Author

Colin Wielga

Date of Award

2013

Document Type

Thesis

Degree Name

Bachelors

Department

Natural Sciences

First Advisor

Rahal, Imad

Keywords

Computer Science, Plagiarism, String Comparison

Area of Concentration

Natural Sciences

Abstract

Source code plagiarism is easy to perform and difficult to catch. Detection approaches vary, with little consensus. This thesis compares several string comparison techniques borrowed from Biology on a large collection of student work containing various types of plagiarism. All the algorithms succeeded in matching a plagiarized file to its original files upwards of 90% of the time. A modification is proposed for these algorithms that drastically improves their runtimes with little or no effect on accuracy. The strengths and weaknesses of each are explored, in the hope of improving future plagiarism detection techniques.

Rights

The author has granted New College of Florida the nonexclusive right to archive, make accessible, and distribute for educational purposes this work in whole or in part in all forms of media, now or hereafter known. The copyright of this work remains with the author.

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