Modelling Structural Coverage and the Number of Failure Occurrences with Non-homogeneous Markov Chains

Most software reliability growth models specify the expected number of failuresexperienced as a function of testing effort or calendar time. However, there areapproaches to model the development of intermediate factors driving failureoccurrences. This paper starts out with presenting a model framework consistingof four consecutive relationships. It is shown that a differential equationrepresenting this framework is a generalization of several finite failures categorymodels.The relationships between the number of test cases executed and expectedstructural coverage, and between expected structural coverage and the expectednumber of failure occurrences are then explored further.A non-homogeneous Markov model allowing for partial redundancy in samplingcode constructs is developed. The model bridges the gap between setupsrelated to operational testing and systematic testing, respectively. Two extensionsof the model considering the development of the number of failureoccurrences are discussed.The paper concludes with showing that the extended models fit into the structureof the differential equation presented at the beginning, which permitsfurther interpretation.