| Adversarial sample detection for deep neural network through model mutation testing J Wang, G Dong, J Sun, X Wang, P Zhang 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE …, 2019 | 183 | 2019 |
| White-box fairness testing through adversarial sampling P Zhang, J Wang, J Sun, G Dong, X Wang, X Wang, JS Dong, T Dai Proceedings of the ACM/IEEE 42nd international conference on software …, 2020 | 118 | 2020 |
| Towards optimal concolic testing X Wang, J Sun, Z Chen, P Zhang, J Wang, Y Lin Proceedings of the 40th International Conference on Software Engineering …, 2018 | 79 | 2018 |
| An empirical study on correlation between coverage and robustness for deep neural networks Y Dong, P Zhang, J Wang, S Liu, J Sun, J Hao, X Wang, L Wang, J Dong, ... 2020 25th International Conference on Engineering of Complex Computer …, 2020 | 62* | 2020 |
| Detecting adversarial samples for deep neural networks through mutation testing J Wang, J Sun, P Zhang, X Wang arXiv preprint arXiv:1805.05010, 2018 | 48 | 2018 |
| Automatic fairness testing of neural classifiers through adversarial sampling P Zhang, J Wang, J Sun, X Wang, G Dong, X Wang, T Dai, JS Dong IEEE Transactions on Software Engineering 48 (9), 3593-3612, 2021 | 21 | 2021 |
| Fairness testing of deep image classification with adequacy metrics P Zhang, J Wang, J Sun, X Wang arXiv preprint arXiv:2111.08856, 2021 | 7 | 2021 |
| QuoTe: Quality-oriented Testing for Deep Learning Systems J Chen, J Wang, X Ma, Y Sun, J Sun, P Zhang, P Cheng ACM Transactions on Software Engineering and Methodology 32 (5), 1-33, 2023 | 5 | 2023 |
| Boosting adversarial training in safety-critical systems through boundary data selection Y Jia, CM Poskitt, P Zhang, J Wang, J Sun, S Chattopadhyay IEEE Robotics and Automation Letters, 2023 | | 2023 |
Sun JunProfessor of SCIS, SMU在 smu.edu.sg 的电子邮件经过验证
