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Abukhalaf, S., Hamdaqa, M., & Khomh, F. On Codex Prompt Engineering for OCL Generation: An Empirical Study [Communication écrite]. 2023 IEEE/ACM 20th International Conference on Mining Software Repositories (MSR 2023), Melbourne, Australia. Lien externe
Aghili, R., Li, H., & Khomh, F. (2023). Studying the characteristics of AIOps projects on GitHub. Empirical Software Engineering, 28(6), 143 (49 pages). Lien externe
Badran, K., Cote, P.-O., Kolopanis, A., Bouchoucha, R., Collante, A., Costa, D. E., Shihab, E., & Khomh, F. (2023). Can Ensembling Preprocessing Algorithms Lead to Better Machine Learning Fairness? Computer, 56(4), 71-79. Lien externe
Ben Braiek, H., & Khomh, F. (2023). Testing Feedforward Neural Networks Training Programs. ACM Transactions on Software Engineering and Methodology, 32(4), 1-61. Lien externe
Berhe, S., Maynard, M., & Khomh, F. (mars 2023). Maintenance Cost of Software Ecosystem Updates [Communication écrite]. 6th International Conference on Emerging Data and Industry 4.0 (EDI40 2023), Leuven, Belgium. Publié dans Procedia Computer Science, 220. Lien externe
Biagiola, M., Cardozo, N., Shin, D., Khomh, F., Stocco, A., & Riccio, V. (2023). Summary of the Fourth International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest 2023). ACM SIGSOFT Software Engineering Notes, 48(4), 39-40. Lien externe
Bosco, M., Cavoto, P., Ungolo, A., Muse, B. A., Khomh, F., Nardone, V., & Di Penta, M. UnityLint: A Bad Smell Detector for Unity [Communication écrite]. 2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC 2023), Melbourne, Australia. Lien externe
Bouchoucha, R., Braiek, H. B., Khomh, F., Bouzidi, S., & Zaatour, R. (2023). Robustness assessment of hyperspectral image CNNs using metamorphic testing. Information and Software Technology, 162, 10 pages. Lien externe
Chembakottu, B., Li, H., & Khomh, F. (2023). A large-scale exploratory study of android sports apps in the google play store. Information and Software Technology, 164, 107321 (18 pages). Lien externe
Dakhel, A. M., Desmarais, M. C., & Khomh, F. (2023). Dev2vec: Representing domain expertise of developers in an embedding space. Information and Software Technology, 159, 12 pages. Lien externe
Dakhel, A. M., Majdinasab, V., Nikanjam, A., Khomh, F., Desmarais, M. C., & Jiang, Z. M. (2023). GitHub Copilot AI pair programmer: Asset or Liability? Journal of Systems and Software, 203, 111734 (23 pages). Lien externe
Ehsan, O., Khomh, F., Zou, Y., & Qiu, D. (2023). Ranking code clones to support maintenance activities. Empirical Software Engineering, 28(3), 38 pages. Lien externe
Hooshyar, H., Guerra, E., Melegati, J., Khanna, D., Aldaeej, A., Matturro, G., Zaina, L., Greer, D., Rafiq, U., Chanin, R., Wang, X., Garbajosa, J., Abrahamsson, P., Khomh, F., & Nguyen-Duc, A. (2023). Impact in Software Engineering Activities After One Year of COVID-19 Restrictions for Startups and Established Companies. IEEE Access, 11, 55178-55203. Lien externe
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
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
Jamshidi, S., Nikanjam, A., Hamdaqa, M. A., & Khomh, F. (2023). Attack Detection by Using Deep Learning for Cyber-Physical System. Dans Artificial Intelligence for Cyber-Physical Systems Hardening (Vol. 2, 155-179). Lien externe
Khomh, F. (décembre 2023). Harnessing Predictive Modeling and Software Analytics in the Age of LLM-Powered Software Development [Résumé]. 19th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2023), San Francisco, CA, USA (1 page). Lien externe
Laberge, G., Pequignot, Y., Mathieu, A., Khomh, F., & Marchand, M. (2023). Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set. Journal of Machine Learning Research, 24(364), 50 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
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
Nardone, V., Muse, B. A., Abidi, M., Khomh, F., & Di Penta, M. (2023). Video Game Bad Smells: What They Are and How Developers Perceive Them. ACM Transactions on Software Engineering and Methodology, 32(4), 1-35. Lien externe
Nouwou Mindom, P. S., Nikanjam, A., & Khomh, F. (2023). A comparison of reinforcement learning frameworks for software testing tasks. Empirical Software Engineering, 28(5), 111 (76 pages). Lien externe
Qasse, I., Mishra, S., Jonsson, B. þ., Khomh, F., & Hamdaqa, M. (juillet 2023). Chat2Code: A Chatbot for Model Specification and Code Generation, The Case of Smart Contracts [Communication écrite]. IEEE International Conference on Software Services Engineering (SSE 2023), Chicago, IL, USA. 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
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
Wu, X., Li, H., & Khomh, F. (2023). On the effectiveness of log representation for log-based anomaly detection. Empirical Software Engineering, 28(6), 137 (39 pages). Lien externe
Yahmed, A. H., Allah Abbassi, A., Nikanjam, A., Li, H., & Khomh, F. (octobre 2023). Deploying deep reinforcement learning systems: a taxonomy of challenges [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2023), Bogota, Colombia. Lien externe
Yahmed, A. H., Bouchoucha, R., Ben Braiek, H., & Khomh, F. (septembre 2023). An Intentional Forgetting-Driven Self-Healing Method for Deep Reinforcement Learning Systems [Communication écrite]. 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023), Echternach, Luxembourg. Lien externe
Yin Ho, S. C., Majdinasab, V., Islam, M., Costa, D. E., Shihab, E., Khomh, F., Nadi, S., & Raza, M. (octobre 2023). An Empirical Study on Bugs Inside PyTorch: A Replication Study [Communication écrite]. 39th IEEE International Conference on Software Maintenance and Evolution (ICSME 2023), Bogota, Colombia. Lien externe
Yousefifeshki, F., Li, H., & Khomh, F. (2023). Studying the challenges of developing hardware description language programs. Information and Software Technology, 159, 16 pages. Lien externe
