Plagiarism Detection in Software Projects Using Abstract Syntax Trees

Files

45_EEICT_selected.pdf(664.62 KB)

Date

2023

Authors

Szymutko, Marek

Seda, Pavel

Publisher

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

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Abstract

Plagiarism is a hot topic in modern education andscience. It requires special attention since committing plagiarismis very easy with the use of the internet. This problem can befought against utilizing prevention or detection methods, whichhave been both used in this work. This paper introduces animplementation of a submission scheme of students’ projects inclasses taught at the Brno University of Technology. Scripts for anautomatic hand-in space for each student were created. Studentshave restricted privileges within these spaces on the GitLabcloud service. For plagiarism detection, a tool written in Pythonwas developed. This tool utilizes Abstract Syntax Trees compiledfrom the source code, which is a part of the Students’ solutions.The output of the comparison is represented with a tabular fileof the format .xlsx, which allows a detailed view. Ongoingimplementation is focused on widening the tool’s usability byadding a Python similarity comparison engine.

Keywords

Abstract Syntax Trees, API, Bash, Detection,Git, GitLab, Java, Metrics, Plagiarism, Python

Citation

Proceedings II of the 29st Conference STUDENT EEICT 2023: Selected papers. s. 45-48. ISBN 978-80-214-6154-3
https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf

Document type

Peer-reviewed

Document version

Published version

Language of document

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