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Modeling interconnected social and technical risks in open source software ecosystems

Schueller, William and Wachs, Johannes ORCID: https://orcid.org/0000-0002-9044-2018 (2024) Modeling interconnected social and technical risks in open source software ecosystems. Collective Intelligence, 3 (1). pp. 1-16. DOI 10.1177/26339137241231912

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Official URL: https://doi.org/10.1177/26339137241231912


Abstract

Open source software ecosystems consist of thousands of interdependent libraries, which users can combine to great effect. Recent work has pointed out two kinds of risks in these systems: that technical problems like bugs and vulnerabilities can spread through dependency links, and that relatively few developers are responsible for maintaining even the most widely used libraries. However, a more holistic diagnosis of systemic risk in software ecosystem should consider how these social and technical sources of risk interact and amplify one another. Motivated by the observation that the same individuals maintain several libraries within dependency networks, we present a methodological framework to measure risk in software ecosystems as a function of both dependencies and developers. In our models, a library’s chance of failure increases as its developers leave and as its upstream dependencies fail. We apply our method to data from the Rust ecosystem, highlighting several systemically important libraries that are overlooked when only considering technical dependencies. We compare potential interventions, seeking better ways to deploy limited developer resources with a view to improving overall ecosystem health and software supply chain resilience.

Item Type:Article
Uncontrolled Keywords:Open source software, decentralized collaboration, systemic risk, networks, social-technical systems
Divisions:Institute of Data Analytics and Information Systems
Subjects:Computer science
Funders:European Research Executive Agency, Hungarian National Scientific Fund
Projects:101086712-LearnData-HORIZON-WIDERA-2022-TALENTS-01, OTKA FK-145960
DOI:10.1177/26339137241231912
ID Code:10471
Deposited By: MTMT SWORD
Deposited On:05 Nov 2024 13:54
Last Modified:05 Nov 2024 13:54

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