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Source-code similarity detection and detection tools used in academia
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Novak, Matija, Joy, Mike and Kermek, Dragutin (2019) Source-code similarity detection and detection tools used in academia. ACM Transactions on Computing Education, 19 (3). 27. doi:10.1145/3313290 ISSN 1946-6226.
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Official URL: https://doi.org/10.1145/3313290
Abstract
Teachers deal with plagiarism on a regular basis, so they try to prevent and detect plagiarism, a task that is complicated by the large size of some classes. Students who cheat often try to hide their plagiarism (obfuscate), and many different similarity detection engines (often called plagiarism detection tools) have been built to help teachers. This article focuses only on plagiarism detection and presents a detailed systematic review of the field of source-code plagiarism detection in academia. This review gives an overview of definitions of plagiarism, plagiarism detection tools, comparison metrics, obfuscation methods, datasets used for comparison, and algorithm types. Perspectives on the meaning of source-code plagiarism detection in academia are presented, together with categorisations of the available detection tools and analyses of their effectiveness. While writing the review, some interesting insights have been found about metrics and datasets for quantitative tool comparison and categorisation of detection algorithms. Also, existing obfuscation methods classifications have been expanded together with a new definition of “source-code plagiarism detection in academia.”
Item Type: | Journal Article | ||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
SWORD Depositor: | Library Publications Router | ||||||
Journal or Publication Title: | ACM Transactions on Computing Education | ||||||
Publisher: | Association for Computing Machinery (ACM) | ||||||
ISSN: | 1946-6226 | ||||||
Official Date: | 21 May 2019 | ||||||
Dates: |
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Volume: | 19 | ||||||
Number: | 3 | ||||||
Article Number: | 27 | ||||||
DOI: | 10.1145/3313290 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Reuse Statement (publisher, data, author rights): | |||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Copyright Holders: | © 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM. | ||||||
Description: | Free access |
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