| An empirical study towards characterizing deep learning development and deployment across different frameworks and platforms. Q Guo, S Chen, X Xie, L Ma, Q Hu, H Liu, Y Liu, J Zhao, X Li Proceedings of the 34th IEEE/ACM International Conference on Automated …, 2019 | 148 | 2019 |
| Deepmutation++: A mutation testing framework for deep learning systems Q Hu, L Ma, X Xie, B Yu, Y Liu, J Zhao 2019 34th IEEE/ACM International Conference on Automated Software …, 2019 | 134 | 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 | 91 | 2020 |
| The scope of chatgpt in software engineering: A thorough investigation W Ma, S Liu, W Wang, Q Hu, Y Liu, C Zhang, L Nie, Y Liu arXiv preprint arXiv:2305.12138, 2023 | 76 | 2023 |
| An empirical study on data distribution-aware test selection for deep learning enhancement Q Hu, Y Guo, M Cordy, X Xie, L Ma, M Papadakis, Y Le Traon ACM Transactions on Software Engineering and Methodology (TOSEM) 31 (4), 1-30, 2022 | 44 | 2022 |
| Secure deep learning engineering: A software quality assurance perspective L Ma, F Juefei-Xu, M Xue, Q Hu, S Chen, B Li, Y Liu, J Zhao, J Yin, S See arXiv preprint arXiv:1810.04538, 2018 | 39 | 2018 |
| Graphcode2vec: Generic code embedding via lexical and program dependence analyses W Ma, M Zhao, E Soremekun, Q Hu, JM Zhang, M Papadakis, M Cordy, ... Proceedings of the 19th International Conference on Mining Software …, 2022 | 35 | 2022 |
| Towards exploring the limitations of active learning: An empirical study Q Hu, Y Guo, M Cordy, X Xie, W Ma, M Papadakis, Y Le Traon 2021 36th IEEE/ACM International Conference on Automated Software …, 2021 | 30 | 2021 |
| DeepGraph: A PyCharm tool for visualizing and understanding deep learning models Q Hu, L Ma, J Zhao 2018 25th Asia-Pacific Software Engineering Conference (APSEC), 628-632, 2018 | 24 | 2018 |
| Unveiling Code Pre-Trained Models: Investigating Syntax and Semantics Capacities W Ma, S Liu, M Zhao, X Xie, W Wang, Q Hu, J Zhang, Y Liu ACM Transactions on Software Engineering and Methodology, 2024 | 20* | 2024 |
| Aries: Efficient Testing of Deep Neural Networks via Labeling-Free Accuracy Estimation Q Hu, Y Guo, X Xie, M Cordy, L Ma, M Papadakis, YL Traon 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE), 2022 | 17* | 2022 |
| DRE: density-based data selection with entropy for adversarial-robust deep learning models Y Guo, Q Hu, M Cordy, M Papadakis, Y Le Traon Neural Computing and Applications 35 (5), 4009-4026, 2023 | 13* | 2023 |
| CodeS: Towards Code Model Generalization Under Distribution Shift Q Hu, Y Guo, X Xie, M Cordy, L Ma, M Papadakis, YL Traon 2023 IEEE/ACM 45th International Conference on Software Engineering: New …, 2022 | 12* | 2022 |
| Mixcode: Enhancing code classification by mixup-based data augmentation Z Dong, Q Hu, Y Guo, M Cordy, M Papadakis, Z Zhang, Y Le Traon, ... 2023 IEEE International Conference on Software Analysis, Evolution and …, 2023 | 11* | 2023 |
| A Black-Box Attack on Code Models via Representation Nearest Neighbor Search J Zhang, W Ma, Q Hu, S Liu, X Xie, YL Traon, Y Liu arXiv preprint arXiv:2305.05896, 2023 | 10* | 2023 |
| Boosting source code learning with data augmentation: An empirical study Z Dong, Q Hu, Y Guo, Z Zhang, M Cordy, M Papadakis, YL Traon, J Zhao arXiv preprint arXiv:2303.06808, 2023 | 10 | 2023 |
| LMs: Understanding Code Syntax and Semantics for Code Analysis W Ma, S Liu, Z Lin, W Wang, Q Hu, Y Liu, C Zhang, L Nie, L Li, Y Liu arXiv preprint arXiv:2305.12138, 2023 | 9 | 2023 |
| Test Optimization in DNN Testing: A Survey Q Hu, Y Guo, X Xie, M Cordy, L Ma, M Papadakis, Y Le Traon ACM Transactions on Software Engineering and Methodology, 2024 | 6 | 2024 |
| LaF: Labeling-free model selection for automated deep neural network reusing Q Hu, Y Guo, X Xie, M Cordy, M Papadakis, Y Le Traon ACM Transactions on Software Engineering and Methodology 33 (1), 1-28, 2023 | 6 | 2023 |
| On the effectiveness of graph data augmentation for source code learning Z Dong, Q Hu, Z Zhang, J Zhao Knowledge-Based Systems 285, 111328, 2024 | 5 | 2024 |
Xiaofei XieSingapore Management UniversityVerified email at smu.edu.sg
