World's Best Scientists 2026 revealed!

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Computer Science

D-Index
42
Citations
6552
World Ranking
8473
National Ranking
3623

Research.com Recognitions

  • 2011 - ACM Distinguished Member

Overview

Satish Chandra is affiliated with Google in the United States, with a research focus primarily in Computer Science. Their scholarly output encompasses 24 publications in this field, with significant contributions to several specialized subfields including Information Systems, Software, Signal Processing, Industrial and Manufacturing Engineering, and Artificial Intelligence.

The topics covered in Satish Chandra's research include Software Engineering Research, Software Testing and Debugging Techniques, Advanced Malware Detection Techniques, Software Reliability and Analysis Research, Software Engineering Techniques and Practices, Explainable Artificial Intelligence (XAI), and Software System Performance and Reliability.

Frequent coauthors collaborating with Satish Chandra include Michael Pradel, Chakkrit Tantithamthavorn, Erik Meijer, Claire Le Goues, and Abhik Roychoudhury. These collaborations reflect ongoing engagement with experts in software engineering and artificial intelligence domains.

Satish Chandra's research has been disseminated through multiple publication venues. Notably, the scientist has published six papers in IEEE Software, four in arXiv (Cornell University), one in the Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, one in Communications of the ACM, and one in the SSRN Electronic Journal.

Recent publications reflect topics in software engineering and explainability in AI. Selected papers include:

  • "Automatic Program Repair" (2021, IEEE Software)
  • "Explainable AI for SE: Challenges and Future Directions" (2023, IEEE Software)
  • "AI in Software Engineering at Facebook" (2021, IEEE Software)
  • "Leveraging test plan quality to improve code review efficacy" (2022, Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering)
  • "What Do Developers Want From AI?" (2024, IEEE Software)

The scientist has been recognized as an ACM Distinguished Member since 2011.

Best Publications

  • SemFix: program repair via semantic analysis

    Hoang Duong Thien Nguyen;Dawei Qi;Abhik Roychoudhury;Satish Chandra

  • A research agenda for distributed software development

    Bikram Sengupta;Satish Chandra;Vibha Sinha

  • Decentralizing execution of composite web services

    Mangala Gowri Nanda;Satish Chandra;Vivek Sarkar

  • Getafix: learning to fix bugs automatically

    Johannes Bader;Andrew Scott;Michael Pradel;Satish Chandra

  • Code Prediction by Feeding Trees to Transformers

    Seohyun Kim;Jinman Zhao;Yuchi Tian;Satish Chandra

  • When deep learning met code search

    Jose Cambronero;Hongyu Li;Seohyun Kim;Koushik Sen

  • Angelic debugging

    Satish Chandra;Emina Torlak;Shaon Barman;Rastislav Bodik

  • Retrieval on source code: a neural code search

    Saksham Sachdev;Hongyu Li;Sifei Luan;Seohyun Kim

  • Enabling Collaboration in Distributed Requirements Management

    Vibha Sinha;Bikram Sengupta;Satish Chandra

  • Snugglebug: a powerful approach to weakest preconditions

    Satish Chandra;Stephen J. Fink;Manu Sridharan

  • Correlation tracking for points-to analysis of javascript

    Manu Sridharan;Julian Dolby;Satish Chandra;Max Schäfer

  • Off-line variable substitution for scaling points-to analysis

    Atanas Rountev;Satish Chandra

  • SapFix: automated end-to-end repair at scale

    Alexandru Marginean;Johannes Bader;Satish Chandra;Mark Harman

  • Packet types: abstract specification of network protocol messages

    Peter J. McCann;Satish Chandra

  • Aroma: code recommendation via structural code search

    Sifei Luan;Di Yang;Celeste Barnaby;Koushik Sen

  • Alias analysis for object-oriented programs

    Manu Sridharan;Satish Chandra;Julian Dolby;Stephen J. Fink

  • Where is time spent in message-passing and shared-memory programs?

    Satish Chandra;James R. Larus;Anne Rogers

  • A survey of static analysis methods for identifying security vulnerabilities in software systems

    M. Pistoia;S. Chandra;S. J. Fink;E. Yahav

  • Automating test automation

    Suresh Thummalapenta;Saurabh Sinha;Nimit Singhania;Satish Chandra

  • TypeWriter: neural type prediction with search-based validation

    Michael Pradel;Georgios Gousios;Jason Liu;Satish Chandra

  • Aroma: Code Recommendation via Structural Code Search

    Sifei Luan;Di Yang;Celeste Barnaby;Koushik Sen

Frequent Co-Authors

James R. Larus
James R. Larus École Polytechnique Fédérale de Lausanne
Manu Sridharan
Manu Sridharan University of California, Riverside
Koushik Sen
Koushik Sen University of California, Berkeley
Stephen J. Fink
Stephen J. Fink Facebook (United States)
Michael Pradel
Michael Pradel University of Stuttgart
Frank Tip
Frank Tip Northeastern University
Eran Yahav
Eran Yahav Technion – Israel Institute of Technology
Rastislav Bodik
Rastislav Bodik University of Washington
Thomas Reps
Thomas Reps University of Wisconsin–Madison
Julian Dolby
Julian Dolby IBM (United States)

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