Measurement-driven dashboards enable leading indicators for requirements and design of large-scale systems

Measurement-driven dashboards provide a unifying mechanism for understanding, evaluating, and predicting the development, management, and economics of large-scale systems and processes. Dashboards enable interactive graphical displays of complex information and support flexible analytic capabilities for user customizability and extensibility. Dashboards commonly include software requirements and design metrics because they provide leading indicators for project size, growth, and stability. This paper focuses on dashboards that have been used on actual large-scale projects as well as example empirical relationships revealed by the dashboards. The empirical results focus on leading indicators for requirements and design of large-scale systems. In the first set of 14 projects focusing on requirements metrics, the ratio of software requirements to source-lines-of code averaged 1:46. Projects that far exceeded the 1:46 requirements-to-code ratio tended to be more effort-intensive and fault-prone during verification. In the second set of 16 projects focusing on design metrics, the components in the top quartile of the number of component internal states had 6.2 times more faults on average than did the components in the bottom quartile, after normalization by size. The components in the top quartile of the number of component interactions had 4.3 times more faults on average than did the components in the bottom quartile, after normalization by size. When the number of component internal states was in the bottom quartile, the component fault-proneness was low even when the number of component interactions was in the upper quartiles, regardless of size normalization. Measurement-driven dashboards reveal insights that increase visibility into large-scale systems and provide feedback to organizations and projects