Maxime Lamothe
Ph.D. (Concordia), M.Eng. (Concordia), B.Eng. (McGill)
Assistant Professor
Department of Computer Engineering and Software Engineering
Department of Computer Engineering and Software Engineering
Areas of expertise
Logic programming Other computing methods Information systems design Software engineering Computer systems software Software and development
Logic programming Other computing methods Information systems design Software engineering Computer systems software Software and development
Primary sphere of excellence in research
Information and Communication Technologies
Information and Communication Technologies
Secondary sphere(s) of excellence in research
Modeling and Artificial Intelligence Industry of the Future and Digital Society
Modeling and Artificial Intelligence Industry of the Future and Digital Society
Research interests and affiliations
Research interests
- Empirical software engineering
- Mining software repositories
- Software APIs
- Software build systems
- Software performance
- Software bug-detection
Expertise type(s) (NSERC subjects)
- 2705 Software and development
- 2706 Software engineering
Publications
Recent publications
Conference paper
Journal article
Journal article
Journal article
Zeng, Z., Xiao, T., Lamothe, M., Hata, H., & McIntosh, S. (2024, April). A Mutation-Guided Assessment of Acceleration Approaches for Continuous Integration: An Empirical Study of YourBase [Paper]. 2024 IEEE/ACM 21st International Conference on Mining Software Repositories (MSR 2024), Lisbon, Portugal.
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).
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).
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).
See all publications (25)
Biography
Maxime Lamothe is an assistant professor at Polytechnique Montreal and is currently looking for master’s and Ph.D. students. Maxime studied software build systems as a postdoctoral researcher in the Software REBELs Lab at the University of Waterloo. His doctoral thesis, conducted in the SENSE Lab at Concordia University, focused on reducing knowledge gaps between the users and developers of software APIs. He obtained his Ph.D. from Concordia University (2020), M. Eng. degree from Concordia University (2017), and B. Eng. from McGill University (2013).
Teaching
- LOG3430 - Méthodes de test et de validation du logiciel
- LOG6305 - Techniques avancées de test du logiciel
Supervision at Polytechnique
COMPLETED
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Master's Thesis (2)
- Bouziane, A. (2023). On-Demand Health Data Provisioning with Custom Temporary Data Views for Big Data Platforms [Master's thesis, Polytechnique Montréal].
- Ghadesi, A. (2023). An Empirical Study of the Causes and Symptoms of Machine Learning Exceptions [Master's thesis, Polytechnique Montréal].
- Bouziane, A. (2023). On-Demand Health Data Provisioning with Custom Temporary Data Views for Big Data Platforms [Master's thesis, Polytechnique Montréal].