Numerical software is central to our computerized society. It is used to design aeroplanes and bridges, operate manufacturing lines, control power plants and refineries, and analyze financial markets. Such software must be accurate, reliable, robust, efficient, easy to use, maintainable and adaptable. Producing high-quality numerical software remains quite difficult, however. In addition to the generic difficulties of complex system design in an era of rapidly changing computer architecture, numerical software developers must also cope with problem domains that do not admit provably reliable solution algorithms and inexact arithmetic systems that make portability difficult to achieve. Quality assessment and control of numerical software is still not well understood. Although measurement is a key element, it remains difficult to assess many components of software quality and to evaluate the trade-offs between them.This volume addresses enabling techniques and tools such as benchmarks, testing methodologies, quality standards, metrics and accuracy control mechanisms and their application to software for differential equations, linear algebra and data analysis, as well as the evaluation of integrals, derivatives and elementary and special functions.
