Documents publiés en "2026"

B

Barbosa, N., Borba, P., & Da Silva, L. (2026). Assessing the effectiveness of Large Language Models in detecting semantic conflicts. Journal of Software Engineering Research and Development, 14(1), 25 pages. Disponible

C

Chen Kuang Piao, Y., Paul, J. C., Da Silva, L., Moradi Dakhel, A., Hamdaqa, M., & Khomh, F. (2026). Refactoring with LLMs: Bridging human expertise and machine understanding. Empirical Software Engineering, 32(1), 11 (51 pages). Lien externe

D

de Araújo Barbosa, N. F., Borba, P., & Da Silva, L. (2026). Supplementary data for: Assessing the effectiveness of large language models in detecting semantic conflicts [Ensemble de données]. Lien externe

F

Foalem, P. L., Da Silva, L., Khomh, F., & Merlo, E. (2026). An empirical study of Policy-as-Code adoption in open-source software projects. Journal of Systems and Software, 242, 113028 (14 pages). Lien externe

Foundjem, A. T., Nganyewou Tidjon, L., Da Silva, L., & Khomh, F. (2026). Multi-Agent AI Framework for Threat Mitigation and Resilience in Machine Learning Systems. ACM Transactions on Software Engineering and Methodology. Lien externe

O

Olewicki, D., Da Silva, L., Ben Sghaier, O., Mujahid, S., Amini, A., Mah, B., Castelluccio, M., Habchi, S., Khomh, F., & Adams, B. (2026). Impact of an LLM-based Review Assistant in Practice: A Mixed Open-/Closed-source Case Study. IEEE Transactions on Software Engineering, 12 pages. Lien externe