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Writing Scientific Software: A Guide to Good Style
90% of respondents would recommend this to a friend
RWF 96016
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By following their advice, readers will learn how to write efficient software, and how to test it for bugs, accuracy and performance.
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What Stands Out
Product Details
| Publisher | Cambridge University Press |
| Publication date | September 18, 2006 |
| Edition | 1st |
| Language | English |
| Print length | 316 pages |
| ISBN-10 | 0521675952 |
| ISBN-13 | 978-0521675956 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 6.85 x 0.63 x 9.72 inches (17.4 x 1.6 x 24.7 cm) |
Who Should Buy?
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Students in Science
Undergraduate or graduate students in scientific fields seeking best practices for writing clean, maintainable code in research projects.
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Research Scientists
Scientists committed to high-quality coding standards to facilitate reproducibility and collaboration in their scientific software development.
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Software Developers
Developers transitioning from general software development to scientific computing who need guidelines on effective coding practices.
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Casual Programmers
Individuals writing non-scientific, casual scripts who may find scientific coding principles unnecessarily complex or irrelevant.
Product Description
Writing Scientific Software: A Guide to Good Style
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Computer Design Editorial Review
**** "Writing Scientific Software: A Guide to Good Style" by Suely Oliveira and David Stewart offers a comprehensive introduction to the essential principles of writing numerical software, making it a valuable resource for students and professionals in the field. The authors, both professors at the University of Iowa, delve into a vast array of topics surrounding scientific programming, including coding styles, computer organization, and design principles, with practical examples in Fortran and C++. Readers appreciate the book for its thorough coverage of important concepts such as the IEEE floating-point standards, numerical accuracy, and stability. It stands out for reinforcing best practices in software development, such as the prudent use of global variables, dynamic memory allocation, and the advantages of object-oriented programming. Notably, it emphasizes the necessity of proper documentation and testing, elements often overlooked in software engineering education. However, the book does have some drawbacks, particularly concerning the clarity of its writing. Various grammatical and technical inaccuracies can obscure the presented information, potentially confusing less experienced programmers. The authors acknowledge some of these errors on their website, but the extent of the issues may detract from the book's overall utility for beginners. Furthermore, critical modern programming languages like Python receive negligible attention, while some explanatory sections could benefit from greater precision and organization. Though it manages to cover a wide range of subjects in under 300 pages, the authors’ handling of complex topics does not always meet the required standard for clarity or precision. As such, the book is best suited for those with some prior experience in programming who can navigate through its inConsistencies. Overall, while "Writing Scientific Software" offers insightful guidance for developing efficient and effective scientific programs, readers should be prepared to supplement their learning with additional resources to address the weaknesses present in this text. **
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Pros
- Comprehensive coverage of coding principles and practices.
- Solid introduction to IEEE floating-point standards and numerical accuracy.
- Encourages best practices in documentation, testing, and software design.
- Quick read with practical examples in Fortran and C++.
Cons
- Numerous grammatical and technical inaccuracies affect clarity.
Product Price History
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RWF 96016
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Features & Benefits
- Essential guide for writing scientific software.
- Focuses on good coding practices for clarity and flexibility.
- Covers design, testing, debugging and modification techniques.
- Includes examples in Fortran 90, C++, C, and Java.
- Teaches readers how to avoid common pitfalls.
- A must-have for anyone involved in scientific computing.
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