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"Numerical software is used to test scientific theories, design airplanes and bridges, operate manufacturing lines, control power plants and refineries, analyze financial derivatives, identify genomes, and provide the understanding necessary to derive and analyze cancer treatments. Because of the high stakes involved, it is essential that results computed using software be accurate, reliable, and robust. Unfortunately, developing accurate and reliable scientific software is notoriously difficult. This book investigates some of the difficulties related to scientific computing and provides insight into how to overcome them and obtain dependable results. The tools to assess existing scientific applications are described, and a variety of techniques that can improve the accuracy and reliability of newly developed applications is discussed.Accuracy and Reliability in Scientific Computing can be considered a handbook for improving the quality of scientific computing. It will help computer scientists address the problems that affect software in general as well as the particular challenges of numerical computation: approximations occurring at all levels, continuous functions replaced by discretized versions, infinite processes replaced by finite ones, and real numbers replaced by finite precision numbers. Divided into three parts, it starts by illustrating some of the difficulties in producing robust and reliable scientific software. Well-known cases of failure are reviewed and the what and why of numerical computations are considered. The second section describes diagnostic tools that can be used to assess the accuracy and reliability of existing scientific applications. In the last section, the authors describe a variety of techniques that can be employed to improve the accuracy and reliability of newly developed scientific applications. The authors of the individual chapters are international experts, many of them members of the IFIP Working Group on Numerical Software."

"The papers combine topics like modeling, benchmarking, testing, performance evaluation, and dependability, and aim at academic and industrial researchers in these areas as well as graduate students and lecturers in related fields."

"This easy-to-read textbook/reference presents an essential guide to object-oriented C++ programming for scientific computing. With a practical focus on learning by example, the theory is supported by numerous exercises. Features, provides a specific focus on the application of C++ to scientific computing, including parallel computing using MPI, stresses the importance of a clear programming style to minimize the introduction of errors into code, presents a practical introduction to procedural programming in C++, covering variables, flow of control, input and output, pointers, functions, and reference variables, exhibits the efficacy of classes, highlighting the main features of object-orientation, examines more advanced C++ features, such as templates and exceptions."

"Engineering reliability concerns failure data analysis, the economics of maintenance policies, and system reliability. This textbook develops the use of probability and statistics in engineering reliability and maintenance problems. The author uses probability models in the analysis of failure data, decision relative to planned maintenance, and prediction relative to preliminary design."

"Here is a monograph that describes current research efforts in the application of symbolic computation to several areas, including dynamical systems, differential geometry, Lie algebras, numerical analysis, fluid dynamics, perturbation theory, control theory, and mechanics. The chapters, which illustrate how symbolic computations can be used to study various mathematical structures, are outgrowths of the invited talks that were presented at the NASA-Ames Workshop on The Use of Symbolic Methods to Solve Algebraic and Geometric Problems Arising in Engineering. More than 100 people participated in the two-day conference, which took place in January 1987 at the NASA-Ames Research Center in Moffett Field, California. The field of symbolic computation is becoming increasingly important in science, engineering, and mathematics. The availability of powerful computer algebra systems on workstations has made symbolic computation an important tool for many researchers."