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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 2

Code vulnerability detection method based on multi-dimensional feature fusion and edge semantic augmentation

Zhang Shuai1,2
Wei Le1,2,3,4
1. School of Software Engineering, Chengdu University of Information Technology, Chengdu 610225, China
2. Automatic Software Generation & Intelligence Service Key Laboratory of Sichuan Province, Chengdu 610225, China
3. Sichuan Manufacturing Information Industry Collaborative Innovation Center Chengdu 610225, China
4. industrial software collaborative research center, Chengdu 610225, China
DOI: 10.19734/j.issn.1001-3695.2025.06.0210

Abstract

Graph-based code vulnerability detection still faces challenges such as graph structural redundancy, disjointed local and global feature representations, and missing edge semantic information. To address these issues, a static detection method based on multidimensional feature fusion and edge semantic augmentation was proposed. First, a hierarchical graph fusion strategy was designed, combining abstract syntax trees and program dependence graphs to construct a lightweight program semantic graph, effectively reducing the number of graph nodes. Second, the typical static structural feature of scope paths in code was explicitly identified. Local syntax and semantic features, along with global contextual constraints of statement nodes, were extracted from three dimensions: code token sequences, abstract syntax trees, and scope paths. Finally, an edge-semantic-augmented graph attention network was constructed to enable collaborative updating of node and edge attributes. Experimental results show accuracies of 93.1% and 91.9%, and F1 scores of 92.8% and 91.6% on C/C++ and Java datasets, respectively. The method outperforms four mainstream approaches, including MGVD and VulMPFF, and demonstrates better adaptability and generalization across multiple common vulnerability types.

Foundation Support

国家重点研发计划工业软件重点专项(2022YFB3305100)
软件自动生成与智能服务四川省重点实验室开放课题(CUIT-SAG202203、CUIT-SAG202207)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.06.0210
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 2

Publish History

[2025-10-27] Accepted Paper

Cite This Article

张帅, 魏乐. 基于多维度特征融合与边语义增强的代码漏洞检测方法 [J]. 计算机应用研究, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0210. (Zhang Shuai, Wei Le. Code vulnerability detection method based on multi-dimensional feature fusion and edge semantic augmentation [J]. Application Research of Computers, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0210. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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