| ICE: A robust framework for learning invariants P Garg, C Löding, P Madhusudan, D Neider International Conference on Computer Aided Verification, 69-87, 2014 | 199 | 2014 |
| Learning invariants using decision trees and implication counterexamples P Garg, D Neider, P Madhusudan, D Roth ACM Sigplan Notices 51 (1), 499-512, 2016 | 182 | 2016 |
| Natural proofs for structure, data, and separation X Qiu, P Garg, A Ştefănescu, P Madhusudan ACM SIGPLAN Notices 48 (6), 231-242, 2013 | 103 | 2013 |
| Feedback-directed unit test generation for C/C++ using concolic execution P Garg, F Ivančić, G Balakrishnan, N Maeda, A Gupta 2013 35th International Conference on Software Engineering (ICSE), 132-141, 2013 | 52 | 2013 |
| Horn-ICE learning for synthesizing invariants and contracts P Ezudheen, D Neider, D D'Souza, P Garg, P Madhusudan Proceedings of the ACM on Programming Languages 2 (OOPSLA), 1-25, 2018 | 41 | 2018 |
| Learning universally quantified invariants of linear data structures P Garg, C Löding, P Madhusudan, D Neider International Conference on Computer Aided Verification, 813-829, 2013 | 39 | 2013 |
| Rebound: scalable checkpointing for coherent shared memory R Agarwal, P Garg, J Torrellas Proceedings of the 38th annual international symposium on Computer …, 2011 | 35 | 2011 |
| Natural proofs for asynchronous programs using almost-synchronous reductions A Desai, P Garg, P Madhusudan Proceedings of the 2014 ACM International Conference on Object Oriented …, 2014 | 30 | 2014 |
| Alchemist: Learning guarded affine functions S Saha, P Garg, P Madhusudan International Conference on Computer Aided Verification, 440-446, 2015 | 18 | 2015 |
| Compositionality entails sequentializability P Garg, P Madhusudan International Conference on Tools and Algorithms for the Construction and …, 2011 | 15 | 2011 |
| Invariant synthesis for incomplete verification engines D Neider, P Garg, P Madhusudan, S Saha, D Park International Conference on Tools and Algorithms for the Construction and …, 2018 | 9 | 2018 |
| Feedback-directed random class unit test generation using symbolic execution P Garg, F Ivancic, G Balakrishnan, N Maeda, A Gupta US Patent App. 13/646,390, 2013 | 8 | 2013 |
| Quantified data automata on skinny trees: An abstract domain for lists P Garg, P Madhusudan, G Parlato International Static Analysis Symposium, 172-193, 2013 | 6 | 2013 |
| Cadence: Conditional anomaly detection for events using noise-contrastive estimation MR Amin, P Garg, B Coskun Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security …, 2019 | 5 | 2019 |
| Sorcar: Property-Driven Algorithms for Learning Conjunctive Invariants D Neider, S Saha, P Garg, P Madhusudan International Static Analysis Symposium, 323-346, 2019 | 5 | 2019 |
| ICE: A robust learning framework for synthesizing invariants P Garg, C Loding, P Madhusudan, D Neider | 3 | 2013 |
| A learning-based approach to synthesizing invariants for incomplete verification engines D Neider, P Madhusudan, S Saha, P Garg, D Park Journal of Automated Reasoning 64 (7), 1523-1552, 2020 | 2 | 2020 |
| Quantified data automata for linear data structures: a register automaton model with applications to learning invariants of programs manipulating arrays and lists P Garg, C Löding, P Madhusudan, D Neider Formal Methods in System Design 47 (1), 120-157, 2015 | 2 | 2015 |
| Learning-based inductive invariant synthesis P Garg University of Illinois at Urbana-Champaign, 2015 | 2 | 2015 |
| Efficient incrementalized runtime checking of linear measures on lists A Gyori, P Garg, E Pek, P Madhusudan 2017 IEEE International Conference on Software Testing, Verification and …, 2017 | 1 | 2017 |
Madhusudan ParthasarathyProfessor of Computer Science, University of Illinois at Urbana-ChampaignVerified email at illinois.edu
