Insights into Dependency Maintenance Trends in the Maven Ecosystem

TL;DR

Dependency freshness in the Maven ecosystem is analyzed through a large-scale Neo4j Maven Central graph using the Goblin framework. The study focuses on a subset of 100000 libraries and 1000000 dependencies to examine how dependency counts relate to missed releases and how up-to-date the dependencies of the latest releases are. It finds that smaller projects tend to miss more releases and have longer outdated times, while larger projects show better maintenance; latest-release dependencies are largely current with a mean outdated time of $2.5$ years, albeit with outliers. The results offer actionable guidance for improving release reliability and dependency maintenance across software ecosystems.

Abstract

As modern software development increasingly relies on reusable libraries and components, managing dependencies has become critical for ensuring software stability and security. However, challenges such as outdated dependencies, missed releases, and the complexity of interdependent libraries can significantly impact project maintenance. In this paper, we present a quantitative analysis of the Neo4j dataset using the Goblin framework to uncover patterns of freshness in projects with different numbers of dependencies. Our analysis reveals that releases with fewer dependencies have a higher number of missed releases. Additionally, our study shows that the dependencies in the latest releases have positive freshness scores, indicating better software management efficacy. These results can encourage better management practices and contribute to the overall health of software ecosystems.

Figures (5)

• Figure 1: Distribution of Dependencies
• Figure 2: Dependency Count Vs Number of Missed Releases
• Figure 3: Dependency Count Vs Outdated Time (Years)
• Figure 4: Distribution of Outdated Time (Years) Across Dependencies
• Figure 5: Distribution of Missed Releases Across Dependencies