The Governance-at-Scale Paradox: Technical Debt Variance across Java Ecosystems
Resumo
Growing software organizations face a tension between team autonomy and cross-project architectural consistency, which we call the governance-at-scale paradox. This study investigates whether the strength of organization-level governance is associated with the variance of code-level technical debt across publicly available Java projects. In a pre-registered observational study, 60 projects from three governance archetypes, namely Google’s standardized scaffolding (17 projects), Apache’s community-process governance (24), and decentralized platform governance represented by Netflix, LinkedIn, and Uber (19), were analyzed with SonarQube, using SQALE debt density as the dependent variable. The pre-registered hypothesis predicted increasing variance from Google to Apache to the decentralized archetype and was evaluated by a conjunctive rule combining a Monte-Carlo-calibrated Brown-Forsythe test with a direct check of the predicted variance ordering. The hypothesis was rejected on both the direct and logarithmic scales: Google exhibited the highest variance, and a post-hoc bootstrap indicates that the predicted ordering rarely arises under resampling of these data. Descriptively, Apache projects show systematically higher debt density, an effect that intensifies when the comparison is restricted to similarly sized projects. Under the conditions of this study, the results suggest that cohesive local technical cultures may be associated with greater cross-project consistency than centralized governance. The pre-registered protocol, amendment history, dataset, and analysis scripts are publicly available for replication.
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