Quantifying Competitive Relationships Among Open-Source Software Projects

2026-02-19

AI Summary

This study addresses the unclear impact of inter-project competition on the sustainability of open-source software initiatives. To this end, the authors propose MIAO, a novel approach that, for the first time, adapts the structural vector autoregression (SVAR) model—commonly used in macroeconomic analysis—to the study of open-source ecosystems. By integrating impulse response functions with large-scale time-series data, MIAO quantifies competitive dynamics among projects and forecasts their trajectories of rise or decline. Empirical evaluation on 187 real-world open-source project pairs demonstrates that MIAO identifies competition-driven project terminations with 81% accuracy and predicts project discontinuation up to one year in advance with 77% accuracy, offering actionable, forward-looking insights into the sustainability of open-source ecosystems.

Technology Category

• Multiagent Systems: Other Foundations of Multi Agent Systems
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Economics, Online Markets and Human Computation: Sustainability of Web economics
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs

Abstract

Throughout the history of software, evolution has occurred in cycles of rise and fall driven by competition, and open-source software (OSS) is no exception. This cycle is accelerating, particularly in rapidly evolving domains such as web development and deep learning. However, the impact of competitive relationships among OSS projects on their survival remains unclear, and there are risks of losing a competitive edge to rivals. To address this, this study proposes a new automated method called ``Mutual Impact Analysis of OSS (MIAO)'' to quantify these competitive relationships. The proposed method employs a structural vector autoregressive model and impulse response functions, normally used in macroeconomic analysis, to analyze the interactions among OSS projects. In an empirical analysis involving mining and analyzing 187 OSS project groups, MIAO identified projects that were forced to cease development owing to competitive influences with up to 81\% accuracy, and the resulting features supported predictive experiments that anticipate cessation one year ahead with up to 77\% accuracy. This suggests that MIAO could be a valuable tool for OSS project maintainers to understand the dynamics of OSS ecosystems and predict the rise and fall of OSS projects.

Problem

• open-source software
• competitive relationships
• project survival
• software evolution
• ecosystem dynamics

Innovation

• Mutual Impact Analysis of OSS
• structural vector autoregressive model
• impulse response function
• open-source software competition
• project cessation prediction