Comprehensive path-sensitive data-flow analysis. - Aditya V. Thakur; R. Govindarajan (CGO, 2008)

Cooperative crug isolation. - Aditya V. Thakur; Rathijit Sen; Ben Liblit; Shan Lu 001 (WODA, 2009)

The YogiProject: Software Property Checking via Static Analysis and Testing. - Aditya V. Nori; Sriram K. Rajamani; SaiDeep Tetali; Aditya V. Thakur (TACAS, 2009)

There's Plenty of Room at the Bottom: Analyzing and Verifying Machine Code. - Thomas W. Reps; Junghee Lim; Aditya V. Thakur; Gogul Balakrishnan; Akash Lal (CAV, 2010)

Directed Proof Generation for Machine Code. - Aditya V. Thakur; Junghee Lim; Akash Lal; Amanda Burton; Evan Driscoll; Matt Elder; Tycho Andersen; Thomas W. Reps (CAV, 2010)

Instrumentation and sampling strategies for cooperative concurrency bug isolation. - Guoliang Jin; Aditya V. Thakur; Ben Liblit; Shan Lu 001 (OOPSLA, 2010)

Proofs from Tests. - Nels E. Beckman; Aditya V. Nori; Sriram K. Rajamani; Robert J. Simmons; SaiDeep Tetali; Aditya V. Thakur (IEEE Trans. Software Eng., 2010)

OpenNWA: A Nested-Word Automaton Library. - Evan Driscoll; Aditya V. Thakur; Thomas W. Reps (CAV, 2012)

A Method for Symbolic Computation of Abstract Operations. - Aditya V. Thakur; Thomas W. Reps (CAV, 2012)

Bilateral Algorithms for Symbolic Abstraction. - Aditya V. Thakur; Matt Elder; Thomas W. Reps (SAS, 2012)

A Generalization of Stålmarck's Method. - Aditya V. Thakur; Thomas W. Reps (SAS, 2012)

PostHat and All That: Automating Abstract Interpretation. - Aditya V. Thakur; Akash Lal; Junghee Lim; Thomas W. Reps (TAPAS@SAS, 2013)

Property-Directed Shape Analysis. - Shachar Itzhaky; Nikolaj S. Bjørner; Thomas W. Reps; Mooly Sagiv; Aditya V. Thakur (CAV, 2014)

Satisfiability modulo abstraction for separation logic with linked lists. - Aditya V. Thakur; Jason Breck; Thomas W. Reps (SPIN, 2014)

Decision Procedures and Abstract Interpretation (Dagstuhl Seminar 14351). - Daniel Kroening; Thomas W. Reps; Sanjit A. Seshia; Aditya V. Thakur (Dagstuhl Reports, 2014)

Scaling up Superoptimization. - Phitchaya Mangpo Phothilimthana; Aditya Thakur 001; Rastislav Bodík; Dinakar Dhurjati (ASPLOS, 2016)

GreenThumb: superoptimizer construction framework. - Phitchaya Mangpo Phothilimthana; Aditya Thakur 001; Rastislav Bodík; Dinakar Dhurjati (CC, 2016)

Automating Abstract Interpretation. - Thomas W. Reps; Aditya V. Thakur (VMCAI, 2016)

Path-based function embeddings. - Daniel DeFreez; Aditya V. Thakur; Cindy Rubio-González (ICSE (Companion Volume), 2018)

Path-based function embedding and its application to error-handling specification mining. - Daniel DeFreez; Aditya V. Thakur; Cindy Rubio-González (ESEC/SIGSOFT FSE, 2018)

Path-Based Function Embedding and its Application to Specification Mining. - Daniel DeFreez; Aditya V. Thakur; Cindy Rubio-González (CoRR, 2018)

A Reinforcement Learning Based Network Scheduler for Deadline-Driven Data Transfers. - Dipak Ghosal; Sambit Shukla 001; Alex Sim; Aditya V. Thakur; Kesheng Wu (GLOBECOM, 2019)

Computing Linear Restrictions of Neural Networks. - Matthew Sotoudeh; Aditya V. Thakur (NeurIPS, 2019)

Effective error-specification inference via domain-knowledge expansion. - Daniel DeFreez; Haaken Martinson Baldwin; Cindy Rubio-González; Aditya V. Thakur (ESEC/SIGSOFT FSE, 2019)

A Symbolic Neural Network Representation and its Application to Understanding, Verifying, and Patching Networks. - Matthew Sotoudeh; Aditya V. Thakur (CoRR, 2019)

A Deep Deterministic Policy Gradient Based Network Scheduler For Deadline-Driven Data Transfers. - Gaurav R. Ghosal; Dipak Ghosal; Alex Sim; Aditya V. Thakur; Kesheng Wu (Networking, 2020)

Analogy-making as a Core primitive in the software engineering toolbox. - Matthew Sotoudeh; Aditya V. Thakur (Onward!, 2020)

Abstract Neural Networks. - Matthew Sotoudeh; Aditya V. Thakur (SAS, 2020)

Deterministic parallel fixpoint computation. - Sung Kook Kim; Arnaud J. Venet; Aditya V. Thakur (Proc. ACM Program. Lang., 2020)

Provable repair of deep neural networks. - Matthew Sotoudeh; Aditya V. Thakur (PLDI, 2021)

SyReNN: A Tool for Analyzing Deep Neural Networks. - Matthew Sotoudeh; Aditya V. Thakur (TACAS (2), 2021)

DICE*: A Formally Verified Implementation of DICE Measured Boot. - Zhe Tao; Aseem Rastogi; Naman Gupta; Kapil Vaswani; Aditya V. Thakur (USENIX Security Symposium, 2021)

Architecture-Preserving Provable Repair of Deep Neural Networks. - Zhe Tao; Stephanie Nawas; Jacqueline Mitchell 001; Aditya V. Thakur (Proc. ACM Program. Lang., 2023)

SyReNN: A tool for analyzing deep neural networks. - Matthew Sotoudeh; Zhe Tao; Aditya V. Thakur (Int. J. Softw. Tools Technol. Transf., 2023)

Provable Editing of Deep Neural Networks using Parametric Linear Relaxation. - Zhe Tao; Aditya V. Thakur (NeurIPS, 2024)

Provable Repair of Vision Transformers. - Stephanie Nawas; Zhe Tao; Aditya V. Thakur (SAIV, 2024)

Towards Verifying Exact Conditions for Implementations of Density Functional Approximations. - Sameerah Helal; Zhe Tao; Cindy Rubio-González; François Gygi; Aditya V. Thakur (SC Workshops, 2024)

Interleaving Static Analysis and LLM Prompting. - Patrick J. Chapman; Cindy Rubio-González; Aditya V. Thakur (SOAP@PLDI, 2024)

Towards Verifying Exact Conditions of Density Functional Theory Approximations. - Sameerah Helal; Zhe Tao; Cindy Rubio-González; François Gygi; Aditya V. Thakur (CoRR, 2024)

Memory-efficient fixpoint computation. - Sung Kook Kim; Arnaud J. Venet; Aditya V. Thakur (Formal Methods Syst. Des., 2025)

Interleaving static analysis and LLM prompting with applications to error specification inference. - Patrick J. Chapman; Cindy Rubio-González; Aditya V. Thakur (Int. J. Softw. Tools Technol. Transf., 2025)