World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
10074
World Ranking
9111
National Ranking
560

Overview

Phil McMinn is affiliated with the University of Sheffield in the United Kingdom. Their research primarily focuses on the field of Computer Science, with significant contributions to software, information systems, and artificial intelligence.

The scientist's main areas of work encompass:

  • Software Testing and Debugging Techniques
  • Software Engineering Research
  • Software Reliability and Analysis Research
  • Advanced Malware Detection Techniques
  • Software System Performance and Reliability
  • Quantum Computing Algorithms and Architecture
  • Web Data Mining and Analysis

Phil McMinn's publication record includes numerous papers across various venues. Notable recent papers include:

  • "A Survey of Flaky Tests" (2021), published in ACM Transactions on Software Engineering and Methodology
  • "Automatically identifying potential regressions in the layout of responsive web pages" (2020), published in Software Testing Verification and Reliability
  • "Automated visual classification of DOM-based presentation failure reports for responsive web pages" (2021), published in Software Testing Verification and Reliability
  • "Effective automated repair of internationalization presentation failures in web applications using style similarity clustering and search-based techniques" (2020), published in Software Testing Verification and Reliability
  • "Empirically evaluating flaky test detection techniques combining test case rerunning and machine learning models" (2023), published in Empirical Software Engineering

Frequent co-authors in McMinn's work include:

  • Owain Parry
  • Gregory M. Kapfhammer
  • Michael Hilton
  • Robert M. Hierons
  • Gordon Fraser

Phil McMinn publishes regularly in venues such as:

  • arXiv (Cornell University)
  • Software Testing Verification and Reliability
  • ACM Transactions on Software Engineering and Methodology
  • Empirical Software Engineering
  • Proceedings of the Annual Hawaii International Conference on System Sciences

Their research subfields break down into software, information systems, artificial intelligence, signal processing, and computer networks and communications, supporting a diverse and interdisciplinary approach to software engineering and related technological challenges.

Best Publications

  • Search‐based software test data generation: a survey

    Phil McMinn

  • The Oracle Problem in Software Testing: A Survey

    Earl T. Barr;Mark Harman;Phil McMinn;Muzammil Shahbaz

  • An orchestrated survey of methodologies for automated software test case generation

    Saswat Anand;Edmund K. Burke;Tsong Yueh Chen;John Clark

  • Search based software engineering: techniques, taxonomy, tutorial

    Mark Harman;Phil McMinn;Jerffeson Teixeira de Souza;Shin Yoo

  • A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search

    M. Harman;P. McMinn

  • Search-Based Software Testing: Past, Present and Future

    Phil McMinn

  • Do Automatically Generated Unit Tests Find Real Faults? An Empirical Study of Effectiveness and Challenges (T)

    Sina Shamshiri;Rene Just;Jose Miguel Rojas;Gordon Fraser

  • A multi-objective approach to search-based test data generation

    Kiran Lakhotia;Mark Harman;Phil McMinn

  • Search-based software test data generation: a survey: Research Articles

    Phil McMinn

  • A Survey of Flaky Tests

    Unknown

  • A theoretical & empirical analysis of evolutionary testing and hill climbing for structural test data generation

    Mark Harman;Phil McMinn

  • The state problem for evolutionary testing

    Phil McMinn;Mike Holcombe

  • Symbolic search-based testing

    Arthur Baars;Mark Harman;Youssef Hassoun;Kiran Lakhotia

  • Optimizing for the Number of Tests Generated in Search Based Test Data Generation with an Application to the Oracle Cost Problem

    Mark Harman;Sung Gon Kim;Kiran Lakhotia;Phil McMinn

  • The species per path approach to SearchBased test data generation

    Phil McMinn;Mark Harman;David Binkley;Paolo Tonella

  • Evolving Readable String Test Inputs Using a Natural Language Model to Reduce Human Oracle Cost

    Sheeva Afshan;Phil McMinn;Mark Stevenson

  • Does Automated Unit Test Generation Really Help Software Testers? A Controlled Empirical Study

    Gordon Fraser;Matt Staats;Phil McMinn;Andrea Arcuri

  • A Memetic Algorithm for whole test suite generation

    Gordon Fraser;Andrea Arcuri;Phil McMinn

  • The impact of input domain reduction on search-based test data generation

    Mark Harman;Youssef Hassoun;Kiran Lakhotia;Phil McMinn

  • Does automated white-box test generation really help software testers?

    Gordon Fraser;Matt Staats;Phil McMinn;Andrea Arcuri

  • Input Domain Reduction through Irrelevant Variable Removal and Its Effect on Local, Global, and Hybrid Search-Based Structural Test Data Generation

    P. McMinn;M. Harman;K. Lakhotia;Y. Hassoun

Frequent Co-Authors

Mark Harman
Mark Harman University College London
Gordon Fraser
Gordon Fraser University of Passau
Shin Yoo
Shin Yoo Korea Advanced Institute of Science and Technology
Mike Holcombe
Mike Holcombe University of Sheffield
Andrea Arcuri
Andrea Arcuri Kristiania University College
William G. J. Halfond
William G. J. Halfond University of Southern California
David Binkley
David Binkley Loyola University Maryland
Mark Stevenson
Mark Stevenson University of Melbourne
Paolo Tonella
Paolo Tonella Universita della Svizzera Italiana
Sheila MacNeil
Sheila MacNeil University of Sheffield

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