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Mirko Boehm

Publications and source records attributed to Mirko Boehm.

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A Toolkit for Measuring the Impacts of Public Funding on Open Source Software Development

Governments are increasingly employing funding for open source software (OSS) development as a policy lever to support the security of software supply chains, digital sovereignty, economic growth, and national competitiveness in science and innovation, among others. However, the impacts of public funding on OSS development remain poorly understood, with a lack of consensus on how to meaningfully measure them. This gap hampers assessments of the return on public investment and impedes the optimisation of public-interest funding strategies. We address this gap with a toolkit of methodological considerations that may inform such measurements, drawing on prior work on OSS valuations and community health metrics by the Community Health Analytics Open Source Software (CHAOSS) project as well as our first-hand learnings as practitioners tasked with evaluating funding programmes by the Next Generation Internet initiative and the Sovereign Tech Agency. We discuss salient considerations, including the importance of accounting for funding objectives, project life stage and social structure, and regional and organisational cost factors. Next, we present a taxonomy of potential social, economic, and technological impacts that can be both positive and negative, direct and indirect, internal (i.e. within a project) and external (i.e. among a project's ecosystem of dependents and users), and manifest over various time horizons. Furthermore, we discuss the merits and limitations of qualitative, quantitative, and mixed-methods approaches, as well as options for and hazards of estimating multiplier effects. With this toolkit, we contribute to the multi-stakeholder conversation about the value and impacts of funding on OSS developers and society at large.

cs.CY

Measuring Software Innovation with Open Source Software Development Data

Existing innovation metrics inadequately capture software innovation, creating blind spots for researchers and policymakers seeking to understand and foster technological innovation in an increasingly software-defined economy. 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 350,000 unique releases from 33,000 unique packages across the JavaScript, Python, and Ruby ecosystems over two years post-release. We find that the semantic versioning types of OSS releases exhibit ecosystem-specific and maturity-dependent patterns in predicting one-year dependency growth, with minor releases showing relatively consistent adoption across contexts while major and patch releases vary significantly by ecosystem and package size. In addition, while semantic versioning correlates with the technical complexity of the change-set, complexity itself shows minimal correlation with downstream adoption, suggesting that versioning signals rather than technical change drive dependency growth. Overall, while semantic versioning release information can be used as a unit of innovation in OSS development complementary to common sources for innovation metrics (e.g. scientific publications, patents, and standards), this measure should be weighted by ecosystem culture, package maturity, and release type to accurately capture innovation dynamics. We conclude with a discussion of the theoretical and practical implications of this novel measure of software innovation as well as future research directions.

cs.SE