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Abidi, M., Rahman, M. S., Openja, M., & Khomh, F. (2022). Multi-language design smells: a backstage perspective. Empirical Software Engineering, 27(5), 52 pages. Lien externe
Abidi, M., Rahman, M. S., Openja, M., & Khomh, F. (2021). Are Multi-Language Design Smells Fault-Prone? An Empirical Study. ACM Transactions on Software Engineering and Methodology, 30(3), 1-56. Lien externe
Jebnoun, H., Rahman, M. S., Khomh, F., & Muse, B. A. (2022). Clones in deep learning code: what, where, and why? Empirical Software Engineering, 27(4). Lien externe
Kermansaravi, Z. A., Rahman, M. S., Khomh, F., Jaafar, F., & Guéhéneuc, Y.-G. (2021). Investigating design anti-pattern and design pattern mutations and their change- and fault-proneness. Empirical Software Engineering, 26(1), 47 pages. Lien externe
Rahman, M. S., Khomh, F., Hamidi, A., Cheng, J., Antoniol, G., & Washizaki, H. (2023). Machine learning application development: practitioners insights. Software Quality Journal, 55 pages. Lien externe
Rahman, M. S., Khomh, F., Rivera, E., Guéhéneuc, Y.-G., & Lehnert, B. (mai 2022). Challenges in machine learning application development : an industrial experience report [Communication écrite]. IEEE/ACM 1st International Workshop on Software Engineering for Responsible Artificial Intelligence (SE4RAI 2022), Pittsburgh, PA, USA. Lien externe
