TF-IDF inspired detection for cross-language source code plagiarism and collusion

• Autorzy: Karnalim Oscar

Identyfikatory

DOI

10.7494/csci.2020.21.1.3389

• Języki publikacji: EN

Abstrakty

EN

Several computing courses allow students to choose which programming language they want to use for completing a programming task. This can lead to cross-language code plagiarism and collusion, in which the copied code file is rewritten in another programming language. In response to that, this paper proposes a detection technique which is able to accurately compare code files written in various programming languages, but with limited effort in accommodating such languages at development stage. The only language-dependent feature used in the technique is source code tokeniser and no code conversion is applied. The impact of coincidental similarity is reduced by applying a TF-IDF inspired weighting, in which rare matches are prioritised. Our evaluation shows that the technique outperforms common techniques in academia for handling language conversion disguises. Furthermore, it is comparable to those techniques when dealing with conventional disguises.

Słowa kluczowe

EN

source code plagiarism and collusion; cross-language detection; TF-IDF; computing education; information retrieval

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2020
• Tom: T. 21 (1)
• Strony: 113--134
• Opis fizyczny: Bibliogr. 56 poz., rys.

Twórcy

autor

Karnalim Oscar

• Maranatha Christian University, Surya Sumantri Street No. 65, Bandung, 40164, Indonesia

Bibliografia

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