CPPCD: A Token-Based Approach to Detecting Potential Clones

Yu-Liang Hung, Shingo Takada
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引用次数: 7

Abstract

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.
CPPCD:一种基于令牌的检测潜在克隆的方法
大多数最先进的克隆检测方法旨在准确和/或有效地发现克隆。然而,一个代码片段是否为克隆,往往根据不同的人的角度和不同的克隆检测工具而有所不同。在本文中,我们提出了CPPCD(基于cp的潜在克隆检测),这是一种基于令牌的检测潜在克隆的新方法。它生成CP(克隆概率)值和CP分布图,供开发人员决定一个方法是否是克隆。我们已经在用Java编写的大型软件项目中评估了我们的方法。我们的实验表明,大多数克隆的CP值大于或等于0.75,并且CPPCD是一种准确(相对于1型、2型和3型克隆)、有效和可扩展的检测潜在克隆的方法。
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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