World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
54
Citations
16371
World Ranking
4466
National Ranking
2089

Audris Mockus 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 Audris Mockus 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: 205 publications — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Audris Mockus 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 Audris Mockus 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: 54 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Overview

Audris Mockus is a researcher affiliated with the University of Tennessee at Knoxville in the United States. Their academic work primarily lies within the field of Computer Science, with substantial contributions to several related subfields including Information Systems, Artificial Intelligence, Management Science and Operations Research, Computer Science Applications, and Information Systems and Management.

Their research topics encompass a variety of areas in software and data management, focusing on Software Engineering Research, Data Quality and Management, Scientific Computing and Data Management, Open Source Software Innovations, Advanced Malware Detection Techniques, Software Engineering Techniques and Practices, and Biomedical and Engineering Education.

Mockus has published extensively across different platforms. Frequent publication venues include:

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

Among the recent papers associated with Mockus's work, the following stand out due to their relevance and number of citations:

  • "World of code: enabling a research workflow for mining and analyzing the universe of open source VCS data," 2021, Empirical Software Engineering
  • "ALFAA: Active Learning Fingerprint based Anti-Aliasing for correcting developer identity errors in version control systems," 2020, Empirical Software Engineering
  • "Deriving a usage-independent software quality metric," 2020, Empirical Software Engineering
  • "The extent of orphan vulnerabilities from code reuse in open source software," 2022, Proceedings of the 44th International Conference on Software Engineering
  • "Do code review measures explain the incidence of post-release defects?," 2020, Empirical Software Engineering

Collaboration has played a significant role in Mockus's research activities. Frequent coauthors include:

  • Tapajit Dey
  • Andrey Karnauch
  • Tanner Fry
  • Dawnie Wolfe Steadman
  • Ahmed Samir Imam Mahmoud

Best Publications

  • Two case studies of open source software development: Apache and Mozilla

    Audris Mockus;Roy T. Fielding;James D. Herbsleb

  • An empirical study of speed and communication in globally distributed software development

    J.D. Herbsleb;A. Mockus

  • A case study of open source software development: the Apache server

    Audris Mockus;Roy T. Fielding;James Herbsleb

  • Does code decay? Assessing the evidence from change management data

    S.G. Eick;T.L. Graves;A.F. Karr;J.S. Marron

  • A large-scale empirical study of just-in-time quality assurance

    Y. Kamei;E. Shihab;B. Adams;A. E. Hassan

  • Distance, dependencies, and delay in a global collaboration

    James D. Herbsleb;Audris Mockus;Thomas A. Finholt;Rebecca E. Grinter

  • Identifying Reasons for Software Changes Using Historic Databases

    Audris Mockus;Lawrence G. Votta

  • An empirical study of global software development: distance and speed

    James D. Herbsleb;Audris Mockus;Thomas A. Finholt;Rebecca E. Grinter

  • Predicting risk of software changes

    Audris Mockus;David M. Weiss

  • Quantifying the Effect of Code Smells on Maintenance Effort

    D. I. K. Sjoberg;A. Yamashita;B. C. D. Anda;A. Mockus

  • Software Dependencies, Work Dependencies, and Their Impact on Failures

    M. Cataldo;A. Mockus;J.A. Roberts;J.D. Herbsleb

  • Expertise Browser: a quantitative approach to identifying expertise

    Audris Mockus;James D. Herbsleb

  • Globalization by chunking: a quantitative approach

    A. Mockus;D.M. Weiss

  • Understanding the sources of variation in software inspections

    Adam Porter;Harvey Siy;Audris Mockus;Lawrence Votta

  • Challenges of global software development

    A. Mockus;J. Herbsleb

  • Visualizing software changes

    S.G. Eick;T.L. Graves;A.F. Karr;A. Mockus

  • Towards building a universal defect prediction model

    Feng Zhang;Audris Mockus;Iman Keivanloo;Ying Zou

  • Large-Scale Code Reuse in Open Source Software

    Audris Mockus

  • What make long term contributors: willingness and opportunity in OSS community

    Minghui Zhou;Audris Mockus

  • Shared Mental Models, Familiarity and Coordination: A Multi-Method Study of Distributed Software Teams

    J. Alberto Espinosa;Robert E. Kraut;Sandra A. Slaughter;Javier F. Lerch

Frequent Co-Authors

Gintaras V. Reklaitis
Gintaras V. Reklaitis Purdue University West Lafayette
James D. Herbsleb
James D. Herbsleb Carnegie Mellon University
Ahmed E. Hassan
Ahmed E. Hassan Queen's University
Yasutaka Kamei
Yasutaka Kamei Kyushu University
Diomidis Spinellis
Diomidis Spinellis Athens University of Economics and Business
Meiyappan Nagappan
Meiyappan Nagappan University of Waterloo
Shane McIntosh
Shane McIntosh McGill University
Bram Adams
Bram Adams Queen's University
Dag I. K. Sjøberg
Dag I. K. Sjøberg University of Oslo
Peter E. Thornton
Peter E. Thornton Oak Ridge National Laboratory

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