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Scientific Software Design

The Object-Oriented Way

Damian Rouson Jim Xia Xiaofeng Xu

$118.95

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Cambridge University Press
06 March 2014
The authors analyze how the structure of a package determines its developmental complexity according to such measures as bug search times and documentation information content. The work presents arguments for why these issues impact solution cost and time more than does scalable performance. The final chapter explores the question of scalable execution and shows how scalable design relates to scalable execution. The book's focus is on program organization, which has received considerable attention in the broader software engineering community, where graphical description standards for modeling software structure and behavior have been developed by computer scientists. These discussions might be enriched by engineers who write scientific codes. This book aims to bring such scientific programmers into discussion with computer scientists. The authors do so by introducing object-oriented software design patterns in the context of scientific simulation.
By:   Damian Rouson, Jim Xia, Xiaofeng Xu
Imprint:   Cambridge University Press
Country of Publication:   United Kingdom
Dimensions:   Height: 254mm,  Width: 178mm,  Spine: 21mm
Weight:   700g
ISBN:   9781107415331
ISBN 10:   1107415330
Pages:   406
Publication Date:   06 March 2014
Audience:   Professional and scholarly ,  College/higher education ,  Undergraduate ,  Primary
Format:   Paperback
Publisher's Status:   Active
Preface; Part I. The Tao of Scientific OOP: 1. Development costs and complexity; 2. The object-oriented way; 3. Scientific OOP; Part II. SOOP to Nuts and Bolts: 4. Design patterns basics; 5. The object pattern; 6. The abstract calculus pattern; 7. The strategy and surrogate patterns; 8. The puppeteer pattern; 9. Factory patterns; Part III. Gumbo SOOP: 10. Formal constraints; 11. Mixed-language programming; 12. Multiphysics architectures.

Damian Rouson is currently the manager of the Reacting Flow Research Department at Sandia National Laboratories. He was formerly Section Head of the US Navy Research Laboratory Division of Combustion Science and Modeling. He was Assistant Professor of Engineering at the City University of New York and Visiting Assistant Professor at the University of Maryland. Damian Rouson received his Masters and Ph.D. in Mechanical Engineering from Stanford University. Dr Jim Xia is currently a software designer and tester at the IBM Test Laboratory in Markham, Ontario, Canada. He received his Ph.D. in Physics from the University of Western Ontario in 1997. Dr Xiaofeng Xu is currently a Software Analyst at General Motors Corp. in Pontiac, Michigan. In this job, he performs airflow and combustion CFD analysis to support base engine designs. He received his Ph.D. in Mechanical Engineering (2003) from Iowa State University in Ames, IA and is the author or co-author of 39 refereed publications.

Reviews for Scientific Software Design: The Object-Oriented Way

'... it's one of those books that I wish I'd read earlier in my programming career. I found many design patterns familiar simply because I'd seen them before in my own code. I'll likely turn to this book in the future whenever I suspect a program design problem might be solved already.' Computing in Science and Engineering 'Scientific software must be consciously designed to grow with a research program and the hardware that supports the research program. And how to do that is precisely what these authors in this book have shown.' Scientific Programming This book makes a good case for the usefulness of design patterns and object-oriented programming for maintainable code, but disregards runtime performance and scienti!c libraries...one of those books that I wish I'd read earlier in my programming career. - Ramses van Zon, Computing in Science and Engineering, Jan/Feb 2012 Scientific software must be consciously designed to grow with a research program and the hardware that supports the research program. And how to do that is precisely what the authors in this book have shown. - Dan Nagel, Scientific Programming


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