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A Source Code Linearization Technique for Detecting Plagiarized Programs

机译:用于检测Pla窃程序的源代码线性化技术

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摘要

It is very important to detect plagiarized programs in the field of computer science education. Therefore, many tools and algorithms have been developed for this purpose. Generally, these tools are operated in two phases. In phase 1, a program plagiarism detecting tool generates an intermediate representation from a given program set. The intermediate representation should reflect the structural characterization of the program. Most tools use the parse tree or token sequence by intermediate representation. In phase 2, the program looks for plagiarized material and evaluates the similarity of two programs. It is helpful to announce the plagiarized metarials between two programs to the instructor. In this paper, we present the static tracing method in order to improve program plagiarism detection accuracy. The static tracing method statically executes a program at the syntax-level and then extracts predefined keywords according to the order of the executed functions. The result of experiment proves this method can detect plagiarism more effectively than the previously released plagiarism detecting method.
机译:在计算机科学教育领域中检测窃的程序非常重要。因此,已为此目的开发了许多工具和算法。通常,这些工具分两个阶段进行操作。在阶段1中,程序窃检测工具从给定的程序集生成中间表示。中间表示应反映程序的结构特征。大多数工具通过中间表示使用解析树或令牌序列。在第2阶段,程序将查找窃的材料并评估两个程序的相似性。向讲师宣布两个程序之间抄袭的meta窃是很有帮助的。在本文中,我们提出了静态跟踪方法,以提高程序窃检测的准确性。静态跟踪方法在语法级别上静态执行程序,然后根据执行功能的顺序提取预定义的关键字。实验结果证明,该方法比以前发布的窃检测方法更有效地检测窃。

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