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Supplementary Material for "Automated Detection of AI-Obfuscated Plagiarism in Modeling Assignments"

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NIAID Data Ecosystem2026-05-01 收录
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https://zenodo.org/record/10442139
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This repository contains additional material supporting the paper titled "Automated Detection of AI-Obfuscated Plagiarism in Modeling Assignments", presented at ICSE 2024 (SEET track). The paper presents a token-based approach for detecting modeling plagiarism. It leverages a novel normalization technique to achieve resilience against common obfuscation attacks. The approach was also integrated into the software plagiarism detector JPlag, thus providing a widely accessible solution. Contents Overview: Source Code: The implementation of our approach (contribution 1) based on the software plagiarism detector JPlag (v4.0.0). Note that JPlag is licensed under the GPL-3.0 license. ChatGPT Study: An exploration of how ChatGPT can be exploited for cheating in modeling assignments. Datasets: The three datasets of our evaluation based on EMF modeling assignments. Raw Results: All raw data of our evaluation results, as used in our plots and tables. Demo: A packaged JAR of our approach's implementation alongside an instruction on how to use it.
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2024-01-26
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