Continuing our discussion of software reliability models, in this chapter we cover the class of models called the reliability growth models . We first discuss the exponential model; then we concisely describe several notable reliability growth models in the literature; and in later sections we discuss several issues such as model assumptions, criteria for model evaluation, the modeling process, the test compression factor, and estimating the distribution of estimated field defects over time.
In contrast to Rayleigh, which models the defect pattern of the entire development process, reliability growth models are usually based on data from the formal testing phases. Indeed it makes more sense to apply these models during the final testing phase when development is virtually complete, especially when the testing is customer oriented. The rationale is that defect arrival or failure patterns during such testing are good indicators of the product's reliability when it is used by customers. During such postdevelopment testing, when failures occur and defects are identified and fixed, the software becomes more stable, and reliability grows over time. Therefore models that address such a process are called reliability growth models.
What Is Software Quality?
Software Development Process Models
Fundamentals of Measurement Theory
Software Quality Metrics Overview
Applying the Seven Basic Quality Tools in Software Development
Defect Removal Effectiveness
The Rayleigh Model
Exponential Distribution and Reliability Growth Models
Quality Management Models
In-Process Metrics for Software Testing
Complexity Metrics and Models
Metrics and Lessons Learned for Object-Oriented Projects
Measuring and Analyzing Customer Satisfaction
Conducting In-Process Quality Assessments
Conducting Software Project Assessments
Dos and Donts of Software Process Improvement
Using Function Point Metrics to Measure Software Process Improvements
A Project Assessment Questionnaire