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Muse, B. A., Nafi, K. W., Khomh, F., & Antoniol, G. (2024). Data-access performance anti-patterns in data-intensive systems. Empirical Software Engineering, 29, 144 (35 pages). Lien externe
Tambon, F., Nikanjam, A., An, L., Khomh, F., & Antoniol, G. (2024). Silent bugs in deep learning frameworks: an empirical study of Keras and TensorFlow. Empirical Software Engineering, 29(1), 10 (34 pages). Lien externe
Zid, C., Belias, F., Di Penta, M., Khomh, F., & Antoniol, G. (mars 2024). List Comprehension Versus for Loops Performance in Real Python Projects: Should we Care? [Communication écrite]. 31st IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2024), Rovaniemi, Finland. Lien externe
Zid, C., Zampetti, F., Antoniol, G., & Di Penta, M. (2024). Replication package for the paper: "A Study on the Pythonic Functional Constructs' Understandability" [Ensemble de données]. Lien externe
