Statistical Methods in Software Engineering
Reliability and Risk
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This book establishes a framework for dealing with uncertainties in software engineering, and for using quantitative measures for decision making in this context. It brings in perspective the large body of work having statistical content that is relevant to software engineering. The audience is computer scientists, software engineers, and reliability analysts, who have some exposure to probability and statistics. The content is pitched at a level that is appropriate for research workers in software reliability, and for graduate level courses in applied statistics computer science, operations research, and software engineering.
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.
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