| Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks Y Zhou, S Liu, J Siow, X Du, Y Liu https://arxiv.org/abs/1909.03496, 2019 | 283 | 2019 |
| DeepStellar: model-based quantitative analysis of stateful deep learning systems X Du, X Xie, Y Li, L Ma, Y Liu, J Zhao Proceedings of the 2019 27th ACM Joint Meeting on European Software …, 2019 | 137* | 2019 |
| Who is real bob? adversarial attacks on speaker recognition systems G Chen, S Chenb, L Fan, X Du, Z Zhao, F Song, Y Liu 2021 IEEE Symposium on Security and Privacy (SP), 694-711, 2021 | 106 | 2021 |
| Leopard: Identifying vulnerable code for vulnerability assessment through program metrics X Du, B Chen, Y Li, J Guo, Y Zhou, Y Liu, Y Jiang 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE …, 2019 | 59 | 2019 |
| Towards characterizing adversarial defects of deep learning software from the lens of uncertainty X Zhang, X Xie, L Ma, X Du, Q Hu, Y Liu, J Zhao, M Sun Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 55 | 2020 |
| Decision-guided weighted automata extraction from recurrent neural networks X Zhang, X Du, X Xie, L Ma, Y Liu, M Sun Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11699 …, 2021 | 12 | 2021 |
| Marble: Model-based robustness analysis of stateful deep learning systems X Du, Y Li, X Xie, L Ma, Y Liu, J Zhao Proceedings of the 35th IEEE/ACM International Conference on Automated …, 2020 | 12 | 2020 |
| Trace-length independent runtime monitoring of quantitative policies in LTL X Du, Y Liu, A Tiu FM 2015: Formal Methods: 20th International Symposium, Oslo, Norway, June 24 …, 2015 | 11 | 2015 |
| On the importance of building high-quality training datasets for neural code search Z Sun, L Li, Y Liu, X Du, L Li Proceedings of the 44th International Conference on Software Engineering …, 2022 | 10 | 2022 |
| A Quantitative Analysis Framework for Recurrent Neural Network X Du, X Xie, Y Li, L Ma, Y Liu, J Zhao 2019 34th IEEE/ACM International Conference on Automated Software …, 2019 | 10 | 2019 |
| CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning Z Sun, X Du, F Song, M Ni, L Li Proceedings of the ACM Web Conference 2022, 652-660, 2022 | 7 | 2022 |
| Vulnerability Analysis, Robustness Verification, and Mitigation Strategy for Machine Learning-Based Power System Stability Assessment Model Under Adversarial Examples C Ren, X Du, Y Xu, Q Song, Y Liu, R Tan IEEE Transactions on Smart Grid 13 (2), 1622-1632, 2021 | 5 | 2021 |
| Trace-length independent runtime monitoring of quantitative policies X Du, A Tiu, K Cheng, Y Liu IEEE Transactions on Dependable and Secure Computing 18 (3), 1489-1510, 2019 | 3 | 2019 |
| Towards building a generic vulnerability detection platform by combining scalable attacking surface analysis and directed fuzzing X Du Formal Methods and Software Engineering: 20th International Conference on …, 2018 | 2 | 2018 |
| Characterizing Python Method Evolution with PyMevol: An Essential Step Towards Enabling Reliable Software Systems H Quan, J Wang, B Li, X Du, K Liu, L Li 2022 IEEE International Symposium on Software Reliability Engineering …, 2022 | | 2022 |
| Learning to Prevent Profitless Neural Code Completion Z Sun, X Du, F Song, S Wang, M Ni, L Li arXiv preprint arXiv:2209.05948, 2022 | | 2022 |
| Marvel: a generic, scalable and effective vulnerability detection platform X Du 2019 IEEE/ACM 41st International Conference on Software Engineering …, 2019 | | 2019 |
| Towards secure and robust stateful deep learning systems with model-based analysis X Du Nanyang Technological University, 2019 | | 2019 |
| FuzzJIT: Oracle-Enhanced Fuzzing for JavaScript Engine JIT Compiler J Wang, Z Zhang, S Liu, X Du, J Chen | | |
Yang LiuNanyang Technological UniversityVerified email at ntu.edu.sg
