cid 0f1f6d49ae3f5c7e31341e3addce060390e7a5f92fab77ad9ec5319e9f5b2b0b · original · open access · via openalex
Title: A Dataset of Dockerfiles Authors: Jordan Henkel; Christian Bird; Shuvendu K. Lahiri; Thomas Reps Venue: International Conference on Mining Software Repositories (MSR) Year: 2020 Canonical: doi:10.1145/3379597.3387498 URL: https://doi.org/10.1145/3379597.3387498 Collector: openalex OA: true ABSTRACT Dockerfiles 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.