Characterizing the Occurrence of Dockerfile Smells in Open-Source Software: An Empirical Study
Yiwen Wu, Yang Zhang, Tao Wang, Huaimin Wang
Abstract
Dockerfile plays an important role in the Docker-based software development process, but many Dockerfile codes are infected with smells in practice. Understanding the occurrence of Dockerfile smells in open-source software can benefit the practice of Dockerfile and enhance project maintenance. In this paper, we perform an empirical study on a large dataset of 6,334 projects to help developers gain some insights into the occurrence of Dockerfile smells, including its coverage, distribution, co-occurrence, and correlation with project characteristics. Our results show that smells are very common in Dockerfile codes and there exists co-occurrence between different types of Dockerfile smells. Further, using linear regression analysis, when controlled for various variables, we statistically identify and quantify the relationships between Dockerfile smells occurrence and project characteristics. We also provide a rich resource of implications for software practitioners.