Extracting Insights from the Topology of the JavaScript Package Ecosystem
This work addresses the problem of limited analysis capabilities for software ecosystems, which is important for businesses, researchers, and policymakers, but it is incremental as it applies an emerging technique to a specific domain.
The paper tackled the challenge of analyzing high-dimensional and complex software ecosystems like npm by applying Topological Data Analysis (TDA) to visualize and study their shape, revealing insights and patterns about existing libraries.
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.