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.

本仓库包含支持发表于ICSE 2024（研究赛道）的论文《基于Token序列归一化的自动化软件抄袭检测》的补充材料。

该论文提出了一种基于程序依赖图（Program Dependence Graphs）的自动化抄袭生成器防御机制，并验证了其对抗基于插入和基于重排序的混淆攻击的有效性。

该防御机制还被集成至软件抄袭检测工具JPlag中，由此提供了一套可广泛复用的解决方案。

内容概览：

数据集：包含PROGpedia数据集集中的2套数据集，以及2套内部数据集。由于数据涉及敏感内容，仅内部数据集的元数据可对外提供。

抄袭样本集：生成的抄袭实例，涵盖插入、重排序以及先重排序再插入等多种混淆手段。

评测数据：包含所有数据集的相似度计算结果与运行时性能测试数据的JSON文件。

源代码：基于软件抄袭检测工具JPlag（v4.0.0）实现的防御机制代码。请注意，JPlag采用GPL-3.0许可证进行授权。

评测代码：用于运行时性能测试的Python代码。

交互式可视化图表：论文中所有图表的HTML可视化版本，可动态展示研究结果，重点呈现基于Token序列归一化的自动化软件抄袭检测方法。

演示程序：封装好的实现程序JAR包，附带运行说明文档。