Recalibrating software reliability models

In spite of much research effort, there is no universally applicable software reliability growth model which can be trusted to give accurate predictions of reliability in all circumstances. Further, it is not even possible to decide a priori which of the many models is most suitable in a particular context. In an attempt to resolve this problem, techniques were developed whereby, for each program, the accuracy of various models can be analyzed. A user is thus enabled to select that model which is giving the most accurate reliability predicitons for the particular program under examination. One of these ways of analyzing predictive accuracy, called the u-plot, in fact allows a user to estimate the relationship between the predicted reliability and the true reliability. It is shown how this can be used to improve reliability predictions in a completely general way by a process of recalibration. Simulation results show that the technique gives improved reliability predictions in a large proportion of cases. However, a user does not need to trust the efficacy of recalibration, since the new reliability estimates prodcued by the technique are truly predictive and so their accuracy in a particular application can be judged using the earlier methods. The generality of this approach would therefore suggest that it be applied as a matter of course whenever a software reliability model is used.