A Correspondence between Two Approaches to Interprocedural Analysis in the Presence of Join. - Ravi Mangal; Mayur Naik; Hongseok Yang (ESOP, 2014)

On abstraction refinement for program analyses in Datalog. - Xin Zhang 035; Ravi Mangal; Radu Grigore; Mayur Naik; Hongseok Yang (PLDI, 2014)

Hybrid top-down and bottom-up interprocedural analysis. - Xin Zhang 035; Ravi Mangal; Mayur Naik; Hongseok Yang (PLDI, 2014)

Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances. - Ravi Mangal; Xin Zhang 035; Aditya V. Nori; Mayur Naik (SAT, 2015)

A user-guided approach to program analysis. - Ravi Mangal; Xin Zhang 035; Aditya V. Nori; Mayur Naik (ESEC/SIGSOFT FSE, 2015)

Scaling Relational Inference Using Proofs and Refutations. - Ravi Mangal; Xin Zhang 035; Aditya Kamath; Aditya V. Nori; Mayur Naik (AAAI, 2016)

Accelerating program analyses by cross-program training. - Sulekha Kulkarni; Ravi Mangal; Xin Zhang 035; Mayur Naik (OOPSLA, 2016)

Query-guided maximum satisfiability. - Xin Zhang 035; Ravi Mangal; Aditya V. Nori; Mayur Naik (POPL, 2016)

Robustness of neural networks: a probabilistic and practical approach. - Ravi Mangal; Aditya V. Nori; Alessandro Orso (ICSE (NIER), 2019)

Probabilistic Lipschitz Analysis of Neural Networks. - Ravi Mangal; Kartik Sarangmath; Aditya V. Nori; Alessandro Orso (SAS, 2020)

Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair. - Klas Leino; Aymeric Fromherz; Ravi Mangal; Matt Fredrikson; Bryan Parno; Corina S. Pasareanu (CoRR, 2021)

Reasoning about programs in statistically modeled first-order environments. - Ravi Mangal (2021)

Self-correcting Neural Networks for Safe Classification. - Klas Leino; Aymeric Fromherz; Ravi Mangal; Matt Fredrikson; Bryan Parno; Corina S. Pasareanu (NSV/FoMLAS@CAV, 2022)

A Cascade of Checkers for Run-time Certification of Local Robustness. - Ravi Mangal; Corina S. Pasareanu (NSV/FoMLAS@CAV, 2022)

Discrete-Event Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components. - Radu Calinescu; Calum Imrie; Ravi Mangal; Corina S. Pasareanu; Misael Alpizar Santana; Gricel Vázquez (CoRR, 2022)

Degradation Attacks on Certifiably Robust Neural Networks. - Klas Leino; Chi Zhang; Ravi Mangal; Matt Fredrikson; Bryan Parno; Corina S. Pasareanu (Trans. Mach. Learn. Res., 2022)

Closed-Loop Analysis of Vision-Based Autonomous Systems: A Case Study. - Corina S. Pasareanu; Ravi Mangal; Divya Gopinath; Sinem Getir Yaman; Calum Imrie; Radu Calinescu; Huafeng Yu (CAV (1), 2023)

Feature-Guided Analysis of Neural Networks. - Divya Gopinath; Luca Lungeanu; Ravi Mangal; Corina S. Pasareanu; Siqi Xie; Huafeng Yu (FASE, 2023)

On the Perils of Cascading Robust Classifiers. - Ravi Mangal; Zifan Wang 001; Chi Zhang; Klas Leino; Corina S. Pasareanu; Matt Fredrikson (ICLR, 2023)

Assumption Generation for Learning-Enabled Autonomous Systems. - Corina S. Pasareanu; Ravi Mangal; Divya Gopinath; Huafeng Yu (RV, 2023)

Assumption Generation for the Verification of Learning-Enabled Autonomous Systems. - Corina S. Pasareanu; Ravi Mangal; Divya Gopinath; Huafeng Yu (CoRR, 2023)

Is Certifying 𝓁p Robustness Still Worthwhile? - Ravi Mangal; Klas Leino; Zifan Wang 001; Kai Hu; Weicheng Yu; Corina S. Pasareanu; Anupam Datta; Matt Fredrikson (CoRR, 2023)

Transfer Attacks and Defenses for Large Language Models on Coding Tasks. - Chi Zhang; Zifan Wang 001; Ravi Mangal; Matt Fredrikson; Limin Jia 001; Corina S. Pasareanu (CoRR, 2023)

Formal Verification Techniques for Vision-Based Autonomous Systems - A Survey. - Sayan Mitra; Corina S. Pasareanu; Pavithra Prabhakar; Sanjit A. Seshia; Ravi Mangal; Yangge Li; Christopher Watson; Divya Gopinath; Huafeng Yu (Principles of Verification (3), 2024)

Attacks and Defenses for Large Language Models on Coding Tasks. - Chi Zhang; Zifan Wang 001; Ruoshi Zhao; Ravi Mangal; Matt Fredrikson; Limin Jia 001; Corina S. Pasareanu (ASE, 2024)

Concept-Based Analysis of Neural Networks via Vision-Language Models. - Ravi Mangal; Nina Narodytska; Divya Gopinath; Boyue Caroline Hu; Anirban Roy; Susmit Jha; Corina S. Pasareanu (SAIV, 2024)

Mechanistically Interpreting a Transformer-based 2-SAT Solver: An Axiomatic Approach. - Nils Palumbo; Ravi Mangal; Zifan Wang 001; Saranya Vijayakumar; Corina S. Pasareanu; Somesh Jha (CoRR, 2024)

Controller Synthesis for Autonomous Systems With Deep-Learning Perception Components. - Radu Calinescu; Calum Imrie; Ravi Mangal; Genaína Nunes Rodrigues; Corina S. Pasareanu; Misael Alpizar Santana; Gricel Vázquez (IEEE Trans. Software Eng., 2024)

Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study). - Boyue Caroline Hu; Divya Gopinath; Corina S. Pasareanu; Nina Narodytska; Ravi Mangal; Susmit Jha (CAIN, 2025)

Random Perturbation Attack on LLMs for Code Generation. - Qiulu Peng; Chi Zhang; Ravi Mangal; Corina S. Pasareanu; Limin Jia 001 (CAIN, 2025)

Scenario-based Compositional Verification of Autonomous Systems with Neural Perception. - Christopher Watson; Rajeev Alur; Divya Gopinath; Ravi Mangal; Corina S. Pasareanu (CoRR, 2025)

Conformal Safety Shielding for Imperfect-Perception Agents. - William Scarbro; Calum Imrie; Sinem Getir Yaman; Kavan Fatehi; Corina S. Pasareanu; Radu Calinescu; Ravi Mangal (CoRR, 2025)

A Mixture of Linear Corrections Generates Secure Code. - Weichen Yu; Ravi Mangal; Terry Yue Zhuo; Matt Fredrikson; Corina S. Pasareanu (CoRR, 2025)