| On abstraction refinement for program analyses in Datalog X Zhang, R Mangal, R Grigore, M Naik, H Yang Proceedings of the 35th ACM SIGPLAN Conference on Programming Language …, 2014 | 91 | 2014 |
| A user-guided approach to program analysis R Mangal, X Zhang, AV Nori, M Naik Proceedings of the 2015 10th Joint Meeting on Foundations of Software …, 2015 | 85 | 2015 |
| Hybrid top-down and bottom-up interprocedural analysis X Zhang, R Mangal, M Naik, H Yang Proceedings of the 35th ACM SIGPLAN Conference on Programming Language …, 2014 | 42 | 2014 |
| Robustness of neural networks: A probabilistic and practical approach R Mangal, AV Nori, A Orso 2019 IEEE/ACM 41st International Conference on Software Engineering: New …, 2019 | 34 | 2019 |
| Accelerating program analyses by cross-program training S Kulkarni, R Mangal, X Zhang, M Naik ACM SIGPLAN Notices 51 (10), 359-377, 2016 | 22 | 2016 |
| A correspondence between two approaches to interprocedural analysis in the presence of join R Mangal, M Naik, H Yang European Symposium on Programming Languages and Systems, 513-533, 2014 | 14 | 2014 |
| Scaling relational inference using proofs and refutations R Mangal, X Zhang, A Kamath, AV Nori, M Naik Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 12 | 2016 |
| Query-guided maximum satisfiability X Zhang, R Mangal, AV Nori, M Naik Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of …, 2016 | 11 | 2016 |
| Volt: A lazy grounding framework for solving very large MaxSAT instances R Mangal, X Zhang, AV Nori, M Naik International Conference on Theory and Applications of Satisfiability …, 2015 | 11 | 2015 |
| Probabilistic Lipschitz Analysis of Neural Networks R Mangal, K Sarangmath, AV Nori, A Orso International Static Analysis Symposium, 274-309, 2020 | 2 | 2020 |
| Creating an interprocedural analyst-oriented data flow representation for binary analysts (CIAO) MA Leger, KM Butler, D Bueno, M Crepeau, C Cuellar, MJ Haas, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 2 | 2018 |
| Reasoning about programs in statistically modeled first-order environments R Mangal Georgia Institute of Technology, 2020 | 1 | 2020 |
| Solving weighted constraints with applications to program analysis R Mangal, X Zhang, M Naik, A Nori Georgia Institute of Technology, 2015 | 1 | 2015 |
| On the Perils of Cascading Robust Classifiers R Mangal, Z Wang, C Zhang, K Leino, C Pasareanu, M Fredrikson arXiv preprint arXiv:2206.00278, 2022 | | 2022 |
| Discrete-Event Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components R Calinescu, C Imrie, R Mangal, C Păsăreanu, MA Santana, G Vázquez arXiv preprint arXiv:2202.03360, 2022 | | 2022 |
| Degradation Attacks on Certifiably Robust Neural Networks K Leino, C Zhang, R Mangal, M Fredrikson, B Parno, C Pasareanu | | 2021 |
| Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair K Leino, A Fromherz, R Mangal, M Fredrikson, B Parno, C Păsăreanu arXiv preprint arXiv:2107.11445, 2021 | | 2021 |
| Checking Probabilistic Properties of Neural Networks via Symbolic Methods and Sampling R Mangal, AV Nori, A Orso | | |
| Observational Abstract Interpreters R MANGAL | | |
| On Optimally Combining Static and Dynamic Analyses For Intensional Program Properties R Mangal, D Devecsery, A Orso | | |
Mayur NaikProfessor of Computer Science, University of PennsylvaniaVerified email at cis.upenn.edu
