1. SQAPlanner: Generating data-informed software quality improvement plans

    Dilini Rajapaksha, Chakkrit Tantithamthavorn, Jirayus Jiarpakdee, Christoph Bergmeir, John Grundy, and Wray Buntine
    IEEE Transactions on Software Engineering
    2021
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  2. Predicting Defective Lines Using a Model-Agnostic Technique

    Supatsara Wattanakriengkrai, Patanamon Thongtanunam, Chakkrit Tantithamthavorn, Hideaki Hata, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2020
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  3. An Empirical Study of Model-Agnostics Techniques for Defect Prediction Models

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, Hoa Khanh Dam, John Grundy
    IEEE Transactions on Software Engineering (TSE)
    2020
    PDF
  4. The Impact of Correlated Metrics on the Interpretation of Defect Models

    Jirayus Jiarpakdee, Chakkrit Tantithamthavorn, and Ahmed E. Hassan
    IEEE Transactions on Software Engineering (TSE)
    2019
    PDF
  5. The Impact of Class Rebalancing Techniques on the Performance and Interpretation of Defect Prediction Models

    Chakkrit Tantithamthavorn, Ahmed E. Hassan, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2019
    PDF
  6. The Impact of Automated Parameter Optimization on Defect Prediction Models

    Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2019
    PDF
  7. An Empirical Comparison of Model Validation Techniques for Defect Prediction Models


    Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2017
    PDF
  8. Comments on "Researcher Bias: The Use of Machine Learning in Software Defect Prediction"

    Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, and Kenichi Matsumoto
    IEEE Transactions on Software Engineering (TSE)
    2016
    PDF