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The system Kato: Detecting cases of plagiarism for answer-set programs

Published online by Cambridge University Press:  09 July 2010

JOHANNES OETSCH ,
JÖRG PÜHRER ,
MARTIN SCHWENGERER  and
HANS TOMPITS
JOHANNES OETSCH
Affiliation:
Technische Universität Wien, Institut für Informationssysteme 184/3, Favoritenstraße 9-11, A-1040 Vienna, Austria (e-mail: oetsch@kr.tuwien.ac.at, puehrer@kr.tuwien.ac.at, schwengerer@kr.tuwien.ac.at, tompits@kr.tuwien.ac.at)
JÖRG PÜHRER
Affiliation:
Technische Universität Wien, Institut für Informationssysteme 184/3, Favoritenstraße 9-11, A-1040 Vienna, Austria (e-mail: oetsch@kr.tuwien.ac.at, puehrer@kr.tuwien.ac.at, schwengerer@kr.tuwien.ac.at, tompits@kr.tuwien.ac.at)
MARTIN SCHWENGERER
Affiliation:
Technische Universität Wien, Institut für Informationssysteme 184/3, Favoritenstraße 9-11, A-1040 Vienna, Austria (e-mail: oetsch@kr.tuwien.ac.at, puehrer@kr.tuwien.ac.at, schwengerer@kr.tuwien.ac.at, tompits@kr.tuwien.ac.at)
HANS TOMPITS
Affiliation:
Technische Universität Wien, Institut für Informationssysteme 184/3, Favoritenstraße 9-11, A-1040 Vienna, Austria (e-mail: oetsch@kr.tuwien.ac.at, puehrer@kr.tuwien.ac.at, schwengerer@kr.tuwien.ac.at, tompits@kr.tuwien.ac.at)
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Abstract

Plagiarism detection is a growing need among educational institutions and solutions for different purposes exist. An important field in this direction is detecting cases of source-code plagiarism. In this paper, we present the tool Kato for supporting the detection of this kind of plagiarism in the area of answer-set programming (ASP). Currently, the tool is implemented for DLV programs but it is designed to handle other logic-programming dialects as well. We review the basic features of Kato, introduce its theoretical underpinnings, and discuss an application of Kato for plagiarism detection in the context of courses on logic programming at the Vienna University of Technology.

Keywords

answer-set programmingprogram analysisplagiarism detection

Information

Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 10 , Special Issue 4-6: 26th International Conference on Logic Programming , July 2010 , pp. 759 - 775
Copyright
Copyright © Cambridge University Press 2010

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References

Arwin, C. and Tahaghoghi, S. M. M. 2006. Plagiarism detection across programming languages. In Proceedings of the Twenty-Ninth Australasian Computer Science Conference (ACSC 2006). CRPIT, vol. 48. Australian Computer Society, Inc., Darlinghurst, Australia, 277–286.Google Scholar
Austin, M. and Brown, L. 1999. Internet plagiarism: Developing strategies to curb student academic dishonesty. The Internet and Higher Education 2, 1, 21–33.CrossRefGoogle Scholar
Bergroth, L., Hakonen, H. and Raita, T. 2000. A survey of longest common subsequence algorithms. In Proceedings of the Seventh International Symposium on String Processing Information Retrieval (SPIRE 2000). IEEE Computer Society, Los Alamitos, California, 39–48.CrossRefGoogle Scholar
Clough, P. 2000. Plagiarism in Natural and Programming Languages: An Overview of Current Tools and Technologies. Technical Report CS-00-05, Department of Computer Science, University of Sheffield, UK.Google Scholar
Denecker, M., Vennekens, J., Bond, S., Gebser, M. and Truszczynski, M. 2009. The second answer set programming competition. In Proceedings of the Tenth International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR 2009). Lecture Notes in Computer Science, vol. 5753. Springer, Berlin, 637–654.CrossRefGoogle Scholar
Eiter, T., Faber, W., Leone, N., Pfeifer, G. and Polleres, A. 2003. A logic-programming approach to knowledge-state planning II: The DLVK system. Artificial Intelligence 144, 2, 157–211.CrossRefGoogle Scholar
Farringdon, J. M. 1996. Analyzing for Authorship: A Guide to the Cusum Technique. University of Wales Press, Cardiff.Google Scholar
Gelfond, M. and Lifschitz, V. 1991. Classical negation in logic programs and disjunctive databases. New Generation Computing 9, 3/4, 365–385.CrossRefGoogle Scholar
Gitchell, D. and Tran, N. 1999. Sim: A utility for detecting similarity in computer programs. In Proceedings of the Thirtieth SIGCSE Technical Symposium on Computer Science Education (SIGCSE 1999). SIGCSE Bulletin, vol. 31. ACM Press, New York, 266–270.CrossRefGoogle Scholar
Halstead, M. H. 1977. Elements of Software Science. Elsevier Science Inc., New York.Google Scholar
Jones, E. L. 2001. Metrics based plagiarism monitoring. Journal of Computing Sciences in Colleges 16, 4, 253–261.Google Scholar
Lancaster, T. and Culwin, F. 2005. Classifications of plagiarism detection engines. ITALICS 4, 2, url: http://www.ics.heacademy.ac.uk/italics/vol4iss2.htm.CrossRefGoogle Scholar
Loose, F., Becker, S., Potthast, M. and Stein, B. 2008. Retrieval-Technologien für die Plagiaterkennung in Programmen. Tech. rep., University of Würzburg, Germany.Google Scholar
Lukácsy, G. and Szeredi, P. 2005. A generic framework for plagiarism detection in programs. In Proceedings of the 4th Japanese-Hungarian Symposium on Discrete Mathematics and Its Applications. 189–198.Google Scholar
Lukácsy, G. and Szeredi, P. 2009. Plagiarism detection in source programs using structural similarities. Acta Cybernetica 19, 1, 191–216.CrossRefGoogle Scholar
Maurer, H., Kappe, F. and Zaka, B. 2006. Plagiarism: A survey. Journal of Universal Computer Science 12, 8, 1050–1084.Google Scholar
Mozgovoy, M. 2008. Enhancing Computer-Aided Plagiarism Detection. VDM Verlag, Saarbrücken, Germany.Google Scholar
Ottenstein, K. J. 1976. An algorithmic approach to the detection and prevention of plagiarism. SIGCSE Bulletin 8, 4, 30–41.CrossRefGoogle Scholar
Prechelt, L., Malpohl, G. and Philippsen, M. 2000. JPlag: Finding Plagiarisms Among a Set of Programs. Technical Report 2000-1, Fakultät für Informatik Universität Karlsruhe, Germany.Google Scholar
Serebrenik, A. and Vanhoof, W. 2007. Fingerprinting logic programs. CoRR abs/cs/0701081.Google Scholar
Verco, K. L. and Wise, M. J. 1996a. Plagiarism a la mode: A comparison of automated systems for detecting suspected plagiarism. The Computer Journal 39, 9, 741–750.CrossRefGoogle Scholar
Verco, K. L. and Wise, M. J. 1996b. YAP3: Improved detection of similarities in computer program and other texts. In Proceedings of the Twenty-Seventh SIGCSE Technical Symposium on Computer Science Education (SIGCSE 1996). ACM Press, New York, NY, USA, 130–134.Google Scholar
Whale, G. 1990. Identification of program similarity in large populations. The Computer Journal 33, 2, 140–146.CrossRefGoogle Scholar
Wise, M. J. 1993. Running Karp-Rabin Matching and Greedy String Tiling. Technical report, Basser Department of Computer Science, University of Sydney, Australia.Google Scholar