World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
72
Citations
20013
World Ranking
1686
National Ranking
863

Tim Menzies 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 Tim Menzies 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: 579 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Tim Menzies 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 Tim Menzies 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: 72 D-Index — 89th percentile

89% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2019 - IEEE Fellow For contributions to software engineering for artificial intelligence

Overview

Tim Menzies is affiliated with North Carolina State University in the United States. Their research output spans a wide range of topics within computer science, with a particular emphasis on software engineering and its associated subfields.

The main fields of study for Tim Menzies include:

  • Computer Science

Within this broader discipline, their work covers several subfields such as:

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

The scientist's research topics focus on areas connected to software engineering and its reliability, including:

  • Software Engineering Research
  • Software Reliability and Analysis Research
  • Software Testing and Debugging Techniques
  • Software System Performance and Reliability
  • Advanced Malware Detection Techniques
  • Adversarial Robustness in Machine Learning
  • Ethics and Social Impacts of AI

Tim Menzies has published numerous papers in multiple venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Software
  • IEEE Transactions on Software Engineering
  • Empirical Software Engineering
  • ACM Transactions on Software Engineering and Methodology

Selected recent papers from their research include:

  • "Fairway: A Way to Build Fair ML Software," 2020, OPAL (Open@LaTrobe) (La Trobe University)
  • "Empirical Standards for Software Engineering Research," 2020, arXiv (Cornell University)
  • "Better Data Labelling With EMBLEM (and how that Impacts Defect Prediction)," 2020, IEEE Transactions on Software Engineering
  • "Identifying Self-Admitted Technical Debts With Jitterbug: A Two-Step Approach," 2020, IEEE Transactions on Software Engineering
  • "FairMask: Better Fairness via Model-Based Rebalancing of Protected Attributes," 2022, IEEE Transactions on Software Engineering

The scientist frequently collaborates with other researchers. Coauthors with whom they have published most often include:

  • Rahul Yedida
  • Huy Tu
  • Joymallya Chakraborty
  • Rui Shu
  • Zhe Yu

Tim Menzies was recognized as an IEEE Fellow in 2019 for contributions related to software engineering for artificial intelligence.

Best Publications

  • Data Mining Static Code Attributes to Learn Defect Predictors

    T. Menzies;J. Greenwald;A. Frank

  • On the relative value of cross-company and within-company data for defect prediction

    Burak Turhan;Tim Menzies;Ayşe B. Bener;Justin Di Stefano

  • Defect prediction from static code features: current results, limitations, new approaches

    Tim Menzies;Zach Milton;Burak Turhan;Bojan Cukic

  • Heterogeneous Defect Prediction

    Jaechang Nam;Wei Fu;Sunghun Kim;Tim Menzies

  • Automated severity assessment of software defect reports

    T. Menzies;A. Marcus

  • The \{PROMISE\} Repository of Software Engineering Databases.

    Jelber Sayyad Shirabad;Tim Menzies

  • Selecting Best Practices for Effort Estimation

    T. Menzies;Z. Chen;J. Hihn;K. Lum

  • Problems with Precision: A Response to "Comments on 'Data Mining Static Code Attributes to Learn Defect Predictors'"

    T. Menzies;A. Dekhtyar;J. Distefano;J. Greenwald

  • On the Value of Ensemble Effort Estimation

    E. Kocaguneli;T. Menzies;J. W. Keung

  • Tuning for software analytics

    Wei Fu;Tim Menzies;Xipeng Shen

  • Bias in machine learning software: why? how? what to do?

    Joymallya Chakraborty;Suvodeep Majumder;Tim Menzies

  • Local versus Global Lessons for Defect Prediction and Effort Estimation

    T. Menzies;A. Butcher;D. Cok;A. Marcus

  • On the value of user preferences in search-based software engineering: a case study in software product lines

    Abdel Salam Sayyad;Tim Menzies;Hany Ammar

  • Exploiting the Essential Assumptions of Analogy-Based Effort Estimation

    E. Kocaguneli;T. Menzies;A. Bener;J. W. Keung

  • Better cross company defect prediction

    Fayola Peters;Tim Menzies;Andrian Marcus

  • On the use of relevance feedback in IR-based concept location

    Sonia Haiduc;Andrian Marcus;Tim Menzies

  • What is wrong with topic modeling? And how to fix it using search-based software engineering

    Amritanshu Agrawal;Wei Fu;Tim Menzies

  • Implications of ceiling effects in defect predictors

    Tim Menzies;Burak Turhan;Ayse Bener

  • Automatic query reformulations for text retrieval in software engineering

    Sonia Haiduc;Gabriele Bavota;Andrian Marcus;Rocco Oliveto

  • Knowledge maintenance: the state of the art

    Tim Menzies

  • Local vs. global models for effort estimation and defect prediction

    Tim Menzies;Andrew Butcher;Andrian Marcus;Thomas Zimmermann

Frequent Co-Authors

Bojan Cukic
Bojan Cukic University of North Carolina at Charlotte
Burak Turhan
Burak Turhan Monash University
Leandro L. Minku
Leandro L. Minku University of Birmingham
Thomas Zimmermann
Thomas Zimmermann Microsoft (United States)
Ayse Bener
Ayse Bener Toronto Metropolitan University
Jacky Keung
Jacky Keung City University of Hong Kong
Barry Boehm
Barry Boehm University of Southern California
Andrian Marcus
Andrian Marcus The University of Texas at Dallas
Christian Bird
Christian Bird Microsoft (United States)
Steve Easterbrook
Steve Easterbrook University of Toronto

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