Abstract

The practice of verification is grounded in mathematics highlighting the fundamental nature of its practice. Models of reality are fundamentally mathematical and verification assures the connection between the modeling intended and achieved in codeCode. Code verificationCode verification is a process where the correctness of a computer codeCode for simulation and modeling is proven. This “proof” is defined by the collection of evidence that the numerical approximationsApproximation are congruent with the model for the physical phenomena. The key metricMetric in codeCodeverificationCode verification is the order of accuracyAccuracy of the approximationApproximation that should match theoretical expectations. In contrast, solution verification is an aspect of uncertaintyUncertainty estimationestimationEstimation associated with numerical errorError in simulations. Solution verification uses many of the same approaches as codeCodeverificationCode verification, but its principal outcome is an estimate of the numerical errorError. The order of convergenceConvergence is a secondary outcome. Together these two practices form an important part of the foundation of quality and credibilityCredibility in modeling and simulation.