@inproceedings{0cfc32eebe914cabb34320dccbdf80bd,
title = "CPPCD: A Token-Based Approach to Detecting Potential Clones",
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.",
keywords = "clone detection, code clone, potential clone",
author = "Hung, {Yu Liang} and Shingo Takada",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 14th IEEE International Workshop on Software Clones, IWSC 2020 ; Conference date: 18-02-2020",
year = "2020",
month = feb,
doi = "10.1109/IWSC50091.2020.9047636",
language = "English",
series = "IWSC 2020 - Proceedings of the 2020 IEEE 14th International Workshop on Software Clones",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "26--32",
editor = "Hitesh Sajnani and Chaiyong Ragkhitwetsagul",
booktitle = "IWSC 2020 - Proceedings of the 2020 IEEE 14th International Workshop on Software Clones",
}