Review of Code Similarity and Plagiarism Detection Research Studies

被引:4
作者
Lee, Gunwoo [1 ]
Kim, Jindae [2 ]
Choi, Myung-seok [1 ]
Jang, Rae-Young [1 ]
Lee, Ryong [1 ]
机构
[1] Korea Inst Sci & Technol Informat KISTI, AI Data Res Ctr, Div Sci & Technol Digital Convergence, Daejeon 34141, South Korea
[2] Seoul Natl Univ Sci & Technol, Dept Comp Sci & Engn, Seoul 01811, South Korea
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 20期
关键词
code similarity detection; plagiarism detection; research trends; CLONE DETECTION; PROGRAM SIMILARITY; CONSTRUCTION; PATTERNS; SYSTEM;
D O I
10.3390/app132011358
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The foundational technique of code similarity detection, which underpins plagiarism detection tools, has already reached a level of maturity where it can be effectively employed for practical applications, demonstrating commendable performance. However, although the understanding of code clones-referred to as similar codes-has evolved, there has been a noticeable decline in the emergence of novel proposals for code similarity detection techniques. The landscape of code similarity detection techniques is diverse and can be divided based on how codes are represented. Each method, designed to cater to different types of detectable code similarity instances, has distinct advantages and drawbacks. Therefore, the selection of an appropriate method is crucial and is contingent on the specific objectives of the analysis. This paper provides a comprehensive exploration of code similarity detection techniques and illuminates the prevailing trends in plagiarism detection research. It acquaints readers with a spectrum of distinct code similarity detection methods, accompanied by the requisite contextual background knowledge. Additionally, it presents a detailed overview of the trajectory of research trends in plagiarism detection.
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页数:26
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