Modelo para Detecção de Plágio em Exercícios de Programação na Linguagem Python

  • Rafael C. Chaves IFPB
  • Kerven M. Albuquerque IFPB
  • Renato C. Chaves IFPB
  • Thiago Gouveia IFPB
DOI: https://doi.org/10.5753/etc.2023.230845

Abstract


This article proposes an approach based on bipartite graphs with unidirectional edges to detect plagiarism in codes written in Python. The graph modeling is designed to allow the identification of the probability of plagiarism through solutions to the Maximal Reward Shortest Path problem.

References

Leping, V., Lepp, M., Niitsoo, M., Tõnisson, E., Vene, V., and Villems, A. (2009). Python prevails. In Proceedings of the International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing, pages 1–5.

Srinath, K. (2017). Python–the fastest growing programming language. International Research Journal of Engineering and Technology, 4(12):354–357.
Published
2023-08-06
How to Cite

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CHAVES, Rafael C.; ALBUQUERQUE, Kerven M.; CHAVES, Renato C.; GOUVEIA, Thiago. Modelo para Detecção de Plágio em Exercícios de Programação na Linguagem Python. In: PROCEEDINGS OF THE THEORY OF COMPUTATION MEETING (ETC), 8. , 2023, João Pessoa/PB. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 196-200. ISSN 2595-6116. DOI: https://doi.org/10.5753/etc.2023.230845.