Documents publiés en "2024"

A

Abidi, M., Rahman, M.S., Openja, M., & Khomh, F. (2024). Design smells in multi-language systems and bug-proneness: a survival analysis. Empirical Software Engineering, 29, 106 (42 pages). Lien externe

Abukhalaf, S., Hamdaqa, M., & Khomh, F. (avril 2024). PathOCL: Path-Based Prompt Augmentation for OCL Generation with GPT-4 [Communication écrite]. 1st IEEE/ACM International Conference on AI Foundation Models and Software Engineering (FORGE 2024), Lisbon, Portugal. Lien externe

C

Côté, P.-O., Nikanjam, A., Ahmed, N., Humeniuk, D., & Khomh, F. (2024). Data cleaning and machine learning: a systematic literature review. Automated Software Engineering, 31(2), 54 (75 pages). Lien externe

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Dakhel, A. M., Nikanjam, A., Khomh, F., Desmarais, M. C., & Washizaki, H. (2024). Generative AI for Software Development: A Family of Studies on Code Generation. Dans Generative AI for Effective Software Development (p. 151-172). Lien externe

Dakhel, A. M., Nikanjam, A., Khomh, F., Desmarais, M. C., & Washizaki, H. (2024). An Overview on Large Language Models. Dans Generative AI for Effective Software Development (p. 3-21). Lien externe

Dakhel, A. M., Nikanjam, A., Majdinasab, V., Khomh, F., & Desmarais, M. C. (2024). Effective test generation using pre-trained Large Language Models and mutation testing. Information and Software Technology, 171, 107468 (17 pages). Lien externe

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Foalem, P. L., Khomh, F., & Li, H. (2024). Studying logging practice in machine learning-based applications. Information and Software Technology, 170, 107450 (17 pages). Lien externe

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Khomh, F., & Jahangirova, G. (2024). Search-based Software Engineering. Lien externe

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Laberge, G., Pequignot, Y., Marchand, M., & Khomh, F. (mai 2024). Tackling the XAI Disagreement Problem with Regional Explanations [Communication écrite]. 27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), Valencia, Spain. Lien externe

M

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

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Nguyen-Duc, A., Abrahamsson, P., & Khomh, F. (2024). Generative AI for effictive software development. Lien externe

O

Openja, M., Laberge, G., & Khomh, F. (2024). Detection and evaluation of bias-inducing features in machine learning. Empirical Software Engineering, 29(1), 71 pages. Lien externe

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Rezgui, J., Jobin, F., Kechout, Y., Turgeon, C., & Khomh, F. (mai 2024). Towards a reliable french speech recognition tool for an automated diagnosis of learning disabilities [Communication écrite]. 2024 International Conference on Smart Applications, Communications and Networking (SmartNets 2024), Harrisonburg, VA, USA (6 pages). Lien externe

Russo, D., Baltes, S., van Berkel, N., Avgeriou, P., Calefato, F., Cabrero-Daniel, B., Catolino, G., Cito, J., Ernst, N., Fritz, T., Hata, H., Holmes, R., Izadi, M., Khomh, F., Kjaergaard, M. B., Liebel, G., Lafuente, A. L., Lambiase, S., Maalej, W., ... Vasilescu, B. (2024). Generative AI in Software Engineering Must Be Human-Centered: The Copenhagen Manifesto. Journal of Systems and Software, 216, 112115 (2 pages). Lien externe

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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

W

Wu, X., Laufer, E., Li, H., Khomh, F., Srinivasan, S., & Luo, J. (2024). Characterizing and classifying developer forum posts with their intentions. Empirical Software Engineering, 29(4), 84 (34 pages). Lien externe