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Statistical Software Engineering

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Status: Available Now

Size: 84 pages, 8.5 x 11

Publication Year:1996

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PAPERBACK ISBN-10: 0-309-05344-7 ISBN-13: 978-0-309-05344-0	$29.00	$26.10	Add to Cart

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Authors:
Panel on Statistical Methods in Software Engineering, National Research Council
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Description:
This book identifies challenges and opportunities in the development and implementation of software that contain significant statistical content. While emphasizing the relevance of using rigorous statistical and probabilistic techniques in software engineering contexts, it presents opportunities for further research in ...
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Table of Contents
Select a link below to start reading online free!
Front Matter	i-x
Executive Summary	1-4	(skim)
Introduction	5-8	(skim)
Case Study: NASA Space Shuttle Flight Control Software	9-12	(skim)
A Software Production Model	13-26	(skim)
Critique of Some Current Applications of Statistics in Software Engineering	27-42	(skim)
Statistical Challenges	43-60	(skim)
Summary and Conclusions	61-66	(skim)
References	67-71	(skim)
Appendix: Forum Program	72-73	(skim)

Description

This book identifies challenges and opportunities in the development and implementation of software that contain significant statistical content. While emphasizing the relevance of using rigorous statistical and probabilistic techniques in software engineering contexts, it presents opportunities for further research in the statistical sciences and their applications to software engineering.
It is intended to motivate and attract new researchers from statistics and the mathematical sciences to attack relevant and pressing problems in the software engineering setting. It describes the "big picture," as this approach provides the context in which statistical methods must be developed. The book's survey nature is directed at the mathematical sciences audience, but software engineers should also find the statistical emphasis refreshing and stimulating. It is hoped that the book will have the effect of seeding the field of statistical software engineering by its indication of opportunities where statistical thinking can help to increase understanding, productivity, and quality of software and software production.

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