IEEE Transactions on Software Engineering (TSE)

International Journal Papers x 13

1. Characterizing and Mitigating Self-Admitted Technical Debt in Build Systems
   Authors - Tao Xiao, Dong Wang, Shane McIntosh, Hideaki Hata, Raula Gaikovina Kula, Takashi Ishio, Kenichi Matsumoto
   Venue - IEEE Transactions on Software Engineering, pp. To appear, 2022
   Preprint - PDF
   Related Tags - TSE 2022 build systems software quality anti-patterns
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, pp. To appear, 2021
   Preprint - PDF
   Related Tags - TSE 2021 software quality defect prediction
3. An Empirical Study of Type-Related Defects in Python Projects
   Authors - Faizan Khan, Boqi Chen, Daniel Varro, Shane McIntosh
   Venue - IEEE Transactions on Software Engineering, pp. To appear, 2021
   Preprint - PDF
   Related Tags - TSE 2021 software quality anti-patterns
4. Accelerating Continuous Integration by Caching Environments and Inferring Dependencies
   Authors - Keheliya Gallaba, John Ewart, Yves Junqueira, Shane McIntosh
   Venue - IEEE Transactions on Software Engineering, pp. To appear, 2021
   Preprint - PDF
   Related Tags - TSE 2021 continuous integration build performance
5. Quantifying, Characterizing, and Mitigating Flakily Covered Program Elements
   Authors - Shivashree Vysali, Shane McIntosh, Bram Adams
   Venue - IEEE Transactions on Software Engineering, pp. To appear, 2021
   Preprint - PDF
   Related Tags - TSE 2021 software quality flaky tests
6. Code Reviews with Divergent Review Scores: An Empirical Study of the OpenStack and Qt Communities
   Authors - Toshiki Hirao, Shane McIntosh, Akinori Ihara, Kenichi Matsumoto
   Venue - IEEE Transactions on Software Engineering, pp. To appear, 2021
   Preprint - PDF
   Related Tags - TSE 2021 code review integration
7. Use and Misuse of Continuous Integration Features: An Empirical Study of Projects that (mis)use Travis CI
   Authors - Keheliya Gallaba, Shane McIntosh
   Venue - IEEE Transactions on Software Engineering, Vol. 46, No. 1, pp. 33–50, 2020
   Preprint - PDF
   Related Tags - TSE 2020 continuous integration anti-patterns software evolution
8. 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
9. 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
10. 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
11. 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
12. 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
13. 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