A comparison of three popular source code similarity tools for detecting student plagiarism

Alireza Ahadi, Luke Mathieson

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Abstract

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.

LanguageEnglish
Title of host publicationACE 2019
Subtitle of host publicationProceedings of the 21st Australasian Computing Education Conference
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery
Pages112-117
Number of pages6
ISBN (Electronic)9781450366229
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event21st Australasian Computing Education Conference, ACE 2019, held in conjunction with Australasian Computer Science Week - Sydney, Australia
Duration: 29 Jan 201931 Jan 2019

Conference

Conference21st Australasian Computing Education Conference, ACE 2019, held in conjunction with Australasian Computer Science Week
CountryAustralia
CitySydney
Period29/01/1931/01/19

Fingerprint

Students
Data structures

Keywords

  • software similarity detection
  • plagiarism
  • programming
  • computer science education

Cite this

Ahadi, A., & Mathieson, L. (2019). A comparison of three popular source code similarity tools for detecting student plagiarism. In ACE 2019: Proceedings of the 21st Australasian Computing Education Conference (pp. 112-117). New York, NY: Association for Computing Machinery. https://doi.org/10.1145/3286960.3286974
Ahadi, Alireza ; Mathieson, Luke. / A comparison of three popular source code similarity tools for detecting student plagiarism. ACE 2019: Proceedings of the 21st Australasian Computing Education Conference. New York, NY : Association for Computing Machinery, 2019. pp. 112-117
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Ahadi, A & Mathieson, L 2019, A comparison of three popular source code similarity tools for detecting student plagiarism. in ACE 2019: Proceedings of the 21st Australasian Computing Education Conference. Association for Computing Machinery, New York, NY, pp. 112-117, 21st Australasian Computing Education Conference, ACE 2019, held in conjunction with Australasian Computer Science Week, Sydney, Australia, 29/01/19. https://doi.org/10.1145/3286960.3286974

A comparison of three popular source code similarity tools for detecting student plagiarism. / Ahadi, Alireza; Mathieson, Luke.

ACE 2019: Proceedings of the 21st Australasian Computing Education Conference. New York, NY : Association for Computing Machinery, 2019. p. 112-117.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

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Ahadi A, Mathieson L. A comparison of three popular source code similarity tools for detecting student plagiarism. In ACE 2019: Proceedings of the 21st Australasian Computing Education Conference. New York, NY: Association for Computing Machinery. 2019. p. 112-117 https://doi.org/10.1145/3286960.3286974