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Izvorni znanstveni članak
https://doi.org/10.31341/jios.41.1.7

Detecting Source Code Plagiarism on .NET Programming Languages using Low-level Representation and Adaptive Local Alignment

Faqih Salban Rabbani   ORCID icon orcid.org/0000-0003-3488-4599 ; Faculty of Information Technology, Maranatha Christian University, Indonesia
Oscar Karnalim   ORCID icon orcid.org/0000-0003-4930-6249 ; Faculty of Information Technology, Maranatha Christian University, Indonesia

Puni tekst: engleski, pdf (2 MB) str. 105-123 preuzimanja: 170* citiraj
APA 6th Edition
Rabbani, F.S. i Karnalim, O. (2017). Detecting Source Code Plagiarism on .NET Programming Languages using Low-level Representation and Adaptive Local Alignment. Journal of Information and Organizational Sciences, 41 (1), 105-123. https://doi.org/10.31341/jios.41.1.7
MLA 8th Edition
Rabbani, Faqih Salban i Oscar Karnalim. "Detecting Source Code Plagiarism on .NET Programming Languages using Low-level Representation and Adaptive Local Alignment." Journal of Information and Organizational Sciences, vol. 41, br. 1, 2017, str. 105-123. https://doi.org/10.31341/jios.41.1.7. Citirano 23.09.2019.
Chicago 17th Edition
Rabbani, Faqih Salban i Oscar Karnalim. "Detecting Source Code Plagiarism on .NET Programming Languages using Low-level Representation and Adaptive Local Alignment." Journal of Information and Organizational Sciences 41, br. 1 (2017): 105-123. https://doi.org/10.31341/jios.41.1.7
Harvard
Rabbani, F.S., i Karnalim, O. (2017). 'Detecting Source Code Plagiarism on .NET Programming Languages using Low-level Representation and Adaptive Local Alignment', Journal of Information and Organizational Sciences, 41(1), str. 105-123. https://doi.org/10.31341/jios.41.1.7
Vancouver
Rabbani FS, Karnalim O. Detecting Source Code Plagiarism on .NET Programming Languages using Low-level Representation and Adaptive Local Alignment. Journal of Information and Organizational Sciences [Internet]. 2017 [pristupljeno 23.09.2019.];41(1):105-123. https://doi.org/10.31341/jios.41.1.7
IEEE
F.S. Rabbani i O. Karnalim, "Detecting Source Code Plagiarism on .NET Programming Languages using Low-level Representation and Adaptive Local Alignment", Journal of Information and Organizational Sciences, vol.41, br. 1, str. 105-123, 2017. [Online]. https://doi.org/10.31341/jios.41.1.7

Sažetak
Even though there are various source code plagiarism detection approaches, only a few works which are focused on low-level representation for deducting similarity. Most of them are only focused on lexical token sequence extracted from source code. In our point of view, low-level representation is more beneficial than lexical token since its form is more compact than the source code itself. It only considers semantic-preserving instructions and ignores many source code delimiter tokens. This paper proposes a source code plagiarism detection which rely on low-level representation. For a case study, we focus our work on .NET programming languages with Common Intermediate Language as its low-level representation. In addition, we also incorporate Adaptive Local Alignment for detecting similarity. According to Lim et al, this algorithm outperforms code similarity state-of-the-art algorithm (i.e. Greedy String Tiling) in term of effectiveness. According to our evaluation which involves various plagiarism attacks, our approach is more effective and efficient when compared with standard lexical-token approach.

Ključne riječi
source code plagiarism detection; source code similarity; low-level language; .NET programming language; adaptive local alignment

Hrčak ID: 183091

URI
https://hrcak.srce.hr/183091

Posjeta: 318 *