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δ-SCALPEL: Docker Image Slimming Based on Source Code Static Analysis
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DOI：10.1109/TSE.2025.3640123.png)
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Abstract
En 中文
Containerization is the mainstream of current software development, which enables software to be used across platforms without additional configuration of running environment. However, many images created by developers are redundant and contain unnecessary code, packages, and components. This excess not only leads to bloated images that are cumbersome to transmit and store but also increases the attack surface, making them more vulnerable to security threats. Therefore, image slimming has emerged as a significant area of interest. Nevertheless, existing image slimming technologies face challenges, particularly regarding the incomplete extraction of environment dependencies required by project code. In this paper, we present a novel image slimming model named <inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula>-SCALPEL. This model employs static data dependency analysis to extract the environment dependencies of the project code and utilizes a directed graph named command link directed graph for modeling the image’s file system. We select 30 NPM projects and two official Docker Hub images to construct a dataset for evaluating <inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula>-SCALPEL. The evaluation results show that <inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula>-SCALPEL is robust and can reduce image sizes by up to 61.4% while ensuring the normal operation of these projects.
Keywords:
Docker image
image slimming
static code analysis
data dependency analysis
command link directed graph
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