Jin Song Dong
- Software top 1%
- Software Testing and Debugging Techniques 32
- Model-Driven Software Engineering Techniques 25
- Software Reliability and Analysis Research 18
- Information Systems top 0.5%
- Service-Oriented Architecture and Web Services 31
- Software Engineering Research 24
- Artificial Intelligence top 1%
- Advanced Software Engineering Methodologies 40
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- Formal Methods in Verification 55
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- Advanced Malware Detection Techniques 24
Jin Song Dong
193 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Software 494
- Information Systems 888
- Artificial Intelligence 1.1k
- Computational Theory and Mathematics 455
- Computer Networks and Communications 621
Countries citing papers authored by Jin Song Dong
This map shows the geographic impact of Jin Song Dong'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 Jin Song Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Song Dong more than expected).
Fields of papers citing papers by Jin Song Dong
This network shows the impact of papers produced by Jin Song Dong. 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 Jin Song Dong. The network helps show where Jin Song Dong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jin Song Dong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 1 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 5 | |
| 11 | 2022 | 4 | |
| 12 | Phishpedia: A Hybrid Deep Learning Based Approach to Visually Identify Phishing Webpages | 2021 | 27 |
| 13 | 2020 | 1 | |
| 14 | AUTHSCAN: Automatic Extraction of Web Authentication Protocols from Implementations. | 2013 | 63 |
| 15 | 2013 | 3 | |
| 16 | 2012 | 4 | |
| 17 | Institution Morphisms for Relating OWL and Z | 2005 | 4 |
| 18 | Reasoning Support for SWRL-FOL Using Alloy. | 2005 | 2 |
| 19 | Induction and Characterization of Laboratory Mutants of Phytophthora capsici Resistant to Dimethomorph and Flumorph | 2005 | 5 |
| 20 | An object-oriented denotational semantics of a small programming language. | 1997 | 2 |
About Jin Song Dong
Jin Song Dong is a scholar working on Software, Computational Theory and Mathematics and Hardware and Architecture, having authored 216 papers that have together received 2.9k indexed citations. Recurring topics across this work include Formal Methods in Verification (55 papers), Advanced Software Engineering Methodologies (40 papers), Software Testing and Debugging Techniques (32 papers), Service-Oriented Architecture and Web Services (31 papers), Model-Driven Software Engineering Techniques (25 papers), Software Engineering Research (24 papers), Advanced Malware Detection Techniques (24 papers) and Software Reliability and Analysis Research (18 papers). The work is most often cited by research in Software (494 citations), Information Systems (888 citations) and Artificial Intelligence (1.1k citations). Jin Song Dong has collaborated with scholars based in Singapore, China and Australia. Frequent co-authors include Jun Sun, Yang Liu, Seyedali Mirjalili, Guangdong Bai, Yun Lin, Andrew Lewis, Lu Huang, Hong Jiang, Rui Han and Dongyou Zhang. Their work appears in journals such as Applied and Environmental Microbiology, IEEE Communications Surveys & Tutorials and Atmospheric Environment.
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.