Computer code models have become the default tool for analysis in many areas of research and industry. The research for evaluating these models has been focused on theoretical simulation methods and overlooks the application of these methods. Many existing and highly valued computer codes and models do not allow for risk and uncertainty quantification, simulation, or other modern computing capabilities. These computer codes are generally comprised of two categories: those with limited operation and older legacy codes. This paper provides a framework to systematically interrogate computer codes, including reduced iteration design of experiments (DoE) methods. While several of these methods are routinely used in other fields, they have not been applied to computer code models. This paper discusses challenges present when evaluating computer codes and offers a decision framework for selecting interrogation methods. New and alternative use cases for existing models is a focus. Interrogation of computer codes is a complex process and multiple methods exist. Defaulting to normal operation or one-factor at a time analysis can provide insufficient understanding of the model. Selections of a method is based on operational characteristics, resources, time, and the required outcome. Application of experiment designs to computer code interrogation enables existing models to be extended to new use cases, such as risk or uncertainty analysis, while maintaining the integrity of code validation.