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Improved plagiarism detection with collaboration network visualization based on source-code similarity
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Novak, Matija, Joy, Mike and Mirza, Olfat M. (2021) Improved plagiarism detection with collaboration network visualization based on source-code similarity. In: 2021 IEEE Technology & Engineering Management Conference – Europe, Dubrovnik, Croatia, 17-21 May 2021. Published in: 2021 IEEE Technology & Engineering Management Conference - Europe (TEMSCON-EUR) pp. 1-6. ISBN 9781665431149. doi:10.1109/TEMSCON-EUR52034.2021.9488644
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Official URL: http://dx.doi.org/10.1109/TEMSCON-EUR52034.2021.94...
Abstract
Plagiarism detection is a serious problem in higher education. Teachers use similarity (plagiarism) detection systems, which highlight similarities between student documents, to help them find plagiarism. Most systems are built for text but there are special systems to find similarities between source-code files. In most cases the results are presented in table form showing similarities between pairs of documents in descending order by similarity, and then a teacher is responsible for confirming which similar documents represent cases of plagiarism. While most systems present their results in the form of tables, only few of them present the results as a graph. Some studies indicate that using clustering algorithms to represent such data graphically can improve the speed and accuracy of finding potential instances of plagiarism in large collections of source-code files. The purpose of the study is to answer the following research questions. Can visualization of student solutions (of source-code similarities) in collaboration networks form help identify new cases of plagiarism? What are the steps to do so? The study was designed in a form of two case studies where one was performed on a graduate level university course and one on a course in professional studies. The article presents empirical results describing two cases where a collaboration network (based on source-code similarity) representation has been used. The article argues that the graphical presentation is able to identify new clusters of plagiarised source-code files that would have been missed using existing tabular presentation of data.
Item Type: | Conference Item (Paper) | ||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
Journal or Publication Title: | 2021 IEEE Technology & Engineering Management Conference - Europe (TEMSCON-EUR) | ||||||
Publisher: | IEEE | ||||||
ISBN: | 9781665431149 | ||||||
Book Title: | 2021 IEEE Technology & Engineering Management Conference - Europe (TEMSCON-EUR) | ||||||
Official Date: | 26 June 2021 | ||||||
Dates: |
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Page Range: | pp. 1-6 | ||||||
DOI: | 10.1109/TEMSCON-EUR52034.2021.9488644 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Reuse Statement (publisher, data, author rights): | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Conference Paper Type: | Paper | ||||||
Title of Event: | 2021 IEEE Technology & Engineering Management Conference – Europe | ||||||
Type of Event: | Conference | ||||||
Location of Event: | Dubrovnik, Croatia | ||||||
Date(s) of Event: | 17-21 May 2021 |
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