World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
6726
World Ranking
9310
National Ranking
224

Romain Robbes 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 Romain Robbes 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: 132 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

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

Romain Robbes 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 Romain Robbes 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Romain Robbes is affiliated with the University of Bordeaux in France and has contributed extensively to the field of computer science, with a focus on software engineering research. Their research output spans multiple aspects of software engineering, including software system performance, reliability, natural language processing techniques, and software testing and debugging techniques.

Robbes' work has addressed the challenges faced in software engineering from empirical, performance, and machine learning perspectives. Their notable recent publications include:

  • Empirical Standards for Software Engineering Research, 2020, arXiv (Cornell University)
  • Big Code!= Big Vocabulary: Open-Vocabulary Models for Source Code, 2020, arXiv (Cornell University)
  • Making the most of small Software Engineering datasets with modern machine learning, 2021, IEEE Transactions on Software Engineering
  • The ACM SIGSOFT Paper and Peer Review Quality Initiative, 2020, ACM SIGSOFT Software Engineering Notes
  • Characteristics of method extractions in Java: a large scale empirical study, 2020, Empirical Software Engineering

In collaboration, Robbes has frequently published with several co-authors, including Andrea Janes, Hlib Babii, Charles Sutton, Rafael-Michael Karampatsis, and Julian Aron Prenner. These collaborations have produced research covering various subdomains within computer science.

The venues where Robbes has regularly published are diverse, reflecting their broad research interests and activities. The most frequent publication venues are:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Transactions on Software Engineering
  • Empirical Software Engineering
  • OPAL (Open@LaTrobe) (La Trobe University)

Robbes' main fields of study focus on computer science overall, while their more specific subfields include:

  • Information Systems
  • Artificial Intelligence
  • Computer Networks and Communications
  • Software
  • Signal Processing

Their core research topics showcase an emphasis on software engineering research, software system performance and reliability, as well as natural language processing and software testing, along with specialized areas like topic modeling, advanced malware detection techniques, and computational physics with Python applications, as indicated by publication counts across these topics:

  • Software Engineering Research
  • Software System Performance and Reliability
  • Natural Language Processing Techniques
  • Software Testing and Debugging Techniques
  • Topic Modeling
  • Advanced Malware Detection Techniques
  • Computational Physics and Python Applications

Best Publications

  • An extensive comparison of bug prediction approaches

    Marco D'Ambros;Michele Lanza;Romain Robbes

  • Evaluating defect prediction approaches: a benchmark and an extensive comparison

    Marco D'Ambros;Michele Lanza;Romain Robbes

  • Software systems as cities: a controlled experiment

    Richard Wettel;Michele Lanza;Romain Robbes

  • Linking e-mails and source code artifacts

    Alberto Bacchelli;Michele Lanza;Romain Robbes

  • Big code != big vocabulary: open-vocabulary models for source code

    Rafael-Michael Karampatsis;Hlib Babii;Romain Robbes;Charles Sutton

  • How do developers react to API deprecation?: the case of a smalltalk ecosystem

    Romain Robbes;Mircea Lungu;David Röthlisberger

  • How Program History Can Improve Code Completion

    R. Robbes;M. Lanza

  • A Change-based Approach to Software Evolution

    Romain Robbes;Michele Lanza

  • On the Relationship Between Change Coupling and Software Defects

    Marco D'Ambros;Michele Lanza;Romain Robbes

  • The Small Project Observatory: Visualizing software ecosystems

    Mircea Lungu;Michele Lanza;Tudor Gîrba;Romain Robbes

  • Can OpenAI's Codex Fix Bugs?: An evaluation on QuixBugs

    Unknown

  • SpyWare: a change-aware development toolset

    Romain Robbes;Michele Lanza

  • Improving code completion with program history

    Romain Robbes;Michele Lanza

  • An empirical study on the impact of static typing on software maintainability

    Stefan Hanenberg;Sebastian Kleinschmager;Romain Robbes;Éric Tanter

  • How do API documentation and static typing affect API usability

    Stefan Endrikat;Stefan Hanenberg;Romain Robbes;Andreas Stefik

  • How (and why) developers use the dynamic features of programming languages: the case of smalltalk

    Oscar Callaú;Romain Robbes;Éric Tanter;David Röthlisberger

  • Empirical Standards for Software Engineering Research

    Paul Ralph;Nauman bin Ali;Sebastian Baltes;Domenico Bianculli

  • Mining a Change-Based Software Repository

    Romain Robbes

  • Proceedings of the 13th International Conference on Mining Software Repositories

    Miryung Kim;Romain Robbes;Christian Bird

  • How do developers react to API evolution? The Pharo ecosystem case

    Andre Hora;Romain Robbes;Nicolas Anquetil;Anne Etien

  • Recovering inter-project dependencies in software ecosystems

    Mircea Lungu;Romain Robbes;Michele Lanza

  • Do static type systems improve the maintainability of software systems? An empirical study

    Sebastian Kleinschmager;Romain Robbes;Andreas Stefik;Stefan Hanenberg

  • Versioning systems for evolution research

    R. Robbes;M. Lanza

Frequent Co-Authors

Michele Lanza
Michele Lanza Universita della Svizzera Italiana
Éric Tanter
Éric Tanter University of Chile
Marco Tulio Valente
Marco Tulio Valente Universidade Federal de Minas Gerais
Stéphane Ducasse
Stéphane Ducasse University of Lille
Charles Sutton
Charles Sutton Google (United States)
Alberto Bacchelli
Alberto Bacchelli University of Zurich
Ahmed E. Hassan
Ahmed E. Hassan Queen's University
Meiyappan Nagappan
Meiyappan Nagappan University of Waterloo
Audris Mockus
Audris Mockus University of Tennessee at Knoxville
Shane McIntosh
Shane McIntosh McGill University

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