Defect Prediction

International Journal Papers x 9

  1. Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets
    Authors - Partha Chakraborty, Krishna Kanth Arumugam, Mahmoud Alfadel, Meiyappan Nagappan, Shane McIntosh
    Venue - IEEE Transactions on Software Engineering, pp. To appear, 2024
    Preprint - PDF
    Related Tags - TSE 2024 software quality defect prediction
  2. The Ghost Commit Problem When Identifying Fix-Inducing Changes: An Empirical Study of Apache Projects
    Authors - Christophe Rezk, Yasutaka Kamei, Shane McIntosh
    Venue - IEEE Transactions on Software Engineering, Vol. 48, No. 9, pp. 3297–3309, 2022
    Preprint - PDF
    Related Tags - TSE 2022 software quality defect prediction
  3. The Impact of Automated Parameter Optimization on Defect Prediction Models
    Authors - Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Kenichi Matsumoto
    Venue - Transactions on Software Engineering, Vol. 45, No. 7, pp. 683–711, 2019
    Preprint - PDF
    Related Tags - TSE 2019 software quality defect prediction
  4. Are Fix-Inducing Changes a Moving Target? A Longitudinal Case Study of Just-In-Time Defect Prediction
    Authors - Shane McIntosh, Yasutaka Kamei
    Venue - IEEE Transactions on Software Engineering, Vol. 44, No. 5, pp. 412–428, 2018
    Preprint - PDF
    Related Tags - TSE 2018 software quality defect prediction
  5. A Framework for Evaluating the Results of the SZZ Approach for Identifying Bug-Introducing Changes
    Authors - Daniel Alencar da Costa, Shane McIntosh, Weiyi Shang, Uirá Kulesza, Roberta Coelho, Ahmed E. Hassan
    Venue - IEEE Transactions on Software Engineering, Vol. 43, No. 7, pp. 641–657, 2017
    Preprint - PDF
    Related Tags - TSE 2017 software quality defect prediction
  6. The Use of Summation to Aggregate Software Metrics Hinders the Performance of Defect Prediction Models
    Authors - Feng Zhang, Ahmed E. Hassan, Shane McIntosh, Ying Zou
    Venue - IEEE Transactions on Software Engineering, Vol. 43, No. 5, pp. 476-491, 2017
    Preprint - PDF
    Related Tags - TSE 2017 software quality defect prediction
  7. An Empirical Comparison of Model Validation Techniques for Defect Prediction Models
    Authors - Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Kenichi Matsumoto
    Venue - IEEE Transactions on Software Engineering, Vol. 41, No. 1, pp. 1-18, 2017
    Preprint - PDF
    Related Tags - TSE 2017 software quality defect prediction
  8. Comments on "Researcher Bias: The Use of Machine Learning in Software Defect Prediction"
    Authors - Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Kenichi Matsumoto
    Venue - IEEE Transactions on Software Engineering, Vol. 42, No. 11, pp. 1092-1094, 2016
    Preprint - PDF
    Related Tags - TSE 2016 software quality defect prediction
  9. Studying just-in-time defect prediction using cross-project models
    Authors - Yasutaka Kamei, Takafumi Fukushima, Shane McIntosh, Kazuhiro Yamashita, Naoyasu Ubayashi, Ahmed E. Hassan
    Venue - Empirical Software Engineering, Vol. 21, No. 5, pp. 2072-2106, 2016
    Preprint - PDF
    Related Tags - EMSE 2016 software quality defect prediction

Full-Length International Conference Papers x 7

  1. TraceJIT: Evaluating the Impact of Behavioral Code Change on JIT Defect Prediction
    Authors - Issei Morita, Yutaro Kashiwa, Masanari Kondo, Jeongju Sohn, Shane McIntosh, Yasutaka Kamei, Naoyasu Ubayashi
    Venue - International Conference on Software Analysis, Evolution, and Reengineering, pp. To appear, 2024
    Acceptance rate - 62/242 (26%)
    Preprint - PDF
    Related Tags - SANER 2024 software quality defect prediction
  2. Leveraging Fault Localisation to Enhance Defect Prediction
    Authors - Jeongju Sohn, Yasutaka Kamei, Shane McIntosh, Shin Yoo
    Venue - International Conference on Software Analysis, Evolution, and Reengineering, pp. 284–294, 2021
    Acceptance rate - 42/165 (25%)
    Preprint - PDF
    Related Tags - SANER 2021 software quality defect prediction
  3. A Large-Scale Study of the Impact of Feature Selection Techniques on Defect Classification Models
    Authors - Baljinder Ghotra, Shane McIntosh, Ahmed E. Hassan
    Venue - International Conference on Mining Software Repositories, pp. 146–157, 2017
    Acceptance rate - 37/121 (31%)
    Preprint - PDF
    Related Tags - MSR 2017 defect prediction
  4. Automated Parameter Optimization of Classification Techniques for Defect Prediction Models
    Authors - Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Kenichi Matsumoto
    Venue - International Conference on Software Engineering, pp. 321-332, 2016
    Acceptance rate - 101/530 (19%)
    Preprint - PDF
    Related Tags - ICSE 2016 software quality defect prediction
  5. The Impact of Mislabelling on the Performance and Interpretation of Defect Prediction Models
    Authors - Chakkrit Tantithamthavorn, Shane McIntosh, Ahmed E. Hassan, Akinori Ihara, Kenichi Matsumoto
    Venue - International Conference on Software Engineering, pp. 812-823, 2015
    Acceptance rate - 84/452 (19%)
    Preprint - PDF
    Related Tags - ICSE 2015 software quality defect prediction
  6. Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models
    Authors - Baljinder Ghotra, Shane McIntosh, Ahmed E. Hassan
    Venue - International Conference on Software Engineering, pp. 789-800, 2015
    Acceptance rate - 84/452 (19%)
    Preprint - PDF
    Related Tags - ICSE 2015 software quality defect prediction
  7. An Empirical Study of Just-In-Time Defect Prediction Using Cross-Project Models
     Invited for journal extension 
    Authors - Takafumi Fukushima, Yasutaka Kamei, Shane McIntosh, Kazuhiro Yamashita, Naoyasu Ubayashi
    Venue - Working Conference on Mining Software Repositories, pp. 172-181, 2014
    Acceptance rate - 29/85 (34%)
    Preprint - PDF
    Related Tags - MSR 2014 software quality defect prediction

Short International Conference Papers x 1

  1. The Relationship between Commit Message Detail and Defect Proneness in Java Projects on GitHub
     Mining challenge runner-up 
    Authors - Jacob G. Barnett, Charles K. Gathuru, Luke S. Soldano, Shane McIntosh
    Venue - International Conference on Mining Software Repositories, Mining challenge, pp. 496-499, 2016
    Acceptance rate - 10/24 (42%)
    Preprint - PDF
    Related Tags - MSR 2016 software quality defect prediction

Theses x 1

  1. Quantifying, Characterizing, and Mitigating the Ghost Commit Problem When Identifying Fix-Inducing Changes
    Authors - Christophe Rezk
    Venue - McGill University, pp. 1-72, 2021
    Preprint - PDF
    Related Tags - Theses 2021 software quality defect prediction