Docker Does Not Guarantee Reproducibility
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866911384377229312 |
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| author | Malka, Julien Zacchiroli, Stefano Zimmermann, Théo |
| author_facet | Malka, Julien Zacchiroli, Stefano Zimmermann, Théo |
| contents | The reproducibility of software environments is a critical concern in modern software engineering, with ramifications ranging from the effectiveness of collaboration workflows to software supply chain security and scientific reproducibility. Containerization technologies like Docker address this problem by encapsulating software environments into shareable filesystem snapshots known as images. While Docker is frequently cited in the literature as a tool that enables reproducibility in theory, the extent of its guarantees and limitations in practice remains under-explored.
In this work, we address this gap through two complementary approaches. First, we conduct a systematic literature review to examine how Docker is framed in scientific discourse on reproducibility and to identify documented best practices for writing Dockerfiles enabling reproducible image building. Then, we perform a large-scale empirical study of 5298 Docker builds collected from GitHub workflows. By rebuilding these images and comparing the results with their historical counterparts, we assess the real reproducibility of Docker images and evaluate the effectiveness of the best practices identified in the literature. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_12811 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Docker Does Not Guarantee Reproducibility Malka, Julien Zacchiroli, Stefano Zimmermann, Théo Software Engineering The reproducibility of software environments is a critical concern in modern software engineering, with ramifications ranging from the effectiveness of collaboration workflows to software supply chain security and scientific reproducibility. Containerization technologies like Docker address this problem by encapsulating software environments into shareable filesystem snapshots known as images. While Docker is frequently cited in the literature as a tool that enables reproducibility in theory, the extent of its guarantees and limitations in practice remains under-explored. In this work, we address this gap through two complementary approaches. First, we conduct a systematic literature review to examine how Docker is framed in scientific discourse on reproducibility and to identify documented best practices for writing Dockerfiles enabling reproducible image building. Then, we perform a large-scale empirical study of 5298 Docker builds collected from GitHub workflows. By rebuilding these images and comparing the results with their historical counterparts, we assess the real reproducibility of Docker images and evaluate the effectiveness of the best practices identified in the literature. |
| title | Docker Does Not Guarantee Reproducibility |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2601.12811 |