| Effort-aware just-in-time defect prediction: simple unsupervised models could be better than supervised models Y Yang, Y Zhou, J Liu, Y Zhao, H Lu, L Xu, B Xu, H Leung Proceedings of the 2016 24th ACM SIGSOFT international symposium on …, 2016 | 285 | 2016 |
| How far we have progressed in the journey? an examination of cross-project defect prediction Y Zhou, Y Yang, H Lu, L Chen, Y Li, Y Zhao, J Qian, B Xu ACM Transactions on Software Engineering and Methodology (TOSEM) 27 (1), 1-51, 2018 | 202 | 2018 |
| Code churn: A neglected metric in effort-aware just-in-time defect prediction J Liu, Y Zhou, Y Yang, H Lu, B Xu 2017 ACM/IEEE International Symposium on Empirical Software Engineering and …, 2017 | 82 | 2017 |
| Are Slice-Based Cohesion Metrics Actually Useful in Effort-Aware Post-Release Fault-Proneness Prediction? An Empirical Study Y Yang, Y Zhou, H Lu, L Chen, Z Chen, B Xu, H Leung, Z Zhang IEEE Transactions on Software Engineering 41 (4), 331-357, 2015 | 81 | 2015 |
| Empirical analysis of network measures for effort-aware fault-proneness prediction W Ma, L Chen, Y Yang, Y Zhou, B Xu Information and Software Technology 69, 50-70, 2016 | 72 | 2016 |
| An empirical study on dependence clusters for effort-aware fault-proneness prediction Y Yang, M Harman, J Krinke, S Islam, D Binkley, Y Zhou, B Xu Proceedings of the 31st IEEE/ACM International Conference on Automated …, 2016 | 42 | 2016 |
| Predicting vulnerable components via text mining or software metrics? An effort-aware perspective Y Tang, F Zhao, Y Yang, H Lu, Y Zhou, B Xu 2015 IEEE International Conference on Software Quality, Reliability and …, 2015 | 41 | 2015 |
| Hunting for bugs in code coverage tools via randomized differential testing Y Yang, Y Zhou, H Sun, Z Su, Z Zuo, L Xu, B Xu Proceedings of the 41st International Conference on Software Engineering …, 2019 | 36 | 2019 |
| Source code size estimation approaches for object-oriented systems from UML class diagrams: A comparative study Y Zhou, Y Yang, B Xu, H Leung, X Zhou Information and Software Technology 56 (2), 220-237, 2014 | 36 | 2014 |
| An empirical analysis of package-modularization metrics: Implications for software fault-proneness Y Zhao, Y Yang, H Lu, Y Zhou, Q Song, B Xu Information and Software Technology 57, 186-203, 2015 | 32 | 2015 |
| Towards an understanding of change types in bug fixing code Y Zhao, H Leung, Y Yang, Y Zhou, B Xu Information and software technology 86, 37-53, 2017 | 30 | 2017 |
| Understanding the value of considering client usage context in package cohesion for fault-proneness prediction Y Zhao, Y Yang, H Lu, J Liu, H Leung, Y Wu, Y Zhou, B Xu Automated Software Engineering 24, 393-453, 2017 | 28 | 2017 |
| The influence of developer quality on software fault-proneness prediction Y Wu, Y Yang, Y Zhao, H Lu, Y Zhou, B Xu 2014 eighth international conference on software security and reliability …, 2014 | 25 | 2014 |
| SMT solver validation empowered by large pre-trained language models M Sun, Y Yang, Y Wang, M Wen, H Jia, Y Zhou 2023 38th IEEE/ACM International Conference on Automated Software …, 2023 | 19 | 2023 |
| Is learning-to-rank cost-effective in recommending relevant files for bug localization? F Zhao, Y Tang, Y Yang, H Lu, Y Zhou, B Xu 2015 IEEE International Conference on Software Quality, Reliability and …, 2015 | 18 | 2015 |
| CBUA: A probabilistic, predictive, and practical approach for evaluating test suite effectiveness P Zhang, Y Li, W Ma, Y Yang, L Chen, H Lu, Y Zhou, B Xu IEEE Transactions on Software Engineering 48 (3), 1067-1096, 2020 | 16 | 2020 |
| Mitigating false positive static analysis warnings: Progress, challenges, and opportunities Z Guo, T Tan, S Liu, X Liu, W Lai, Y Yang, Y Li, L Chen, W Dong, Y Zhou IEEE Transactions on Software Engineering, 2023 | 14 | 2023 |
| Deep learning-based software engineering: progress, challenges, and opportunities X Chen, X Hu, Y Huang, H Jiang, W Ji, Y Jiang, Y Jiang, B Liu, H Liu, X Li, ... Science China Information Sciences 68 (1), 1-88, 2025 | 12 | 2025 |
| Automatic Self-Validation for Code Coverage Profilers Y Yang, Y Jiang, Z Zuo, Y Wang, H Sun, H Lu, Y Zhou, B Xu Proceedings of the 34th International Conference on Automated Software …, 2019 | 12 | 2019 |
| Isolating compiler optimization faults via differentiating finer-grained options J Yang, Y Yang, M Sun, M Wen, Y Zhou, H Jin 2022 IEEE International Conference on Software Analysis, Evolution and …, 2022 | 9 | 2022 |
Baowen XuNanjing Universitynju.edu.cn의 이메일 확인됨