Software Solutions For Engineers And Scientists
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Software Solutions for Engineers and Scientists
Software requirements for engineering and scientific applications are almost always computational and possess an advanced mathematical component. However, an application that calls for calculating a statistical function, or performs basic differentiation of integration, cannot be easily developed in C++ or most programming languages. In such a case, the engineer or scientist must assume the role of software developer. And even though scientists who take on the role as programmer can sometimes be the originators of major software products, they often waste valuable time developing algorithms that lead to untested and unreliable routines. Software Solutions for Engineers and Scientists addresses the ever present demand for professionals to develop their own software by supplying them with a toolkit and problem-solving resource for developing computational applications. The authors' provide shortcuts to avoid complications, bearing in mind the technical and mathematical ability of their audience. The first section introduces the basic concepts of number systems, storage of numerical data, and machine arithmetic. Chapters on the Intel math unit architecture, data conversions, and the details of math unit programming establish a framework for developing routines in engineering and scientific code. The second part, entitled Application Development, covers the implementation of a C++ program and flowcharting. A tutorial on Windows programming supplies skills that allow readers to create professional quality programs. The section on project engineering examines the software engineering field, describing its common qualities, principles, and paradigms. This is followed by a discussion on the description and specification of software projects, including object-oriented approaches to software development. With the introduction of this volume, professionals can now design effective applications that meet their own field-specific requirements using modern tools and technology.
Software Solutions for Engineers and Scientists
Software requirements for engineering and scientific applications are almost always computational and possess an advanced mathematical component. However, an application that calls for calculating a statistical function, or performs basic differentiation of integration, cannot be easily developed in C++ or most programming languages. In such a case, the engineer or scientist must assume the role of software developer. And even though scientists who take on the role as programmer can sometimes be the originators of major software products, they often waste valuable time developing algorithms that lead to untested and unreliable routines. Software Solutions for Engineers and Scientists addresses the ever present demand for professionals to develop their own software by supplying them with a toolkit and problem-solving resource for developing computational applications. The authors' provide shortcuts to avoid complications, bearing in mind the technical and mathematical ability of their audience. The first section introduces the basic concepts of number systems, storage of numerical data, and machine arithmetic. Chapters on the Intel math unit architecture, data conversions, and the details of math unit programming establish a framework for developing routines in engineering and scientific code. The second part, entitled Application Development, covers the implementation of a C++ program and flowcharting. A tutorial on Windows programming supplies skills that allow readers to create professional quality programs. The section on project engineering examines the software engineering field, describing its common qualities, principles, and paradigms. This is followed by a discussion on the description and specification of software projects, including object-oriented approaches to software development. With the introduction of this volume, professionals can now design effective applications that meet their own field-specific requirements using modern tools and technology.
Software Engineering for Science
Software Engineering for Science provides an in-depth collection of peer-reviewed chapters that describe experiences with applying software engineering practices to the development of scientific software. It provides a better understanding of how software engineering is and should be practiced, and which software engineering practices are effective for scientific software. The book starts with a detailed overview of the Scientific Software Lifecycle, and a general overview of the scientific software development process. It highlights key issues commonly arising during scientific software development, as well as solutions to these problems. The second part of the book provides examples of the use of testing in scientific software development, including key issues and challenges. The chapters then describe solutions and case studies aimed at applying testing to scientific software development efforts. The final part of the book provides examples of applying software engineering techniques to scientific software, including not only computational modeling, but also software for data management and analysis. The authors describe their experiences and lessons learned from developing complex scientific software in different domains. About the Editors Jeffrey Carver is an Associate Professor in the Department of Computer Science at the University of Alabama. He is one of the primary organizers of the workshop series on Software Engineering for Science (http://www.SE4Science.org/workshops). Neil P. Chue Hong is Director of the Software Sustainability Institute at the University of Edinburgh. His research interests include barriers and incentives in research software ecosystems and the role of software as a research object. George K. Thiruvathukal is Professor of Computer Science at Loyola University Chicago and Visiting Faculty at Argonne National Laboratory. His current research is focused on software metrics in open source mathematical and scientific software.