Identifying Plagiarised Programming Assignments with Detection Tool Consensus

被引:2
|
作者
Cheers, Hayden [1 ]
Lin, Yuqing [1 ,2 ]
Yan, Weigen [2 ]
机构
[1] Univ Newcastle, Callaghan, NSW 2308, Australia
[2] Jimei Univ, Xiamen, Fujian, Peoples R China
来源
INFORMATICS IN EDUCATION | 2023年 / 22卷 / 01期
关键词
source code plagiarism detection; behavioural similarity; source code similarity; SOURCE-CODE; SIMILARITY; SEMANTICS;
D O I
10.15388/infedu.2023.05
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to ad dress this problem. However, most of these tools only measure the similarity between assignment submissions, and do not actually identify which are suspicious of plagia rism. This work presents a semi-automatic approach that enables the indication of suspicious assignment submissions by analysing source code similarity scores among the submissions. The proposed approach seeks the consensus of multiple source code plagiarism detection tools in order to identify program pairs that are consistently evaluated with high similarity. A case study is presented to demonstrate the use of the proposed approach. The results of this case study indicate that it can accurately identify assignment submissions that are suspicious of plagiarism.
引用
收藏
页码:1 / 19
页数:19
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