Discrete software reliability growth models
Shioeru Yamada, Shunji Osaki · Applied Stochastic Models and Data Analysis · 1985
Abstract A general description of a discrete software reliability growth model, which adopts the number of test runs or the number of executed test cases as the unit of error detection period, is presented. Two classes of discrete software reliability growth models are proposed and discussed. These models can be described by non‐homogeneous Poisson processes, in which the random variable is denned as the number of errors detected by n test runs (n = 0, 1, 2,…). The application and comparison of these models to actual software error data are shown.