Object-Oriented Symbol Management in Syntax-Directed Compiler Systems. - Mayur Naik; Rajeev Kumar (ACM SIGPLAN Notices, 1999)

Efficient Message Dispatch in Object-Oriented Systems. - Mayur Naik; Rajeev Kumar (ACM SIGPLAN Notices, 2000)

From symptom to cause: localizing errors in counterexample traces. - Thomas Ball 001; Mayur Naik; Sriram K. Rajamani (POPL, 2003)

Compiling with code-size constraints. - Mayur Naik; Jens Palsberg (ACM Trans. Embed. Comput. Syst., 2004)

Scalable statistical bug isolation. - Ben Liblit; Mayur Naik; Alice X. Zheng; Alex Aiken; Michael I. Jordan (PLDI, 2005)

Statistical debugging: simultaneous identification of multiple bugs. - Alice X. Zheng; Michael I. Jordan; Ben Liblit; Mayur Naik; Alex Aiken (ICML, 2006)

Effective static race detection for Java. - Mayur Naik; Alex Aiken; John Whaley (PLDI, 2006)

Conditional must not aliasing for static race detection. - Mayur Naik; Alex Aiken (POPL, 2007)

A type system equivalent to a model checker. - Mayur Naik; Jens Palsberg (ACM Trans. Program. Lang. Syst., 2008)

Effective static race detection for Java. - Mayur Naik (2008)

CalFuzzer: An Extensible Active Testing Framework for Concurrent Programs. - Pallavi Joshi; Mayur Naik; Chang-Seo Park; Koushik Sen (CAV, 2009)

Effective static deadlock detection. - Mayur Naik; Chang-Seo Park; Koushik Sen; David Gay (ICSE, 2009)

Lightweight annotations for controlling sharing in concurrent data structures. - Zachary R. Anderson; David Gay; Mayur Naik (PLDI, 2009)

A randomized dynamic program analysis technique for detecting real deadlocks. - Pallavi Joshi; Chang-Seo Park; Koushik Sen; Mayur Naik (PLDI, 2009)

Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression. - Ling Huang 001; Jinzhu Jia; Bin Yu 001; Byung-Gon Chun; Petros Maniatis; Mayur Naik (NIPS, 2010)

A dynamic evaluation of the precision of static heap abstractions. - Percy Liang; Omer Tripp; Mayur Naik; Mooly Sagiv (OOPSLA, 2010)

An effective dynamic analysis for detecting generalized deadlocks. - Pallavi Joshi; Mayur Naik; Koushik Sen; David Gay (SIGSOFT FSE, 2010)

CloneCloud: Boosting Mobile Device Applications Through Cloud Clone Execution - Byung-Gon Chun; Sunghwan Ihm; Petros Maniatis; Mayur Naik (CoRR, 2010)

Mantis: Predicting System Performance through Program Analysis and Modeling - Byung-Gon Chun; Ling Huang 001; Sangmin Lee; Petros Maniatis; Mayur Naik (CoRR, 2010)

CloneCloud: elastic execution between mobile device and cloud. - Byung-Gon Chun; Sunghwan Ihm; Petros Maniatis; Mayur Naik; Ashwin Patti (EuroSys, 2011)

Scaling abstraction refinement via pruning. - Percy Liang; Mayur Naik (PLDI, 2011)

Learning minimal abstractions. - Percy Liang; Omer Tripp; Mayur Naik (POPL, 2011)

Yada: Straightforward parallel programming. - David Gay; Joel Galenson; Mayur Naik; Kathy Yelick (Parallel Comput., 2011)

Abstractions from tests. - Mayur Naik; Hongseok Yang; Ghila Castelnuovo; Mooly Sagiv (POPL, 2012)

Computing in cirrus clouds: the challenge of intermittent connectivity. - Cong Shi; Mostafa H. Ammar; Ellen W. Zegura; Mayur Naik (MCC@SIGCOMM, 2012)

Automated concolic testing of smartphone apps. - Saswat Anand; Mayur Naik; Mary Jean Harrold; Hongseok Yang (SIGSOFT FSE, 2012)

Finding optimum abstractions in parametric dataflow analysis. - Xin Zhang 035; Mayur Naik; Hongseok Yang (PLDI, 2013)

Dynodroid: an input generation system for Android apps. - Aravind Machiry; Rohan Tahiliani; Mayur Naik (ESEC/SIGSOFT FSE, 2013)

Mantis: Automatic Performance Prediction for Smartphone Applications. - Yongin Kwon; Sangmin Lee; Hayoon Yi; Donghyun Kwon; Seungjun Yang; Byung-Gon Chun; Ling Huang 001; Petros Maniatis; Mayur Naik; Yunheung Paek (USENIX ATC, 2013)

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

COSMOS: computation offloading as a service for mobile devices. - Cong Shi; Karim Habak; Pranesh Pandurangan; Mostafa H. Ammar; Mayur Naik; Ellen W. Zegura (MobiHoc, 2014)

Large-scale configurable static analysis. - Mayur Naik (SOAP@PLDI, 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)

Modularity in Lattices: A Case Study on the Correspondence Between Top-Down and Bottom-Up Analysis. - Ghila Castelnuovo; Mayur Naik; Noam Rinetzky; Mooly Sagiv; Hongseok Yang (SAS, 2015)

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)

FlexJava: language support for safe and modular approximate programming. - Jongse Park; Hadi Esmaeilzadeh; Xin Zhang 035; Mayur Naik; William Harris (ESEC/SIGSOFT FSE, 2015)

Mantis: Efficient Predictions of Execution Time, Energy Usage, Memory Usage and Network Usage on Smart Mobile Devices. - Yongin Kwon; Sangmin Lee; Hayoon Yi; Donghyun Kwon; Seungjun Yang; Byung-Gon Chun; Ling Huang 001; Petros Maniatis; Mayur Naik; Yunheung Paek (IEEE Trans. Mob. Comput., 2015)

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

On Incremental Core-Guided MaxSAT Solving. - Xujie Si; Xin Zhang 035; Vasco Manquinho; Mikolás Janota; Alexey Ignatiev; Mayur Naik (CP, 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)

APISan: Sanitizing API Usages through Semantic Cross-Checking. - Insu Yun; Changwoo Min; Xujie Si; Yeongjin Jang; Taesoo Kim; Mayur Naik (USENIX Security Symposium, 2016)

Maximum Satisfiability in Software Analysis: Applications and Techniques. - Xujie Si; Xin Zhang 035; Radu Grigore; Mayur Naik (CAV (1), 2017)

Constraint-Based Synthesis of Datalog Programs. - Aws Albarghouthi; Paraschos Koutris; Mayur Naik; Calvin Smith (CP, 2017)

Combining the logical and the probabilistic in program analysis. - Xin Zhang 035; Xujie Si; Mayur Naik (MAPL@PLDI, 2017)

Effective interactive resolution of static analysis alarms. - Xin Zhang 035; Radu Grigore; Xujie Si; Mayur Naik (Proc. ACM Program. Lang., 2017)

Effective Program Debloating via Reinforcement Learning. - Kihong Heo; Woosuk Lee; Pardis Pashakhanloo; Mayur Naik (CCS, 2018)

FEAST'18 - 2018 Workshop on Forming an Ecosystem around Software Transformation. - Yan Shoshitaishvili; Mayur Naik (CCS, 2018)

Learning Loop Invariants for Program Verification. - Xujie Si; Hanjun Dai; Mukund Raghothaman; Mayur Naik; Le Song (NeurIPS, 2018)

Accelerating search-based program synthesis using learned probabilistic models. - Woosuk Lee; Kihong Heo; Rajeev Alur; Mayur Naik (PLDI, 2018)

User-guided program reasoning using Bayesian inference. - Mukund Raghothaman; Sulekha Kulkarni; Kihong Heo; Mayur Naik (PLDI, 2018)

Syntax-guided synthesis of Datalog programs. - Xujie Si; Woosuk Lee; Richard Zhang 004; Aws Albarghouthi; Paraschos Koutris; Mayur Naik (ESEC/SIGSOFT FSE, 2018)

Learning a Meta-Solver for Syntax-Guided Program Synthesis. - Xujie Si; Yuan Yang; Hanjun Dai; Mayur Naik; Le Song (ICLR (Poster), 2019)

Learning Neurosymbolic Generative Models via Program Synthesis. - Halley Young; Osbert Bastani; Mayur Naik (ICML, 2019)

Synthesizing Datalog Programs using Numerical Relaxation. - Xujie Si; Mukund Raghothaman; Kihong Heo; Mayur Naik (IJCAI, 2019)

Continuously reasoning about programs using differential Bayesian inference. - Kihong Heo; Mukund Raghothaman; Xujie Si; Mayur Naik (PLDI, 2019)

Rethinking Static Analysis by Combining Discrete and Continuous Reasoning. - Mayur Naik (SAS, 2019)

PolyDroid: Learning-Driven Specialization of Mobile Applications. - Brian Heath; Neelay Velingker; Osbert Bastani; Mayur Naik (CoRR, 2019)

Code2Inv: A Deep Learning Framework for Program Verification. - Xujie Si; Aaditya Naik; Hanjun Dai; Mayur Naik; Le Song (CAV (2), 2020)

Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs. - Elizabeth Dinella; Hanjun Dai; Ziyang Li; Mayur Naik; Le Song; Ke Wang (ICLR, 2020)

Generating Programmatic Referring Expressions via Program Synthesis. - Jiani Huang; Calvin Smith; Osbert Bastani; Rishabh Singh; Aws Albarghouthi; Mayur Naik (ICML, 2020)

Provenance-guided synthesis of Datalog programs. - Mukund Raghothaman; Jonathan Mendelson; David Zhao 001; Mayur Naik; Bernhard Scholz (Proc. ACM Program. Lang., 2020)

GENSYNTH: Synthesizing Datalog Programs without Language Bias. - Jonathan Mendelson; Aaditya Naik; Mukund Raghothaman; Mayur Naik (AAAI, 2021)

Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning. - Jiani Huang; Ziyang Li; Binghong Chen; Karan Samel; Mayur Naik; Le Song; Xujie Si (NeurIPS, 2021)

Example-guided synthesis of relational queries. - Aalok Thakkar; Aaditya Naik; Nathaniel Sands; Rajeev Alur; Mayur Naik; Mukund Raghothaman (PLDI, 2021)

ARBITRAR: User-Guided API Misuse Detection. - Ziyang Li; Aravind Machiry; Binghong Chen; Mayur Naik; Ke Wang; Le Song (SP, 2021)

Sporq: An Interactive Environment for Exploring Code using Query-by-Example. - Aaditya Naik; Jonathan Mendelson; Nathaniel Sands; Yuepeng Wang 001; Mayur Naik; Mukund Raghothaman (UIST, 2021)

PacJam: Securing Dependencies Continuously via Package-Oriented Debloating. - Pardis Pashakhanloo; Aravind Machiry; Hyon-Young Choi; Anthony Canino; Kihong Heo; Insup Lee 001; Mayur Naik (AsiaCCS, 2022)

CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation. - Pardis Pashakhanloo; Aaditya Naik; Yuepeng Wang 001; Hanjun Dai; Petros Maniatis; Mayur Naik (ICLR, 2022)

Learning to Select Pivotal Samples for Meta Re-weighting. - Yinjun Wu; Adam Stein; Jacob Gardner; Mayur Naik (AAAI, 2023)

Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. - Hanlin Zhang 002; Jiani Huang; Ziyang Li; Mayur Naik; Eric P. Xing (ACL (Findings), 2023)

Do Machine Learning Models Learn Statistical Rules Inferred from Data? - Aaditya Naik; Yinjun Wu; Mayur Naik; Eric Wong 001 (ICML, 2023)

Do Machine Learning Models Learn Common Sense? - Aaditya Naik; Yinjun Wu; Mayur Naik; Eric Wong 001 (CoRR, 2023)

LASER: Neuro-Symbolic Learning of Semantic Video Representations. - Jiani Huang; Ziyang Li; David Jacobs; Mayur Naik; Ser-Nam Lim (CoRR, 2023)

Rectifying Group Irregularities in Explanations for Distribution Shift. - Adam Stein; Yinjun Wu; Eric Wong 001; Mayur Naik (CoRR, 2023)

MDB: Interactively Querying Datasets and Models. - Aaditya Naik; Adam Stein; Yinjun Wu; Eric Wong 001; Mayur Naik (CoRR, 2023)

Program Structure Aware Precondition Generation. - Elizabeth Dinella; Shuvendu K. Lahiri; Mayur Naik (CoRR, 2023)

Scallop: A Language for Neurosymbolic Programming. - Ziyang Li; Jiani Huang; Mayur Naik (Proc. ACM Program. Lang., 2023)

Relational Query Synthesis ⋈ Decision Tree Learning. - Aaditya Naik; Aalok Thakkar; Adam Stein; Rajeev Alur; Mayur Naik (Proc. VLDB Endow., 2023)

DeepMerge: Learning to Merge Programs. - Elizabeth Dinella; Todd Mytkowicz; Alexey Svyatkovskiy; Christian Bird; Mayur Naik; Shuvendu K. Lahiri (IEEE Trans. Software Eng., 2023)

Synthesizing Formal Network Specifications From Input-Output Examples. - Haoxian Chen 001; Chenyuan Wu; Andrew Zhao; Mukund Raghothaman; Mayur Naik; Boon Thau Loo (IEEE/ACM Trans. Netw., 2023)

Mobius: Synthesizing Relational Queries with Recursive and Invented Predicates. - Aalok Thakkar; Nathaniel Sands; George Petrou; Rajeev Alur; Mayur Naik; Mukund Raghothaman (Proc. ACM Program. Lang., 2023)

Relational Programming with Foundational Models. - Ziyang Li; Jiani Huang; Jason Liu; Felix Zhu; Eric Zhao 007; William Dodds; Neelay Velingker; Rajeev Alur; Mayur Naik (AAAI, 2024)

Towards Compositionality in Concept Learning. - Adam Stein; Aaditya Naik; Yinjun Wu; Mayur Naik; Eric Wong 001 (ICML, 2024)

DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation. - Yinjun Wu; Mayank Keoliya; Kan Chen; Neelay Velingker; Ziyang Li; Emily J. Getzen; Qi Long; Mayur Naik; Ravi B. Parikh; Eric Wong 001 (ICML, 2024)

Data-Efficient Learning with Neural Programs. - Alaia Solko-Breslin; Seewon Choi; Ziyang Li; Neelay Velingker; Rajeev Alur; Mayur Naik; Eric Wong 001 (NeurIPS, 2024)

Inferring Natural Preconditions via Program Transformation. - Elizabeth Dinella; Shuvendu K. Lahiri; Mayur Naik (SIGSOFT FSE Companion, 2024)

TYGR: Type Inference on Stripped Binaries using Graph Neural Networks. - Chang Zhu; Ziyang Li; Anton Xue; Ati Priya Bajaj; Wil Gibbs; Yibo Liu; Rajeev Alur; Tiffany Bao; Hanjun Dai; Adam Doupé; Mayur Naik; Yan Shoshitaishvili; et al. (USENIX Security Symposium, 2024)

LLM-Assisted Static Analysis for Detecting Security Vulnerabilities. - Ziyang Li; Saikat Dutta 001; Mayur Naik (CoRR, 2024)

Dolphin: A Programmable Framework for Scalable Neurosymbolic Learning. - Aaditya Naik; Jason Liu; Claire Wang; Saikat Dutta 001; Mayur Naik; Eric Wong 001 (CoRR, 2024)

Relational Programming with Foundation Models. - Ziyang Li; Jiani Huang; Jason Liu; Felix Zhu; Eric Zhao 007; William Dodds; Neelay Velingker; Rajeev Alur; Mayur Naik (CoRR, 2024)

Neurosymbolic Programming in Scallop: Principles and Practice. - Ziyang Li; Jiani Huang; Jason Liu; Mayur Naik (Found. Trends Program. Lang., 2024)

TorchQL: A Programming Framework for Integrity Constraints in Machine Learning. - Aaditya Naik; Adam Stein; Yinjun Wu; Mayur Naik; Eric Wong 001 (Proc. ACM Program. Lang., 2024)

LASER: A Neuro-Symbolic Framework for Learning Spatio-Temporal Scene Graphs with Weak Supervision. - Jiani Huang; Ziyang Li; Mayur Naik; Ser-Nam Lim (ICLR, 2025)

IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities. - Ziyang Li; Saikat Dutta 001; Mayur Naik (ICLR, 2025)

Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities. - Avishree Khare; Saikat Dutta 001; Ziyang Li; Alaia Solko-Breslin; Rajeev Alur; Mayur Naik (ICST, 2025)

Where's the Bug? Attention Probing for Scalable Fault Localization. - Adam Stein; Arthur Wayne; Aaditya Naik; Mayur Naik; Eric Wong 001 (CoRR, 2025)

Lobster: A GPU-Accelerated Framework for Neurosymbolic Programming. - Paul Biberstein; Ziyang Li; Joseph Devietti; Mayur Naik (CoRR, 2025)

The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models. - Adam Stein; Aaditya Naik; Neelay Velingker; Mayur Naik; Eric Wong 001 (CoRR, 2025)