I am a software engineer at Meta, working on developing machine leaning based solutions to industry-scale software engineering problems. My research aims to address practical problems in software development, such as bug attribution, root cause analysis, code generation/synthesis, etc. using machine learning solutions. Recently I am interested in representation learning for various software artifacts common in large scale industrial software development. The projects I have worked on have found significant industrial impact at Meta.

Publications

  1. Detecting Privacy-Sensitive Code Changes with Language Modeling
    Gokalp Demirci, Vijayaraghavan Murali, Imad Ahmad, Rajeev Rao, Gareth Ari Aye
    MSR 2022 Industry Track
  2. Counterfactual Explanations for Models of Code
    Jurgen Cito, Isil Dillig, Vijayaraghavan Murali, Satish Chandra
    ICSE SEIP 2022
  3. Improving Code Autocompletion with Transfer Learning
    Wen Zhou, Sonia Kim, Vijayaraghavan Murali, Ari Aye
    ICSE SEIP 2022
  4. Explaining mispredictions of machine learning models using rule induction
    Jurgen Cito, Isil Dillig, Sonia Kim, Vijayaraghavan Murali, Satish Chandra
    FSE 2021
  5. Industry-scale IR-based Bug Localization: A Perspective from Facebook
    Vijayaraghavan Murali, Lee Gross, Rebecca Qian, Satish Chandra
    ICSE SEIP 2021 - Distinguished Paper award
  6. Scalable Statistical Root Cause Analysis on App Telemetry
    Vijayaraghavan Murali, Edward Yao, Umang Mathur, Satish Chandra
    ICSE SEIP 2021
  7. Scaffle: bug localization on millions of files
    Michael Pradel, Vijayaraghavan Murali, Rebecca Qian, Mateusz Machalica, Erik Meijer, Satish Chandra
    ISSTA 2020
  8. Debugging crashes using continuous contrast set mining
    Rebecca Qian, Yang Yu, Wonhee Park, Vijayaraghavan Murali, Stephen Fink, Satish Chandra
    ICSE SEIP 2020
  9. Neural query expansion for code search
    Jason Liu, Sonia Kim, Vijayaraghavan Murali, Swarat Chaudhuri, Satish Chandra
    MAPL 2019
  10. Programmatically Interpretable Reinforcement Learning
    Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh, Pushmeet Kohli, Swarat Chaudhuri
    ICML 2018
  11. Neural Sketch Learning for Conditional Program Generation
    Vijayaraghavan Murali, Letao Qi, Swarat Chaudhuri, Chris Jermaine
    ICLR 2018
  12. Abridging Source Code
    Binhang Yuan, Vijayaraghavan Murali, Chris Jermaine
    OOPSLA 2017
  13. Bayesian Specification Learning for Finding API Usage Errors
    Vijayaraghavan Murali, Swarat Chaudhuri, Chris Jermaine
    FSE 2017
  14. A Path-Sensitively Sliced Control Flow Graph
    Joxan Jaffar, Vijayaraghavan Murali
    FSE 2014
  15. Lazy Symbolic Execution for Enhanced Learning
    Duc-Hiep Chu, Joxan Jaffar, Vijayaraghavan Murali
    RV 2014
  16. A Hybrid Algorithm for Error Trace Explanation
    Vijayaraghavan Murali, Nishant Sinha, Emina Torlak, Satish Chandra
    VSTTE 2014
  17. Boosting Concolic Testing via Interpolation
    Joxan Jaffar, Vijayaraghavan Murali, Jorge A. Navas
    FSE 2013
  18. Path-Sensitive Backward Slicing
    Joxan Jaffar, Vijayaraghavan Murali, Jorge A. Navas, Andrew E. Santosa
    SAS 2012
  19. TRACER: A Symbolic Execution Tool for Verification
    Joxan Jaffar, Vijayaraghavan Murali, Jorge A. Navas, Andrew E. Santosa
    CAV 2012
  20. Towards predictive modeling of message passing communication
    Verdi March, Vijayaraghavan Murali, Yong Meng Teo, Simon See, James T. Himer
    HPCC 2009

Blog Posts

Service

  • PLDI 2022
  • ISSTA 2020
  • CAV 2019
  • POPL 2015 (Artifact Committee)
  • FSE 2014 (Artifact Committee)

Bio

I have been a software engineer at Meta (Facebook) since 2018, where I work in developer infrastructure. Before, I was a Research Scientist (postdoc) at Rice University from 2015-2018, working with Swarat Chaudhuri on the Pliny project. Prior to that, I was a Ph.D. student at the National University of Singapore (NUS) from 2009-2014, advised by Joxan Jaffar. I interned at IBM Research India during my Ph.D., working with Satish Chandra. My Ph.D. background is originally in programming languages and formal methods, but my “ML coach” was Chris Jermaine during my postdoc at Rice. I obtained my B.Computing also from NUS in 2009.

My hometown is Chennai in south India. Outside research, I enjoy video games, backyard gardening, and traveling.