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Computer Science

D-Index
43
Citations
7399
World Ranking
8016
National Ranking
10

Overview

Mike Papadakis is affiliated with the University of Luxembourg in Luxembourg and conducts research primarily in the field of Computer Science. Their work extensively covers several subfields, including Software, Artificial Intelligence, Information Systems, Computer Networks and Communications, and Signal Processing.

Their research spans a variety of topics, with a strong focus on Software Testing and Debugging Techniques, Software Engineering Research, Software Reliability and Analysis Research, Adversarial Robustness in Machine Learning, Software System Performance and Reliability, Topic Modeling, and Advanced Malware Detection Techniques.

Among their recent publications are:

  • Test Selection for Deep Learning Systems (2021), published in ACM Transactions on Software Engineering and Methodology
  • Improving machine translation systems via isotopic replacement (2022), Proceedings of the 44th International Conference on Software Engineering
  • An Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement (2022), ACM Transactions on Software Engineering and Methodology
  • Safety and efficacy of arimoclomol for inclusion body myositis: a multicentre, randomised, double-blind, placebo-controlled trial (2023), The Lancet Neurology
  • Killing Stubborn Mutants with Symbolic Execution (2021), Open Repository and Bibliography (University of Luxembourg)

They have frequently collaborated with several researchers including Yves Le Traon, Maxime Cordy, Yuejun Guo, Renzo Degiovanni, and Qiang Hu, indicating a consistent engagement in cooperative research efforts.

Mike Papadakis publishes in a range of venues with multiple publications in arXiv (Cornell University), ACM Transactions on Software Engineering and Methodology, IEEE Transactions on Software Engineering, Empirical Software Engineering, and Proceedings of the 44th International Conference on Software Engineering.

They have also contributed to academic literature through book publications, notably a book titled Search-Based Software Engineering released in 2022 by Springer Science+Business Media.

Best Publications

  • Mutation Testing Advances: An Analysis and Survey

    Mike Papadakis;Marinos Kintis;Jie Zhang;Yue Jia

  • Static analysis of android apps

    Li Li;Tegawend F. Bissyand;Mike Papadakis;Siegfried Rasthofer

  • Metallaxis-FL: mutation-based fault localization

    Mike Papadakis;Yves Le Traon

  • Bypassing the Combinatorial Explosion: Using Similarity to Generate and Prioritize T-Wise Test Configurations for Software Product Lines

    Christopher Henard;Mike Papadakis;Gilles Perrouin;Jacques Klein

  • PIT: a practical mutation testing tool for Java (demo)

    Henry Coles;Thomas Laurent;Christopher Henard;Mike Papadakis

  • Comparing white-box and black-box test prioritization

    Christopher Henard;Mike Papadakis;Mark Harman;Yue Jia

  • Semantic fuzzing with zest

    Rohan Padhye;Caroline Lemieux;Koushik Sen;Mike Papadakis

  • Trivial compiler equivalence: a large scale empirical study of a simple, fast and effective equivalent mutant detection technique

    Mike Papadakis;Yue Jia;Mark Harman;Yves Le Traon

  • Combining multi-objective search and constraint solving for configuring large software product lines

    Christopher Henard;Mike Papadakis;Mark Harman;Yves Le Traon

  • An empirical study on mutation, statement and branch coverage fault revelation that avoids the unreliable clean program assumption

    Thierry Titcheu Chekam;Mike Papadakis;Yves Le Traon;Mark Harman

  • Automatic Mutation Test Case Generation via Dynamic Symbolic Execution

    Mike Papadakis;Nicos Malevris

  • An Empirical Evaluation of the First and Second Order Mutation Testing Strategies

    Mike Papadakis;Nicos Malevris

  • Multi-objective test generation for software product lines

    Christopher Henard;Mike Papadakis;Gilles Perrouin;Jacques Klein

  • Threats to the validity of mutation-based test assessment

    Mike Papadakis;Christopher Henard;Mark Harman;Yue Jia

  • PIT a Practical Mutation Testing Tool for Java

    Henry Coles;Thomas Laurent;Christopher Henard;Mike Papadakis

  • Evaluating Mutation Testing Alternatives: A Collateral Experiment

    Marinos Kintis;Mike Papadakis;Nicos Malevris

  • Using Mutants to Locate "Unknown" Faults

    Mike Papadakis;Yves Le Traon

  • A Replicable Comparison Study of NER Software: StanfordNLP, NLTK, OpenNLP, SpaCy, Gate

    Xavier Schmitt;Sylvain Kubler;Jeremy Robert;Mike Papadakis

  • Are mutation scores correlated with real fault detection?: a large scale empirical study on the relationship between mutants and real faults

    Mike Papadakis;Donghwan Shin;Shin Yoo;Doo-Hwan Bae

  • Detecting Trivial Mutant Equivalences via Compiler Optimisations

    Marinos Kintis;Mike Papadakis;Yue Jia;Nicos Malevris

  • Validity fuzzing and parametric generators for effective random testing

    Rohan Padhye;Caroline Lemieux;Koushik Sen;Mike Papadakis

Frequent Co-Authors

Yves Le Traon
Yves Le Traon University of Luxembourg
Jacques Klein
Jacques Klein University of Luxembourg
Mark Harman
Mark Harman University College London
Tegawendé F. Bissyandé
Tegawendé F. Bissyandé University of Luxembourg
Koushik Sen
Koushik Sen University of California, Berkeley
Yue Jia
Yue Jia University College London
Patrick Heymans
Patrick Heymans University of Namur
Axel Legay
Axel Legay Université Catholique de Louvain
Shin Yoo
Shin Yoo Korea Advanced Institute of Science and Technology
Lu Zhang
Lu Zhang Peking University

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