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Most of the resources accessible to us are freely available online. The following is an annotated list of important documents we know about which relate to plagiarism and are not available online without subscription.
Gerard K. Rambally and Mauricio le Sagen (1990). “An Inductive Inference Approach to Plagiarism Detection in Computer Programs”. National Educational Computing Conference , Nashville, TN, pp. 23-29.
Introduces an automated system that identifies “almost” identical Pascal programs, developed and implemented in LISP on a VAX 8600. Institutional Tool for Program Advising (ITPAD). The Knowledge Representation System: ID3 algorithm is used to to identify a classification rule from the data in the knowledge system. Classification rules and the building of a classification tree.
C.W. Johnson and I.C. Wand (1992). A Critical Evaluation Of Jankowitz’s Algorithm For The Detection Of Plagiarism In Student Pascal Programs . Technical Report YCS186, Department of Computer Science, University of York.
Definition of the terms robustness and efficiency in Plagiarism detection. Two stages of Automating The Detecting of Plagiarism. Introduces Janokwitz’s Algorithm (stage 1: static execution tree for each program; stage 2: syntactic and structural analysis).
Mike Joy and Michael Luck (1999). “Plagiarism in Programming Assignments”. IEEE Transactions in Education 42 (2) pp. 129-133.
Detailed account of the algorithm used by the source-code plagiarism detector Sherlock and its implementation. Information is slightly out of date due to work that has occurred on the software since publication.
Maxim Mozgovoy (2006). “Desktop Tools for Offline Plagiarism Detection in Computer Programs”. Informatics in Education 5 (1) pp. 97-112.
This paper categorizes plagiarism detection tools, and describes their capabilities, advantages and disadvantages. The author describes modern plagiarism software solutions, and desktop systems intended for detecting plagiarism in program code.
Kristina L. Verco and Michael J. Wise (1996). “Plagiarism à la Mode: A Comparison of Automated Systems for Detecting Suspected Plagiarism”. The Computer Journal 39 (9) pp. 741-750.
History and Types of Plagiarism Detection Systems (three types: attribute-counting-metric; attribute-counting and structure metrics; structure metrics). Comparisons of System Performance on two sets of Pascal programs. Concludes that structure metrics perform better.
Kristina L. Verco and Michael J. Wise (1996). “Software for Detecting Suspected Plagiarism: Comparing Structure and Attribute Counting Systems”. In Proceedings of the First Australasian Conference on Computer Science Education , Sydney, Australia.
Introduction of the new approach, the “sif”; tool: approximate fingerprints. Two methods of approximate fingerprints based on file checksums (synchronisation by extracting text strings which start with anchors; subset of fingerprints based on value). Four extensions to the system (adapting to different file types, different treatment of small and large files, directory comparison, custom output).
Michael J. Wise (1992). “Detection of Similarities in Student Programs: YAP’ing may be preferable to Plague’ing”. ACM SIGCSE Bulletin 24 (1) pp. 268-271.
Background to Plague (the three phases: tokenising, comparison of structure profiles, token sequence comparison) and the problems with Plague. The Components of YAP: two phases (generation and comparison), common structure of the tokenization suites). Formula to calculate the result from value analysis of sdiff’s output. Discussion of techniques for disguising. Strength and Weakness of YAP compared with Plague. Real Limitation of system’s accuracy.
Geoffrey Whale (1990a). “Identification of Program Similarity in Large Populations”. The Computer Journal 33 (2) pp. 140-146.
Introduces the importance of program similarity in commercial software field and educational institution. Need for plagiarism detection software. Origins of Program similarity. Techniques used to disguise programs. Evaluation Detection (success of a similarity detection systems and Key factors in system evaluation). Similarity Detection Techniques including cyclomatic complexity and scope number attribute counts. Comparison of Similarity Detection Methods.
Geoffrey Whale (1990b). “Software Metrics and Plagiarism Detection”. Journal of Systems and Software 13 (2) pp. 131-138.
Purpose of developing software metrics. Four important criteria for a satisfactory metric. Four different types of metrics (fixed-size metrics, variable-size metrics, structure profiles, data-usage metrics). Derivation and matching of structure profiles.
P. Ashworth, P. Bannister and P. Thorne (1997). “Guilty in Whose Eyes? University Students’ Perceptions of Cheating and Plagiarism in Academic Work and Assessment”. Studies in Higher Education , 22 (2) pp. 187-203.
This paper describes the attitudes of 19 British university students concerning plagiarism and cheating.
P. Ashworth, M. Freewood and R. Macdonald (2003). “The Student Lifeworld and the Meanings of Plagiarism”. Journal of Phenomenological Psychology 34 pp. 257-277.
This paper describes students’ perceptions on plagiarism.
J. Baggaley and B. Spencer (2005). “The Mind of a Plagiarist”. Learning, Media and Technology 30 (1) pp. 55-62.
This paper describes a case of ‘serial plagiarism’, in the work of a graduate student in an online distance education program.
Marcia Devlin (2006). “Policy, Preparation, and Prevention: Proactive Minimization of Student Plagiarism”. Journal of Higher Education Policy and Management 28 (1) pp. 45-58.
This paper describes one example of an approach for dealing with plagiarism and details the ways in which this approach has been implemented across a university.
The Library at St. Mary’s, (External) Academic Integrity: Selected Resources
This site contains lots of very useful papers on plagiarism, Prevalence, Prevention and Detection, Policy and Honor Codes, and Other Issues.
Assessment in Higher Education – (External) Plagiarism
Contains links to anti-plagiarism sites, paper mills and ‘cheat’ sites, books, online articles, and offline articles.
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