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Morovati, M. M., Nikanjam, A., Tambon, F., Khomh, F., & Jiang, Z. M. (2024). Bug characterization in machine learning-based systems. Empirical Software Engineering, 29(1), 14 (29 pages). Lien externe
Morovati, M. M., Tambon, F., Taraghi, M., Nikanjam, A., & Khomh, F. (2024). Common challenges of deep reinforcement learning applications development: an empirical study. Empirical Software Engineering, 29, 95 (33 pages). Lien externe
Morovati, M. M., Nikanjam, A., Khomh, F., & Jiang, Z. M. (2023). Bugs in machine learning-based systems: a faultload benchmark. Empirical Software Engineering, 28(3), 33 pages. Lien externe
Morovati, M. M., Nikanjam, A., Khomh, F., & Jiang, Z. M. (2023). Bugs in machine learning-based systems: a faultload benchmark [Ensemble de données]. Lien externe
Nikanjam, A., Ben Braiek, H., Morovati, M. M., & Khomh, F. (2022). Automatic Fault Detection for Deep Learning Programs Using Graph Transformations. ACM Transactions on Software Engineering and Methodology, 31(1), 1-27. Lien externe
Nikanjam, A., Morovati, M. M., Khomh, F., & Ben Braiek, H. (2022). Faults in deep reinforcement learning programs: a taxonomy and a detection approach. Automated Software Engineering, 29(1), 8 (32 pages). Lien externe
Openja, M., Morovati, M. M., An, L., Khomh, F., & Abidi, M. (2022). Technical debts and faults in open-source quantum software systems: An empirical study. Journal of Systems and Software, 193, 28 pages. Lien externe