Towards Predictive Modeling of Message-Passing Communication. - Verdi March; Vijayaraghavan Murali; Yong Meng Teo; Simon See; James T. Himer (HPCC, 2009)

TRACER: A Symbolic Execution Tool for Verification. - Joxan Jaffar; Vijayaraghavan Murali; Jorge A. Navas; Andrew E. Santosa (CAV, 2012)

Path-Sensitive Backward Slicing. - Joxan Jaffar; Vijayaraghavan Murali; Jorge A. Navas; Andrew E. Santosa (SAS, 2012)

Boosting concolic testing via interpolation. - Joxan Jaffar; Vijayaraghavan Murali; Jorge A. Navas (ESEC/SIGSOFT FSE, 2013)

Lazy Symbolic Execution for Enhanced Learning. - Duc-Hiep Chu; Joxan Jaffar; Vijayaraghavan Murali (RV, 2014)

A path-sensitively sliced control flow graph. - Joxan Jaffar; Vijayaraghavan Murali (SIGSOFT FSE, 2014)

What Gives? A Hybrid Algorithm for Error Trace Explanation. - Vijayaraghavan Murali; Nishant Sinha 001; Emina Torlak; Satish Chandra 001 (VSTTE, 2014)

Incremental Quantitative Analysis on Dynamic Costs. - Duc-Hiep Chu; Joxan Jaffar; Vijayaraghavan Murali (CoRR, 2016)

Bayesian specification learning for finding API usage errors. - Vijayaraghavan Murali; Swarat Chaudhuri; Chris Jermaine (ESEC/SIGSOFT FSE, 2017)

Finding Likely Errors with Bayesian Specifications. - Vijayaraghavan Murali; Swarat Chaudhuri; Chris Jermaine (CoRR, 2017)

Bayesian Sketch Learning for Program Synthesis. - Vijayaraghavan Murali; Swarat Chaudhuri; Chris Jermaine (CoRR, 2017)

Abridging source code. - Binhang Yuan; Vijayaraghavan Murali; Christopher M. Jermaine (Proc. ACM Program. Lang., 2017)

Neural Sketch Learning for Conditional Program Generation. - Vijayaraghavan Murali; Letao Qi; Swarat Chaudhuri; Chris Jermaine (ICLR, 2018)

Programmatically Interpretable Reinforcement Learning. - Abhinav Verma 001; Vijayaraghavan Murali; Rishabh Singh; Pushmeet Kohli; Swarat Chaudhuri (ICML, 2018)

Neural query expansion for code search. - Jason Liu; Seohyun Kim 001; Vijayaraghavan Murali; Swarat Chaudhuri; Satish Chandra 001 (MAPL@PLDI, 2019)

Debugging Crashes using Continuous Contrast Set Mining. - Rebecca Qian; Yang Yu; Wonhee Park; Vijayaraghavan Murali; Stephen Fink; Satish Chandra 001 (CoRR, 2019)

Debugging crashes using continuous contrast set mining. - Rebecca Qian; Yang Yu; Wonhee Park; Vijayaraghavan Murali; Stephen Fink; Satish Chandra 001 (ICSE (SEIP), 2020)

Scaffle: bug localization on millions of files. - Michael Pradel; Vijayaraghavan Murali; Rebecca Qian; Mateusz Machalica; Erik Meijer 001; Satish Chandra 001 (ISSTA, 2020)

Industry-Scale IR-Based Bug Localization: A Perspective from Facebook. - Vijayaraghavan Murali; Lee Gross; Rebecca Qian; Satish Chandra 001 (ICSE (SEIP), 2021)

Scalable Statistical Root Cause Analysis on App Telemetry. - Vijayaraghavan Murali; Edward Yao; Umang Mathur 001; Satish Chandra 001 (ICSE (SEIP), 2021)

Explaining mispredictions of machine learning models using rule induction. - Jürgen Cito; Isil Dillig; Seohyun Kim 001; Vijayaraghavan Murali; Satish Chandra 001 (ESEC/SIGSOFT FSE, 2021)

Improving Code Autocompletion with Transfer Learning. - Wen Zhou; Seohyun Kim 001; Vijayaraghavan Murali; Gareth Ari Aye (ICSE (SEIP), 2022)

Detecting Privacy-Sensitive Code Changes with Language Modeling. - Gökalp Demirci; Vijayaraghavan Murali; Imad Ahmad; Rajeev Rao; Gareth Ari Aye (MSR, 2022)

Learning to Learn to Predict Performance Regressions in Production at Meta. - Moritz Beller; Hongyu Li; Vivek Nair; Vijayaraghavan Murali; Imad Ahmad; Jürgen Cito; Drew Carlson; Gareth Ari Aye; Wes Dyer (AST, 2023)

CodeCompose: A Large-Scale Industrial Deployment of AI-assisted Code Authoring. - Vijayaraghavan Murali; Chandra Shekhar Maddila; Imad Ahmad; Michael Bolin; Daniel Cheng; Negar Ghorbani; Renuka Fernandez; Nachiappan Nagappan (CoRR, 2023)

Counterfactual Explanations for Models of Code. - Jürgen Cito; Isil Dillig; Vijayaraghavan Murali; Satish Chandra 001 (Software Engineering, 2024)

Multi-line AI-Assisted Code Authoring. - Omer Dunay; Daniel Cheng; Adam Tait; Parth Thakkar; Peter C. Rigby; Andy Chiu; Imad Ahmad; Arun Ganesan; Chandra Shekhar Maddila; Vijayaraghavan Murali; Ali Tayyebi; Nachiappan Nagappan (SIGSOFT FSE Companion, 2024)

AI-Assisted SQL Authoring at Industry Scale. - Chandra Shekhar Maddila; Negar Ghorbani; Kosay Jabre; Vijayaraghavan Murali; Edwin Kim; Parth Thakkar; Nikolay Pavlovich Laptev; Olivia Harman; Diana Hsu; Rui Abreu 001; Peter C. Rigby (CoRR, 2024)

Moving Faster and Reducing Risk: Using LLMs in Release Deployment. - Rui Abreu 001; Vijayaraghavan Murali; Peter C. Rigby; Chandra Shekhar Maddila; Weiyan Sun; Jun Ge; Kaavya Chinniah; Audris Mockus; Megh Mehta; Nachiappan Nagappan (CoRR, 2024)

AI-Assisted Code Authoring at Scale: Fine-Tuning, Deploying, and Mixed Methods Evaluation. - Vijayaraghavan Murali; Chandra Shekhar Maddila; Imad Ahmad; Michael Bolin; Daniel Cheng; Negar Ghorbani; Renuka Fernandez; Nachiappan Nagappan; Peter C. Rigby (Proc. ACM Softw. Eng., 2024)

AI-Assisted Fixes to Code Review Comments at Scale. - Chandra Shekhar Maddila; Negar Ghorbani; James Saindon; Parth Thakkar; Vijayaraghavan Murali; Rui Abreu 001; Jingyue Shen; Brian Zhou; Nachiappan Nagappan; Peter C. Rigby (CoRR, 2025)

Agentic Program Repair from Test Failures at Scale: A Neuro-symbolic approach with static analysis and test execution feedback. - Chandra Shekhar Maddila; Adam Tait; Claire Chang; Daniel Cheng; Nauman Ahmad; Vijayaraghavan Murali; Marshall Roch; Arnaud Avondet; Aaron Meltzer; Victor Montalvao; Michael Hopko; Chris Waterson; et al. (CoRR, 2025)