Machine Learning for Information Systems, Mining Software Repositories, Empirical Software Engineering, Software/Data Analytics, Natural Language Processing.
The main research field of Dr. El Mezouar is Empirical Software Engineering. She uses methodologies such as machine learning, statistics and qualitative techniques (e.g., surveys and interviews) to better understand the software development phenomena. She analyzes historical data (particularly textual data) using NLP techniques to provide approaches and techniques that can support software practitioners in the workplace.
Dr. El Mezouar obtained a PhD in Computing from Queen's University in 2019, where she was a member of the Software Evolution and Analytics Lab. Prior to that, she completed her M.Sc. in Software Engineering at Al Akhawayn University in Morocco.
She joined the Department of Mathematics and Computer Science at RMC in 2022.
- El Mezouar, M., Zhang, F. & Zou, Y. Are tweets useful in the bug fixing process? An empirical study on Firefox and Chrome. Empir Software Eng 23, 1704–1742 (2018).
- El Mezouar, M., Zhang, F. & Zou, Y. An empirical study on the teams structures in social coding using GITHUB projects. Empir Software Eng 24, 3790–3823 (2019).
- Ehsan, O., Hassan, S., Mezouar, M. E., & Zou, Y. (2020). An empirical study of developer discussions in the gitter platform. ACM Transactions on Software Engineering and Methodology (TOSEM), 30(1), 1-39
- El Mezouar, M., Zhang, F., & Zou, Y. (2016, October). Local versus global models for effort-aware defect prediction. In Proceedings of the 26th Annual International Conference on Computer Science and Software Engineering (pp. 178-187)
- M. E. Mezouar, D. A. da Costa, D. M. German and Y. Zou, "Exploring the Use of Chatrooms by Developers: An Empirical Study on Slack and Gitter," in IEEE Transactions on Software Engineering, vol. 48, no. 10, pp. 3988-4001, 1 Oct. 2022, doi: 10.1109/TSE.2021.3109617.
A complete list of her publications can be found on Google Scholar.