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Computer Science
Luxembourg
2026

D-Index & Metrics

Computer Science

D-Index
75
Citations
21772
World Ranking
1421
National Ranking
1

Research.com Recognitions

  • 2026 - Research.com Computer Science in Luxembourg Leader Award
  • 2025 - Research.com Computer Science in Luxembourg Leader Award
  • 2023 - Research.com Computer Science in Luxembourg Leader Award
  • 2022 - Research.com Computer Science in Luxembourg Leader Award

Overview

Yves Le Traon is affiliated with the University of Luxembourg in Luxembourg. Their research primarily focuses on computer science, with a significant body of work in software engineering and related subfields.

The main fields of study for Yves Le Traon include:

  • Computer Science

Their research spans several subfields of study:

  • Software
  • Artificial Intelligence
  • Information Systems
  • Electrical and Electronic Engineering
  • Signal Processing

Yves Le Traon's work covers a variety of research topics, notably in software testing and debugging, software engineering research, and machine learning applications. The main topics they have worked on are:

  • Software Testing and Debugging Techniques
  • Software Engineering Research
  • Adversarial Robustness in Machine Learning
  • Software Reliability and Analysis Research
  • Advanced Malware Detection Techniques
  • Software System Performance and Reliability
  • Anomaly Detection Techniques and Applications

The scientist has coauthored numerous publications with several frequent collaborators, including:

  • Maxime Cordy
  • Mike Papadakis
  • Yuejun Guo
  • Qiang Hu
  • Xiaofei Xie

Yves Le Traon has contributed papers to a range of publication venues. Some of the most common venues for their work are:

  • arXiv (Cornell University)
  • Software Testing Verification and Reliability
  • ACM Transactions on Software Engineering and Methodology
  • Empirical Software Engineering
  • SSRN Electronic Journal

Their recent papers include:

  • Permissioned blockchain frameworks in the industry: A comparison, 2020, ICT Express
  • Test Selection for Deep Learning Systems, 2021, ACM Transactions on Software Engineering and Methodology
  • Multi-agent deep reinforcement learning based Predictive Maintenance on parallel machines, 2022, Robotics and Computer-Integrated Manufacturing
  • An Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement, 2022, ACM Transactions on Software Engineering and Methodology
  • Killing Stubborn Mutants with Symbolic Execution, 2021, Open Repository and Bibliography (University of Luxembourg)

These publications reflect a consistent focus on software testing, deep learning, and reinforcement learning within industrial and academic contexts. The combination of topics and research venues indicates a multidisciplinary approach intersecting software engineering and artificial intelligence.

Best Publications

  • FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps

    Steven Arzt;Siegfried Rasthofer;Christian Fritz;Eric Bodden

  • AndroZoo: collecting millions of Android apps for the research community

    Kevin Allix;Tegawende F. Bissyande;Jacques Klein;Yves Le Traon

  • IccTA: detecting inter-component privacy leaks in Android apps

    Li Li;Alexandre Bartel;Tegawende F. Bissyande;Jacques Klein

  • Effective inter-component communication mapping in Android with Epicc: an essential step towards holistic security analysis

    Damien Octeau;Patrick McDaniel;Somesh Jha;Alexandre Bartel

  • A state-of the-art survey & testbed of fuzzy AHP (FAHP) applications

    Sylvain Kubler;Jérémy Robert;William Derigent;Alexandre Voisin

  • Mutation Testing Advances: An Analysis and Survey

    Mike Papadakis;Marinos Kintis;Jie Zhang;Yue Jia

  • Automatic test generation: a use case driven approach

    C. Nebut;F. Fleurey;Y. Le Traon;J.-M. Jezequel

  • Refactoring UML Models

    Gerson Sunyé;Damien Pollet;Yves Le Traon;Jean-Marc Jézéquel

  • 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

  • FixMiner: Mining relevant fix patterns for automated program repair

    Anil Koyuncu;Kui Liu;Tegawendé François D Assise Bissyande;Dongsun Kim

  • Dexpler: converting Android Dalvik bytecode to Jimple for static analysis with Soot

    Alexandre Bartel;Jacques Klein;Yves Le Traon;Martin Monperrus

  • Automated and Scalable T-wise Test Case Generation Strategies for Software Product Lines

    Gilles Perrouin;Sagar Sen;Jacques Klein;Benoit Baudry

  • Improving test suites for efficient fault localization

    Benoit Baudry;Franck Fleurey;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

  • Comparing white-box and black-box test prioritization

    Christopher Henard;Mike Papadakis;Mark Harman;Yue Jia

  • Dexpler: Converting Android Dalvik Bytecode to Jimple for Static Analysis with Soot

    Alexandre Bartel;Jacques Klein;Martin Monperrus;Yves Le Traon

  • Semantic fuzzing with zest

    Rohan Padhye;Caroline Lemieux;Koushik Sen;Mike Papadakis

  • Efficient object-oriented integration and regression testing

    Y. Le Traon;T. Jeron;J.-M. Jezequel;P. Morel

  • Metamodel-based Test Generation for Model Transformations: an Algorithm and a Tool

    E. Brottier;F. Fleurey;J. Steel;B. Baudry

  • 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

Frequent Co-Authors

Jacques Klein
Jacques Klein University of Luxembourg
Mike Papadakis
Mike Papadakis University of Luxembourg
Tegawendé F. Bissyandé
Tegawendé F. Bissyandé University of Luxembourg
Benoit Baudry
Benoit Baudry University of Montreal
Jean-Marc Jézéquel
Jean-Marc Jézéquel University of Rennes
Martin Monperrus
Martin Monperrus Royal Institute of Technology
Franck Fleurey
Franck Fleurey Tellu IoT AS
David Lo
David Lo Singapore Management University
Mark Harman
Mark Harman University College London
Koushik Sen
Koushik Sen University of California, Berkeley

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