| Exploiting the unique expression for improved sentiment analysis in software engineering text K Sun, H Gao, H Kuang, X Ma, G Rong, D Shao, H Zhang 2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC …, 2021 | 14 | 2021 |
| Using frugal user feedback with closeness analysis on code to improve IR-based traceability recovery H Kuang, H Gao, H Hu, X Ma, J Lü, P Mäder, A Egyed 2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC …, 2019 | 14 | 2019 |
| Using consensual biterms from text structures of requirements and code to improve IR-based traceability recovery H Gao, H Kuang, K Sun, X Ma, A Egyed, P Mäder, G Rong, D Shao, ... Proceedings of the 37th IEEE/ACM International Conference on Automated …, 2022 | 8 | 2022 |
| Propagating frugal user feedback through closeness of code dependencies to improve IR-based traceability recovery H Gao, H Kuang, X Ma, H Hu, J Lü, P Mäder, A Egyed Empirical Software Engineering 27 (2), 41, 2022 | 7 | 2022 |
| Incorporating pre-trained transformer models into TextCNN for sentiment analysis on software engineering texts K Sun, X Shi, H Gao, H Kuang, X Ma, G Rong, D Shao, Z Zhao, H Zhang Proceedings of the 13th Asia-Pacific Symposium on Internetware, 127-136, 2022 | 2 | 2022 |
| TRIAD: Automated Traceability Recovery based on Biterm-enhanced Deduction of Transitive Links among Artifacts H Gao, H Kuang, WKG Assunção, C Mayr-Dorn, G Rong, H Zhang, X Ma, ... ICSE '24: Proceedings of the IEEE/ACM 46th International Conference on …, 2024 | | 2024 |
Xiaoxing MaProfessor of Computer Science and Technology, Nanjing University在 nju.edu.cn 的电子邮件经过验证
