Software Engineering for Science

ISBN: 9781498743853 出版年:2016 页码:311 CRC Press

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内容简介

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 Carveris 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 Hongis 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. Thiruvathukalis 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.

Amazon评论
Christopher Stone

This text provides a great survey software engineering for science. It presents a variety of case studies of computational science development projects with established software engineering practices as well as projects starting from scratch in terms of SE. The sections on automated unit and regression testing methods for scientific software should be especially useful for both individual developers and development teams. The text is readable for those without formal software engineering or computer science backgrounds. As such, it will be a useful guide for development staff and students, faculty, and project leads on how to incorporate the essential features of software engineering into their computational science development teams.

Christopher Stone

This text provides a great survey software engineering for science. It presents a variety of case studies of computational science development projects with established software engineering practices as well as projects starting from scratch in terms of SE. The sections on automated unit and regression testing methods for scientific software should be especially useful for both individual developers and development teams. The text is readable for those without formal software engineering or computer science backgrounds. As such, it will be a useful guide for development staff and students, faculty, and project leads on how to incorporate the essential features of software engineering into their computational science development teams.

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