An approach to automatically building Docker images by using domain knowledge

Wei CHEN; Hongjie YE; Jiahong ZHOU; Jun WEI

doi:10.11959/j.issn.2096-0271.2021005

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An approach to automatically building Docker images by using domain knowledge

Data-Driven Intelligent Software Development | 更新时间：2024-06-03

- An approach to automatically building Docker images by using domain knowledge
- Big Data Research Vol. 7, Issue 1, Pages: 2021005-1(2021)
- 作者机构：
  
  1. 中国科学院大学，北京 100190
  2. 中国科学院软件研究所，北京 100190
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2021005
  CLC： TP311
- Online First：2021-01，
  
  Published：15 January 2021
- 稿件说明：
移动端阅览
Wei CHEN, Hongjie YE, Jiahong ZHOU, et al. An approach to automatically building Docker images by using domain knowledge[J]. Big Data Research, 2021, 7(1): 2021005-1.
DOI：

Wei CHEN, Hongjie YE, Jiahong ZHOU, et al. An approach to automatically building Docker images by using domain knowledge[J]. Big Data Research, 2021, 7(1): 2021005-1. DOI： 10.11959/j.issn.2096-0271.2021005.

摘要

Dockerfile是构建Docker应用镜像的脚本代码，包含软件系统镜像构建所需的软件包及其依赖的下载、安装和配置的所有指令。编写Dockerfile需要丰富的领域知识，否则编写的Dockerfile容易产生镜像构建错误。针对此问题，提出一种基于领域知识的Docker镜像自动构建方法。该方法通过对大规模Dockerfile的自动解析，分析提取构建Docker镜像所需的软件依赖及安装配置等领域知识；在面向特定软件系统构建镜像时，从已构建的领域知识库中分析推断指定软件的依赖关系及安装操作，生成Dockerfile来构建Docker镜像。实验结果表明，该方法具有利用领域知识推断系统依赖关系和软件包安装方式、生成不同软件Dockerfile的能力。

Abstract

A Dockerfile builds a Docker image by specifying how to construct a software system by downloading

installing and configuring software packages and their dependencies. However

manually writing a Dockerfile can be error-prone because system dependency resolution requires a lot of domain knowledge. Therefore

an approach to automating Dockerfile generation based on domain knowledge was proposed. The approach automatically parses Dockerfiles and extracts knowledge of building Docker images and stores the knowledge in a graph database. When generating new Dockerfiles

the system dependencies and their installation operations for the designated software based on the knowledge base were inferred. Experiments indicate that it is viable to automate Dockerfile generation for diversified software by inferring system dependencies and software package installations with the domain knowledge.

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references

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