Hailong Sun

3.8k total citations · 1 hit paper
161 papers, 2.3k citations indexed

About

Hailong Sun is a scholar working on Information Systems, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Hailong Sun has authored 161 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 92 papers in Information Systems, 66 papers in Computer Networks and Communications and 59 papers in Artificial Intelligence. Recurrent topics in Hailong Sun's work include Service-Oriented Architecture and Web Services (31 papers), Mobile Crowdsensing and Crowdsourcing (28 papers) and Software Engineering Research (25 papers). Hailong Sun is often cited by papers focused on Service-Oriented Architecture and Web Services (31 papers), Mobile Crowdsensing and Crowdsourcing (28 papers) and Software Engineering Research (25 papers). Hailong Sun collaborates with scholars based in China, Hong Kong and United States. Hailong Sun's co-authors include Xu Wang, Hongyu Zhang, Zicheng Huang, Xi Chen, Xudong Liu, Xudong Liu, Jian Zhang, Jinpeng Huai, Xudong Liu and Richong Zhang and has published in prestigious journals such as IEEE Access, ACM Computing Surveys and Information Sciences.

In The Last Decade

Hailong Sun

146 papers receiving 2.3k citations

Hit Papers

A Novel Neural Source Code Representation Based on Abstra... 2019 2026 2021 2023 2019 100 200 300
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. A Novel Neural Source Code Representation Based on Abstract Syntax Tree
    2019 392 citations Hailong Sun 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
Hailong Sun China 20 1.7k 950 765 402 278 161 2.3k
Xin Peng China 29 2.1k 1.2× 1.5k 1.6× 1.1k 1.5× 756 1.9× 337 1.2× 225 3.0k
Mohammad Alshayeb Saudi Arabia 23 1.7k 1.0× 443 0.5× 539 0.7× 891 2.2× 252 0.9× 114 2.2k
Soyeon Park United States 23 1.2k 0.7× 1.4k 1.5× 718 0.9× 934 2.3× 182 0.7× 80 2.7k
Malcolm Munro United Kingdom 25 1.6k 1.0× 530 0.6× 712 0.9× 852 2.1× 141 0.5× 136 2.1k
Julia Rubin Canada 22 1.2k 0.7× 434 0.5× 1.1k 1.4× 558 1.4× 250 0.9× 67 2.0k
Filomena Ferrucci Italy 27 1.7k 1.0× 446 0.5× 486 0.6× 1.0k 2.5× 268 1.0× 168 2.3k
Filippo Ricca Italy 32 2.4k 1.4× 915 1.0× 764 1.0× 1.7k 4.2× 378 1.4× 165 3.0k
Elisabetta Di Nitto Italy 27 1.6k 1.0× 1.5k 1.6× 781 1.0× 222 0.6× 92 0.3× 138 2.5k
Robert Martin United States 18 1.2k 0.7× 442 0.5× 910 1.2× 538 1.3× 166 0.6× 62 2.2k
Federica Sarro United Kingdom 30 1.8k 1.1× 422 0.4× 684 0.9× 1.0k 2.5× 280 1.0× 128 2.7k

Countries citing papers authored by Hailong Sun

Since Specialization
Citations

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

Fields of papers citing papers by Hailong Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hailong Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Hailong Sun. A scholar is included among the top collaborators of Hailong Sun 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 Hailong Sun. Hailong Sun 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.
Li, Li, Xiang Gao, Hailong Sun, et al.. (2025). Software Engineering for OpenHarmony: A Research Roadmap. ACM Computing Surveys. 58(2). 1–36. 2 indexed citations
2.
Yang, Y., et al.. (2025). Context-Enhanced Vulnerability Detection Based on Large Language Models. ACM Transactions on Software Engineering and Methodology.
3.
Gao, Xiang, et al.. (2025). Reference-Based Retrieval-Augmented Unit Test Generation. ACM Transactions on Software Engineering and Methodology.
4.
Sun, Hailong, et al.. (2025). Toward Open-World Domain Adaptation via Iteratively Contrastive Learning and Clustering. IEEE Transactions on Neural Networks and Learning Systems. 36(10). 18408–18421.
5.
Sun, Hailong, Dawei Zhou, De‐Chuan Zhan, & Han-Jia Ye. (2025). PILOT: a pre-trained model-based continual learning toolbox. Science China Information Sciences. 68(4). 4 indexed citations
6.
Sun, Hailong, et al.. (2024). Target Structure Learning Framework for Unsupervised Multi-Class Domain Adaptation. ACM Transactions on Multimedia Computing Communications and Applications. 20(11). 1–23. 1 indexed citations
7.
Wen, Ming, et al.. (2024). Reducing False Positives of Static Bug Detectors Through Code Representation Learning. 681–692. 2 indexed citations
8.
9.
Sun, Hailong, et al.. (2024). Investigating and Detecting Silent Bugs in PyTorch Programs. 272–283. 2 indexed citations
10.
Sun, Hailong, et al.. (2023). Neural-Hidden-CRF: A Robust Weakly-Supervised Sequence Labeler. arXiv (Cornell University). 274–285.
11.
Sun, Hailong, et al.. (2021). The trend effect of probability estimation and its influence on decision-making from the perspective of psychological momentum. Advances in Psychological Science. 29(11). 2062–2072.
12.
Wang, Lei, et al.. (2020). A Scalable Operating System Experiment Platform Supporting Learning Behavior Analysis. IEEE Transactions on Education. 63(3). 232–239. 9 indexed citations
13.
LI, Aimei, et al.. (2016). A Literature Review of Implicit Theories and Consumer Decision-making. Waiguo jingji yu guanli. 38(9). 38–50. 1 indexed citations
14.
Sun, Hailong, et al.. (2016). Incorporating external knowledge into crowd intelligence for more specific knowledge acquisition. International Joint Conference on Artificial Intelligence. 1541–1547. 16 indexed citations
15.
Song, Yangqiu, Chenguang Wang, Ming Zhang, Hailong Sun, & Qiang Yang. (2015). Spectral label refinement for noisy and missing text labels. e+i Elektrotechnik und Informationstechnik. 5 indexed citations
16.
Sun, Hailong, et al.. (2013). Towards a Scalable PaaS for Service Oriented Software. 522–527. 1 indexed citations
17.
Chen, Yih-Farn, et al.. (2009). Project GeoTV: a three-screen service. 58–59. 1 indexed citations
18.
Zhang, Yandong, et al.. (2007). [Soil respiration in temperate secondary forest and Larix gmelinii plantation in Northeast China].. PubMed. 18(12). 2668–74. 3 indexed citations
19.
Sun, Hailong, et al.. (2006). RCT: A Self-Adaptive Overlay for Efficient Computational Resource Discovery in Grid Systems. 64–64. 2 indexed citations
20.
Huai, Jinpeng, Chunming Hu, Jianxin Li, Hailong Sun, & Tianyu Wo. (2006). CROWN: A service grid middleware with trust management mechanism. Science in China Series F Information Sciences. 49(6). 731–758. 17 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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