Detection of Plagiarism in University Projects Using Metrics-based Spectral Similarity

Author Ettore Merlo



PDF
Thumbnail PDF

File

DagSemProc.06301.7.pdf
  • Filesize: 148 kB
  • 10 pages

Document Identifiers

Author Details

Ettore Merlo

Cite As Get BibTex

Ettore Merlo. Detection of Plagiarism in University Projects Using Metrics-based Spectral Similarity. In Duplication, Redundancy, and Similarity in Software. Dagstuhl Seminar Proceedings, Volume 6301, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007) https://doi.org/10.4230/DagSemProc.06301.7

Abstract

An original method of spectral similarity analysis for plagiarism
detection in university project is presented. The approach is based on
a clone detection tool called CLAN that performs metrics based
similarity analysis of source code fragments. Definitions and
algorithms for spectral similarity analysis are presented and
discussed. Experiments performed on university projects are
presented. Experimental results include the distribution of similarity
in C and C++ projects. Analysis of spectral similarity distribution
identifies the most similar pairs of projects that can be considered as
candidates for plagiarism.

Subject Classification

Keywords
  • Plagiarism detection
  • software comparison
  • clone detection
  • spectral analysis
  • code metrics

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail