Characterizing Cross-Project Correlated Bug Resolution in the Python Ecosystem

Abstract

Modern software development increasingly depends on complex supply chains, where a single application relies on numerous upstream libraries. This interdependence causes Cross-Project Correlated Bugs (CPCBs). CPCBs are defects where the root cause resides in an upstream project, but the symptoms manifest in a downstream application. To understand the dynamics of CPCBs, we conducted a mixed-methods study in the Python Ecosystem. We performed a qualitative manual analysis of CPCBs to construct a taxonomy of resolution strategies and structural configurations. We integrated socio-technical data to empirically analyze the factors associated with Time-to-Fix (TTF) across different resolution contexts. Our analysis identifies six distinct resolution strategies and fourteen structural configurations that characterize how CPCBs are reported and resolved. Among these, Wait-for-Upstream Fix emerged as the most prevalent strategy. This study advances the understanding of defect propagation in software supply chains by formalizing CPCB resolution strategies and linking structural configurations to resolution outcomes. Our taxonomy and empirical findings provide a conceptual and analytical basis for future research on cross-project coordination and dependency risk management.