# Mining Container Image Repositories for Software Configuration and Beyond

arXiv: https://arxiv.org/abs/1802.03558 · HTML: https://mlsanity.com/paper/1802.03558/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Feb 2018.

## Built on by (most cited first, 2 of 2)

- [Configuration Validation with Large Language Models](https://mlsanity.com/paper/2310.09690/) (2023)
- [ML in a Box: Analyzing Containerization Practices in Open Source ML Projects](https://mlsanity.com/paper/2607.10126/) (2026)

## Abstract (arXiv)

This paper introduces the idea of mining container image repositories for configuration and other deployment information of software systems. Unlike traditional software repositories (e.g., source code repositories and app stores), image repositories encapsulate the entire execution ecosystem for running target software, including its configurations, dependent libraries and components, and OS-level utilities, which contributes to a wealth of data and information. We showcase the opportunities based on concrete software engineering tasks that can benefit from mining image repositories. To facilitate future mining efforts, we summarize the challenges of analyzing image repositories and the approaches that can address these challenges. We hope that this paper will stimulate exciting research agenda of mining this emerging type of software repositories.