| Symbolic discovery of optimization algorithms X Chen, C Liang, D Huang, E Real, K Wang, H Pham, X Dong, T Luong, ... Advances in Neural Information Processing Systems 36, 2024 | 443 | 2024 |
| Towards practical program repair with on-demand candidate generation J Hua, M Zhang, K Wang, S Khurshid The 40th International Conference on Software Engineering, ICSE 2018, 2018 | 179 | 2018 |
| Symbolic execution for importance analysis and adversarial generation in neural networks D Gopinath, M Zhang, K Wang, IB Kadron, C Pasareanu, S Khurshid 2019 IEEE 30th International Symposium on Software Reliability Engineering …, 2019 | 120* | 2019 |
| Automated Test Generation and Mutation Testing for Alloy A Sullivan, K Wang, RN Zaeem, S Khurshid The 10th IEEE International Conference on Software Testing, Verification and …, 2017 | 59 | 2017 |
| Automated model repair for Alloy K Wang, A Sullivan, S Khurshid Proceedings of the 33rd ACM/IEEE International Conference on Automated …, 2018 | 49 | 2018 |
| Sketch-Fix: A Tool for Automated Program Repair Approach Using Lazy Candidate Generation J Hua, M Zhang, K Wang, S Khurshid Foundations of Software Engineering, 2018 | 48 | 2018 |
| Fault localization for declarative models in alloy K Wang, A Sullivan, D Marinov, S Khurshid 2020 IEEE 31st International Symposium on Software Reliability Engineering …, 2020 | 38 | 2020 |
| Towards Refactoring-Aware Regression Test Selection K Wang, C Zhu, A Celik, J Kim, D Batory, M Gligoric The 40th International Conference on Software Engineering, ICSE 2018, 2018 | 37 | 2018 |
| AUnit: a test automation tool for Alloy A Sullivan, K Wang, S Khurshid The 11th IEEE International Conference on Software Testing, Verification and …, 2018 | 28 | 2018 |
| Moët: Interpretable and verifiable reinforcement learning via mixture of expert trees M Vasic, A Petrovic, K Wang, M Nikolic, R Singh, S Khurshid arXiv preprint arXiv:1906.06717, 2019 | 27 | 2019 |
| MuAlloy: a mutation testing framework for Alloy K Wang, A Sullivan, S Khurshid The 40th International Conference on Software Engineering, ICSE 2018, 2018 | 25 | 2018 |
| MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning M Vasić, A Petrović, K Wang, M Nikolić, R Singh, S Khurshid Neural Networks 151, 34-47, 2022 | 24 | 2022 |
| Symbolic discovery of optimization algorithms. arxiv 2023 X Chen, C Liang, D Huang, E Real, K Wang, Y Liu, H Pham, X Dong, ... arXiv preprint arXiv:2302.06675, 2023 | 23 | 2023 |
| Evaluating State Modeling Techniques in Alloy. A Sullivan, K Wang, S Khurshid, D Marinov SQAMIA, 2017 | 21 | 2017 |
| Systematic generation of non-equivalent expressions for relational algebra K Wang, A Sullivan, M Koukoutos, D Marinov, S Khurshid Abstract State Machines, Alloy, B, TLA, VDM, and Z: 6th International …, 2018 | 20 | 2018 |
| ASketch: A Sketching Framework for Alloy K Wang, A Sullivan, D Marinov, S Khurshid Foundations of Software Engineering, 2018 | 19 | 2018 |
| A study of symmetry breaking predicates and model counting W Wang, M Usman, A Almaawi, K Wang, KS Meel, S Khurshid Tools and Algorithms for the Construction and Analysis of Systems: 26th …, 2020 | 18 | 2020 |
| ARepair: a repair framework for alloy K Wang, A Sullivan, S Khurshid 2019 IEEE/ACM 41st International Conference on Software Engineering …, 2019 | 18 | 2019 |
| Evolved optimizer for vision X Chen, C Liang, D Huang, E Real, Y Liu, K Wang, CJ Hsieh, Y Lu, QV Le First Conference on Automated Machine Learning (Late-Breaking Workshop), 2022 | 16 | 2022 |
| EdSynth: Synthesizing API sequences with conditionals and loops Z Yang, J Hua, K Wang, S Khurshid 2018 IEEE 11th International Conference on Software Testing, Verification …, 2018 | 15 | 2018 |
Sarfraz KhurshidProfessor, University of Texas at Austin確認したメール アドレス: ece.utexas.edu