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Efficient plagiarism detection for large code repositories

Authors:

Steven Burrows,

S. M. M. Tahaghoghi,

Justin ZobelAuthors Info & Claims

Software—Practice & Experience, Volume 37, Issue 2

Pages 151 - 175

Published: 01 February 2007 Publication History

Abstract

Unauthorized re-use of code by students is a widespread problem in academic institutions, and raises liability issues for industry. Manual plagiarism detection is time-consuming, and current effective plagiarism detection approaches cannot be easily scaled to very large code repositories. While there are practical text-based plagiarism detection systems capable of working with large collections, this is not the case for code-based plagiarism detection. In this paper, we propose techniques for detecting plagiarism in program code using text similarity measures and local alignment. Through detailed empirical evaluation on small and large collections of programs, we show that our approach is highly scalable while maintaining similar levels of effectiveness to that of the popular JPlag and MOSS systems. Copyright © 2006 John Wiley & Sons, Ltd.

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Efficient plagiarism detection for large code repositories

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Information & Contributors

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Published In

cover image Software

Software Volume 37, Issue 2

February 2007

113 pages

ISSN:0038-0644

EISSN:1097-024X

Issue’s Table of Contents

Publisher

John Wiley & Sons, Inc.

United States

Publication History

Published: 01 February 2007

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Cited By

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https://dl.acm.org/doi/10.1145/3669901
Ou WDing STian YSong L(2023)SCS-Gan: Learning Functionality-Agnostic Stylometric Representations for Source Code Authorship VerificationIEEE Transactions on Software Engineering10.1109/TSE.2022.317722849:4(1426-1442)Online publication date: 1-Apr-2023
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Li ZChen GChen CZou YXu SDwyer MDamian DZeller A(2022)RoPGenProceedings of the 44th International Conference on Software Engineering10.1145/3510003.3510181(1906-1918)Online publication date: 21-May-2022
https://dl.acm.org/doi/10.1145/3510003.3510181
Abuhamad MAbuhmed TMohaisen DNyang D(2021)Large-scale and Robust Code Authorship Identification with Deep Feature LearningACM Transactions on Privacy and Security10.1145/346166624:4(1-35)Online publication date: 19-Jul-2021
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Bora PAwalgaonkar TPalve HJoshi RGoel P(2021)ICodeNet - A Hierarchical Neural Network Approach For Source Code Author IdentificationProceedings of the 2021 13th International Conference on Machine Learning and Computing10.1145/3457682.3457709(180-185)Online publication date: 26-Feb-2021
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Wu XQin LYu BXie XMa LXue YLiu YZhao J(2020)How are Deep Learning Models Similar?Proceedings of the 28th International Conference on Program Comprehension10.1145/3387904.3389254(172-183)Online publication date: 13-Jul-2020
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Novak MJoy MKermek D(2019)Source-code Similarity Detection and Detection Tools Used in AcademiaACM Transactions on Computing Education10.1145/331329019:3(1-37)Online publication date: 21-May-2019
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Ahadi AMathieson LSimon Luxton-Reilly A(2019)A Comparison of Three Popular Source code Similarity Tools for Detecting Student PlagiarismProceedings of the Twenty-First Australasian Computing Education Conference10.1145/3286960.3286974(112-117)Online publication date: 29-Jan-2019
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