Lin Shi

928 total citations · 1 hit paper
42 papers, 517 citations indexed

About

Lin Shi is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Lin Shi has authored 42 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Information Systems, 19 papers in Artificial Intelligence and 9 papers in Computer Networks and Communications. Recurrent topics in Lin Shi's work include Software Engineering Research (34 papers), Topic Modeling (12 papers) and Software Engineering Techniques and Practices (11 papers). Lin Shi is often cited by papers focused on Software Engineering Research (34 papers), Topic Modeling (12 papers) and Software Engineering Techniques and Practices (11 papers). Lin Shi collaborates with scholars based in China, United States and Canada. Lin Shi's co-authors include Qing Wang, Fabio Palomba, Muhammad Ilyas Azeem, Celia Chen, Barry Boehm, Ye Yang, Qing Wang, Qing Wang, Song Wang and Junjie Wang and has published in prestigious journals such as Information and Software Technology, ACM Transactions on Software Engineering and Methodology and Requirements Engineering.

In The Last Decade

Lin Shi

40 papers receiving 502 citations

Hit Papers

Machine learning techniques for code smell detection: A s... 2019 2026 2021 2023 2019 50 100 150
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. Machine learning techniques for code smell detection: A systematic literature review and meta-analysis
    2019 181 citations Lin Shi, Qing Wang 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
Lin Shi China 12 404 247 151 91 86 42 517
Toufique Ahmed United States 11 351 0.9× 154 0.6× 264 1.7× 109 1.2× 58 0.7× 25 524
DongGyun Han United Kingdom 12 417 1.0× 254 1.0× 127 0.8× 147 1.6× 50 0.6× 27 492
André Hora Brazil 12 449 1.1× 159 0.6× 152 1.0× 187 2.1× 129 1.5× 49 508
Csaba Nagy Switzerland 14 491 1.2× 226 0.9× 148 1.0× 193 2.1× 69 0.8× 43 570
Nuthan Munaiah United States 10 343 0.8× 142 0.6× 58 0.4× 112 1.2× 109 1.3× 17 405
Daniel Alencar da Costa New Zealand 13 552 1.4× 338 1.4× 64 0.4× 197 2.2× 67 0.8× 41 605
Suhaib Mujahid Canada 10 297 0.7× 144 0.6× 75 0.5× 123 1.4× 68 0.8× 19 369
Hazeline U. Asuncion United States 8 368 0.9× 139 0.6× 135 0.9× 84 0.9× 44 0.5× 25 456
Byron J. Williams United States 12 356 0.9× 177 0.7× 101 0.7× 110 1.2× 81 0.9× 31 429

Countries citing papers authored by Lin Shi

Since Specialization
Citations

This map shows the geographic impact of Lin Shi'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 Lin Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Shi more than expected).

Fields of papers citing papers by Lin Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lin Shi. 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 Lin Shi. The network helps show where Lin Shi may publish in the future.

Co-authorship network of co-authors of Lin Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Lin Shi. A scholar is included among the top collaborators of Lin Shi 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 Lin Shi. Lin Shi 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.
Wu, Di, et al.. (2024). iSMELL: Assembling LLMs with Expert Toolsets for Code Smell Detection and Refactoring. 1345–1357. 3 indexed citations
2.
Shi, Lin, et al.. (2024). ClarifyGPT: A Framework for Enhancing LLM-Based Code Generation via Requirements Clarification. Proceedings of the ACM on software engineering.. 1(FSE). 2332–2354. 18 indexed citations
3.
Huang, Yue-Kai, Junjie Wang, Song Wang, et al.. (2024). Deep API Sequence Generation via Golden Solution Samples and API Seeds. ACM Transactions on Software Engineering and Methodology. 34(2). 1–21. 1 indexed citations
4.
Shi, Lin, et al.. (2023). Developer-Intent Driven Code Comment Generation. 768–780. 16 indexed citations
5.
Niu, Nan, et al.. (2022). Testing software’s changing features with environment-driven abstraction identification. Requirements Engineering. 27(4). 405–427. 9 indexed citations
6.
Zhang, Hongyu, et al.. (2022). Where is your app frustrating users?. arXiv (Cornell University). 2427–2439. 14 indexed citations
7.
Shi, Lin, et al.. (2022). Automatic Comment Generation via Multi-Pass Deliberation. 1–12. 9 indexed citations
8.
Shi, Lin, Yumin Zhang, Ye Yang, et al.. (2022). BugListener. 299–311. 2 indexed citations
9.
Shi, Lin, Xiaohong Chen, Song Wang, et al.. (2022). Are we building on the rock? on the importance of data preprocessing for code summarization. 107–119. 40 indexed citations
10.
Niu, Nan, et al.. (2021). Environment-Driven Abstraction Identification for Requirements-Based Testing. 1. 245–256. 7 indexed citations
11.
12.
Shi, Lin, et al.. (2020). A Deep Context-wise Method for Coreference Detection in Natural Language Requirements. Swinburne Research Bank (Swinburne University of Technology). 180–191. 11 indexed citations
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Shi, Lin, et al.. (2020). Detection of hidden feature requests from massive chat messages via deep siamese network. 641–653. 19 indexed citations
16.
Shi, Lin, et al.. (2017). Understanding feature requests by leveraging fuzzy method and linguistic analysis. 440–450. 16 indexed citations
17.
Boehm, Barry, et al.. (2016). The Key Roles of Maintainability in an Ontology for System Qualities. INCOSE International Symposium. 26(1). 2026–2040. 7 indexed citations
18.
Shi, Lin, et al.. (2014). Study and Applications on Integrated Drilling Engineering Software for Drilling Engineering Design and Real-time Optimization (Russian). SPE Annual Caspian Technical Conference and Exhibition. 1 indexed citations
19.
Liu, Wei, et al.. (2013). Development and Application of Pressure Control Drilling System (PCDS) for Drilling Complex Problem. International Petroleum Technology Conference. 2 indexed citations
20.
Shi, Lin, Hongwei Jiang, Qingfeng Guo, & Peng Song. (2012). Investigation on the Differential Pressure Leakage of Thief Formation. IADC/SPE Asia Pacific Drilling Technology Conference and Exhibition. 2 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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