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Humeniuk, D., Khomh, F., & Antoniol, G. (2023). AmbieGen: A search-based framework for autonomous systems testing. Science of Computer Programming, 230, 102990 (10 pages). Lien externe
Muse, B. A., Khomh, F., & Antoniol, G. (2023). Refactoring practices in the context of data-intensive systems. Empirical Software Engineering, 28(2), 46 (66 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
Tambon, F., Khomh, F., & Antoniol, G. (2023). A probabilistic framework for mutation testing in deep neural networks. Information and Software Technology, 155, 107129 (13 pages). Lien externe
Humeniuk, D., Khomh, F., & Antoniol, G. RIGAA at the SBFT 2023 Tool Competition - Cyber-Physical Systems Track [Communication écrite]. 2023 IEEE/ACM International Workshop on Search-Based and Fuzz Testing (SBFT 2023), Melbourne, Australia. Lien externe
Tambon, F., Majfinasab, V., Nikanjam, A., Khomh, F., & Antoniol, G. (avril 2023). Mutation testing of deep reinforcement learning based on real faults [Communication écrite]. 16th IEEE Conference on Software Testing, Verification and Validation (ICST 2023), Dublin, Ireland. Lien externe