| A systematic literature review of android malware detection using static analysis Y Pan, X Ge, C Fang, Y Fan IEEE Access 8, 116363-116379, 2020 | 187 | 2020 |
| AMDroid: android malware detection using function call graphs X Ge, Y Pan, Y Fan, C Fang 2019 IEEE 19th International Conference on Software Quality, Reliability and …, 2019 | 28 | 2019 |
| An empirical study of class rebalancing methods for actionable warning identification X Ge, C Fang, T Bai, J Liu, Z Zhao IEEE Transactions on Reliability 72 (4), 1648-1662, 2023 | 10 | 2023 |
| Impact of datasets on machine learning based methods in android malware detection: an empirical study X Ge, Y Huang, Z Hui, X Wang, X Cao 2021 IEEE 21st International Conference on Software Quality, Reliability and …, 2021 | 10 | 2021 |
| Leveraging android automated testing to assist crowdsourced testing X Ge, S Yu, C Fang, Q Zhu, Z Zhao IEEE Transactions on Software Engineering 49 (4), 2318-2336, 2022 | 8 | 2022 |
| A survey of source code search: A 3-dimensional perspective W Sun, C Fang, Y Ge, Y Hu, Y Chen, Q Zhang, X Ge, Y Liu, Z Chen ACM Transactions on Software Engineering and Methodology 33 (6), 1-51, 2024 | 6 | 2024 |
| An unsupervised feature selection approach for actionable warning identification X Ge, C Fang, J Liu, M Qing, X Li, Z Zhao Expert Systems with Applications 227, 120152, 2023 | 6 | 2023 |
| Machine learning for actionable warning identification: A comprehensive survey X Ge, C Fang, X Li, W Sun, D Wu, J Zhai, SW Lin, Z Zhao, Y Liu, Z Chen ACM Computing Surveys 57 (2), 1-35, 2024 | 5 | 2024 |
| Locality-based security bug report identification via active learning X Ge, C Fang, M Qian, Y Ge, M Qing Information and Software Technology 147, 106899, 2022 | 5 | 2022 |
| An empirical study on spectral clustering-based software defect detection M Qing, X Ge, ZW Hui, Y Pan, Y Fan, X Wang, X Cao 2021 8th International Conference on Dependable Systems and Their …, 2021 | 5 | 2021 |
| Semantic-based false alarm detection approach via machine learning M Qian, J Luo, Y Ge, C Sun, X Ge, W Huang 2021 IEEE 21st International Conference on Software Quality, Reliability and …, 2021 | 3 | 2021 |
| Pre-trained Model-based Actionable Warning Identification: A Feasibility Study X Ge, C Fang, Q Zhang, D Wu, B Yu, Q Zheng, A Guo, S Lin, Z Zhao, Y Liu, ... arXiv preprint arXiv:2403.02716, 2024 | 2 | 2024 |
| A machine learning-based static analysis warning prioritization M Qing, X Feng, J Luo, W Huang, J Zhang, P Wang, Y Fan, X Ge, Y Pan 2021 IEEE 21st International Conference on Software Quality, Reliability and …, 2021 | 2 | 2021 |
| A Large-Scale Empirical Study of Actionable Warning Distribution within Projects X Ge, C Fang, X Li, Q Zheng, J Liu, Z Zhao, Z Chen IEEE Transactions on Dependable and Secure Computing, 2024 | 1 | 2024 |
| Test case classification via few-shot learning Y Zhao, S Liu, Q Zhang, X Ge, J Liu Information and Software Technology 160, 107228, 2023 | 1 | 2023 |
| Static Code Analyzer Recommendation via Preference Mining X Ge, C Fang, X Li, Y Shang, M Zhang, Y Pan arXiv preprint arXiv:2412.18393, 2024 | | 2024 |
| CooTest: An Automated Testing Approach for V2X Communication Systems A Guo, X Gao, Z Chen, Y Xiao, J Liu, X Ge, W Sun, C Fang Proceedings of the 33rd ACM SIGSOFT International Symposium on Software …, 2024 | | 2024 |
| Pattern Mining-based Warning Prioritization by Refining Abstract Syntax Tree X Ge, X Li, Y Sun, M Qing, H Zheng, H Zhang, X Wu International Journal of Software Engineering and Knowledge Engineering, 2024 | | 2024 |
| Improving actionable warning identification via the refined warning-inducing context representation X Ge, C Fang, X Li, Q Zhang, J Liu, Z Zhao, Z Chen Science China Information Sciences 67 (5), 1-2, 2024 | | 2024 |
| Reducing Label Errors for Actionable Warning Identification H Chen, X Chen, X Sun, Q Zheng, X Ge 2023 IEEE 23rd International Conference on Software Quality, Reliability …, 2023 | | 2023 |
