Research on source code plagiarism detection based on multiple features

Yue Sun; Cong Hou; Xiaotian Xu; Min Li; Ranxin Gao

doi:10.1117/12.3031075

19 July 2024 Research on source code plagiarism detection based on multiple features

Yue Sun, Cong Hou, Xiaotian Xu, Min Li, Ranxin Gao

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131817F (2024) https://doi.org/10.1117/12.3031075
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

In the field of code plagiarism detection, assessing the presence of shared code fragments or similar structures has always been a challenge. Traditional text-based code plagiarism detection methods cannot provide accurate results for code with these characteristics. Therefore, this paper introduces a source code plagiarism detection technique based on multiple feature values. It outlines a method for extracting features from source code comments, structures, code text statements, and structures, and provides a measurement model for source code plagiarism detection. Through comparative experiments with the authoritative code plagiarism detection system Moss, the results indicate that the source code plagiarism detection technique based on multiple feature values achieves a more accurate code detection performance.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yue Sun, Cong Hou, Xiaotian Xu, Min Li, and Ranxin Gao "Research on source code plagiarism detection based on multiple features", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131817F (19 July 2024); https://doi.org/10.1117/12.3031075

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