Ming Wen

3.0k total citations · 2 hit papers
105 papers, 1.9k citations indexed

About

Ming Wen is a scholar working on Information Systems, Software and Signal Processing. According to data from OpenAlex, Ming Wen has authored 105 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Information Systems, 50 papers in Software and 20 papers in Signal Processing. Recurrent topics in Ming Wen's work include Software Engineering Research (45 papers), Software Testing and Debugging Techniques (42 papers) and Software Reliability and Analysis Research (33 papers). Ming Wen is often cited by papers focused on Software Engineering Research (45 papers), Software Testing and Debugging Techniques (42 papers) and Software Reliability and Analysis Research (33 papers). Ming Wen collaborates with scholars based in China, Hong Kong and United States. Ming Wen's co-authors include Shing-Chi Cheung, Rongxin Wu, Dan Hao, Junjie Chen, Yepang Liu, Shangwen Wang, Xiaoguang Mao, Bo Lin, Hai Jin and Bin Zhang and has published in prestigious journals such as Journal of The Electrochemical Society, IEEE Transactions on Software Engineering and IEEE Transactions on Electron Devices.

In The Last Decade

Ming Wen

97 papers receiving 1.9k citations

Hit Papers

Context-aware patch generation for better automated progr... 2018 2026 2020 2023 2018 2024 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Context-aware patch generation for better automated program repair
    2018 217 citations Ming Wen, Rongxin Wu et al. Rare & Special e-Zone (The Hong Kong University of Science and Technology) profile →
  2. Automatic Root Cause Analysis via Large Language Models for Cloud Incidents
    2024 57 citations Minghua Ma, Ming Wen et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ming Wen China 23 1.0k 808 415 364 295 105 1.9k
Xiaoxing Ma China 20 673 0.7× 503 0.6× 138 0.3× 641 1.8× 532 1.8× 163 1.5k
Manoj Singh Gaur India 28 850 0.8× 350 0.4× 524 1.3× 2.0k 5.5× 609 2.1× 185 2.7k
Weihang Wang United States 17 219 0.2× 73 0.1× 453 1.1× 251 0.7× 706 2.4× 43 1.4k
Xinyu Xing United States 22 742 0.7× 261 0.3× 149 0.4× 732 2.0× 942 3.2× 103 1.9k
Shaowei Cai China 24 230 0.2× 219 0.3× 222 0.5× 798 2.2× 674 2.3× 113 1.9k
Cong Sun China 18 236 0.2× 94 0.1× 346 0.8× 394 1.1× 360 1.2× 80 1.1k
Eric Medvet Italy 19 505 0.5× 231 0.3× 60 0.1× 482 1.3× 643 2.2× 125 1.4k
Hongsong Zhu China 19 334 0.3× 76 0.1× 253 0.6× 452 1.2× 477 1.6× 93 1.2k
Ding Li United States 22 209 0.2× 54 0.1× 2.1k 5.0× 547 1.5× 60 0.2× 66 2.3k

Countries citing papers authored by Ming Wen

Since Specialization
Citations

This map shows the geographic impact of Ming Wen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ming Wen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Wen more than expected).

Fields of papers citing papers by Ming Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming Wen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ming Wen. The network helps show where Ming Wen may publish in the future.

Co-authorship network of co-authors of Ming Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Wen. A scholar is included among the top collaborators of Ming Wen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ming Wen. Ming Wen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wen, Ming, et al.. (2025). CXXCrafter: An LLM-Based Agent for Automated C/C++ Open Source Software Building. Proceedings of the ACM on software engineering.. 2(FSE). 2618–2640.
2.
Yan, Haoran, Minghua Ma, Ming Wen, et al.. (2025). An Empirical Study of Production Incidents in Generative AI Cloud Services. 359–370.
3.
Wen, Ming, et al.. (2025). A study on prompt design, advantages and limitations of ChatGPT for deep learning program repair. Automated Software Engineering. 32(1). 9 indexed citations
4.
Li, Shichun, et al.. (2024). Ultra-short term wind power prediction based on quadratic variational mode decomposition and multi-model fusion of deep learning. Computers & Electrical Engineering. 116. 109157–109157. 12 indexed citations
5.
Wen, Ming, et al.. (2024). Generalization-Enhanced Code Vulnerability Detection via Multi-Task Instruction Fine-Tuning. 10507–10521. 3 indexed citations
6.
Wen, Ming, et al.. (2024). Reducing False Positives of Static Bug Detectors Through Code Representation Learning. 681–692. 2 indexed citations
7.
Xia, Ke, et al.. (2024). Tunneling Barrier Thickness Dependence of Spin Polarization of Ferromagnet in Magnetic Tunnel Junctions. Chinese Physics Letters. 41(11). 117201–117201.
8.
9.
Wen, Ming, et al.. (2024). Towards Understanding the Effectiveness of Large Language Models on Directed Test Input Generation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1408–1420. 2 indexed citations
10.
Tian, Yongqiang, Ming Wen, Shing-Chi Cheung, et al.. (2023). Finding Deviated Behaviors of the Compressed DNN Models for Image Classifications. ACM Transactions on Software Engineering and Methodology. 32(5). 1–32. 3 indexed citations
11.
Fu, Cai, et al.. (2023). Toward Interpretable Graph Tensor Convolution Neural Network for Code Semantics Embedding. ACM Transactions on Software Engineering and Methodology. 32(5). 1–40. 3 indexed citations
12.
13.
Wang, Ying, Ming Wen, Yepang Liu, et al.. (2020). Watchman. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 125–135. 47 indexed citations
14.
Qin, Zhenxing, Wenhai Wang, Ming Wen, et al.. (2019). Multicolor emissive sulfur, nitrogen co-doped carbon dots and their application in ion detection and solid lighting. Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy. 229. 117859–117859. 25 indexed citations
15.
Wen, Ming, Yepang Liu, Rongxin Wu, et al.. (2019). Exposing Library API Misuses Via Mutation Analysis. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 866–877. 31 indexed citations
16.
Wu, Rongxin, Ming Wen, Shing-Chi Cheung, & Hongyu Zhang. (2018). ChangeLocator. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 536–536. 7 indexed citations
17.
Xu, Jing-Ping, et al.. (2018). Effects of HfO2 encapsulation on electrical performances of few-layered MoS2 transistor with ALD HfO2 as back-gate dielectric. Nanotechnology. 29(34). 345201–345201. 40 indexed citations
18.
Dai, Wei, et al.. (2005). [Effect and mechanism of rhubarb on fibrinolysis in secondary damaged central nerve system of rats with acute hemorrhagic stroke].. PubMed. 25(1). 38–41. 3 indexed citations
19.
20.
Yeh, K. Y., et al.. (2005). Focal right ventricular tachycardia originating from the subtricuspid septum. EP Europace. 7(4). 348–352. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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