenges -- 6.1.2 Review of Research Status -- 6.1.3 Analysis on Research Status -- 6.1.4 Research Goal -- 6.1.5 Research Questions -- 6.1.6 Evaluation Metrics -- 6.2 Experiments -- 6.2.1 Datasets -- 6.2.2 SDP Approaches for Comparisons -- 6.2.3 Experimental Design -- 6.2.4 Experimental Results -- 6.3 Discussions -- References -- 7 Other Research Questions of SDP -- 7.1 Cross-Version Defect Prediction -- 7.1.1 Methodology -- 7.1.2 Experiments -- 7.1.3 Discussions -- 7.2 Just-in-Time Defect Prediction -- 7.2.1 Methodology -- 7.2.2 Experiments -- 7.2.2.1 Experiment Setup -- 7.2.2.2 Evaluation Metrics -- 7.2.2.3 Research Questions -- 7.2.3 Discussions -- 7.3 Effort-Aware Just-in-Time Defect Prediction -- 7.3.1 Methodology -- 7.3.1.1 Dependent and Independent Variables -- 7.3.1.2 Simple Unsupervised Models -- 7.3.1.3 The Supervised Models -- 7.3.1.4 Research Questions -- 7.3.1.5 Performance Indicators -- 7.3.2 Experiments -- 7.3.3 Discussions -- References -- 8 Conclusion -- 8.1 Conclusion. 700 $aJing$b Xiao-Yuan$01588644 701 $aChen$b Haowen$01588645 701 $aXu$b Baowen$01588646 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910805580003321 996 $aIntelligent Software Defect Prediction$93882668 997 $aUNINA