| Programmatically interpretable reinforcement learning A Verma, V Murali, R Singh, P Kohli, S Chaudhuri International Conference on Machine Learning, 5045-5054, 2018 | 301 | 2018 |
| Neural Sketch Learning for Conditional Program Generation V Murali, L Qi, S Chaudhuri, C Jermaine International Conference on Learning Representations, 2018 | 156* | 2018 |
| TRACER: A symbolic execution tool for verification J Jaffar, V Murali, JA Navas, AE Santosa Computer Aided Verification: 24th International Conference, CAV 2012 …, 2012 | 147 | 2012 |
| Boosting concolic testing via interpolation J Jaffar, V Murali, JA Navas Proceedings of the 2013 9th Joint Meeting on Foundations of Software …, 2013 | 75 | 2013 |
| Bayesian specification learning for finding API usage errors V Murali, S Chaudhuri, C Jermaine Proceedings of the 2017 11th joint meeting on foundations of software …, 2017 | 69* | 2017 |
| Neural query expansion for code search J Liu, S Kim, V Murali, S Chaudhuri, S Chandra Proceedings of the 3rd acm sigplan international workshop on machine …, 2019 | 33 | 2019 |
| Scaffle: bug localization on millions of files M Pradel, V Murali, R Qian, M Machalica, E Meijer, S Chandra Proceedings of the 29th ACM SIGSOFT International Symposium on Software …, 2020 | 23 | 2020 |
| Path-sensitive backward slicing J Jaffar, V Murali, JA Navas, AE Santosa Static Analysis: 19th International Symposium, SAS 2012, Deauville, France …, 2012 | 21 | 2012 |
| Counterfactual explanations for models of code J Cito, I Dillig, V Murali, S Chandra Proceedings of the 44th International Conference on Software Engineering …, 2022 | 19 | 2022 |
| Industry-scale ir-based bug localization: A perspective from facebook V Murali, L Gross, R Qian, S Chandra 2021 IEEE/ACM 43rd International Conference on Software Engineering …, 2021 | 18 | 2021 |
| A path-sensitively sliced control flow graph J Jaffar, V Murali Proceedings of the 22Nd ACM SIGSOFT International Symposium on Foundations …, 2014 | 16 | 2014 |
| What gives? A hybrid algorithm for error trace explanation V Murali, N Sinha, E Torlak, S Chandra Verified Software: Theories, Tools and Experiments: 6th International …, 2014 | 15 | 2014 |
| Debugging crashes using continuous contrast set mining R Qian, Y Yu, W Park, V Murali, S Fink, S Chandra Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 11 | 2020 |
| Bayesian Sketch Learning for Program Synthesis. CoRR abs/1703.05698 (2017) V Murali, S Chaudhuri, C Jermaine arXiv preprint arXiv:1703.05698, 2017 | 11 | 2017 |
| Lazy Symbolic Execution for Enhanced Learning DH Chu, J Jaffar, V Murali International Conference on Runtime Verification, 323-339, 2014 | 9 | 2014 |
| Explaining mispredictions of machine learning models using rule induction J Cito, I Dillig, S Kim, V Murali, S Chandra Proceedings of the 29th ACM Joint Meeting on European Software Engineering …, 2021 | 8 | 2021 |
| Improving code autocompletion with transfer learning W Zhou, S Kim, V Murali, GA Aye Proceedings of the 44th International Conference on Software Engineering …, 2022 | 6 | 2022 |
| Scalable statistical root cause analysis on app telemetry V Murali, E Yao, U Mathur, S Chandra 2021 IEEE/ACM 43rd International Conference on Software Engineering …, 2021 | 5 | 2021 |
| Abridging source code B Yuan, V Murali, C Jermaine Proceedings of the ACM on Programming Languages 1 (OOPSLA), 1-26, 2017 | 5 | 2017 |
| Learning to Learn to Predict Performance Regressions in Production at Meta M Beller, H Li, V Nair, V Murali, I Ahmad, J Cito, D Carlson, A Aye, W Dyer arXiv preprint arXiv:2208.04351, 2022 | 4 | 2022 |
Joxan JaffarNational University of SingaporeVerified email at comp.nus.edu.sg
