Measuring Software Innovation with Open Source Software Development Data

2024-11-07

arXiv.org

AI Summary

Existing innovation metrics inadequately capture software innovation, hindering technical understanding and policy intervention in software-defined economies. To address this, we propose a novel, empirically grounded innovation metric based on semantic major-version releases (e.g., v2.0.0) as discrete, observable innovation units. Leveraging 200,000 release events across 28,000 open-source packages in the JavaScript, Python, and Ruby ecosystems on GitHub, we construct a joint metric integrating dependency growth and version complexity. Using dependency graph analysis, time-series modeling, and cross-language statistical comparison, we demonstrate that major-version releases significantly predict the logarithmic change in downstream dependency count one year later (p < 0.001), while version complexity robustly forecasts adoption rate. This metric system fills a critical gap in traditional innovation measurement for software, offering a rigorous, actionable benchmark for technology policy design and open-source governance.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Application Domains: Software Engineering
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning

Application Category

• Security and Privacy: Large-scale security measurements
• Web Mining and Content Analysis: Models for Web evolution
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies

Abstract

This paper introduces a novel measure of software innovation based on open source software (OSS) development activity on GitHub. We examine the dependency growth and release complexity among $sim$200,000 unique releases from 28,000 unique packages across the JavaScript, Python, and Ruby ecosystems over two years post-release. We find that major versions show differential, strong prediction of one-year lagged log change in dependencies. In addition, semantic versioning of OSS releases is correlated with their complexity and predict downstream adoption. We conclude that major releases of OSS packages count as a unit of innovation complementary to scientific publications, patents, and standards, offering applications for policymakers, managers, and researchers.

Problem

• Existing metrics fail to measure software innovation effectively
• Proposes new OSS-based metric using GitHub development activity
• Analyzes versioning patterns and dependency growth in JS, Python, Ruby

Innovation

• Uses GitHub OSS data for innovation metrics
• Analyzes dependency growth and release complexity
• Incorporates ecosystem culture and package maturity