Source Code Plagiarism Detection Based on Abstract Syntax Tree Fingerprintings

被引：0

作者：

Suttichaya, Vasin ^{[1
]}

Eakvorachai, Niracha ^{[2
]}

Lurkraisit, Tunchanok ^{[2
]}

机构：

[1] Mahidol Univ, Fac Engn, Dept Comp Engn, 25-25 Salaya, Phuttamonthon 73170, Nakhon Pathom, Thailand

[2] Mahidol Univ Int Coll, Dept Comp Engn, 999 Salaya, Phuttamonthon 73170, Nakhon Pathom, Thailand

来源：

2022 17TH INTERNATIONAL JOINT SYMPOSIUM ON ARTIFICIAL INTELLIGENCE AND NATURAL LANGUAGE PROCESSING (ISAI-NLP 2022) / 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INTERNET OF THINGS (AIOT 2022) | 2022年

关键词：

Source Code Similarities; Plagiarism Detection; MOSS; Abstract Syntax Tree; Fingerprinting;

D O I：

10.1109/ISAI-NLP56921.2022.9960266

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

.Abstract Syntax Tree (AST) is an abstract logical structure of source code represented as a tree. This research utilizes information of fingerprinting with AST to locate the similarities between source codes. The proposed method can detect plagiarism in source codes using the number of duplicated logical structures. The structural information of program is stored in the fingerprints format. Then, the fingerprints of source codes are compared to identify number of similar nodes. The final output is calculated from number of similar nodes known as similarities scores. The result shows that the proposed method accurately captures the common modification techniques from basic to advance.

引用

页数：6

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