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CPPCD: A Token-Based Approach to Detecting Potential Clones

机译:CPPCD:基于令牌的潜在克隆检测方法

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Most state-of-the-art clone detection approaches are aimed at finding clones accurately and/or efficiently. Yet, whether a code fragment is a clone often varies according to different people's perspectives and different clone detection tools. In this paper, we present CPPCD (CP-based Potential Clone Detection), a novel token-based approach to detecting potential clones. It generates CP (clone probability) values and CP distribution graphs for developers to decide if a method is a clone. We have evaluated our approach on large-scale software projects written in Java. Our experiments suggest that the majority of clones have CP values greater than or equal to 0.75 and that CPPCD is an accurate (with respect to Type-1, Type-2, and Type-3 clones), efficient, and scalable approach to detecting potential clones.
机译:大多数最新的克隆检测方法旨在准确和/或高效地找到克隆。但是,代码片段是否是克隆通常会根据不同的人的观点和不同的克隆检测工具而有所不同。在本文中,我们介绍了CPPCD(基于CP的潜在克隆检测),这是一种基于令牌的新型检测潜在克隆的方法。它生成CP(克隆概率)值和CP分布图,供开发人员确定方法是否为克隆。我们已经对用Java编写的大型软件项目的方法进行了评估。我们的实验表明,大多数克隆的CP值均大于或等于0.75,并且CPPCD是一种准确的(相对于Type-1,Type-2和Type-3克隆),高效且可扩展的检测潜能的方法克隆。

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