Characterizing Dependency Update Practice of NPM, PyPI, and Cargo Packages

Core Concepts

Measuring the updatedness of dependencies and vulnerable dependencies in NPM, PyPI, and Cargo packages is crucial for software supply chain security.

Abstract

This study focuses on characterizing the dependency update practice of packages in NPM, PyPI, and Cargo ecosystems. It introduces two new metrics, Time-Out-Of-Date (TOOD) and Post-Fix-Exposure-Time (PFET), to measure the updatedness of dependencies and vulnerable dependencies. The study conducts a large-scale empirical analysis with 2.9M packages, 66.8M package versions, and 26.8M unique package-dependency relations. Results show that PyPI packages update dependencies faster, while Cargo packages update vulnerable dependencies faster. The study also explores the relationship between TOOD and PFET metrics. Index: Abstract Introduction Problem and Scope Challenges Goal Statement Approach Research Gap Definitions Update Metrics Research Methodology Results Discussion

Stats

"We analyze 26.8 million package-dependency relations from 2.9 million packages in these three ecosystems." "Cargo and PyPI have a concentrated distribution, with most PFET being less than 1000 days." "TOOD in NPM has a mean of 582 days, with a maximum of 4495 days." "PFET in NPM has a mean of 962 days, with a maximum of 4295 days." "Spearman, Pearson, and Kendall correlation coefficients between TOOD and PFET are 0.7, 0.7, and 0.5, respectively."

Quotes

"We propose focusing on the updatedness of dependencies and the updatedness of vulnerable dependencies within a package as new metrics." "Developers may use packages’ dependency update practice as one of the selection criteria for choosing a package as a dependency." "Our study proposes focusing on the updatedness of dependencies and the updatedness of vulnerable dependencies within a package as new metrics."

Key Insights Distilled From

Characterizing Dependency Update Practice of NPM, PyPI and Cargo Packages

by Imranur Rahm... at arxiv.org 03-27-2024

https://arxiv.org/pdf/2403.17382.pdf

Deeper Inquiries

How can the findings of this study be applied to improve software supply chain security beyond the analyzed ecosystems?

The findings of this study can be applied to improve software supply chain security in various ways. Firstly, the metrics developed in this study, such as Time-Out-Of-Date (TOOD) and Post-Fix-Exposure-Time (PFET), can be utilized by other software ecosystems to assess the updatedness of dependencies and the presence of vulnerable dependencies. By implementing similar metrics, software developers and organizations can proactively monitor and manage their dependencies to reduce the risk of security vulnerabilities. Additionally, the methodology used in this study, such as the temporal dependency resolution algorithm, can be adapted and applied to different ecosystems to analyze and improve their dependency update practices.

What are the potential drawbacks of using TOOD as a proxy for PFET in assessing security risks?

While using TOOD as a proxy for PFET can provide some insights into the security risks associated with outdated dependencies, there are potential drawbacks to consider. One drawback is that TOOD only focuses on the updatedness of dependencies and does not directly account for the presence of vulnerabilities. This means that a package could have an outdated dependency without any known vulnerabilities, leading to a false sense of security. Additionally, TOOD may not capture the severity of security risks posed by vulnerable dependencies, as it does not consider the specific vulnerabilities or their impact on the package. Therefore, relying solely on TOOD as a proxy for PFET may overlook critical security issues and result in inadequate risk assessment.

How can the concept of technical debt in software development be related to the findings of this study?

The concept of technical debt in software development can be related to the findings of this study in the context of dependency management and software maintenance. Just as technical debt refers to the implied cost of additional rework required in software development due to choosing a fast but limited solution over a better approach, the findings of this study highlight the implications of not keeping dependencies up-to-date. By neglecting to update dependencies promptly, software developers accumulate a form of technical debt in the form of outdated dependencies, which can lead to increased security risks and maintenance challenges in the future. The longer a package maintains outdated or vulnerable dependencies, the higher the technical debt it incurs in terms of potential security vulnerabilities and the effort required to remediate them. Therefore, addressing dependency update practices and mitigating technical debt in this context is crucial for ensuring the security and sustainability of software supply chains.