Supplementary Material for "Detecting Automatic Software Plagiarism via Token Sequence Normalization"

This repository contains additional material supporting the paper titled "Detecting Automatic Software Plagiarism via Token Sequence Normalization", presented at ICSE 2024 (research track). The paper presents a defense mechanism against automated plagiarism generators utilizing program dependence graphs and demonstrates its effectiveness in countering insertion-based and reordering-based obfuscation attacks. The defense mechanism was also integrated into the software plagiarism detector JPlag, thus providing a widely accessible solution. Contents Overview: Datasets: Two datasets from the PROGpedia collection and two internal datasets. For the latter, only the metadata is available due to the sensitive nature of the data. Plagiarized Submissions: Generated plagiarism instances illustrating various obfuscation methods such as insertion, reordering, and insert-after-reordering. Evaluation Data: JSON files detailing calculated similarities and runtime measurements for all datasets. Source Code: The implementation of our defense mechanism based on the software plagiarism detector JPlag (v4.0.0). Note that JPlag is licensed under the GPL-3.0 license. Evaluation Code: Python code for runtime measurements. Interactive Plots: HTML visualizations of the paper's plots, offering dynamic insights into the research findings. particularly focusing on the detection of automatic software plagiarism through token sequence normalization. Demo: A packaged JAR of our implementation alongside an instruction on how to execute it.