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 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.

Open-Source Lab: How to Build Your Own Hardware and Reduce Scientific Research Costs details the development of the free and open-source hardware revolution. The combination of open-source 3D printing and microcontrollers running on free software enables scientists, engineers, and lab personnel in every discipline to develop powerful research tools at unprecedented low costs.After reading Open-Source Lab, you will be able to: - Lower equipment costs by making your own hardware - Build open-source hardware for scientific research - Actively participate in a community in which scientific results are more easily replicated and cited - Numerous examples of technologies and the open-source user and developer communities that support them - Instructions on how to take advantage of digital design sharing - Explanations of Arduinos and RepRaps for scientific use - A detailed guide to open-source hardware licenses and basic principles of intellectual property

Market_Desc: · Programmers· Software Engineers· Requirements Engineers· Software Quality Engineers Special Features: · Offers detailed coverage of software measures. Exposes students to quantitative methods of identifying important features of software products and processes· Complete Case Study. Through an air traffic control study, students can trace the application of methods and practices in each chapter· Problems. A broad range of problems and references follow each chapter· Glossary of technical terms and acronyms facilitate review of basic ideas· Example code given in C++ and Java· References to related web pages make it easier for students to expand horizons About The Book: This book is the first comprehensive study of a quantitative approach to software engineering, outlining prescribed software design practices and measures necessary to assess software quality, cost, and reliability. It also introduces Computational Intelligence, which can be applied to the development of software systems.

Developing projects outside of a classroom setting can be intimidating for students and is not always a seamless process. Real-World Software Projects for Computer Science and Engineering Students is a quick, easy source for tackling such issues. Filling a critical gap in the research literature, the book: Is ideal for academic project supervisors. Helps researchers conduct interdisciplinary research. Guides computer science students on undertaking and implementing research-based projects This book explains how to develop highly complex, industry-specific projects touching on real-world complexities of software developments. It shows how to develop projects for students who have not yet had the chance to gain real-world experience, providing opportunity to become familiar with the skills needed to implement projects using standard development methodologies. The book is also a great source for teachers of undergraduate students in software engineering and computer science as it can help students prepare for the risk and uncertainty that is typical of software development in industrial settings.

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12 selected papres from those presented at a series of symposia held at Kyoto University and ASTEM RI/Kyoto during the years 1986 through 1990 under the title 'Software Science and Engineering'.