MULTI: Multi-objective effort-aware just-in-time software defect prediction X Chen, Y Zhao, Q Wang, Z Yuan Information and Software Technology 93, 1-13, 2018 | 140 | 2018 |
Variable strength interaction testing with an ant colony system approach X Chen, Q Gu, A Li, D Chen 2009 16th Asia-Pacific Software Engineering Conference, 160-167, 2009 | 119 | 2009 |
Improving defect prediction with deep forest T Zhou, X Sun, X Xia, B Li, X Chen Information and Software Technology 114, 204-216, 2019 | 117 | 2019 |
Improving high-impact bug report prediction with combination of interactive machine learning and active learning X Wu, W Zheng, X Chen, Y Zhao, T Yu, D Mu Information and Software Technology 133, 106530, 2021 | 106 | 2021 |
An empirical study on pareto based multi-objective feature selection for software defect prediction C Ni, X Chen, F Wu, Y Shen, Q Gu Journal of Systems and Software 152, 215-238, 2019 | 105 | 2019 |
Empirical studies of a two-stage data preprocessing approach for software fault prediction W Liu, S Liu, Q Gu, J Chen, X Chen, D Chen IEEE Transactions on Reliability 65 (1), 38-53, 2015 | 102 | 2015 |
Software defect number prediction: Unsupervised vs supervised methods X Chen, D Zhang, Y Zhao, Z Cui, C Ni Information and Software Technology 106, 161-181, 2019 | 99 | 2019 |
Applying particle swarm optimization to pairwise testing X Chen, Q Gu, J Qi, D Chen 2010 IEEE 34th Annual Computer Software and Applications Conference, 107-116, 2010 | 95 | 2010 |
A cluster based feature selection method for cross-project software defect prediction C Ni, WS Liu, X Chen, Q Gu, DX Chen, QG Huang Journal of Computer Science and Technology 32, 1090-1107, 2017 | 91 | 2017 |
FECAR: A feature selection framework for software defect prediction S Liu, X Chen, W Liu, J Chen, Q Gu, D Chen 2014 IEEE 38th annual computer software and applications conference, 426-435, 2014 | 91 | 2014 |
HSFal: Effective fault localization using hybrid spectrum of full slices and execution slices X Ju, S Jiang, X Chen, X Wang, Y Zhang, H Cao Journal of Systems and Software 90, 3-17, 2014 | 82 | 2014 |
A comparative study of class rebalancing methods for security bug report classification W Zheng, Y Xun, X Wu, Z Deng, X Chen, Y Sui IEEE Transactions on Reliability 70 (4), 1658-1670, 2021 | 80 | 2021 |
Survey of static software defect prediction 陈翔, 顾庆, 刘望舒, 刘树龙, 倪超 Journal of Software 27 (1), 1-25, 2015 | 79 | 2015 |
A comprehensive study of deep learning compiler bugs Q Shen, H Ma, J Chen, Y Tian, SC Cheung, X Chen Proceedings of the 29th ACM Joint meeting on european software engineering …, 2021 | 76 | 2021 |
Revisiting supervised and unsupervised methods for effort-aware cross-project defect prediction C Ni, X Xia, D Lo, X Chen, Q Gu IEEE Transactions on Software Engineering 48 (3), 786-802, 2020 | 76 | 2020 |
Automated query reformulation for efficient search based on query logs from stack overflow K Cao, C Chen, S Baltes, C Treude, X Chen 2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE …, 2021 | 65 | 2021 |
DeepCount: Crowd counting with WiFi via deep learning S Liu, Y Zhao, F Xue, B Chen, X Chen arXiv preprint arXiv:1903.05316, 2019 | 62 | 2019 |
Interpretability application of the Just-in-Time software defect prediction model W Zheng, T Shen, X Chen, P Deng Journal of Systems and Software 188, 111245, 2022 | 61 | 2022 |
DeepCPDP: Deep learning based cross-project defect prediction D Chen, X Chen, H Li, J Xie, Y Mu IEEE Access 7, 184832-184848, 2019 | 57 | 2019 |
Building prioritized pairwise interaction test suites with ant colony optimization X Chen, Q Gu, X Zhang, D Chen 2009 ninth international conference on quality software, 347-352, 2009 | 56 | 2009 |