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PDetect: A Clustering Approach for Detecting Plagiarism in Source Code Datasets

机译:PDetect:一种用于在源代码数据集中检测抄袭的聚类方法

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摘要

Efficient detection of plagiarism in programming assignments of students is of a great importance to the educational procedure. This paper presents a clustering oriented approach for facing the problem of source code plagiarism. The implemented software, called PDetect, accepts as input a set of program sources and extracts subsets (the clusters of plagiarism) such that each program within a particular subset has been derived from the same original. PDetect proposes the use of an appropriate measure for evaluating plagiarism detection performance and supports the idea of combining different plagiarism detection schemes. Furthermore, a cluster analysis is performed in order to provide information beneficial to the plagiarism detection process. PDetect is designed such that it may be easily adapted over any keyword-based programming language and it is quite beneficial when compared with earlier (state-of-the-art) plagiarism detection approaches.
机译:有效地检测学生编程作业中的窃行为对教育程序至关重要。本文提出了一种面向集群的方法来解决源代码抄袭问题。称为PDetect的已实现软件接受一组程序源作为输入,并提取子集(窃群集),以使特定子集中的每个程序都源自同一原始文件。 PDetect建议使用适当的方法来评估evaluating窃检测性能,并支持组合不同different窃检测方案的想法。此外,执行聚类分析以便提供有益于the窃检测过程的信息。 PDetect的设计使其可以轻松地适应任何基于关键字的编程语言,并且与早期(最新)的pla窃检测方法相比,它非常有益。

著录项

  • 来源
    《The Computer journal》 |2005年第6期|p.651-661|共11页
  • 作者单位

    Division of Computing Systems, Department of Industrial Informatics, Technological Educational Institute of Kavala, GR-65404 Kavala, Greece;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算技术、计算机技术;
  • 关键词

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