Extracting Insights from the Topology of the JavaScript Package Ecosystem

TL;DR

This paper applies Topological Data Analysis to visualize and analyze the high-dimensional structure of the npm JavaScript package ecosystem, uncovering patterns and insights about library relationships.

Contribution

It introduces the use of topological methods to analyze software ecosystems, providing a novel perspective on their complex high-dimensional data.

Findings

Revealed patterns in npm ecosystem topology

Identified localities indicating library clusters

Provided insights into ecosystem structure

Abstract

Software ecosystems have had a tremendous impact on computing and society, capturing the attention of businesses, researchers, and policy makers alike. Massive ecosystems like the JavaScript node package manager (npm) is evidence of how packages are readily available for use by software projects. Due to its high-dimension and complex properties, software ecosystem analysis has been limited. In this paper, we leverage topological methods in visualize the high-dimensional datasets from a software ecosystem. Topological Data Analysis (TDA) is an emerging technique to analyze high-dimensional datasets, which enables us to study the shape of data. We generate the npm software ecosystem topology to uncover insights and extract patterns of existing libraries by studying its localities. Our real-world example reveals many interesting insights and patterns that describes the shape of a software ecosystem.