Plagiarism Detection Framework: A Technique for Detecting Source Code Plagiarism

Authors

  • Ankur Nagaich M.Tech Scholar, Department of ECE, Shri Ram College of Engineering and Management, Gwalior, M.P., India
  • Anuj Bhargava Professor, Department of ECE, Shri Ram College of Engineering and Management, Gwalior, M.P., India
  • Prashant Badal Professor, Department of ECE, Shri Ram College of Engineering and Management, Gwalior, M.P., India

DOI:

https://doi.org/10.24113/ijoscience.v3i3.60

Keywords:

Source-Code, Programming Language, Plagiarism Detection, Textual Similarity

Abstract

Academic dishonesty is a universal problem. The educational community across the world is facing the increasing problem of plagiarism. This widespread problem has motivated the need of an efficient, robust and fast detection procedure that is difficult to be achieved manually. Detecting duplicated text among natural language artifacts is a well-documented task. However, performing similar analysis on source code presents unique problems. Source-code plagiarism detection in programming, concerns the identification of source-code files that contain similar and/or identical source-code fragments. In this paper, a brief discussion of source code Plagiarism is presented as well as comparative study of the application of various techniques in textual similarity processing on source code.

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References

A. Parker and J. Hamblen. Computer algorithms for plagiarism detection. IEEE Transactions on Education, 32(2):94–99, 1989.

Michael J. Wise. YAP3: Improved detection of similarities in computer program and other texts. ACM, SIGCSE, 28:130–134, 1996.

Fintan Culwin, Anna MacLeod, and Thomas Lancaster. Source code plagiarism in UK HE computing schools, issues, attitudes and tools. Technical report, South Bank University (SBU) SCISM Technical Report, 2001.

Michael Philippsen Lutz Prechelt, Guido Malpohl. Finding plagiarism among a set of programs with JPlag. Journal of Universal Computer Science, 8(11):1016–1038, 2002.

Alex Aiken. Moss: A system for detecting software plagiarism, 2005.

Christian Arwin and S.M.M. Tahaghoghi. Plagiarism detection across programming languages. Proceedings of the 29th Australasian Computer Science Conference, 48:277–286, 2006.

C. Kustanto and I. Liem, “Automatic source code plagiarism detection,” in Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, 2009. SNPD ’09. 10th ACIS International Conference on, May 2009, pp. 481–486.

C. G. and J. M., “An approach to source-code plagiarism detection and investigation using latent semantic analysis,” Computers, IEEE Transactions on, vol. 61, no. 3, pp. 379–394, March 2012.

B. Muddu, A. Asadullah, and V. Bhat, “Cpdp: A robust technique for plagiarism detection in source code,” in Software Clones (IWSC), 7th International Workshop on, May 2013, pp. 39–45.

O. Ajmal, M. Missen, T. Hashmat, M. Moosa, and T. Ali, “Eplag: A two layer source code plagiarism detection system,” in Digital Information Management (ICDIM), 2013 Eighth International Conference on, Sept, 2013, pp. 256–261.

Giovanni Acampora and Georgina Cosma, “A Fuzzy-based Approach to Programming Language Independent Source-Code Plagiarism Detection”, IEEE, 2015.

http://www.cs.queensu.ca/queensu.ca/TechReports/Reports/2007-541.pdf.

David Gitchell 81 Nicholas Tran, “Sim: A Utility For Detecting Similarity in Computer Programs”, ACM, 1999, pp. 266-270.

Aiken A Moss. A system for detecting software plagiarism, http://www.cs.berkeley.edu/~aiken/moss.html.

M. J. Wise, “Detection of Similarities in Student Programs: YAP'ing may be Preferable to Plague'ing,” ACM SIGSCE, 2002.

Lutz Prechelt, Guido Malpohl, Michael Phlippsen, “JPlag: Finding plagiarisms among a set of programs”, Technical Report, University of Karlsruhe, Germany, 2000.

Jadalla, A. Elnagar, “A. PDE4Java: Plagiarism Detection Engine for Java sourcecode: a clustering approach”, IJBIDM, vol. 3, issue 2, 2008, pp. 121-135.

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Published

03/31/2017

How to Cite

Nagaich, A., Bhargava, A., & Badal, P. (2017). Plagiarism Detection Framework: A Technique for Detecting Source Code Plagiarism. SMART MOVES JOURNAL IJOSCIENCE, 3(3), 1–5. https://doi.org/10.24113/ijoscience.v3i3.60