| Statistical Methods in Software Engineering: Reliability and Risk Softcover Repri Edition Contributor(s): Singpurwalla, Nozer D. (Author), Wilson, Simon P. (Author) |
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ISBN: 1461268206 ISBN-13: 9781461268208 Publisher: Springer OUR PRICE: $113.99 Product Type: Paperback - Other Formats Published: September 2012 |
| Additional Information |
| BISAC Categories: - Mathematics | Probability & Statistics - General - Computers | Software Development & Engineering - General - Mathematics | Applied |
| Dewey: 005.1 |
| Series: Springer Statistics |
| Physical Information: 0.66" H x 6.14" W x 9.21" (0.98 lbs) 297 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: This preface pertains to three issues that we would like to bring to the attention of the readers: our objectives, our intended audience, and the nature of the material. We have in mind several objectives. The first is to establish a framework for dealing with uncertainties in software engineering, and for using quantitative measures for decision making in this context. The second is to bring into perspective the large body of work having statistical content that is relevant to software engineering, which may not have appeared in the traditional outlets devoted to it. Connected with this second objective is a desire to streamline and organize our own thinking and work in this area. Our third objective is to provide a platform that facilitates an interface between computer scientists and statisticians to address a class of problems in computer science. It appears that such an interface is necessary to provide the needed synergism for solving some difficult problems that the subject poses. Our final objective is to serve as an agent for stimulating more cross-disciplinary research in computer science and statistics. To what extent the material here will meet our objectives can only be assessed with the passage of time. Our intended audience is computer scientists, software engineers, and reliability analysts, who have some exposure to probability and statistics. Applied statisticians interested in reliability problems are also a segment of our intended audience. |
