| Where shall we log? studying and suggesting logging locations in code blocks Z Li, TH Chen, W Shang Proceedings of the 35th IEEE/ACM International Conference on Automated …, 2020 | 65 | 2020 |
| DLFinder: characterizing and detecting duplicate logging code smells Z Li, TH Chen, J Yang, W Shang 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE …, 2019 | 63 | 2019 |
| Deeplv: Suggesting log levels using ordinal based neural networks Z Li, H Li, TH Chen, W Shang 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE …, 2021 | 45 | 2021 |
| Did We Miss Something Important? Studying and Exploring Variable-Aware Log Abstraction Z Li, C Luo, TH Chen, W Shang, S He, Q Lin, D Zhang 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2023 | 38 | 2023 |
| Studying duplicate logging statements and their relationships with code clones Z Li, TH Chen, J Yang, W Shang IEEE Transactions on Software Engineering, 2021 | 25 | 2021 |
| Code Search Is All You Need? Improving Code Suggestions with Code Search J Chen, X Hu, Z Li, C Gao, X Xia, D Lo Proceedings of the 46th IEEE/ACM International Conference on Software …, 2024 | 21 | 2024 |
| Thinkrepair: Self-directed automated program repair X Yin, C Ni, S Wang, Z Li, L Zeng, X Yang Proceedings of the 33rd ACM SIGSOFT International Symposium on Software …, 2024 | 16 | 2024 |
| Deep Learning Based Code Generation Methods: Literature Review Z Yang, S Chen, C Gao, Z Li, G Li, M Lyu arXiv preprint arXiv:2303.01056, 2023 | 16 | 2023 |
| Towards providing automated supports to developers on writing logging statements Z Li Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 13 | 2020 |
| Are They All Good? Studying Practitioners' Expectations on the Readability of Log Messages Z Li, AR Chen, X Hu, X Xia, TH Chen, W Shang Proceedings of the 38th IEEE/ACM International Conference on Automated …, 2023 | 12 | 2023 |
| Characterizing and detecting duplicate logging code smells Z Li 2019 IEEE/ACM 41st International Conference on Software Engineering …, 2019 | 11 | 2019 |
| Reasoning runtime behavior of a program with llm: How far are we? J Chen, Z Pan, X Hu, Z Li, G Li, X Xia arXiv preprint arXiv:2403.16437, 2024 | 10* | 2024 |
| A survey on modern code review: Progresses, challenges and opportunities Z Yang, C Gao, Z Guo, Z Li, K Liu, X Xia, Y Zhou arXiv preprint arXiv:2405.18216, 2024 | 7 | 2024 |
| Towards effectively detecting and explaining vulnerabilities using large language models Q Mao, Z Li, X Hu, K Liu, X Xia, J Sun arXiv preprint arXiv:2406.09701, 2024 | 6 | 2024 |
| Studying and suggesting logging locations in code blocks Z Li Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 6 | 2020 |
| Nlperturbator: Studying the robustness of code llms to natural language variations J Chen, Z Li, X Hu, X Xia arXiv preprint arXiv:2406.19783, 2024 | 3 | 2024 |
| Discovery of Timeline and Crowd Reaction of Software Vulnerability Disclosures YW Heng, Z Ma, H Zhang, Z Li, THP Chen arXiv e-prints, arXiv: 2411.07480, 2024 | 1 | 2024 |
| An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities Z Yang, S Chen, C Gao, Z Li, X Hu, K Liu, X Xia ACM Transactions on Software Engineering and Methodology, 2025 | | 2025 |
| Studying and Benchmarking Large Language Models For Log Level Suggestion YW Heng, Z Ma, Z Li, DJ Kim, THP Chen arXiv preprint arXiv:2410.08499, 2024 | | 2024 |
| Studying Practitioners' Expectations on Clear Code Review Comments Z Li, J Chen, Q Mao, X Hu, K Liu, X Xia arXiv preprint arXiv:2410.06515, 2024 | | 2024 |