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  1. No Access

    Chapter

    Introduction

    With the increasing pressures of expediting software projects that is always increasing in size and complexity to meet rapidly changing business needs, quality assurance activities such as fault prediction mod...

    **ao-Yuan **g, Haowen Chen, Baowen Xu in Intelligent Software Defect Prediction (2023)

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    Chapter

    Machine Learning Techniques for Intelligent SDP

    In this chapter, several common learning algorithms and their applications in software defect prediction are briefly introduced, including deep learning, transfer learning, dictionary learning, semi-supervised...

    **ao-Yuan **g, Haowen Chen, Baowen Xu in Intelligent Software Defect Prediction (2023)

  3. No Access

    Chapter

    Conclusion

    This book provides a comprehensive guide to the basic theory of SDP, as well as some discussion of solutions to the corresponding problems, and some of the problems in this field. We believe this content will ...

    **ao-Yuan **g, Haowen Chen, Baowen Xu in Intelligent Software Defect Prediction (2023)

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    Chapter

    Within-Project Defect Prediction

    In order to improve the quality of a software system, software defect prediction aims to automatically identify defective software modules for efficient software test. To predict software defect, those classif...

    **ao-Yuan **g, Haowen Chen, Baowen Xu in Intelligent Software Defect Prediction (2023)

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    Chapter

    Heterogeneous Defect Prediction

    Cross-company defect prediction (CCDP) learns a prediction model by using training data from one or multiple projects of a source company and then applies the model to the target company data. Existing CCDP me...

    **ao-Yuan **g, Haowen Chen, Baowen Xu in Intelligent Software Defect Prediction (2023)

  6. No Access

    Chapter

    Other Research Questions of SDP

    Sorting software modules in order of defect count can help testers to focus on software modules with more defects. One of the most popular methods for sorting modules is generalized linear regression. However,...

    **ao-Yuan **g, Haowen Chen, Baowen Xu in Intelligent Software Defect Prediction (2023)

  7. No Access

    Chapter

    Cross-Project Defect Prediction

    The challenge of CPDP methods is the distribution difference between the data from different projects. Transfer learning can transfer the knowledge from the source domain to the target domain with the aim to m...

    **ao-Yuan **g, Haowen Chen, Baowen Xu in Intelligent Software Defect Prediction (2023)

  8. No Access

    Chapter

    An Empirical Study on HDP Approaches

    Software defect prediction has always been a hot research topic in the field of software engineering owing to its capability of allocating limited resources reasonably. Compared with cross-project defect predi...

    **ao-Yuan **g, Haowen Chen, Baowen Xu in Intelligent Software Defect Prediction (2023)

  9. No Access

    Book

    Intelligent Software Defect Prediction

    **ao-Yuan **g, Haowen Chen, Baowen Xu (2023)