Software Reliability: Measurement, Prediction, Application (Mcgraw-Hill Series in Software Engineering and Technology) [Hardcover]

John D. Musa (Author), Anthony Iannino (Author), Kazuhira Okumoto (Author)

Book Description

ISBN-10: 007044093X | ISBN-13: 978-0070440937 | Publication Date: May 1987 | Edition: First Edition

This pioneering text for emerging courses in Software Reliability and Software Testing integrates the theoretical and pragmatic aspects of Software Reliability measurement. It contains helpful appendices, glossaries of symbols and terms, challenging real-world cases, and extensive exercises.

Product Details

• Hardcover: 621 pages
• Publisher: Mcgraw-Hill College; First Edition edition (May 1987)
• Language: English
• ISBN-10: 007044093X
• ISBN-13: 978-0070440937
• Product Dimensions: 9.5 x 6.5 x 1.4 inches
• Shipping Weight: 2.2 pounds
• Average Customer Review: 5.0 out of 5 stars  See all reviews (2 customer reviews)
• Amazon Best Sellers Rank: #2,190,514 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

7 of 8 people found the following review helpful:

5.0 out of 5 stars Seminal book that is still up-to-date, June 2, 2002

By 

Mike Tarrani "www.tarrani.com" (Deltona, FL USA) - See all my reviews
(COMMUNITY FORUM 04)    (REAL NAME)   

This review is from: Software Reliability: Measurement, Prediction, Application (Mcgraw-Hill Series in Software Engineering and Technology) (Hardcover)

This book is classified as a seminal work in that it was the first mainstream book to address software reliability. The author is considered to be one of the founders of the discipline. Although the body of knowledge has grown significantly since this book was first published it remains a valid text because unlike technology, the underlying math and modeling are nearly timeless. The book serves as an introduction to software reliability as a discipline, and gives a solid foundation of the basics. Be aware that this is a math-intensive text and requires both statistics and probability skills. You also need a background in software development to fully benefit from this book (although the author provides appendices to fill in knowledge and experience gaps if your background isn't strong or recent).

Software and hardware reliability concepts, common reliability models and how the concepts and models apply to systems engineering and project management are provided to set context. The next part of the book goes into the practical application of reliability models and techniques. This part of the book is complete and covers all of the key elements of software reliability from design, development and implementation perspectives.

This book is more suited to college-level courses on software reliability. The author's later work, "Software Reliability Engineered Testing", is better suited for real world application because it approaches reliability from process and methodology perspectives and is more focused on practice than theory. However, this is still useful as a primer for practicing professionals.

2 of 2 people found the following review helpful:

5.0 out of 5 stars A little dated, but still great., January 10, 2003

By 

Walter Stoneburner (Ashburn, VA USA) - See all my reviews
(REAL NAME)   

This review is from: Software Reliability: Measurement, Prediction, Application (Mcgraw-Hill Series in Software Engineering and Technology) (Hardcover)

This book covers not just the concepts of reliability modeling but also how to do it in the practical real-world.

As with any book that shows the real-world approach, this one has sadly become dated, but the principles are the same. For instance, they recommend SMERFS ...what you really want is SMERFS^3, which does more only better. However, the models and math are equally applicable today as they were when the book was first written.

While you can read any of the raving reviews for the contents, I'd like to provide some special kudos for the Appendix. This is bar far one of the best introductions to practical statistics. It skips a lot of the how-we-got-the-formula and instead demonstrates what the formulas are doing and why using pictures and text.

There're list of formulas and conversions, a well-written glossary of terms, and my personal favorite: the glossary of notation.

See, a big part of the problem in reading texts that deal with mathematics is that you see some strange symbol in the page and your brain has no idea what it is. You have no name for that symbol, you don't know whether it's an operation, a function, or a value. This explains all that, making it easier to digest other books of similar kind.

The book is presented much like a college text book, so there are excercises (with explainatory answers in the back) so you can validate you're on the right track as you go.