Vijayaraghavan Murali

42 papers A* 2A 2B 2C 3Journal 18Unranked 15
YearRankTypeTitle / Venue / Authors
2025 J jnl
AI-Assisted Fixes to Code Review Comments at Scale.
CoRR
Chandra Shekhar Maddila, Negar Ghorbani, James Saindon, Parth Thakkar, Vijayaraghavan Murali, Rui Abreu, Jingyue Shen, Brian Zhou, Nachiappan Nagappan, Peter C. Rigby
2025 — conf
AI-Assisted SQL Authoring at Industry Scale.
SEIP@ICSE
Chandra Shekhar Maddila, Negar Ghorbani, Kosay Jabre, Vijayaraghavan Murali, Edwin Kim, Parth Thakkar, Nikolay Pavlovich Laptev, Olivia Harman, Diana Hsu, Rui Abreu, Peter C. Rigby
2025 J jnl
Agentic Program Repair from Test Failures at Scale: A Neuro-symbolic approach with static analysis and test execution feedback.
CoRR
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, Parth Thakkar, Renuka Fernandez, Kristian Kristensen, Sivan Barzily, Sherry Chen, Rui Abreu, Nachiappan Nagappan, Payam Shodjai, Killian Murphy, James Everingham, Aparna Ramani, Peter C. Rigby
2025 — conf
Moving Faster and Reducing Risk: Using LLMs in Release Deployment.
SEIP@ICSE
Rui Abreu, Vijayaraghavan Murali, Peter C. Rigby, Chandra Shekhar Maddila, Weiyan Sun, Jun Ge, Kaavya Chinniah, Audris Mockus, Megh Mehta, Nachiappan Nagappan
2024 J jnl
AI-Assisted Code Authoring at Scale: Fine-Tuning, Deploying, and Mixed Methods Evaluation.
Proc. ACM Softw. Eng.
Vijayaraghavan Murali, Chandra Shekhar Maddila, Imad Ahmad, Michael Bolin, Daniel Cheng, Negar Ghorbani, Renuka Fernandez, Nachiappan Nagappan, Peter C. Rigby
2024 J jnl
AI-Assisted SQL Authoring at Industry Scale.
CoRR
Chandra Shekhar Maddila, Negar Ghorbani, Kosay Jabre, Vijayaraghavan Murali, Edwin Kim, Parth Thakkar, Nikolay Pavlovich Laptev, Olivia Harman, Diana Hsu, Rui Abreu, Peter C. Rigby
2024 C conf
Counterfactual Explanations for Models of Code.
Software Engineering
Jürgen Cito, Isil Dillig, Vijayaraghavan Murali, Satish Chandra
2024 J jnl
Moving Faster and Reducing Risk: Using LLMs in Release Deployment.
CoRR
Rui Abreu, Vijayaraghavan Murali, Peter C. Rigby, Chandra Shekhar Maddila, Weiyan Sun, Jun Ge, Kaavya Chinniah, Audris Mockus, Megh Mehta, Nachiappan Nagappan
2024 — conf
Multi-line AI-Assisted Code Authoring.
SIGSOFT FSE Companion
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
2024 J jnl
Multi-line AI-assisted Code Authoring.
CoRR
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
2023 J jnl
CodeCompose: A Large-Scale Industrial Deployment of AI-assisted Code Authoring.
CoRR
Vijayaraghavan Murali, Chandra Shekhar Maddila, Imad Ahmad, Michael Bolin, Daniel Cheng, Negar Ghorbani, Renuka Fernandez, Nachiappan Nagappan
2023 C conf
Learning to Learn to Predict Performance Regressions in Production at Meta.
AST
Moritz Beller, Hongyu Li, Vivek Nair, Vijayaraghavan Murali, Imad Ahmad, Jürgen Cito, Drew Carlson, Gareth Ari Aye, Wes Dyer
2022 — conf
Counterfactual Explanations for Models of Code.
ICSE (SEIP)
Jürgen Cito, Isil Dillig, Vijayaraghavan Murali, Satish Chandra
2022 A conf
Detecting Privacy-Sensitive Code Changes with Language Modeling.
MSR
Gökalp Demirci, Vijayaraghavan Murali, Imad Ahmad, Rajeev Rao, Gareth Ari Aye
2022 — conf
Improving Code Autocompletion with Transfer Learning.
ICSE (SEIP)
Wen Zhou, Seohyun Kim, Vijayaraghavan Murali, Gareth Ari Aye
2022 J jnl
Learning to Learn to Predict Performance Regressions in Production at Meta.
CoRR
Moritz Beller, Hongyu Li, Vivek Nair, Vijayaraghavan Murali, Imad Ahmad, Jürgen Cito, Drew Carlson, Gareth Ari Aye, Wes Dyer
2021 J jnl
Counterfactual Explanations for Models of Code.
CoRR
Jürgen Cito, Isil Dillig, Vijayaraghavan Murali, Satish Chandra
2021 — conf
Explaining mispredictions of machine learning models using rule induction.
ESEC/SIGSOFT FSE
Jürgen Cito, Isil Dillig, Seohyun Kim, Vijayaraghavan Murali, Satish Chandra
2021 J jnl
Improving Code Autocompletion with Transfer Learning.
CoRR
Wen Zhou, Seohyun Kim, Vijayaraghavan Murali, Gareth Ari Aye
2021 — conf
Industry-Scale IR-Based Bug Localization: A Perspective from Facebook.
ICSE (SEIP)
Vijayaraghavan Murali, Lee Gross, Rebecca Qian, Satish Chandra
2021 — conf
Scalable Statistical Root Cause Analysis on App Telemetry.
ICSE (SEIP)
Vijayaraghavan Murali, Edward Yao, Umang Mathur, Satish Chandra
2020 — conf
Debugging crashes using
ICSE (SEIP)
Rebecca Qian, Yang Yu, Wonhee Park, Vijayaraghavan Murali, Stephen Fink, Satish Chandra
2020 J jnl
Industry-scale IR-based Bug Localization: A Perspective from Facebook.
CoRR
Vijayaraghavan Murali, Lee Gross, Rebecca Qian, Satish Chandra
2020 A conf
Scaffle: bug localization on millions of files.
ISSTA
Michael Pradel, Vijayaraghavan Murali, Rebecca Qian, Mateusz Machalica, Erik Meijer, Satish Chandra
2020 J jnl
Scalable Statistical Root Cause Analysis on App Telemetry.
CoRR
Vijayaraghavan Murali, Edward Yao, Umang Mathur, Satish Chandra
2019 J jnl
Debugging Crashes using Continuous Contrast Set Mining.
CoRR
Rebecca Qian, Yang Yu, Wonhee Park, Vijayaraghavan Murali, Stephen Fink, Satish Chandra
2019 — conf
Neural query expansion for code search.
MAPL@PLDI
Jason Liu, Seohyun Kim, Vijayaraghavan Murali, Swarat Chaudhuri, Satish Chandra
2018 — conf
Neural Sketch Learning for Conditional Program Generation.
ICLR
Vijayaraghavan Murali, Letao Qi, Swarat Chaudhuri, Chris Jermaine
2018 A* conf
Programmatically Interpretable Reinforcement Learning.
ICML
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri
2018 J jnl
Programmatically Interpretable Reinforcement Learning.
CoRR
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri
2017 J jnl
Abridging source code.
Proc. ACM Program. Lang.
Binhang Yuan, Vijayaraghavan Murali, Christopher M. Jermaine
2017 J jnl
Bayesian Sketch Learning for Program Synthesis.
CoRR
Vijayaraghavan Murali, Swarat Chaudhuri, Chris Jermaine
2017 — conf
Bayesian specification learning for finding API usage errors.
ESEC/SIGSOFT FSE
Vijayaraghavan Murali, Swarat Chaudhuri, Chris Jermaine
2017 J jnl
Finding Likely Errors with Bayesian Specifications.
CoRR
Vijayaraghavan Murali, Swarat Chaudhuri, Chris Jermaine
2016 J jnl
Incremental Quantitative Analysis on Dynamic Costs.
CoRR
Duc-Hiep Chu, Joxan Jaffar, Vijayaraghavan Murali
2014 — conf
A path-sensitively sliced control flow graph.
SIGSOFT FSE
Joxan Jaffar, Vijayaraghavan Murali
2014 B conf
Lazy Symbolic Execution for Enhanced Learning.
RV
Duc-Hiep Chu, Joxan Jaffar, Vijayaraghavan Murali
2014 — conf
What Gives? A Hybrid Algorithm for Error Trace Explanation.
VSTTE
Vijayaraghavan Murali, Nishant Sinha, Emina Torlak, Satish Chandra
2013 — conf
Boosting concolic testing via interpolation.
ESEC/SIGSOFT FSE
Joxan Jaffar, Vijayaraghavan Murali, Jorge A. Navas
2012 B conf
Path-Sensitive Backward Slicing.
SAS
Joxan Jaffar, Vijayaraghavan Murali, Jorge A. Navas, Andrew E. Santosa
2012 A* conf
TRACER: A Symbolic Execution Tool for Verification.
CAV
Joxan Jaffar, Vijayaraghavan Murali, Jorge A. Navas, Andrew E. Santosa
2009 C conf
Towards Predictive Modeling of Message-Passing Communication.
HPCC
Verdi March, Vijayaraghavan Murali, Yong Meng Teo, Simon See, James T. Himer