Automated Testing Coverage and Knowledge Transfer for Regression Risk in Mobile Application Releases

Abstract

The rapid evolution of mobile application development has necessitated the adoption of continuous integration and continuous deployment paradigms, which inherently introduce the risk of software regression. Regression risk, defined as the probability that previously functioning features will fail following new code modifications, remains a critical challenge for software engineering teams. This paper provides a comprehensive investigation into how regression risk can be explained and mitigated through two primary dimensions: automated testing coverage and knowledge transfer among development teams. By analyzing the interplay between machine-driven quality assurance metrics and human-centric cognitive processes, this research bridges a critical gap in contemporary software engineering literature. Extensive empirical observations derived from longitudinal studies of mobile application repositories indicate that while automated testing coverage provides a foundational safety net, its efficacy is severely bounded by the diminishing returns of test suite expansion. Conversely, knowledge transfer mechanisms, encompassing code review participation, documentation practices, and cross-functional team socialization, act as a vital moderating variable that significantly enhances defect detection and prevention. The findings demonstrate that a synergistic approach, which equally prioritizes high-fidelity automated test coverage and systematic knowledge dissemination, yields the most resilient mobile application releases. This study contributes to the broader academic discourse by proposing a multidimensional framework for regression risk assessment, offering actionable insights for optimizing software release cycles in fast-paced mobile environments.