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Hardcover Handbook of Software Reliability Engineering Book

ISBN: 0070394008

ISBN13: 9780070394001

Handbook of Software Reliability Engineering

Software reliability engineering is the statistical study of how well software systems satisfy user requirements on user premises, and for how long. This book compiles data, analysis and case studies,... This description may be from another edition of this product.

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Format: Hardcover

Condition: Good

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Customer Reviews

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The best handbook I've seen on the subject.

Professor Lyu defines, catalogs, explains, and demonstrates concepts and models for reliability. If you're trying to answer questions like "based on historical data, when is the next expected failure," or "what model best predicts my software's reliability," or "when will the software be stable" then you need this book. True to its name, it is a handbook, so you can jump around and cross reference, but you can also read it like a book.Note, however, that there is some fairly heavy statistical math. Don't let all the greek letters scare you. It's all explained, and it has a fantastic appendix that covers all you need to know concerning statistics to use the book without the mumbo-jumbo.To complete your collection, go to the web and obtain a copy of SMERFS^3, which is a software package developed by Dr. William Farr that does all the modeling math for you. Additionally, check out the book Software Reliability by Musa/Iannio/Okumoto (0-07-044093-X). These two things, together with this book will equip you for just about anything you need to measure.

Standard for the field of S/W Reliability

This is an excellent technical book that should be a standard reference for anyone working in the field of S/W QA/Reliablity. The work assumes a mathematical background at the upper division/graduate level. The section on orthogonal defect classification is especially good. This is an essential work for anyone compiling metrics for gauging how well a S/W development effort is progressing. Software is supplied for performing one's own analyses. Meaty stuff for the serious S/W QA engineer! Well done.
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