A Comparison of Three Popular Source code Similarity Tools for Detecting Student Plagiarism

Ahadi, A; Mathieson, L

A Comparison of Three Popular Source code Similarity Tools for Detecting Student Plagiarism

Ahadi, A

Mathieson, L

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Publication Type:: Conference Proceeding
Citation:: ACM International Conference Proceeding Series, 2019, pp. 112 - 117
Issue Date:: 2019-01-29

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Field	Value	Language
dc.contributor.author	Ahadi, A https://orcid.org/0000-0002-2018-3065	en_US
dc.contributor.author	Mathieson, L https://orcid.org/0000-0001-6470-2296	en_US
dc.date.issued	2019-01-29	en_US
dc.identifier.citation	ACM International Conference Proceeding Series, 2019, pp. 112 - 117	en_US
dc.identifier.isbn	9781450366229	en_US
dc.identifier.uri	http://hdl.handle.net/10453/132088
dc.description.abstract	© 2019 Association for Computing Machinery. This paper investigates automated code plagiarism detection in the context of an undergraduate level data structures and algorithms module. We compare three software tools which aim to detect plagiarism in the students' programming source code. We evaluate the performance of these tools on an individual basis and the degree of agreement between them. Based on this evaluation we show that the degree of agreement between these tools is relatively low. We also report the challenges faced during utilization of these methods and suggest possible future improvements for tools of this kind. The discrepancies in the results obtained by these detection techniques were used to devise guidelines for effectively detecting code plagiarism.	en_US
dc.relation.ispartof	ACM International Conference Proceeding Series	en_US
dc.relation.isbasedon	10.1145/3286960.3286974	en_US
dc.title	A Comparison of Three Popular Source code Similarity Tools for Detecting Student Plagiarism	en_US
dc.type	Conference Proceeding
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2019 Association for Computing Machinery. This paper investigates automated code plagiarism detection in the context of an undergraduate level data structures and algorithms module. We compare three software tools which aim to detect plagiarism in the students' programming source code. We evaluate the performance of these tools on an individual basis and the degree of agreement between them. Based on this evaluation we show that the degree of agreement between these tools is relatively low. We also report the challenges faced during utilization of these methods and suggest possible future improvements for tools of this kind. The discrepancies in the results obtained by these detection techniques were used to devise guidelines for effectively detecting code plagiarism.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/132088