The hyper-geometric distribution software reliability growth model (HGDM): precise formulation and applicability

The hyper-geometric distribution is used to estimate the number of initial faults residual in software at the beginning of the test-and-debug phase. The hyper-geometric distribution growth model (HGD model) is well suited to making estimates for the observed growth curves of the accumulated number of detected faults. The advantage of the proposed model is the applicability to all kinds of observed data. By application of a single model, exponential growth curves as well as S-shaped growth curves can be estimated. The precise formulation of the HGD model is presented. The exact relationship of this model to the NHPP Goel-Okumoto growth model and the delayed S-shaped growth model is shown. With the introduction of a variable fault detection rate, the goodness of fit of the estimated growth curve to the growth curve of real observed faults is increased significantly. Different examples of the applicability of the model to real observed data are presented