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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
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
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
