Quantifying the Impact of Staged Rollout Policies on Software Process and Product Metrics

Abstract

Software processes define specific sequences of activities performed to effectively produce software, whereas tools provide concrete computational artifacts by which these processes are carried out. Tool independent modeling of processes and related practices enable quantitative assessment of software and competing approaches. This paper presents a framework to assess an approach employed in modern software development known as staged rollout, which releases new or updated software features to a fraction of the user base in order to accelerate defect discovery without imposing the possibility of failure on all users. The framework quantifies process metrics such as delivery time and product metrics, including reliability, availability, security, and safety, enabling tradeoff analysis to objectively assess the quality of software produced by vendors, establish baselines, and guide process and product improvement. Failure data collected during software testing is employed to emulate the approach as if the project were ongoing. The underlying problem is to identify a policy that decides when to perform various stages of rollout based on the software’s failure intensity. The illustrations demonstrate how alternative policies impose tradeoffs between two or more of the process and product metrics.