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Computer Science

D-Index
41
Citations
7503
World Ranking
8818
National Ranking
3768

Overview

Madanlal Musuvathi is affiliated with Microsoft in the United States. Their research contributions primarily lie in the field of Computer Science, with a focus on several interconnected subfields and topics.

The main fields of study associated with Musuvathi's work include:

  • Artificial Intelligence
  • Information Systems
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Software

Their research topics cover multiple areas, notably:

  • Parallel Computing and Optimization Techniques
  • Software Engineering Research
  • Software Testing and Debugging Techniques
  • Ferroelectric and Negative Capacitance Devices
  • Security and Verification in Computing
  • Distributed Systems and Fault Tolerance
  • Advanced Memory and Neural Computing

Musuvathi has authored several papers published between 2021 and 2023. Key publications include:

  • "Interactive Code Generation via Test-Driven User-Intent Formalization," 2022, arXiv (Cornell University)
  • "Fault-Aware Neural Code Rankers," 2022, arXiv (Cornell University)
  • "Safe-by-default Concurrency for Modern Programming Languages," 2021, ACM Transactions on Programming Languages and Systems
  • "GC3: An Optimizing Compiler for GPU Collective Communication," 2022, arXiv (Cornell University)
  • "WAFFLE: Exposing Memory Ordering Bugs Efficiently with Active Delay Injection," 2023, Zenodo (CERN European Organization for Nuclear Research)

The majority of their publications have appeared in arXiv (Cornell University), with additional contributions to ACM Transactions on Programming Languages and Systems as well as Zenodo (CERN European Organization for Nuclear Research).

Frequent co-authors working alongside Musuvathi include:

  • Shuvendu K. Lahiri
  • Jeevana Priya Inala
  • Jianfeng Gao
  • Saeed Maleki
  • Lun Liu

Best Publications

  • Finding and reproducing Heisenbugs in concurrent programs

    Madanlal Musuvathi;Shaz Qadeer;Thomas Ball;Gerard Basler

  • Iterative context bounding for systematic testing of multithreaded programs

    Madanlal Musuvathi;Shaz Qadeer

  • CMC: a pragmatic approach to model checking real code

    Madanlal Musuvathi;David Y. W. Park;Andy Chou;Dawson R. Engler

  • Using model checking to find serious file system errors

    Junfeng Yang;Paul Twohey;Dawson Engler;Madanlal Musuvathi

  • LiteRace: effective sampling for lightweight data-race detection

    Daniel Marino;Madanlal Musuvathi;Satish Narayanasamy

  • A randomized scheduler with probabilistic guarantees of finding bugs

    Sebastian Burckhardt;Pravesh Kothari;Madanlal Musuvathi;Santosh Nagarakatte

  • Effective data-race detection for the kernel

    John Erickson;Madanlal Musuvathi;Sebastian Burckhardt;Kirk Olynyk

  • CHET: an optimizing compiler for fully-homomorphic neural-network inferencing

    Roshan Dathathri;Olli Saarikivi;Hao Chen;Kim Laine

  • Model checking large network protocol implementations

    Madanlal Musuvathi;Dawson R. Engler

  • On the verification problem for weak memory models

    Mohamed Faouzi Atig;Ahmed Bouajjani;Sebastian Burckhardt;Madanlal Musuvathi

  • Static analysis versus software model checking for bug finding

    Dawson Engler;Madanlal Musuvathi

  • Line-up: a complete and automatic linearizability checker

    Sebastian Burckhardt;Chris Dern;Madanlal Musuvathi;Roy Tan

  • Effective Program Verification for Relaxed Memory Models

    Sebastian Burckhardt;Madanlal Musuvathi

  • EVA: an encrypted vector arithmetic language and compiler for efficient homomorphic computation

    Roshan Dathathri;Blagovesta Kostova;Olli Saarikivi;Wei Dai

  • Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup

    Yufei Ding;Yue Zhao;Xipeng Shen;Madanlal Musuvathi

  • Retro: Targeted resource management in multi-tenant distributed systems

    Jonathan Mace;Peter Bodik;Rodrigo Fonseca;Madanlal Musuvathi

  • Fair stateless model checking

    Madanlal Musuvathi;Shaz Qadeer

  • End-to-end sequential consistency

    Abhayendra Singh;Satish Narayanasamy;Daniel Marino;Todd Millstein

  • Data-parallel finite-state machines

    Todd Mytkowicz;Madanlal Musuvathi;Wolfram Schulte

  • DRFX: a simple and efficient memory model for concurrent programming languages

    Daniel Marino;Abhayendra Singh;Todd Millstein;Madanlal Musuvathi

  • CHESS: A Systematic Testing Tool for Concurrent Software

    Madanlal Musuvathi;Shaz Qadeer

  • A combination method for generating interpolants

    Greta Yorsh;Madanlal Musuvathi

  • Finding protocol manipulation attacks

    Nupur Kothari;Ratul Mahajan;Todd Millstein;Ramesh Govindan

Frequent Co-Authors

Todd Millstein
Todd Millstein University of California, Los Angeles
Shaz Qadeer
Shaz Qadeer Microsoft (United States)
Dawson Engler
Dawson Engler Stanford University
Satish Narayanasamy
Satish Narayanasamy University of Michigan–Ann Arbor
Thomas Ball
Thomas Ball Microsoft (United States)
Shuvendu K. Lahiri
Shuvendu K. Lahiri Microsoft (United States)
Emre Kiciman
Emre Kiciman Microsoft (United States)
Benjamin Livshits
Benjamin Livshits Imperial College London
David L. Dill
David L. Dill Stanford University
Rodrigo Fonseca
Rodrigo Fonseca Brown University

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