The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
YAP3: improved detection of similarities in computer program and other texts
Open accessAbstract
In spite of years of effort, plagiarism in student assignment submissions still causes considerable difficulties for course designers; if students' work is not their own, how can anyone be certain they have learnt anything? YAP is a system for detecting suspected plagiarism in computer programs and other texts submitted by students. The paper reviews YAP3, the third version of YAP, focusing on its novel underlying algorithm - Running-Karp-Rabin Greedy-String-Tiling (or RKS-GST), whose development arose from the observation with YAP and other systems that students shuffle independent code segments. YAP3 is able to detect transposed subsequences, and is less perturbed by spurious additional statements. The paper concludes with a discussion of recent extension of YAP to English texts, further illustrating the flexibility of the YAP approach.
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Cites
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Karp, R. M., & Rabin, M. O. (1987) · IBM Journal of Research and Development · doi:10.1147/rd.312.0249 · Cited by 1,269
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Faidhi, J. A. W., & Robinson, S. K. (1987) · Computers & Education · doi:10.1016/0360-1315(87)90042-x · Cited by 198
A technique for isolating differences between files
Heckel, P. (1978) · Communications of the ACM · doi:10.1145/359460.359467 · Cited by 124
A tool that detects plagiarism in Pascal programs
Grier, S. (1981) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/800037.800954 · Cited by 116
Identification of Program Similarity in Large Populations
Whale, G. (1990) · The Computer Journal · doi:10.1093/comjnl/33.2.140 · Cited by 103
Detection of similarities in student programs
Wise, M. J. (1992) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/134510.134564 · Cited by 88
Self-citationPlagiarism a la Mode: A Comparison of Automated Systems for Detecting Suspected Plagiarism
Verco, K. L. (1996) · The Computer Journal · doi:10.1093/comjnl/39.9.741 · Cited by 37
Wise, M. J. (1995) · PubMed · Cited by 33
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Cited by
A comparison of code similarity analysers
Ragkhitwetsagul, C., Krinke, J., & Clark, D. (2018) · Empirical Software Engineering · doi:10.1007/s10664-017-9564-7 · Cited by 122
Source-code Similarity Detection and Detection Tools Used in Academia: A Systematic Review
Novak, M., Joy, M., & Kermek, D. (2019) · ACM Transactions on Computing Education · doi:10.1145/3313290 · Cited by 117
Plagiarism detection using the Levenshtein distance and Smith-Waterman algorithm
Su, Z., Ahn, B.-R., Eom, K.-Y., Kang, M.-K., Kim, J.-P., & Kim, M.-K. (2008) · 2008 3rd International Conference on Innovative Computing Information and Control · doi:10.1109/icicic.2008.422 · Cited by 107
The toolbox for local and global plagiarism detection
Butakov, S., & Scherbinin, V. (2009) · Computers & Education · doi:10.1016/j.compedu.2008.12.001 · Cited by 79
Plagiarism in Programming Assessments: A Systematic Review
Albluwi, I. (2020) · ACM Transactions on Computing Education · doi:10.1145/3371156 · Cited by 63
Metadata
- Authors
- Wise, M. J.
- Venue
- Proceedings of the twenty-seventh SIGCSE technical symposium on Computer science education
- Publisher
- ACM
- Published
- 1996-03
- Pages
- 130-134
- OpenAlex
- W2073265902
- Cited by
- 294
- References
- 10
- FWCI
- 4.27
- Type
- conference paper
- Language
- en
- Open access
- bronze
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
