World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
5607
World Ranking
8113
National Ranking
396

Michael Pradel 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 Michael Pradel 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: 116 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Michael Pradel 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 Michael Pradel 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Michael Pradel is affiliated with the University of Stuttgart in Germany. Their research primarily focuses on computer science, with a notable concentration on software engineering and related subfields.

The main fields of study for Michael Pradel encompass computer science, with specialized attention to information systems, artificial intelligence, software, computer networks and communications, and signal processing.

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

Within their body of work, Michael Pradel covers several key topics including software engineering research, software testing and debugging techniques, advanced malware detection techniques, software reliability and analysis research, topic modeling, software system performance and reliability, and parallel computing and optimization techniques.

  • Software Engineering Research
  • Software Testing and Debugging Techniques
  • Advanced Malware Detection Techniques
  • Software Reliability and Analysis Research
  • Topic Modeling
  • Software System Performance and Reliability
  • Parallel Computing and Optimization Techniques

The scientist has contributed to publications in various venues, with numerous papers appearing in arXiv (Cornell University), Zenodo (CERN European Organization for Nuclear Research), and Proceedings of the ACM on Software Engineering. Other venues include the Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering and ACM Computing Surveys.

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Proceedings of the ACM on software engineering.
  • Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
  • ACM Computing Surveys

Some of Michael Pradel's recent papers include:

  • A Survey of Compiler Testing (2020), published in ACM Computing Surveys
  • Bugs in Quantum computing platforms: an empirical study (2022), published in Proceedings of the ACM on Programming Languages
  • Code Search: A Survey of Techniques for Finding Code (2022), published in ACM Computing Surveys
  • Automatic Program Repair (2021), published in IEEE Software
  • Code Generation Tools (Almost) for Free? A Study of Few-Shot, Pre-Trained Language Models on Code (2022), published in arXiv (Cornell University)

Frequent collaborators in Michael Pradel's work include Matteo Paltenghi, Islem Bouzenia, Jibesh Patra, Beatriz Souza, and Daniel Lehmann.

  • Matteo Paltenghi
  • Islem Bouzenia
  • Jibesh Patra
  • Beatriz Souza
  • Daniel Lehmann

Best Publications

  • Automated program repair

    Claire Le Goues;Michael Pradel;Abhik Roychoudhury

  • DeepBugs: a learning approach to name-based bug detection

    Michael Pradel;Koushik Sen

  • Getafix: learning to fix bugs automatically

    Johannes Bader;Andrew Scott;Michael Pradel;Satish Chandra

  • Automatic Generation of Object Usage Specifications from Large Method Traces

    Michael Pradel;Thomas R. Gross

  • Fuzz4ALL: Universal Fuzzing with Large Language Models

    Unknown

  • A Survey of Compiler Testing

    Junjie Chen;Jibesh Patra;Michael Pradel;Yingfei Xiong

  • Performance issues and optimizations in JavaScript: an empirical study

    Marija Selakovic;Michael Pradel

  • NL2Type: inferring JavaScript function types from natural language information

    Rabee Sohail Malik;Jibesh Patra;Michael Pradel

  • Small World with High Risks: A Study of Security Threats in the npm Ecosystem

    Markus Zimmermann;Cristian-Alexandru Staicu;Cam Tenny;Michael Pradel

  • Performance Regression Testing of Concurrent Classes.

    Michael Pradel;Markus Huggler;Thomas R. Gross

  • How many of all bugs do we find? a study of static bug detectors

    Andrew Habib;Michael Pradel

  • SYNODE: Understanding and Automatically Preventing Injection Attacks on NODE.JS.

    Cristian-Alexandru Staicu;Michael Pradel;Benjamin Livshits

  • Statically checking API protocol conformance with mined multi-object specifications

    Michael Pradel;Ciera Jaspan;Jonathan Aldrich;Thomas R. Gross

  • A Survey of Dynamic Analysis and Test Generation for JavaScript

    Esben Andreasen;Liang Gong;Anders Møller;Michael Pradel

  • Fully automatic and precise detection of thread safety violations

    Michael Pradel;Thomas R. Gross

  • JITProf: pinpointing JIT-unfriendly JavaScript code

    Liang Gong;Michael Pradel;Koushik Sen

  • TypeWriter: neural type prediction with search-based validation

    Michael Pradel;Georgios Gousios;Jason Liu;Satish Chandra

  • DLint: dynamically checking bad coding practices in JavaScript

    Liang Gong;Michael Pradel;Manu Sridharan;Koushik Sen

  • A framework for the evaluation of specification miners based on finite state machines

    Michael Pradel;Philipp Bichsel;Thomas R. Gross

  • Leveraging test generation and specification mining for automated bug detection without false positives

    Michael Pradel;Thomas R. Gross

  • Freezing the Web: A Study of ReDoS Vulnerabilities in JavaScript-based Web Servers

    Cristian-Alexandru Staicu;Michael Pradel

  • Everything Old is New Again: Binary Security of WebAssembly

    Daniel Lehmann;Johannes Kinder;Michael Pradel

  • Statically checking API protocol conformance with mined multi-object specifications: companion report

    Michael Pradel;Cierra Jaspan;Jonathan Aldrich;Thomas K.R. Gross

Frequent Co-Authors

Koushik Sen
Koushik Sen University of California, Berkeley
Daniel Lehmann
Daniel Lehmann Hebrew University of Jerusalem
Satish Chandra
Satish Chandra Association for Computing Machinery
Claire Le Goues
Claire Le Goues Carnegie Mellon University
Anders Møller
Anders Møller Aarhus University
Abhik Roychoudhury
Abhik Roychoudhury National University of Singapore
Andrei Sabelfeld
Andrei Sabelfeld Chalmers University of Technology
George C. Necula
George C. Necula University of California, Berkeley
André DeHon
André DeHon University of Pennsylvania

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