A generalized geometric de-eutrophication software-reliability model

The authors present a new software reliability model, called the lognormal proportional model (LPM). It belongs to the class of proportional models and can be viewed as a Bayes generalization of Moranda´s geometric de-eutrophication model or deterministic proportional model (DPM). It is based on the idea that the modeling of software improvement should be stochastic rather than deterministic. The LPM appears to be a variance components linear model that leads to the computation of several estimators of the parameters. The authors present a statistical test to compare the goodness-of-fit of the general LPM and the DPM, for a given realization of the failure process. An application to actual software failure data is briefly described. The LPM fits most data sets better than the DPM. This emphasizes the great variability of most software reliability data