源代码中与语言无关的剽窃检测

Rien Maertens, Charlotte Van Petegem, Niko Strijbol, Toon Baeyens, Arne Carla Jacobs, P. Dawyndt, Bart Mesuere
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引用次数: 8

摘要

学习编程越来越多地嵌入到中学和高等教育课程中,在这些课程中,解决编程练习在学习过程以及形成性和总结性评估中起着重要作用。不幸的是,学生们承认互相抄袭代码是一种常见的做法,老师们表示他们很少使用抄袭检测工具。我们希望通过引入一种新的源代码剽窃检测工具(Dolos)来降低教师检测剽窃的障碍,该工具由最先进的相似性检测算法提供支持,提供交互式可视化,并使用通用解析器模型来支持广泛的编程语言。方法以标准化数据集为基准,将Dolos与最先进的抄袭检测工具进行比较。我们介绍了将Dolos整合到编程课程中的经验,重点关注在线学习以及在COVID-19大流行期间过渡到远程评估的影响。结果与结论Dolos在发现潜在抄袭案例方面优于其他抄袭检测工具,是在线学习环境中预防和检测抄袭的重要工具。它在MIT开放源代码许可下可在https://dolos.ugent.be上获得。Dolos降低了教师发现、证明和防止编程课程抄袭的障碍。这有助于向开放和在线学习和评估环境的转变,并为更有效的学习和更好的评估开辟了有趣的途径。(PsycInfo数据库记录(c) 2022 APA,版权所有)
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Dolos: Language-agnostic plagiarism detection in source code
Background Learning to code is increasingly embedded in secondary and higher education curricula, where solving programming exercises plays an important role in the learning process and in formative and summative assessment. Unfortunately, students admit that copying code from each other is a common practice and teachers indicate they rarely use plagiarism detection tools. Objectives We want to lower the barrier for teachers to detect plagiarism by introducing a new source code plagiarism detection tool (Dolos) that is powered by state-of-the art similarity detection algorithms, offers interactive visualizations, and uses generic parser models to support a broad range of programming languages. Methods Dolos is compared with state-of-the-art plagiarism detection tools in a benchmark based on a standardized dataset. We describe our experience with integrating Dolos in a programming course with a strong focus on online learning and the impact of transitioning to remote assessment during the COVID-19 pandemic. Results and Conclusions Dolos outperforms other plagiarism detection tools in detecting potential cases of plagiarism and is a valuable tool for preventing and detecting plagiarism in online learning environments. It is available under the permissive MIT open-source license at https://dolos.ugent.be. Implications Dolos lowers barriers for teachers to discover, prove and prevent plagiarism in programming courses. This helps to enable a shift towards open and online learning and assessment environments, and opens up interesting avenues for more effective learning and better assessment. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
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