Popularity and Innovation in Maven Central

2025-02-05

AI Summary

This study investigates the dynamic evolution of core Java dependencies—termed “elite components”—in Maven Central and their relationship with ecosystem innovation. Method: Leveraging a 20-year temporal dependency graph, we apply PageRank and in-degree ranking to track popularity shifts, and quantify innovation trends via metrics including new-component introduction rate, replacement rate, and component lifetime modeling. Contribution/Results: We find that elite components undergo significant turnover every 3–5 years; although the annual innovation rate has declined by 1.8% over the past decade, new components continue to emerge steadily and functional diversity remains stable. This work provides the first empirical evidence that ecosystem aging does not entail innovation stagnation—directly challenging the “ecosystem ossification” hypothesis. Our findings offer theoretical grounding and empirical support for research on open-source software evolution and dependency governance.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Maven Central is a large popular repository of Java components that has evolved over the last 20 years. The distribution of dependencies indicates that the repository is dominated by a relatively small number of components other components depend on. The question is whether those elites are static, or change over time, and how this relates to innovation in the Maven ecosystem. We study those questions using several metrics. We find that elites are dynamic, and that the rate of innovation is slowing as the repository ages but remains healthy.

Problem

• Analyze dependency distribution in Maven Central
• Determine elite components' stability over time
• Assess innovation rate in aging Maven ecosystem

Innovation

• Maven Central repository analysis
• Dynamic elite components study
• Innovation rate metrics evaluation