X9: An Obfuscation Resilient Approach for Source Code Plagiarism Detection in Virtual Learning Environments

Bruno Prado, Kalil Bispo, Raul Andrade

2018

Abstract

In computer programming courses programming assignments are almost mandatory, especially in a virtual classroom environment. However, the source code plagiarism is a major issue in evaluation of students, since it prevents a fair assessment of their programming skills. This paper proposes an obfuscation resilient approach based on the static and dynamic source code analysis in order to detect and discourage plagiarized solutions. Rather than focusing on the programming language syntax which is susceptible to lexical and structural refactoring, an instruction and an execution flow semantic analysis is performed to compare the behavior of source code. Experiments were based on case studies from real graduation projects and automatic obfuscation methods, showing a high accuracy and robustness in plagiarism assessments.

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Paper Citation


in Harvard Style

Prado B., Bispo K. and Andrade R. (2018). X9: An Obfuscation Resilient Approach for Source Code Plagiarism Detection in Virtual Learning Environments.In Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-298-1, pages 517-524. DOI: 10.5220/0006668705170524


in Bibtex Style

@conference{iceis18,
author={Bruno Prado and Kalil Bispo and Raul Andrade},
title={X9: An Obfuscation Resilient Approach for Source Code Plagiarism Detection in Virtual Learning Environments},
booktitle={Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2018},
pages={517-524},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006668705170524},
isbn={978-989-758-298-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - X9: An Obfuscation Resilient Approach for Source Code Plagiarism Detection in Virtual Learning Environments
SN - 978-989-758-298-1
AU - Prado B.
AU - Bispo K.
AU - Andrade R.
PY - 2018
SP - 517
EP - 524
DO - 10.5220/0006668705170524