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Maxime Lamothe
Ph.D. (Concordia), M.Eng. (Concordia), B.Eng. (McGill)

Phone: Ext. 7140 Fax: (514) 340-5139 Room: M-4115
Google Scholar

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


Recent publications
Journal article
Meidani, M., Lamothe, M. & McIntosh, S. (2023). Assessing the exposure of software changes: The DiPiDi approach. Empirical Software Engineering, 28(2), 36 pages. Retrieved from
Journal article
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. Retrieved from
Journal article
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. Retrieved from
Conference paper
Kazemi, F., Lamothe, M. & McIntosh, S. (2022). Exploring the Notion of Risk in Code Reviewer Recommendation. Paper presented at the IEEE International Conference on Software Maintenance and Evolution (ICSME 2022), Limassol, Cyprus (pp. 139-150). Retrieved from


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).