Identifying Plagiarised Programming Assignments with Detection Tool Consensus

Author:

Cheers Hayden,Lin Yuqing,Yan Weigen

Abstract

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.

Publisher

Vilnius University Press

Subject

Computer Science Applications,Communication,Education,General Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Detecting AI assisted submissions in introductory programming via code anomaly;Education and Information Technologies;2024-02-16

2. BIOPLAG: An Approach to Detect Programming Plagiarism;Anais da Academia Brasileira de Ciências;2023

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