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Aghili, R., Li, H., & Khomh, F. (juin 2025). Protecting Privacy in Software Logs: What Should Be Anonymized? [Communication écrite]. ACM International Conference on the Foundations of Software Engineering (FSE 2025), Trondheim, Norway. Publié dans Proceedings of the ACM on Software Engineering, 2(FSE). Lien externe
Aghili, R., Li, H., & Khomh, F. (2025). Protecting Privacy in Software Logs: What Should Be Anonymized? Proceedings of the ACM on software engineering., 2(FSE), 1317-1338. Lien externe
Caumartin, G., Qin, Q., Chatragadda, S., Panjrolia, J., Li, H., & Elias Costa, D. (mars 2025). Exploring the Potential of Llama Models in Automated Code Refinement: A Replication Study [Communication écrite]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2025), Montreal, QC, Canada. Lien externe
Foalem, P. L., Da Silva, L. M. P., Khomh, F., Li, H., & Merlo, E. (2025). Logging requirement for continuous auditing of responsible machine learning-based applications. Empirical Software Engineering, 30(3), 97 (37 pages). Lien externe
Ghari, S., Fokaefs, M., & Li, H. (juin 2025). SparkPerf: A Benchmarking Framework for Evaluating the Performance of Spark Data Analytics Projects [Communication écrite]. IEEE Cloud Summit 2025, Washington, DC, USA. Lien externe
Huang, S.-W., Wu, X., & Li, H. (juin 2025). LogLSHD: Fast Log Parsing with Locality-Sensitive Hashing and Dynamic Time Warping [Communication écrite]. 21st International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2025)), Trondheim, Norway. Lien externe
Jin, B., Li, H., & Zou, Y. (2025). Impact of extensions on browser performance: An empirical study on google chrome. Empirical Software Engineering, 30(3), 41 pages. Lien externe
Jin, B., Li, H., Nie, P., & Zou, Y. (avril 2026). Energy-Efficient Software Development: A Multi-dimensional Empirical Analysis of Stack Overflow . Dans IEEE/ACM International Conference on Software Engineering (ICSE 2026), Rio de Janeiro, Brazil. Lien externe
Liao, L., Eismann, S., Li, H., Bezemer, C.-P., Costa, D. E., van Hoorn, A., & Shang, W. (avril 2025). Early Detection of Performance Regressions by Bridging Local Performance Data and Architectural Models [Communication écrite]. 47th International Conference on Software Engineering (ICSE 2025), Ottawa, ON, Canada. Lien externe
Liu, Y., Foundjem, A. T., Khomh, F., & Li, H. (2025). Adversarial attack classification and robustness testing for large language models for code. Empirical Software Engineering, 30(5). Lien externe
Ma, N., & Li, H. (2025). Understanding and Estimating the Execution Time of Quantum Circuits. ACM Transactions on Software Engineering and Methodology. Lien externe
Majidi, F., Khomh, F., Li, H., & Nikanjam, A. (2025). An efficient model maintenance approach for MLOps. Empirical Software Engineering, 31(1), 48 pages. Lien externe
Njoku, A. O., Li, H., & Khomh, F. (mai 2025). Kernel-Level Event-Based Performance Anomaly Detection in Software Systems under Varying Load Conditions [Communication écrite]. 16th International Conference on Performance Engineering (ICPE 2025), Toronto, ON, Canada. Lien externe
Noei, S., Li, H., & Zhou, Y. (2025). An empirical study on release-wise refactoring patterns. [Autre type de communication de conférence]. Proceedings of the ACM on Software Engineering, 2(FSE), 403-424. Présentée à ACM SIGSOFT International Conference on Software Testing and Analysis (ISSTA), Trondheim, Norway. Disponible
Qin, Q., Aghili, R., Li, H., & Merlo, E. (mars 2025). Preprocessing is All You Need: Boosting the Performance of Log Parsers with a General Preprocessing Framework [Communication écrite]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2025), Montreal, QC, Canada. Lien externe
Qin, Q., Djian, B. P. P., Merlo, E., Li, H., & Gambs, S. (2025). Representation-based fairness evaluation and bias correction robustness assessment in neural networks. Information and Software Technology, 107876 (21 pages). Lien externe
Qin, Q., Li, H., Merlo, E., & Lamothe, M. (2025). Automated, Unsupervised, and Auto-parameterized Inference of Data Patterns and Anomaly Detection [Ensemble de données]. Lien externe
Qin, Q., Li, H., Merlo, E., & Lamothe, M. (avril 2025). Automated, Unsupervised, and Auto-Parameterized Inference of Data Patterns and Anomaly Detection [Communication écrite]. 47th International Conference on Software Engineering (ICSE 2025), Ottawa, ON, Canada. Lien externe
Shahedi, K., Lamothe, M., Khomh, F., & Li, H. (avril 2025). JPerfEvo: A Tool for Tracking Method-Level Performance Changes in Java Projects [Communication écrite]. 22nd International Conference on Mining Software Repositories (MSR 2025), Ottawa, ON, Canada. Lien externe
Shahedi, K., Li, H., Lamothe, M., & Khomh, F. (2025). Tracing Optimization for Performance Modeling and Regression Detection. ACM Transactions on Software Engineering and Methodology. Lien externe
Wu, X., Li, H., & Khomh, F. (2025). What information contributes to log-based anomaly detection? Insights from a configurable transformer-based approach. Automated Software Engineering, 32(2), 29 pages. Lien externe
