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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 6

Code clone detection with enhanced control flow graph and siamese neural network architecture

Xiong Shuchu1,2
Duan Jinyan1
Yin Lu1
Zeng Zhiyong2
1. School of Computer Science, Hunan University of Technology & Business, Changsha 410205, China
2. School of Frontier Crossover Studies, Hunan University of Technology & Business, Changsha 410205, China
DOI: 10.19734/j.issn.1001-3695.2024.11.0441

Abstract

To address the issues of missing contextual information and weak semantic learning capabilities in existing code clone detection methods, we propose a method based on an enhanced control flow graph (ECFG) and twin network architecture. First, we design ECFG, which embeds cross-node correlation edges to strengthen contextual awareness. Then, we introduce CGSMN (Code Graph Semantic Matching Network) , a semantic matching model based on twin networks. This model integrates a multi-head attention mechanism to extract key information from the nodes, then improves the relational graph attention network to capture inter-node associations and generate graph feature vectors. Finally, it explores the semantic relationships between these feature vectors and computes the semantic similarity. Empirical evaluation is conducted on two representative datasets. The results show that, compared to methods such as ASTNN, FA-AST, and DHAST, the F1 score on the BigCloneBench dataset improves by 0.5 to 15.5 percentage points, and by 1.5 to 16.5 percentage points on the Google Code Jam dataset, demonstrating the effectiveness of the proposed method for semantic clone detection.

Foundation Support

国家社会科学基金资助项目(21BTQ088)
湖南省教育厅科学研究重点项目(20A133)
湖南省研究生科研创新项目(QL20230270)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.11.0441
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 6

Publish History

[2025-03-10] Accepted Paper

Cite This Article

熊曙初, 段金焱, 尹璐, 等. 基于增强控制流图与孪生网络架构的代码克隆检测方法 [J]. 计算机应用研究, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.11.0441. (Xiong Shuchu, Duan Jinyan, Yin Lu, et al. Code clone detection with enhanced control flow graph and siamese neural network architecture [J]. Application Research of Computers, 2025, 42 (6). (2025-03-10). https://doi.org/10.19734/j.issn.1001-3695.2024.11.0441. )

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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