Risk Aware Test Planning Model for Large Scale Agile Software Development Projects

Abstract

Large-scale agile projects require flexible test planning because requirement changes, code complexity, business importance, defect history, and sprint dependencies vary across development cycles. This study presents a risk-aware test planning model that converts these factors into risk scores for user stories and features. The scores guide test strategy selection, priority setting, tester allocation, automation support, and environment use. The model was evaluated across eight agile sprints and compared with uniform and history-based planning. Results showed that the proposed approach maintained higher test coverage in low-, medium-, and high-risk conditions, with the greatest gains during complex and critical sprints. It also improved the use of limited testing resources by directing deeper testing toward unstable, defect-prone, and business-critical items. The model supports more reliable sprint planning, stronger cross-team coordination, earlier defect detection, and lower overall release risk in large-scale agile software projects.