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Computer Science

D-Index
78
Citations
26922
World Ranking
1195
National Ranking
633

Research.com Recognitions

  • 2014 - ACM Fellow For contributions to software analysis, testing, and verification.

Overview

Michael D. Ernst is affiliated with the University of Washington in the United States. Their research activity focuses extensively on computer science, particularly within the fields of software, information systems, and computer networks and communications.

The scientist has contributed to several main topics in computer science research, including:

  • Software Testing and Debugging Techniques
  • Software Engineering Research
  • Software System Performance and Reliability
  • Software Reliability and Analysis Research
  • Parallel Computing and Optimization Techniques
  • Formal Methods in Verification
  • Advanced Malware Detection Techniques

Michael D. Ernst's recent publications showcase a range of work across software engineering and system analysis. Selected papers include:

  • Visualizing Distributed System Executions, 2020, ACM Transactions on Software Engineering and Methodology
  • MeMo: Automatically identifying metamorphic relations in Javadoc comments for test automation, 2021, Journal of Systems and Software
  • Removing biased data to improve fairness and accuracy, 2021, arXiv (Cornell University)
  • MeMo: Automatically Identifying Metamorphic Relations in Javadoc Comments for Test Automation, 2021, Zenodo (CERN European Organization for Nuclear Research)
  • DesCert: Design for Certification, 2022, arXiv (Cornell University)

The frequent co-authors with whom Michael D. Ernst has collaborated include:

  • Martin Kellogg
  • Manu Sridharan
  • Narges Shadab
  • Pritam Gharat
  • Shuvendu K. Lahiri

The most common venues where Michael D. Ernst publishes are:

  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)
  • ACM Transactions on Software Engineering and Methodology
  • OPAL (Open@LaTrobe) (La Trobe University)
  • Journal of Systems and Software

Michael D. Ernst's contributions to the field have been recognized with the ACM Fellow award in 2014, citing their work in software analysis, testing, and verification.

Best Publications

  • Dynamically Discovering Likely Program Invariants to Support Program Evolution

    Michael D. Ernst;Jake Cockrell;William G. Griswold;David Notkin

  • The Daikon system for dynamic detection of likely invariants

    Michael D. Ernst;Jeff H. Perkins;Philip J. Guo;Stephen McCamant

  • Defects4J: a database of existing faults to enable controlled testing studies for Java programs

    René Just;Darioush Jalali;Michael D. Ernst

  • HaLoop: efficient iterative data processing on large clusters

    Yingyi Bu;Bill Howe;Magdalena Balazinska;Michael D. Ernst

  • An overview of JML tools and applications

    Lilian Burdy;Yoonsik Cheon;David Cok;Michael D. Ernst

  • Feedback-Directed Random Test Generation

    Carlos Pacheco;Shuvendu K. Lahiri;Michael D. Ernst;Thomas Ball

  • An overview of JML tools and applications

    Lilian Burdy;Yoonsik Cheon;David R. Cok;Michael D. Ernst

  • Are mutants a valid substitute for real faults in software testing

    René Just;Darioush Jalali;Laura Inozemtseva;Michael D. Ernst

  • Randoop: feedback-directed random testing for Java

    Carlos Pacheco;Michael D. Ernst

  • Automatic creation of SQL Injection and cross-site scripting attacks

    Adam Kieyzun;Philip J. Guo;Karthick Jayaraman;Michael D. Ernst

  • Automatically patching errors in deployed software

    Jeff H. Perkins;Sunghun Kim;Sam Larsen;Saman Amarasinghe

  • Static and dynamic analysis: synergy and duality

    Michael D. Ernst

  • Evaluating and improving fault localization

    Spencer Pearson;Jose Campos;Rene Just;Gordon Fraser

  • Verdi: a framework for implementing and formally verifying distributed systems

    James R. Wilcox;Doug Woos;Pavel Panchekha;Zachary Tatlock

  • Eclat: automatic generation and classification of test inputs

    Carlos Pacheco;Michael D. Ernst

  • HAMPI: a solver for string constraints

    Adam Kiezun;Vijay Ganesh;Philip J. Guo;Pieter Hooimeijer

  • Quickly detecting relevant program invariants

    Michael D. Ernst;Adam Czeisler;William G. Griswold;David Notkin

  • An empirical analysis of c preprocessor use

    M.D. Ernst;G.J. Badros;D. Notkin

  • Proactive detection of collaboration conflicts

    Yuriy Brun;Reid Holmes;Michael D. Ernst;David Notkin

  • Leveraging existing instrumentation to automatically infer invariant-constrained models

    Ivan Beschastnikh;Yuriy Brun;Sigurd Schneider;Michael Sloan

  • Automated support for program refactoring using invariants

    Y. Kataoka;M.D. Ernst;W.G. Griswold;D. Notkin

Frequent Co-Authors

Yuriy Brun
Yuriy Brun University of Massachusetts Amherst
David Notkin
David Notkin University of Washington
Philip J. Guo
Philip J. Guo University of California, San Diego
Dan Grossman
Dan Grossman University of Washington
Sunghun Kim
Sunghun Kim Hong Kong University of Science and Technology
Arvind Krishnamurthy
Arvind Krishnamurthy University of Washington
Thomas Anderson
Thomas Anderson University of Washington
William G. Griswold
William G. Griswold University of California, San Diego
Danny Dig
Danny Dig University of Colorado Boulder

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