World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
8398
World Ranking
5690
National Ranking
2585

Lingming Zhang 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 Lingming Zhang 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: 122 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Lingming Zhang 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 Lingming Zhang 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Lingming Zhang is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research primarily falls within the field of computer science, with a focus on software engineering and artificial intelligence. Zhang has a prolific publication record covering multiple subfields, including software, artificial intelligence, information systems, computer networks and communications, and signal processing.

The scientist's work has been featured extensively in several prominent venues. These include:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Proceedings of the 44th International Conference on Software Engineering
  • Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
  • ACM Transactions on Software Engineering and Methodology

The main topics covered in their publications involve software testing and debugging techniques, software engineering research, software system performance and reliability, advanced malware detection techniques, software reliability and analysis research, adversarial robustness in machine learning, and machine learning and data classification. A complete list of these topics includes:

  • Software Testing and Debugging Techniques
  • Software Engineering Research
  • Software System Performance and Reliability
  • Advanced Malware Detection Techniques
  • Software Reliability and Analysis Research
  • Adversarial Robustness in Machine Learning
  • Machine Learning and Data Classification

Lingming Zhang's collaborative work includes frequent partnerships with several coauthors, namely Jiawei Liu, Yinlin Deng, Chunqiu Steven Xia, Yuxiang Wei, and Chenyuan Yang.

Recent publications by Zhang and collaborators include:

  • "Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation," 2023, published in arXiv (Cornell University)
  • "Less training, more repairing please: revisiting automated program repair via zero-shot learning," 2022, Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
  • "Practical Accuracy Estimation for Efficient Deep Neural Network Testing," 2020, ACM Transactions on Software Engineering and Methodology
  • "Free lunch for testing," 2022, Proceedings of the 44th International Conference on Software Engineering
  • "Fuzzing deep-learning libraries via automated relational API inference," 2022, Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Best Publications

  • DeepRoad: GAN-based metamorphic testing and input validation framework for autonomous driving systems

    Mengshi Zhang;Yuqun Zhang;Lingming Zhang;Cong Liu

  • Automated Program Repair in the Era of Large Pre-trained Language Models

    Unknown

  • DeepFL: integrating multiple fault diagnosis dimensions for deep fault localization

    Xia Li;Wei Li;Yuqun Zhang;Lingming Zhang

  • Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation

    Unknown

  • Less training, more repairing please: revisiting automated program repair via zero-shot learning

    Unknown

  • Automated Program Repair via Conversation: Fixing 162 out of 337 Bugs for $0.42 Each using ChatGPT

    Unknown

  • Fuzz4ALL: Universal Fuzzing with Large Language Models

    Unknown

  • An extensive study on pre-trained models for program understanding and generation

    Unknown

  • Bridging the gap between the total and additional test-case prioritization strategies

    Lingming Zhang;Dan Hao;Lu Zhang;Gregg Rothermel

  • Predictive Mutation Testing

    Jie Zhang;Lingming Zhang;Mark Harman;Dan Hao

  • A Static Approach to Prioritizing JUnit Test Cases

    Hong Mei;Dan Hao;Lingming Zhang;Lu Zhang

  • Practical program repair via bytecode mutation

    Ali Ghanbari;Samuel Benton;Lingming Zhang

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

    Owolabi Legunsen;Farah Hariri;August Shi;Yafeng Lu

  • Test generation via Dynamic Symbolic Execution for mutation testing

    Lingming Zhang;Tao Xie;Lu Zhang;Nikolai Tillmann

  • DeepBillboard: systematic physical-world testing of autonomous driving systems

    Husheng Zhou;Wei Li;Zelun Kong;Junfeng Guo

  • Boosting spectrum-based fault localization using PageRank

    Mengshi Zhang;Xia Li;Lingming Zhang;Sarfraz Khurshid

  • Transforming Programs and Tests in Tandem for Fault Localization

    Xia Li;Lingming Zhang

  • A Unified Test Case Prioritization Approach

    Dan Hao;Lingming Zhang;Lu Zhang;Gregg Rothermel

  • Localizing failure-inducing program edits based on spectrum information

    Lingming Zhang;Miryung Kim;Sarfraz Khurshid

  • Free Lunch for Testing: Fuzzing Deep-Learning Libraries from Open Source

    Unknown

  • Boosting coverage-based fault localization via graph-based representation learning

    Yiling Lou;Qihao Zhu;Jinhao Dong;Xia Li

  • An information retrieval approach for regression test prioritization based on program changes

    Ripon K. Saha;Lingming Zhang;Sarfraz Khurshid;Dewayne E. Perry

  • How does regression test prioritization perform in real-world software evolution?

    Yafeng Lu;Yiling Lou;Shiyang Cheng;Lingming Zhang

  • Operator-based and random mutant selection: better together

    Lingming Zhang;Milos Gligoric;Darko Marinov;Sarfraz Khurshid

  • Hybrid regression test selection

    Lingming Zhang

  • Faster mutation testing inspired by test prioritization and reduction

    Lingming Zhang;Darko Marinov;Sarfraz Khurshid

  • Predictive mutation testing

    Jie Zhang;Ziyi Wang;Lingming Zhang;Dan Hao

Frequent Co-Authors

Lu Zhang
Lu Zhang Peking University
Dan Hao
Dan Hao Peking University
Sarfraz Khurshid
Sarfraz Khurshid The University of Texas at Austin
Darko Marinov
Darko Marinov University of Illinois at Urbana-Champaign
Hong Mei
Hong Mei Peking University
Miryung Kim
Miryung Kim University of California, Los Angeles
Yingfei Xiong
Yingfei Xiong Peking University
Gregg Rothermel
Gregg Rothermel North Carolina State University
W. Eric Wong
W. Eric Wong The University of Texas at Dallas
Bei Yu
Bei Yu Chinese University of Hong Kong

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