Who Made This Copy? An Empirical Analysis of Code Clone Authorship

TL;DR

This paper empirically investigates code clone authorship in Java projects, revealing clone prevalence, author contribution patterns, and multi-author clone sets to inform better clone management strategies.

Contribution

It provides the first empirical analysis of code clone authorship across multiple projects, highlighting clone characteristics and authorship patterns.

Findings

Average of 18.5% clone lines across projects

Authors contributing to non-clone lines also contribute to clone lines

One-third of clone sets are mainly contributed to by multiple authors

Abstract

Code clones are code snippets that are identical or similar to other snippets within the same or different files. They are often created through copy-and-paste practices during development and maintenance activities. Since code clones may require consistent updates and coherent management, they present a challenging issue in software maintenance. Therefore, many studies have been conducted to find various types of clones with accuracy, scalability, or performance. However, the exploration of the nature of code clones has been limited. Even the fundamental question of whether code snippets in the same clone set were written by the same author or different authors has not been thoroughly investigated. In this paper, we investigate the characteristics of code clones with a focus on authorship. We analyzed the authorship of code clones at the line-level granularity for Java files in 153 Apache projects stored on GitHub and addressed three research questions. Based on these research questions, we found that there are a substantial number of clone lines across all projects (an average of 18.5\% for all projects). Furthermore, authors who contribute to many non-clone lines also contribute to many clone lines. Additionally, we found that one-third of clone sets are primarily contributed to by multiple leading authors. These results confirm our intuitive understanding of clone characteristics, although no previous publications have provided empirical validation data from multiple projects. As the results could assist in designing better clone management techniques, we will explore the implications of developing an effective clone management tool.