World's Best Scientists 2026 revealed!
Yann-Gaël Guéhéneuc

Yann-Gaël Guéhéneuc

D-Index & Metrics

Computer Science

D-Index
62
Citations
13413
World Ranking
2946
National Ranking
110

Yann-Gaël Guéhéneuc publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Yann-Gaël Guéhéneuc sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 306 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Yann-Gaël Guéhéneuc D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Yann-Gaël Guéhéneuc sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 62 D-Index — 80th percentile

80% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Yann-Gaël Guéhéneuc is affiliated with Concordia University in Canada. Their research activity is primarily situated within the field of Computer Science, with a focus on subfields such as Information Systems, Computer Networks and Communications, Artificial Intelligence, Sociology and Political Science, and Software.

Their work covers several main topics, including:

  • Software Engineering Research
  • Software System Performance and Reliability
  • Digital Games and Media
  • Advanced Software Engineering Methodologies
  • Software Engineering Techniques and Practices
  • IoT and Edge/Fog Computing
  • Advanced Malware Detection Techniques

Yann-Gaël Guéhéneuc has contributed to numerous scientific papers. Some of their recent publications include:

  • "A practical guide on conducting eye tracking studies in software engineering," 2020, Empirical Software Engineering
  • "A Systematic Review of API Evolution Literature," 2021, ACM Computing Surveys
  • "A systematic literature review on automated log abstraction techniques," 2020, Information and Software Technology
  • "A taxonomy of service identification approaches for legacy software systems modernization," 2020, Journal of Systems and Software
  • "What skills do IT companies look for in new developers? A study with Stack Overflow jobs," 2020, Information and Software Technology

The frequent collaborators in their research include:

  • Fábio Petrillo
  • Cristiano Politowski
  • Naouel Moha
  • Gabriel C. Ullmann
  • Nicolas Anquetil

The main venues where Yann-Gaël Guéhéneuc has published work are:

  • arXiv (Cornell University)
  • Information and Software Technology
  • IEEE Transactions on Software Engineering
  • Zenodo (CERN European Organization for Nuclear Research)
  • Empirical Software Engineering

Best Publications

  • DECOR: A Method for the Specification and Detection of Code and Design Smells

    N. Moha;Y.-G. Gueheneuc;L. Duchien;A.-F. Le Meur

  • Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval

    D. Poshyvanyk;Y.-G. Gueheneuc;A. Marcus;G. Antoniol

  • Is it a bug or an enhancement?: a text-based approach to classify change requests

    Giuliano Antoniol;Kamel Ayari;Massimiliano Di Penta;Foutse Khomh

  • An exploratory study of the impact of antipatterns on class change- and fault-proneness

    Foutse Khomh;Massimiliano Di Penta;Yann-Gaël Guéhéneuc;Giuliano Antoniol

  • An Exploratory Study of the Impact of Code Smells on Software Change-proneness

    Foutse Khomh;Massimiliano Di Penta;Yann-Gael Gueheneuc

  • An Empirical Study of the Impact of Two Antipatterns, Blob and Spaghetti Code, on Program Comprehension

    Marwen Abbes;Foutse Khomh;Yann-Gael Gueheneuc;Giuliano Antoniol

  • Code smells and refactoring: A tertiary systematic review of challenges and observations

    Guilherme Lacerda;Guilherme Lacerda;Fabio Petrillo;Marcelo Pimenta;Yann Gaël Guéhéneuc

  • A Bayesian Approach for the Detection of Code and Design Smells

    Foutse Khomh;Stéphane Vaucher;Yann-Gaël Guéhéneuc;Houari Sahraoui

  • DeMIMA: A Multilayered Approach for Design Pattern Identification

    Y.-G. Gueheneuc;G. Antoniol

  • A systematic literature review on the usage of eye-tracking in software engineering

    Zohreh Sharafi;Zéphyrin Soh;Yann-Gaël Guéhéneuc

  • Fingerprinting design patterns

    Gueheneuc Y-G;H. Sahraoui;F. Zaidi

  • BDTEX: A GQM-based Bayesian approach for the detection of antipatterns

    Foutse Khomh;Stephane Vaucher;Yann-Gaël Guéhéneuc;Houari Sahraoui

  • CERBERUS: Tracing Requirements to Source Code Using Information Retrieval, Dynamic Analysis, and Program Analysis

    M. Eaddy;A.V. Aho;G. Antoniol;Y.-G. Gueheneuc

  • AURA: a hybrid approach to identify framework evolution

    Wei Wu;Yann-Gaël Guéhéneuc;Giuliano Antoniol;Miryung Kim

  • Combining Probabilistic Ranking and Latent Semantic Indexing for Feature Identification

    D. Poshyvanyk;A. Marcus;V. Rajlich;Y.-G. Gueheneuc

  • Feature identification: a novel approach and a case study

    G. Antoniol;Y.-G. Gueheneuc

  • Instantiating and detecting design patterns: putting bits and pieces together

    H. Albin-Amiot;P. Cointe;Y.-G. Gueheneuc;N. Jussien

  • Do Design Patterns Impact Software Quality Positively

    F. Khomh;Y.-G. Gueheneuc

  • Recovering binary class relationships: putting icing on the UML cake

    Yann-Gaël Guéhéneuc;Hervé Albin-Amiot

  • SMURF: A SVM-based Incremental Anti-pattern Detection Approach

    Abdou Maiga;Nasir Ali;Neelesh Bhattacharya;Aminata Sabane

  • Online repository for tertiary systematic review about code smells and refactoring

    Guilherme Lacerda;Fabio Petrillo;Marcelo Pimenta;Yann Gaël Guéhéneuc

Frequent Co-Authors

Giuliano Antoniol
Giuliano Antoniol Polytechnique Montréal
Foutse Khomh
Foutse Khomh Polytechnique Montréal
Massimiliano Di Penta
Massimiliano Di Penta University of Sannio
Bram Adams
Bram Adams Queen's University
Houari Sahraoui
Houari Sahraoui University of Montreal
Rocco Oliveto
Rocco Oliveto University of Molise
Jane Huffman Hayes
Jane Huffman Hayes University of Kentucky
Gaston Godin
Gaston Godin Université Laval
Tom Mens
Tom Mens University of Mons
Paolo Tonella
Paolo Tonella Universita della Svizzera Italiana

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