Source code similarity detection by using data mining methods

E. Stankov, M. Jovanov, A. Bogdanova
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引用次数: 5

Abstract

Programming courses at university and high school level, and competitions in informatics (programming), often require fast assessment of received solutions of the programming tasks. This problem is usually solved by use of automated systems that check the produced output for some test cases for every solution. In our paper we present a novel approach of representation of the programming codes as vectors, and use of these vectors in data mining analysis that could produce better assessment of the solutions. We present the results of cluster analysis that go up to 88% of correctly clustered items on average.
利用数据挖掘方法进行源代码相似度检测
大学和高中的编程课程,以及信息学(编程)的竞赛,通常需要对编程任务的解决方案进行快速评估。这个问题通常是通过使用自动化系统来解决的,该系统为每个解决方案检查一些测试用例的生成输出。在我们的论文中,我们提出了一种将编程代码表示为向量的新方法,并在数据挖掘分析中使用这些向量,可以更好地评估解决方案。我们给出了聚类分析的结果,平均高达88%的正确聚类项目。
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