Author | Singpurwalla, Nozer D. author |
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Title | Statistical Methods in Software Engineering [electronic resource] : Reliability and Risk / by Nozer D. Singpurwalla, Simon P. Wilson |
Imprint | New York, NY : Springer New York : Imprint: Springer, 1999 |
Connect to | http://dx.doi.org/10.1007/978-1-4612-0565-4 |
Descript | XIV, 297 p. online resource |
1 Introduction and Overview -- 1.1 What is Software Engineering? -- 1.2 Uncertainty in Software Production -- 1.3 The Quantification of Uncertainty -- 1.4 The Role of Statistical Methods in Software Engineering -- 1.5 Chapter Summary -- 2 Foundational Issues: Probability and Reliability -- 2.0 Preamble -- 2.1 The Calculus of Probability -- 2.2 Probability Models and Their Parameters -- 2.3 Point Processes and Counting Process Models -- 2.4 Fundamentals of Reliability -- 2.5 Chapter Summary -- Exercises for Chapter 2 -- 3 Models for Measuring Software Reliability -- 3.1 Background: The Failure of Software -- 3.2 Models Based on the Concatenated Failure Rate Function -- 3.3 Models Based on Failure Counts -- 3.4 Models Based on Times Between Failures -- 3.5 Unification of Software Reliability Models -- 3.6 An Adaptive Concatenated Failure Rate Model -- 3.7 Chapter Summary -- Exercises for Chapter 3 -- 4 Statistical Analysis of Software Failure Data -- 4.1 Background: The Role of Failure Data -- 4.2 Bayesian Inference, Predictive Distributions, and Maximization of Likelihood -- 4.3 Specification of Prior Distributions -- 4.4 Inference and Prediction Using a Hierarchical Model -- 4.5 Inference and Predictions Using Dynamic Models -- 4.6 Prequential Prediction, Bayes Factors, and Model Comparison -- 4.7 Inference for the Concatenated Failure Rate Model -- 4.8 Chapter Summary -- Exercises for Chapter 4 -- 5 Software Productivity and Process Management -- 5.1 Background: Producing Quality Software -- 5.2 A Growth-Curve Model for Estimating Software Productivity -- 5.3 The Capability Maturity Model for Process Management -- 5.4 Chapter Summary -- Exercises for Chapter 5 -- 6 The Optimal Testing and Release of Software -- 6.1 Background: Decision Making and the Calculus of Probability -- 6.2 Decision Making Under Uncertainty -- 6.3 Utility and Choosing the Optimal Decision -- 6.4 Decision Trees -- 6.5 Software Testing Plans -- 6.6 Examples of Optimal Testing Plans -- 6.7 Application: Testing the NTDS Data -- 6.8 Chapter Summary -- Exercises for Chapter 6 -- 7 Other Developments: Open Problems -- 7.0 Preamble -- 7.1 Dynamic Modeling and the Operational Profile -- 7.2 Statistical Aspects of Software Testing: Experimental Designs -- 7.3 The Integration of Module and System Performance -- Appendices -- Appendix A Statistical Computations Using the Gibbs Sampler -- A.1 An Overview of the Gibbs Sampler -- A.2 Generating Random Variates The Rejection Method -- A.3 Examples: Using the Gibbs Sampler -- A.3.1 Gibbs Sampling the Jelinski-Moranda Model -- A.3.2 Gibbs Sampling the Hierarchical Model -- A.3.3 Gibbs Sampling the Adaptive Kalman Filter Model -- A.3.4 Gibbs Sampling the Non-Gaussian Kalman Filter Model -- Appendix B The Maturity Questionnaire and Responses -- B. 1 The Maturity Questionnaire -- B.2 Binary (Yes, No) Responses to the Maturity Questionnaire -- B.3 Prior Probabilities and Likelihoods -- References -- Author Index