Token-Based Plagiarism Detection for Statecharts

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Version vom 19. April 2023, 14:47 Uhr von Erik Burger (Diskussion | Beiträge)
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Vortragende(r) Jonas Strittmatter
Vortragstyp Bachelorarbeit
Betreuer(in) Timur Sağlam
Termin Fr 28. April 2023
Vortragsmodus in Präsenz
Kurzfassung In the field of software engineering, existing plagiarism detection systems have primarily focused on detecting cases of plagiarism in code. However, other artefacts such as models also play a crucial role in the development process. Statecharts, in particular, are used to model the behavior of a system. This thesis investigates the applicability and challenges of applying token-based plagiarism detection systems to statecharts. We extend the plagiarism detector JPlag to support detecting cases of plagiarism in statecharts. Our approach is evaluated using a dataset of student assignments from a modeling course, where we generate plagiarized statecharts by adopting common obfuscation attacks. We study the effects of the token-extraction strategy, sorting techniques and the minimum token match parameter. The results suggest that an approach tailored to the specific kind of model, such as statecharts, works better than a generic solution for models.