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Gallaba, K., Lamothe, M., & McIntosh, S. (mai 2022). Lessons from eight years of operational data from a continuous integration service: An exploratory case study of CircleCI [Communication écrite]. IEEE/ACM 44th International Conference on Software Engineering (ICSE 2022), Pittsburgh, PA, USA. Lien externe
Gauthier, I. X., Lamothe, M., Mussbacher, G., & McIntosh, S. (novembre 2021). Is Historical Data an Appropriate Benchmark for Reviewer Recommendation Systems? : AA Case Study of the Gerrit Community [Communication écrite]. 36th IEEE/ACM International Conference on Automated Software Engineering (ASE 2021), Melbourne, Australia. Lien externe
Kazemi, F., Lamothe, M., & McIntosh, S. (octobre 2022). Exploring the Notion of Risk in Code Reviewer Recommendation [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2022), Limassol, Cyprus. Lien externe
Lamothe, M., Shang, W., & Chen, T.-H. P. (2022). A3: Assisting Android API Migrations Using Code Examples. IEEE Transactions on Software Engineering, 48(2), 417-431. Lien externe
Lamothe, M., Li, H., & Shang, W. (2022). Assisting Example-based API Misuse Detection via Complementary Artificial Examples. IEEE Transactions on Software Engineering, 48(9), 3410-3422. Lien externe
Lamothe, M., Gueheneuc, Y. G., & Shang, W. (2021). A Systematic Review of API Evolution Literature. ACM Computing Surveys, 54(8), 1-36. Lien externe
Lamothe, M. (juin 2020). Bridging the divide between API users and API developers by mining public code repositories [Communication écrite]. 42nd ACM/IEEE International Conference on Software Engineering, Seoul, South Korea. Lien externe
Lamothe, M., & Shang, W. (juin 2020). When APIs are intentionally bypassed [Communication écrite]. 42nd ACM/IEEE International Conference on Software Engineering, Seoul, South Korea. Lien externe
Lamothe, M., & Shang, W. (mai 2018). Exploring the use of automated API migrating techniques in practice [Communication écrite]. 15th International Conference on Mining Software Repositories, Gothenburg, Sweden. Lien externe
Meidani, M., Lamothe, M., & McIntosh, S. (2023). Assessing the exposure of software changes: The DiPiDi approach. Empirical Software Engineering, 28(2), 36 pages. Lien externe
Quach, S., Lamothe, M., Kamei, Y., & Shang, W. (2021). An empirical study on the use of SZZ for identifying inducing changes of non-functional bugs. Empirical Software Engineering, 26(4). Lien externe
Quach, S., Lamothe, M., Adams, B., Kamei, Y., & Shang, W. (2021). Evaluating the impact of falsely detected performance bug-inducing changes in JIT models. Empirical Software Engineering, 26(5). Lien externe
Wen, R., Lamothe, M., & McIntosh, S. (mai 2022). How does code reviewing feedback evolve?: A longitudinal study at Dell EMC [Communication écrite]. IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Practice (ICSE 2022), Pittsburgh, PA, USA. Lien externe
Zhang, H., Tang, Y., Lamothe, M., Li, H., & Shang, W. (2022). Studying logging practice in test code. Empirical Software Engineering, 27(4), 83 (45 pages). Lien externe
