Directory of Experts

Li, Heng

Directory of Experts

Li, Heng

Directory of Experts

Publications by date

Journal article (32) Conference paper (17) Book Book chapter Patent Report Thesis (1) Dataset (5) Teaching resource Image Audio recording Video recording Other

Heng Li (55)

2025 (3)
- Noei, S., Li, H., & Zhou, Y. (2025, June). An Empirical Study on Release-Wise Refactoring Patterns [Paper]. ACM International Conference on the Foundations of Software Engineering (FSE 2025), Trondheim, Norway (21 pages). Published in Proceedings of the ACM on Software Engineering, 2(FSE).
- Qin, Q., Li, H., Merlo, E., & Lamothe, M. (2025). Automated, Unsupervised, and Auto-parameterized Inference of Data Patterns and Anomaly Detection [Dataset].
- Aghili, R., Li, H., & Khomh, F. (2025, June). Protecting Privacy in Software Logs: What Should Be Anonymized? [Paper]. ACM International Conference on the Foundations of Software Engineering (FSE 2025), Trondheim, Norway. Published in Proceedings of the ACM on Software Engineering, 2(FSE).
2024 (11)
- 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).
- 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).
- 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.
- 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).
- 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, -.
- 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).
- Wu, X., Li, H., Yoshioka, N., Washizaki, H., & Khomh, F. (2024, March). Refining GPT-3 Embeddings with a Siamese Structure for Technical Post Duplicate Detection [Paper]. 31st IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2024), Rovaniemi, Finland.
- Foalem, P. L., Khomh, F., & Li, H. (2024). Studying logging practice in machine learning-based applications. Information and Software Technology, 170, 107450 (17 pages).
- Aghili, R., Qin, Q., Li, H., & Khomh, F. (2024, October). Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization [Paper]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2024), Flagstaff, AZ, USA.
- 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).
- Traini, L., & Li, H. (2024, May). Workshop on Challenges in Performance Methods for Software Development (WOSP-C) [Abstract]. 15th ACM/SPEC International Conference on Performance Engineering, London, United Kingdom.
2023 (11)
- 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).
- 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.
- Yahmed, A. H., Allah Abbassi, A., Nikanjam, A., Li, H., & Khomh, F. (2023, October). Deploying deep reinforcement learning systems: a taxonomy of challenges [Paper]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2023), Bogota, Colombia.
- 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).
- Zishuo, D., Yiming, T., Yang, L., Li, H., & Weiyi, S. (2023, May). On the Temporal Relations between Logging and Code [Paper]. 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE 2023), Melbourne, Australia.
- Dai, H., Tang, Y., Li, H., & Shang, W. PILAR: Studying and Mitigating the Influence of Configurations on Log Parsing [Paper]. 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE 2023), Melbourne, Australia.
- Yousefifeshki, F., Li, H., & Khomh, F. (2023). Studying the challenges of developing hardware description language programs. Information and Software Technology, 159, 16 pages.
- Aghili, R., Li, H., & Khomh, F. (2023). Studying the characteristics of AIOps projects on GitHub. Empirical Software Engineering, 28(6), 143 (49 pages).
- Wu, X., Li, H., & Khomh, F. (2023). Supplimental Materials - Truncated Spirit and Thunderbird datasets [Dataset].
- 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.
- Ghadesi, A., Li, H., & Lamothe, M. (2023). What Causes Exceptions in Machine Learning Applications? Mining Machine Learning-Related Stack Traces on Stack Overflow [Dataset].
2022 (10)
- 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.
- Majidi, F., Openja, M., Khomh, F., & Li, H. (2022, October). An Empirical Study on the Usage of Automated Machine Learning Tools [Paper]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2022), Limassol, Cyprus.
- 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.
- 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.
- 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.
- 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.
- Ding, Z., Li, H., & Shang, W. (2022, March). LoGenText: Automatically generating logging texts using neural machine translation [Paper]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022), Honolulu, HI, USA.
- Hassan, S., Li, H., & Hassan, A. E. (2022, March). On the importance of performing app analysis within peer groups [Paper]. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022), Honolulu, HI, USA.
- 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).
- Openja, M., Majidi, F., Khomh, F., Chembakottu, B., & Li, H. (2022, June). Studying the Practices of Deploying Machine Learning Projects on Docker [Paper]. 26th ACM International Conference on Evaluation and Assessment in Software Engineering (EASE 2022), Gothenburg, Sweden.
2021 (9)
- 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.
- Gujral, H., Lal, S., & Li, H. (2021). An exploratory semantic analysis of logging questions. Journal of Software: Evolution and Process, 33(7), 35 pages.
- 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.
- Li, Z., Li, H., Chen, T.-H. P., & Shang, W. (2021, May). DeepLV: Suggesting log levels using ordinal based neural networks [Paper]. 43rd International Conference on Software Engineering (ICSE 2021) (12 pages).
- 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.
- 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 [Dataset].
- 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.
- Liao, L., Chen, J., Li, H., Zeng, Y., Shang, W., Sporea, C., Toma, A., & Sajedi, S. (2021). TSE2021 Replication Package [Dataset].
- El aoun, M. R., Li, H., Khomh, F., & Openja, M. (2021, September). Understanding Quantum Software Engineering Challenges An Empirical Study on Stack Exchange Forums and GitHub Issues [Paper]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2021), Luxembourg, Netherlands.
2020 (4)
- 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.
- 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.
- 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.
- 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.
2019 (1)
- Shariff, S. M., Li, H., Bezemer, C.-P., Hassan, A. E., Nguyen, T. H. D., & Flora, P. (2019, May). Improving the testing efficiency of selenium-based load tests [Paper]. 14th IEEE/ACM International Workshop on Automation of Software Test (AST 2019), Montréal, Québec.
2018 (4)
- Li, H., Chen, T.-H. P., Hassan, A. E., Nasser, M., & Flora, P. (2018, May). Adopting Autonomic Computing Capabilities in Existing Large-Scale Systems: An Industrial Experience Report [Paper]. 40th International Conference on Software Engineering (ICSE-SEIP 2018), Gothenburg, Sweden (10 pages).
- Li, H. (2018). Mining development knowledge to understand and support software logging practices [Ph.D. Thesis].
- Li, H., & Zhang, Z. (2018, September). Predicting the receivers of football passes [Paper]. Machine Learning and Data Mining for Sports Analytics (MLSA 2018), Dublin, Ireland.
- 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.
2017 (2)
- 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.
- 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.

Directory of Experts

Li, Heng

Directory of Experts

Li, Heng

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Publications by date

Heng Li (55)