Plagiarism detection based on blinded logical test automation results and detection of textual similarity between source codes

D. Campos, D. Ferreira
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引用次数: 1

Abstract

This Research to Practice Full Paper presents in this paper. Finding logical errors is the most difficult skill for students from all sorts of disciplines that involve computer programming. Unfortunately, because of this difficulty, some students resort to plagiarism. Plagiarism corrupts the evaluation process. Several tools are used in different researches for this purpose. Recent research has defined a taxonomy of the most relevant types of plagiarism that can be found in source codes. The Hybrid Framework was made to map the student plagiarisms using NLP tecnhics and software test automation techniques for automatic exercise correction with tools available for this purpose. This framework has been tested in the laboratory with promising results.
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基于盲法逻辑测试自动化结果和源代码文本相似度检测的抄袭检测
本文提出了本研究的实践全文。对于所有涉及计算机编程的学科的学生来说,发现逻辑错误是最困难的技能。不幸的是,由于这个困难,一些学生诉诸抄袭。剽窃破坏了评估过程。为此目的,在不同的研究中使用了几种工具。最近的研究已经定义了一种可以在源代码中找到的最相关的剽窃类型的分类。使用NLP技术和软件测试自动化技术来绘制学生抄袭的地图,并使用可用于此目的的工具进行自动练习纠正。该框架已在实验室进行了测试,结果令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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