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Computer Science
Switzerland
2025

D-Index & Metrics

Computer Science

D-Index
65
Citations
16868
World Ranking
2460
National Ranking
58

Harald C. Gall 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 Harald C. Gall 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: 272 publications — 68th percentile

68% of scientists in this discipline score the same or lower.

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

Harald C. Gall 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 Harald C. Gall 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: 65 D-Index — 83rd percentile

83% 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

  • 2025 - Research.com Computer Science in Switzerland Leader Award
  • 2022 - Research.com Computer Science in Switzerland Leader Award

Overview

Harald C. Gall is affiliated with the University of Zurich in Switzerland. Their research primarily spans the field of Computer Science, with an emphasis on several subfields including Artificial Intelligence, Software, Information Systems, Computer Networks and Communications, and Signal Processing.

The main topics covered in their work include Software Testing and Debugging Techniques, Software Engineering Research, Software Reliability and Analysis Research, Software System Performance and Reliability, Topic Modeling, Advanced Malware Detection Techniques, and Natural Language Processing Techniques.

Harald C. Gall has published extensively, with a substantial number of papers appearing in various notable venues. Frequent publication venues for their work are:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Transactions on Software Engineering
  • Empirical Software Engineering
  • ACM Transactions on Software Engineering and Methodology

Their recent papers include:

  • "An empirical characterization of bad practices in continuous integration," 2020, Empirical Software Engineering
  • "Automatic Detection and Repair Recommendation of Directive Defects in Java API Documentation," 2020, IEEE Transactions on Software Engineering
  • "Adversarial Robustness of Deep Code Comment Generation," 2022, ACM Transactions on Software Engineering and Methodology
  • "Boosting API Recommendation With Implicit Feedback," 2021, IEEE Transactions on Software Engineering
  • "User Review-Based Change File Localization for Mobile Applications," 2020, IEEE Transactions on Software Engineering

Harald C. Gall has collaborated regularly with several co-authors, notably:

  • Pasquale Salza
  • Taolue Chen
  • Marco Edoardo Palma
  • Yu Zhou
  • Carmine Vassallo

Their research contributions focus on advancing knowledge on software engineering practices, software testing, debugging, and reliability, as well as natural language processing techniques applied to software artifacts. Multiple publications have examined software system performance and reliability alongside research on advanced malware detection.

Best Publications

  • Software engineering for machine learning: a case study

    Saleema Amershi;Andrew Begel;Christian Bird;Robert DeLine

  • Cross-project defect prediction: a large scale experiment on data vs. domain vs. process

    Thomas Zimmermann;Nachiappan Nagappan;Harald Gall;Emanuel Giger

  • Change Distilling:Tree Differencing for Fine-Grained Source Code Change Extraction

    B. Fluri;M. Wursch;M. Pinzger;H.C. Gall

  • Populating a Release History Database from version control and bug tracking systems

    M. Fischer;M. Pinzger;H. Gall

  • Detection of logical coupling based on product release history

    H. Gall;K. Hajek;M. Jazayeri

  • How can i improve my app? Classifying user reviews for software maintenance and evolution

    Sebastiano Panichella;Andrea Di Sorbo;Emitza Guzman;Corrado A. Visaggio

  • Don't touch my code!: examining the effects of ownership on software quality

    Christian Bird;Nachiappan Nagappan;Brendan Murphy;Harald Gall

  • CVS release history data for detecting logical couplings

    H. Gall;M. Jazayeri;J. Krajewski

  • Does distributed development affect software quality?: an empirical case study of Windows Vista

    Christian Bird;Nachiappan Nagappan;Premkumar Devanbu;Harald Gall

  • What would users change in my app? summarizing app reviews for recommending software changes

    Andrea Di Sorbo;Sebastiano Panichella;Carol V. Alexandru;Junji Shimagaki

  • Do Code and Comments Co-Evolve? On the Relation between Source Code and Comment Changes

    B. Fluri;M. Wursch;H.C. Gall

  • Predicting the fix time of bugs

    Emanuel Giger;Martin Pinzger;Harald Gall

  • Putting It All Together: Using Socio-technical Networks to Predict Failures

    Christian Bird;Nachiappan Nagappan;Harald Gall;Brendan Murphy

  • Classifying Change Types for Qualifying Change Couplings

    B. Fluri;H.C. Gall

  • Combining text mining and data mining for bug report classification

    Yu Zhou;Yu Zhou;Yanxiang Tong;Ruihang Gu;Harald Gall

  • Generation of business process models for object life cycle compliance

    Jochen M. Küster;Ksenia Ryndina;Harald Gall

  • Software evolution observations based on product release history

    H. Gall;M. Jazayeri;R.R. Klosch;G. Trausmuth

  • Visualizing multiple evolution metrics

    Martin Pinzger;Harald Gall;Michael Fischer;Michele Lanza

  • Visualizing software release histories: the use of color and third dimension

    H. Gall;M. Jazayeri;C. Riva

  • Analyzing and relating bug report data for feature tracking

    M. Fischer;M. Pinzger;H. Gall

  • Predicting the fix time of bugs

    E. Giger;M. Pinzger;H.C. Gall

Frequent Co-Authors

Sebastiano Panichella
Sebastiano Panichella University of Zurich
Martin Pinzger
Martin Pinzger University of Klagenfurt
Philipp Leitner
Philipp Leitner University of Gothenburg
Fabio Palomba
Fabio Palomba University of Salerno
Nachiappan Nagappan
Nachiappan Nagappan Facebook (United States)
Brendan Murphy
Brendan Murphy Microsoft (United States)
Christian Bird
Christian Bird Microsoft (United States)
Gerardo Canfora
Gerardo Canfora University of Sannio
Abraham Bernstein
Abraham Bernstein University of Zurich

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