Stochastic reliability growth: A model with applications to computer software faults and hardware design faults

An assumption commonly made in early models of software reliability is that the failure rate of a program is a constant multiple of the number of faults remaining. This implies that all faults have the same effect upon the overall failure rate. The assumption is challenged and an alternative proposed. The suggested model results in earlier fault-fixes having a greater effect than later ones (the worst faults show themselves earlier and so are fixed earlier), and the DFR property between fault-fixes (confidence in programs increases during periods of failure-free operations, as well as at fault-fixes). The model shows a high degree of mathematical tractability, and allows a range of reliability measures to be calculated exactly. Predictions of total execution time to achieve a target reliability, and total number of fault-fixes to target reliability, are obtained. It is suggested that the model might also find applications in those hardware reliability growth situations where design errors are being eliminated.