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An Evaluation of Cross-Project Defect Prediction Approaches on Cross-Personalized Defect Prediction

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Product-Focused Software Process Improvement (PROFES 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13709))

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Abstract

Context: Just-in-time software defect prediction (JIT SDP) helps to prioritize fault-prone commits for efficient software quality assurance. As each commit can be attributed to each developer, JIT SDP can also be personalized to each developer as a personalized defect prediction. A question is whether the commit data of other developers, namely, cross-personalized data, are still valuable for prediction. Cross-project defect prediction (CPDP) approaches are a promising answer. Objective: To clarify the effectiveness of cross-personalized defect prediction with CPDP approaches. Method: An experiment with 23 CPDP approaches was conducted on 9 project datasets. Results: Some CPDP approaches using cross-personalized data were often better than the personalized defect prediction using one’s data. Conclusion: It is recommended to use the CPDP approach to achieve better predictions. Turhan09 is our recommendation.

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Notes

  1. 1.

    http://doi.org/10.5281/zenodo.2594681.

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Acknowledgment

This work was partially supported by JSPS KAKENHI Grant #21K11831, #21K11833, and Wesco Scientific Promotion Foundation.

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Authors and Affiliations

  1. Okayama Prefectural University, 111 Kuboki, Soja, 719-1197, Japan

    Sousuke Amasaki & Tomoyuki Yokogawa

  2. Center for Information Technology, Ehime University, Matsuyama, 790-8577, Japan

    Hirohisa Aman

Authors
  1. Sousuke Amasaki
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  2. Hirohisa Aman
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  3. Tomoyuki Yokogawa
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Corresponding author

Correspondence to Sousuke Amasaki .

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Editors and Affiliations

  1. Tampere University, Tampere, Finland

    Davide Taibi

  2. Reutlingen University, Reutlingen, Germany

    Marco Kuhrmann

  3. University of Jyväskylä, Jyväskylä, Finland

    Tommi Mikkonen

  4. Leibniz University Hannover, Hannover, Germany

    Jil Klünder

  5. University of Jyväskylä, Jyväskylä, Finland

    Pekka Abrahamsson

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Amasaki, S., Aman, H., Yokogawa, T. (2022). An Evaluation of Cross-Project Defect Prediction Approaches on Cross-Personalized Defect Prediction. In: Taibi, D., Kuhrmann, M., Mikkonen, T., Klünder, J., Abrahamsson, P. (eds) Product-Focused Software Process Improvement. PROFES 2022. Lecture Notes in Computer Science, vol 13709. Springer, Cham. https://doi.org/10.1007/978-3-031-21388-5_30

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  • DOI: https://doi.org/10.1007/978-3-031-21388-5_30

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