Statistical Methods in Software Engineering

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.