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Ghadesi, A., Lamothe, M., & Li, H. (2024). What causes exceptions in machine learning applications? Mining machine learning-related stack traces on Stack Overflow. Empirical Software Engineering, 29, 107 (37 pages). Lien externe
Kazemi, F., Lamothe, M., & McIntosh, S. (2024). Characterizing the Prevalence Distribution and Duration of Stale Reviewer Recommendations. IEEE Transactions on Software Engineering, 3422369 (14 pages). Lien externe
Kazemi, F., Lamothe, M., & McIntosh, S. (2024). Replication Package and Online Appendix for "Characterizing the impact, distribution, and duration of stale reviewer recommendations" [Ensemble de données]. Lien externe
Robillard, M. P., Arya, D. M., Ernst, N. A., Guo, J. L. C., Lamothe, M., Nassif, M., Novielli, N., Serebrenik, A., Steinmacher, I., & Stol, K.-J. (2024). Communicating Study Design Trade-offs in Software Engineering. ACM Transactions on Software Engineering and Methodology, 33(5), 112 (10 pages). Lien externe
Zeng, Z., Xiao, T., Lamothe, M., Hata, H., & McIntosh, S. (2024). How Trustworthy is Your CI Accelerator? A Comparison of the Trustworthiness of CI Acceleration Products. IEEE Software, 3395616 (6 pages). Lien externe
Zeng, Z., Xiao, T., Lamothe, M., Hata, H., & McIntosh, S. (avril 2024). A Mutation-Guided Assessment of Acceleration Approaches for Continuous Integration: An Empirical Study of YourBase [Communication écrite]. 2024 IEEE/ACM 21st International Conference on Mining Software Repositories (MSR 2024), Lisbon, Portugal. Lien externe
