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Statistical Software Engineering (1996)

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Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
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References

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Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
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Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×

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Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×

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Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×

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Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×
Page 67
Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×
Page 68
Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×
Page 69
Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×
Page 70
Suggested Citation:"References." National Research Council. 1996. Statistical Software Engineering. Washington, DC: The National Academies Press. doi: 10.17226/5018.
×
Page 71
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Statistical Software Engineering Get This Book
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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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