Intelligent Software Defect Prediction

• Record Nr.: UNINA9910805580003321
• Autore: Jing Xiao-Yuan
• Pubbl/distr/stampa: Singapore : , : Springer Singapore Pte. Limited, , 2024; ©2023
• ISBN: 981-9928-42-7
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (210 pages)
• Altri autori (Persone): ChenHaowen; XuBaowen
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- 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.; 5 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.