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Ravi Mangal
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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
1062015
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
1012014
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
932019
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
512014
Closed-loop analysis of vision-based autonomous systems: A case study
CS Păsăreanu, R Mangal, D Gopinath, S Getir Yaman, C Imrie, ...
International conference on computer aided verification, 289-303, 2023
342023
Accelerating program analyses by cross-program training
S Kulkarni, R Mangal, X Zhang, M Naik
ACM SIGPLAN Notices 51 (10), 359-377, 2016
262016
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
202014
Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components
R Calinescu, C Imrie, R Mangal, GN Rodrigues, C Păsăreanu, ...
IEEE Transactions on Software Engineering, 2024
19*2024
Probabilistic Lipschitz analysis of neural networks
R Mangal, K Sarangmath, AV Nori, A Orso
Static Analysis: 27th International Symposium, SAS 2020, Virtual Event …, 2020
132020
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
132015
Scaling relational inference using proofs and refutations
R Mangal, X Zhang, A Kamath, A Nori, M Naik
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
122016
Self-correcting Neural Networks for Safe Classification
K Leino, A Fromherz, R Mangal, M Fredrikson, B Parno, C Păsăreanu
Software Verification and Formal Methods for ML-Enabled Autonomous Systems …, 2022
11*2022
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
112016
Assumption Generation for Learning-Enabled Autonomous Systems
CS Păsăreanu, R Mangal, D Gopinath, H Yu
International Conference on Runtime Verification, 3-22, 2023
6*2023
Attacks and Defenses for Large Language Models on Coding Tasks
C Zhang, Z Wang, R Zhao, R Mangal, M Fredrikson, L Jia, C Pasareanu
Proceedings of the 39th IEEE/ACM International Conference on Automated …, 2024
4*2024
Degradation Attacks on Certifiably Robust Neural Networks
K Leino, C Zhang, R Mangal, M Fredrikson, B Parno, C Pasareanu
Transactions of Machine Learning Research, 2022
42022
Concept-based analysis of neural networks via vision-language models
R Mangal, N Narodytska, D Gopinath, BC Hu, A Roy, S Jha, ...
International Symposium on AI Verification, 49-77, 2024
22024
Is Certifying Robustness Still Worthwhile?
R Mangal, K Leino, Z Wang, K Hu, W Yu, C Pasareanu, A Datta, ...
arXiv preprint arXiv:2310.09361, 2023
22023
Feature-Guided Analysis of Neural Networks.
D Gopinath, L Lungeanu, R Mangal, CS Pasareanu, S Xie, H Yu
FASE, 133-142, 2023
22023
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
22018
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