Inter-Project Functional Clone Detection Toward Building Libraries - An Empirical Study on 13,000 Projects

Abstract

Libraries created from commonly used functionalities offer a variety of benefits to developers. To locate such widely used functionalities, clone detection on a large corpus of source code could be useful. However, existing clone detection techniques did not address the creation of libraries. Therefore, existing clone detectors are sometimes unbefitting to detect candidates to be included in libraries. This paper proposes a method-based clone detection technique focusing on building libraries. This method-level granularity is appropriate for building libraries because a method composes a functionally coherent unit, and so it can be easily pulled up into libraries. Also, such a granularity realizes a scalable detection on huge data sets. Our experimental results on a huge data set (360 million lines of code, 13,000 projects) showed that the proposed technique could detect functional clones which might be beneficial on the creation of libraries within a short time frame.