Stochastic Reliability-Growth: A Model for Fault-Removal in Computer-Programs and Hardware-Designs

Abstract

An assumption commonly made in early models of software reliability is that the failure rate of a program is a constant multiple of the (unknown) number of faults remaining. This implies that all faults contribute the same amount to the failure rate of the program. The assumption is challenged and an alternative proposed. The suggested model results in earlier fault-fixes having a greater effect than later ones (the faults which make the greatest contribution to the overall failure rate tend to show themselves earlier, and so are fixed earlier), and the DFR property between fault fixes (assurance about programs increases during periods of failure-free operation, as well as at fault fixes). The model is tractable and allows a variety of reliability measures to be calculated. Predictions of total execution time to achieve a target reliability, and total number of fault fixes to target reliability, are obtained. The model might also apply to hardware reliability growth resulting from the elimination of design errors.