- Title
- Identifying Plagiarised Programming Assignments with Detection Tool Consensus
- Creator
- Cheers, Hayden; Lin, Yuqing; Yan, Weigen
- Relation
- Informatics in Education Vol. 22, Issue 1, p. 1-19
- Publisher Link
- http://dx.doi.org/10.15388/infedu.2023.05
- Publisher
- Vilniaus Universitetas * Matematikos ir Informatikos Insititutas,Vilnius University, Institute of Mathematics and Informatics
- Resource Type
- journal article
- Date
- 2023
- Description
- Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, most of these tools only measure the similarity between assignment submissions, and do not actually identify which are suspicious of plagiarism. 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.
- Subject
- source code plagiarism detection; behavioural similarity; source code similarity; case study
- Identifier
- http://hdl.handle.net/1959.13/1488739
- Identifier
- uon:52523
- Identifier
- ISSN:1648-5831
- Rights
- x
- Language
- eng
- Reviewed
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