World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
13075
World Ranking
3841
National Ranking
1822

Darko Marinov 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 Darko Marinov 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: 185 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

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

Darko Marinov 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 Darko Marinov 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: 57 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Overview

Darko Marinov is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their primary area of research is within computer science, with a significant focus on software-related disciplines.

The main fields of study for Marinov include:

  • Computer Science

Within these, their subfields of study are:

  • Software
  • Information Systems
  • Computer Networks and Communications
  • Artificial Intelligence
  • Information Systems and Management

Marinov's research covers various main topics, notably:

  • Software Testing and Debugging Techniques
  • Software Engineering Research
  • Software Reliability and Analysis Research
  • Software System Performance and Reliability
  • Advanced Software Engineering Methodologies
  • Scientific Computing and Data Management
  • Cell Image Analysis Techniques

Key recent publications by Marinov include:

  • "A large-scale longitudinal study of flaky tests," 2020, Proceedings of the ACM on Programming Languages
  • "Learning from reproducing computational results: introducing three principles and the Reproduction Package," 2021, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • "Preempting flaky tests via non-idempotent-outcome tests," 2022, Proceedings of the 44th International Conference on Software Engineering
  • "Finding Polluter Tests Using Java PathFinder," 2021, ACM SIGSOFT Software Engineering Notes
  • "Suboptimal Comments in Java Projects: From Independent Comment Changes to Commenting Practices," 2022, ACM Transactions on Software Engineering and Methodology

The frequent publication venues where Marinov's work appears are:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • OPAL (Open@LaTrobe) (La Trobe University)
  • Proceedings of the ACM on Programming Languages
  • Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences

Marinov has collaborated frequently with several co-authors, including:

  • Anjiang Wei
  • Wing Lam
  • Tao Xie
  • Pu Yi
  • Tianyin Xu

Best Publications

  • CUTE: a concolic unit testing engine for C

    Koushik Sen;Darko Marinov;Gul Agha

  • Korat: automated testing based on Java predicates

    Chandrasekhar Boyapati;Sarfraz Khurshid;Darko Marinov

  • An empirical analysis of flaky tests

    Qingzhou Luo;Farah Hariri;Lamyaa Eloussi;Darko Marinov

  • Usage, costs, and benefits of continuous integration in open-source projects

    Michael Hilton;Timothy Tunnell;Kai Huang;Darko Marinov

  • Symstra: a framework for generating object-oriented unit tests using symbolic execution

    Tao Xie;Darko Marinov;Wolfram Schulte;David Notkin

  • TestEra: a novel framework for automated testing of Java programs

    D. Marinov;S. Khurshid

  • Automated Detection of Refactorings in Evolving Components

    Danny Dig;Can Comertoglu;Darko Marinov;Ralph Johnson

  • Automated testing of refactoring engines

    Brett Daniel;Danny Dig;Kely Garcia;Darko Marinov

  • Practical regression test selection with dynamic file dependencies

    Milos Gligoric;Lamyaa Eloussi;Darko Marinov

  • TestEra: Specification-Based Testing of Java Programs Using SAT

    Sarfraz Khurshid;Darko Marinov

  • Trade-offs in continuous integration: assurance, security, and flexibility

    Michael Hilton;Nicholas Nelson;Timothy Tunnell;Darko Marinov

  • Message from the program chairs of icse 2020

    Jane Cleland-Huang;Darko Marinov

  • @tComment: Testing Javadoc Comments to Detect Comment-Code Inconsistencies

    Shin Hwei Tan;Darko Marinov;Lin Tan;Gary T. Leavens

  • Test generation through programming in UDITA

    Milos Gligoric;Tihomir Gvero;Vilas Jagannath;Sarfraz Khurshid

  • Rostra: a framework for detecting redundant object-oriented unit tests

    Tao Xie;D. Notkin;D. Marinov

  • Toddler: detecting performance problems via similar memory-access patterns

    Adrian Nistor;Linhai Song;Darko Marinov;Shan Lu

  • DeFlaker: automatically detecting flaky tests

    Jonathan Bell;Owolabi Legunsen;Michael Hilton;Lamyaa Eloussi

  • iDFlakies: A Framework for Detecting and Partially Classifying Flaky Tests

    Wing Lam;Reed Oei;August Shi;Darko Marinov

  • Comparing non-adequate test suites using coverage criteria

    Milos Gligoric;Alex Groce;Chaoqiang Zhang;Rohan Sharma

  • ReAssert: Suggesting Repairs for Broken Unit Tests

    Brett Daniel;Vilas Jagannath;Danny Dig;Darko Marinov

  • An extensive study of static regression test selection in modern software evolution

    Owolabi Legunsen;Farah Hariri;August Shi;Yafeng Lu

  • State extensions for java pathfinder

    Tihomir Gvero;Milos Gligoric;Steven Lauterburg;Marcelo d'Amorim

Frequent Co-Authors

Sarfraz Khurshid
Sarfraz Khurshid The University of Texas at Austin
Danny Dig
Danny Dig University of Colorado Boulder
Tao Xie
Tao Xie Peking University
Lingming Zhang
Lingming Zhang University of Illinois at Urbana-Champaign
Grigore Rosu
Grigore Rosu University of Illinois at Urbana-Champaign
Gul Agha
Gul Agha University of Illinois at Urbana-Champaign
Mahesh Viswanathan
Mahesh Viswanathan University of Illinois at Urbana-Champaign
Jennifer C. Hou
Jennifer C. Hou University of Illinois at Urbana-Champaign
David Notkin
David Notkin University of Washington

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