Software quality assurance for mathematical modeling systems

Abstract

With increasing importance placed on standard quality assurance methodolo- gies by large companies and government organizations, many software companies have implemented rigorous quality assurance (QA) processes to ensure that these standards are met. The use of standard QA methodologies cuts maintenance costs, increases reliability, and reduces cycle time for new distributions. Modeling systems differ from most software systems in that a model may fail to solve to optimality without the modeling system being defective. This additional level of complexity requires specific QA activities. To make software quality assurance (SQA) more cost-effective, the focus is on reproducible and automated techniques. In this paper we describe some of the main SQA methodologies as applied to modeling systems. In particular, we focus on configuration management, quality control, and testing as they are handled in the GAMS build framework, emphasizing reproducibility, automation, and an open-source public-domain framework. © 2005 Springer Science+Business Media, Inc.