© 1999

Statistical Methods in Software Engineering

Reliability and Risk


Part of the Springer Series in Statistics book series (SSS)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Nozer D. Singpurwalla, Simon P. Wilson
    Pages 1-11
  3. Nozer D. Singpurwalla, Simon P. Wilson
    Pages 13-66
  4. Nozer D. Singpurwalla, Simon P. Wilson
    Pages 67-99
  5. Nozer D. Singpurwalla, Simon P. Wilson
    Pages 101-167
  6. Nozer D. Singpurwalla, Simon P. Wilson
    Pages 169-190
  7. Nozer D. Singpurwalla, Simon P. Wilson
    Pages 191-219
  8. Nozer D. Singpurwalla, Simon P. Wilson
    Pages 221-245
  9. Back Matter
    Pages 247-297

About this book


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.


Capability Maturity Model Likelihood Probability distribution Random variable Software Engineering Statistical Methods classification complexity design modeling object oriented design productivity programming statistical model

Authors and affiliations

  1. 1.Department of Operations ResearchThe George Washington UniversityUSA
  2. 2.Department of StatisticsTrinity CollegeDublin 2Ireland

Bibliographic information

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