Vijayaraghavan Murali

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 30

Top Topics

Contrast Set Mining

Bug Localization

Symbolic Execution

Reinforcement Learning

Top Venues

ESEC/SIGSOFT FSE

Publications

Vijayaraghavan Murali, Chandra Shekhar Maddila, Imad Ahmad, Michael Bolin, Daniel Cheng, Negar Ghorbani, Renuka Fernandez, Nachiappan Nagappan, Peter C. Rigby
AI-Assisted Code Authoring at Scale: Fine-Tuning, Deploying, and Mixed Methods Evaluation. Proc. ACM Softw. Eng. 1 (FSE) (2024)
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
Multi-line AI-Assisted Code Authoring. SIGSOFT FSE Companion (2024)
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
AI-Assisted SQL Authoring at Industry Scale. CoRR (2024)
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
Multi-line AI-assisted Code Authoring. CoRR (2024)
Jürgen Cito, Isil Dillig, Vijayaraghavan Murali, Satish Chandra
Counterfactual Explanations for Models of Code. Software Engineering (2024)
Vijayaraghavan Murali, Chandra Shekhar Maddila, Imad Ahmad, Michael Bolin, Daniel Cheng, Negar Ghorbani, Renuka Fernandez, Nachiappan Nagappan
CodeCompose: A Large-Scale Industrial Deployment of AI-assisted Code Authoring. CoRR (2023)
Moritz Beller, Hongyu Li, Vivek Nair, Vijayaraghavan Murali, Imad Ahmad, Jürgen Cito, Drew Carlson, Gareth Ari Aye, Wes Dyer
Learning to Learn to Predict Performance Regressions in Production at Meta. AST (2023)
Gökalp Demirci, Vijayaraghavan Murali, Imad Ahmad, Rajeev Rao, Gareth Ari Aye
Detecting Privacy-Sensitive Code Changes with Language Modeling. MSR (2022)
Wen Zhou, Seohyun Kim, Vijayaraghavan Murali, Gareth Ari Aye
Improving Code Autocompletion with Transfer Learning. ICSE (SEIP) (2022)
Moritz Beller, Hongyu Li, Vivek Nair, Vijayaraghavan Murali, Imad Ahmad, Jürgen Cito, Drew Carlson, Gareth Ari Aye, Wes Dyer
Learning to Learn to Predict Performance Regressions in Production at Meta. CoRR (2022)
Jürgen Cito, Isil Dillig, Vijayaraghavan Murali, Satish Chandra
Counterfactual Explanations for Models of Code. ICSE (SEIP) (2022)
Wen Zhou, Seohyun Kim, Vijayaraghavan Murali, Gareth Ari Aye
Improving Code Autocompletion with Transfer Learning. CoRR (2021)
Jürgen Cito, Isil Dillig, Vijayaraghavan Murali, Satish Chandra
Counterfactual Explanations for Models of Code. CoRR (2021)
Vijayaraghavan Murali, Lee Gross, Rebecca Qian, Satish Chandra
Industry-Scale IR-Based Bug Localization: A Perspective from Facebook. ICSE (SEIP) (2021)
Jürgen Cito, Isil Dillig, Seohyun Kim, Vijayaraghavan Murali, Satish Chandra
Explaining mispredictions of machine learning models using rule induction. ESEC/SIGSOFT FSE (2021)
Vijayaraghavan Murali, Edward Yao, Umang Mathur, Satish Chandra
Scalable Statistical Root Cause Analysis on App Telemetry. ICSE (SEIP) (2021)
Rebecca Qian, Yang Yu, Wonhee Park, Vijayaraghavan Murali, Stephen Fink, Satish Chandra
contrast set mining. ICSE (SEIP) (2020)
Vijayaraghavan Murali, Lee Gross, Rebecca Qian, Satish Chandra
Industry-scale IR-based Bug Localization: A Perspective from Facebook. CoRR (2020)
Vijayaraghavan Murali, Edward Yao, Umang Mathur, Satish Chandra
Scalable Statistical Root Cause Analysis on App Telemetry. CoRR (2020)
Michael Pradel, Vijayaraghavan Murali, Rebecca Qian, Mateusz Machalica, Erik Meijer, Satish Chandra
Scaffle: bug localization on millions of files. ISSTA (2020)
Jason Liu, Seohyun Kim, Vijayaraghavan Murali, Swarat Chaudhuri, Satish Chandra
Neural query expansion for code search. MAPL@PLDI (2019)
Rebecca Qian, Yang Yu, Wonhee Park, Vijayaraghavan Murali, Stephen Fink, Satish Chandra
Debugging Crashes using Continuous Contrast Set Mining. CoRR (2019)
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri
Programmatically Interpretable Reinforcement Learning. CoRR (2018)
Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri
Programmatically Interpretable Reinforcement Learning. ICML (2018)
Vijayaraghavan Murali, Letao Qi, Swarat Chaudhuri, Chris Jermaine
Neural Sketch Learning for Conditional Program Generation. ICLR (2018)
Binhang Yuan, Vijayaraghavan Murali, Christopher M. Jermaine
Abridging source code. Proc. ACM Program. Lang. 1 (OOPSLA) (2017)
Vijayaraghavan Murali, Swarat Chaudhuri, Chris Jermaine
Bayesian specification learning for finding API usage errors. ESEC/SIGSOFT FSE (2017)
Vijayaraghavan Murali, Swarat Chaudhuri, Chris Jermaine
Bayesian Sketch Learning for Program Synthesis. CoRR (2017)
Vijayaraghavan Murali, Swarat Chaudhuri, Chris Jermaine
Finding Likely Errors with Bayesian Specifications. CoRR (2017)
Duc-Hiep Chu, Joxan Jaffar, Vijayaraghavan Murali
Incremental Quantitative Analysis on Dynamic Costs. CoRR (2016)
Duc-Hiep Chu, Joxan Jaffar, Vijayaraghavan Murali
Lazy Symbolic Execution for Enhanced Learning. RV (2014)
Joxan Jaffar, Vijayaraghavan Murali
A path-sensitively sliced control flow graph. SIGSOFT FSE (2014)
Vijayaraghavan Murali, Nishant Sinha, Emina Torlak, Satish Chandra
What Gives? A Hybrid Algorithm for Error Trace Explanation. VSTTE (2014)
Joxan Jaffar, Vijayaraghavan Murali, Jorge A. Navas
Boosting concolic testing via interpolation. ESEC/SIGSOFT FSE (2013)
Joxan Jaffar, Vijayaraghavan Murali, Jorge A. Navas, Andrew E. Santosa
Path-Sensitive Backward Slicing. SAS (2012)
Joxan Jaffar, Vijayaraghavan Murali, Jorge A. Navas, Andrew E. Santosa
TRACER: A Symbolic Execution Tool for Verification. CAV (2012)
Verdi March, Vijayaraghavan Murali, Yong Meng Teo, Simon See, James T. Himer
Towards Predictive Modeling of Message-Passing Communication. HPCC (2009)