A Dataset of Dockerfiles

International Conference on Software Engineering(2020)

引用 11|浏览87
暂无评分
摘要
ABSTRACTDockerfiles are one of the most prevalent kinds of DevOps artifacts used in industry. Despite their prevalence, there is a lack of sophisticated semantics-aware static analysis of Dockerfiles. In this paper, we introduce a dataset of approximately 178,000 unique Dockerfiles collected from GitHub. To enhance the usability of this data, we describe five representations we have devised for working with, mining from, and analyzing these Dockerfiles. Each Dockerfile representation builds upon the previous ones, and the final representation, created by three levels of nested parsing and abstraction, makes tasks such as mining and static checking tractable. The Dockerfiles, in each of the five representations, along with metadata and the tools used to shepard the data from one representation to the next are all available at: https://doi.org/10.5281/zenodo.3628771.
更多
查看译文
关键词
Datasets, Docker, DevOps, Bash, Mining
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要