Documents dont l'auteur est "Li, Heng"

Heng LiDépartement de génie informatique et génie logicielVoir sa fiche dans le Répertoire des Expertises de Polytechnique Montréal

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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

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

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

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

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

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

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

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

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

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

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

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., 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

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

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

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

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

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

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

Noei, S., Li, H., & Zou, Y. (2024). Detecting Refactoring Commits in Machine Learning Python Projects: A Machine Learning-Based Approach. ACM Transactions on Software Engineering and Methodology, 24 pages. Lien externe

Lyu, Y., Li, H., Jiang, Z. M., & Hassan, A. E. (2024). On the Model Update Strategies for Supervised Learning in AIOps Solutions. ACM Transactions on Software Engineering and Methodology, -. Lien externe

Traini, L., & Li, H. (mai 2024). Workshop on Challenges in Performance Methods for Software Development (WOSP-C) [Résumé]. 15th ACM/SPEC International Conference on Performance Engineering, London, United Kingdom. Lien externe

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

Batoun, M. A., Sayagh, M., Aghili, R., Ouni, A., & Li, H. (2024). A literature review and existing challenges on software logging practices: From the creation to the analysis of software logs. Empirical Software Engineering, 29, 103 (61 pages). Lien externe

Ding, Z., Tang, Y., Cheng, X., Li, H., & Shang, W. (2024). LoGenText-Plus : Improving Neural Machine Translation Based Logging Texts Generation with Syntactic Templates. ACM Transactions on Software Engineering and Methodology, 33(2), 38 (45 pages). Lien externe

Xia, Y., Liao, L., Chen, J., Li, H., & Shang, W. (2024). Reducing the Length of Field-replay Based Load Testing. IEEE Transactions on Software Engineering, 3408079 (17 pages). Lien externe

Wu, X., Li, H., Yoshioka, N., Washizaki, H., & Khomh, F. (mars 2024). Refining GPT-3 Embeddings with a Siamese Structure for Technical Post Duplicate Detection [Communication écrite]. 31st IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2024), Rovaniemi, Finland. Lien externe

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

Aghili, R., Qin, Q., Li, H., & Khomh, F. (octobre 2024). Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2024), Flagstaff, AZ, USA. Lien externe

Ghadesi, A., Lamothe, M., & Li, H. (2024). What causes exceptions in machine learning applications? Mining machine learning-related stack traces on Stack Overflow. Empirical Software Engineering, 29, 107 (37 pages). Lien externe

Wu, X., Li, H., & Khomh, F. (2023). Supplimental Materials - Truncated Spirit and Thunderbird datasets [Ensemble de données]. Lien externe

Ghadesi, A., Li, H., & Lamothe, M. (2023). What Causes Exceptions in Machine Learning Applications? Mining Machine Learning-Related Stack Traces on Stack Overflow [Ensemble de données]. Lien externe

Liao, L., Li, H., Shang, W., Sporea, C., Toma, A., & Sajedi, S. (décembre 2023). Adapting Performance Analytic Techniques in a Real-World Database-Centric System: An Industrial Experience Report [Communication écrite]. 31st ACM Joint Meeting of the European Software Engineering Conference / Symposium on the Foundations-of-Software-Engineering (ESEC/FSE), San Francisco, CA San Francisco, CA. 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

Noei, S., Li, H., Georgiou, S., & Zou, Y. (2023). An Empirical Study of Refactoring Rhythms and Tactics in the Software Development Process. IEEE Transactions on Software Engineering, 49(12), 5103-5119. Lien externe

Chen, J., Ding, Z., Tang, Y., Sayagh, M., Li, H., Adams, B., & Shang, W. (décembre 2023). IoPV : on inconsistent option performance variations [Communication écrite]. 2023 ESEC/FSE Conferences, San Francisco, CA, USA (13 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

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

Zishuo, D., Yiming, T., Yang, L., Li, H., & Weiyi, S. (mai 2023). On the Temporal Relations between Logging and Code [Communication écrite]. 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE 2023), Melbourne, Australia. Lien externe

Dai, H., Tang, Y., Li, H., & Shang, W. PILAR: Studying and Mitigating the Influence of Configurations on Log Parsing [Communication écrite]. 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE 2023), Melbourne, Australia. 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

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

Ding, Z., Li, H., Shang, W., & Chen, T.-H. P. (2023). Towards Learning Generalizable Code Embeddings Using Task-agnostic Graph Convolutional Networks. ACM Transactions on Software Engineering and Methodology, 32(2), 1-43. Lien externe

Zhang, H., Wang, S., Li, H., Chen, T.-H. P., & Hassan, A. E. (2022). A study of C/C++ code weaknesses on stack overflow. IEEE Transactions on Software Engineering, 48(7), 2359-2375. Lien externe

Lamothe, M., Li, H., & Shang, W. (2022). Assisting Example-based API Misuse Detection via Complementary Artificial Examples. IEEE Transactions on Software Engineering, 48(9), 3410-3422. Lien externe

Ding, Z., Li, H., Shang, W., & Chen, T.-H. P. (2022). Can pre-trained code embeddings improve model performance? Revisiting the use of code embeddings in software engineering tasks. Empirical Software Engineering, 27(3), 38 pages. Lien externe

Liao, L., Li, H., Shang, W., & Ma, L. (2022). An Empirical Study of the Impact of Hyperparameter Tuning and Model Optimization on the Performance Properties of Deep Neural Networks. ACM Transactions on Software Engineering and Methodology, 31(3), 1-40. Lien externe

Majidi, F., Openja, M., Khomh, F., & Li, H. (octobre 2022). An Empirical Study on the Usage of Automated Machine Learning Tools [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2022), Limassol, Cyprus. Lien externe

Locke, S., Li, H., Chen, T.-H., Shang, W., & Liu, W. (2022). LogAssist: Assisting Log Analysis Through Log Summarization. IEEE Transactions on Software Engineering, 48(9), 3227-3241. Lien externe

Ding, Z., Li, H., & Shang, W. (mars 2022). LoGenText: Automatically generating logging texts using neural machine translation [Communication écrite]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022), Honolulu, HI, USA. Lien externe

Hassan, S., Li, H., & Hassan, A. E. (mars 2022). On the importance of performing app analysis within peer groups [Communication écrite]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022), Honolulu, HI, USA. Lien externe

Zhang, H., Tang, Y., Lamothe, M., Li, H., & Shang, W. (2022). Studying logging practice in test code. Empirical Software Engineering, 27(4), 83 (45 pages). Lien externe

Openja, M., Majidi, F., Khomh, F., Chembakottu, B., & Li, H. (juin 2022). Studying the Practices of Deploying Machine Learning Projects on Docker [Communication écrite]. 26th ACM International Conference on Evaluation and Assessment in Software Engineering (EASE 2022), Gothenburg, Sweden. Lien externe

Liao, L., Chen, J., Li, H., Zeng, Y., Shang, W., Sporea, C., Toma, A., & Sajedi, S. (2021). Replication package - Locating Performance Regression Root Causes in the Field for Web-based Systems [Ensemble de données]. Lien externe

Li, Z., Li, H., Chen, T.-H. P., & Shang, W. (mai 2021). DeepLV: Suggesting log levels using ordinal based neural networks [Communication écrite]. 43rd International Conference on Software Engineering (ICSE 2021) (12 pages). Lien externe

Lyu, Y., Li, H., Sayagh, M., Jiang, Z. M., & Hassan, A. E. (2021). An empirical study of the impact of data splitting decisions on the performance of AiOps solutions. ACM Transactions on Software Engineering and Methodology, 30(4), 1-38. Lien externe

Gujral, H., Lal, S., & Li, H. (2021). An exploratory semantic analysis of logging questions. Journal of Software: Evolution and Process, 33(7), 35 pages. Lien externe

Liao, L., Chen, J., Li, H., Zeng, Y., Shang, W., Sporea, C., Toma, A., & Sajedi, S. (2021). Locating Performance Regression Root Causes in the Field Operations of Web-based Systems: An Experience Report. IEEE Transactions on Software Engineering, 22 pages. Lien externe

Li, H., Shang, W., Adams, B., Sayagh, M., & Hassan, A. E. (2021). A qualitative study of the benefits and costs of logging from developers' perspectives. IEEE Transactions on Software Engineering, 47(12), 2858-2873. Lien externe

Li, H., Zhang, H., Wang, S., & Hassan, A. E. (2021). Studying the Practices of Logging Exception Stack Traces in Open-Source Software Projects. IEEE Transactions on Software Engineering, 19 pages. Lien externe

Liao, L., Chen, J., Li, H., Zeng, Y., Shang, W., Sporea, C., Toma, A., & Sajedi, S. (2021). TSE2021 Replication Package [Ensemble de données]. Lien externe

El aoun, M. R., Li, H., Khomh, F., & Openja, M. (septembre 2021). Understanding Quantum Software Engineering Challenges An Empirical Study on Stack Exchange Forums and GitHub Issues [Communication écrite]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2021), Luxembourg, Netherlands. Lien externe

Dai, H., Li, H., Chen, C.-S., Shang, W., & Chen, T.-H. (2020). Logram: Efficient log parsing using n-gram dictionaries. IEEE Transactions on Software Engineering, 14 pages. Lien externe

Li, Y., Jiang, Z. M., Li, H., Hassan, A. E., He, C., Huang, R., Zeng, Z., Wang, M., & Chen, P. (2020). Predicting node failures in an ultra-large-scale cloud computing platform: An AIOps solution. ACM Transactions on Software Engineering and Methodology, 29(2), 13:1-13:24-13:1-13:24. Lien externe

Yao, K., Li, H., Shang, W., & Hassan, A. E. (2020). A study of the performance of general compressors on log files. Empirical Software Engineering, 25(5), 3043-3085. Lien externe

Liao, L., Chen, J., Li, H., Zeng, Y., Shang, W., Guo, J., Sporea, C., Toma, A., & Sajedi, S. (2020). Using black-box performance models to detect performance regressions under varying workloads: an empirical study. Empirical Software Engineering, 25(5), 4130-4160. Lien externe

Shariff, S. M., Li, H., Bezemer, C.-P., Hassan, A. E., Nguyen, T. H. D., & Flora, P. (mai 2019). Improving the testing efficiency of selenium-based load tests [Communication écrite]. 14th IEEE/ACM International Workshop on Automation of Software Test (AST 2019), Montréal, Québec. Lien externe

Li, H., Chen, T.-H. P., Hassan, A. E., Nasser, M., & Flora, P. (mai 2018). Adopting Autonomic Computing Capabilities in Existing Large-Scale Systems: An Industrial Experience Report [Communication écrite]. 40th International Conference on Software Engineering (ICSE-SEIP 2018), Gothenburg, Sweden (10 pages). Lien externe

Li, H. (2018). Mining development knowledge to understand and support software logging practices [Thèse de doctorat]. Lien externe

Li, H., & Zhang, Z. (septembre 2018). Predicting the receivers of football passes [Communication écrite]. Machine Learning and Data Mining for Sports Analytics (MLSA 2018), Dublin, Ireland. Lien externe

Li, H., Chen, T.-H. P., Shang, W., & Hassan, A. E. (2018). Studying software logging using topic models. Empirical Software Engineering, 23(5), 2655-2694. Lien externe

Li, H., Shang, W., Zou, Y., & Hassan, A. E. (2017). Towards just-in-time suggestions for log changes. Empirical Software Engineering, 22(4), 1831-1865. Lien externe

Li, H., Shang, W., & Hassan, A. E. (2017). Which log level should developers choose for a new logging statement? Empirical Software Engineering, 22(4), 1684-1716. Lien externe