A theoretical basis for the analysis of redundant software subject to coincident errors

Abstract

Fundamental to the development of redundant software techniques fault-tolerant software, is an understanding of the impact of multiple-joint occurrences of coincident errors. A theoretical basis for the study of redundant software is developed which provides a probabilistic framework for empirically evaluating the effectiveness of the general (N-Version) strategy when component versions are subject to coincident errors, and permits an analytical study of the effects of these errors. The basic assumptions of the model are: (1) independently designed software components are chosen in a random sample; and (2) in the user environment, the system is required to execute on a stationary input series. The intensity of coincident errors, has a central role in the model. This function describes the propensity to introduce design faults in such a way that software components fail together when executing in the user environment. The model is used to give conditions under which an N-Version system is a better strategy for reducing system failure probability than relying on a single version of software. A condition which limits the effectiveness of a fault-tolerant strategy is studied, and it is posted whether system failure probability varies monotonically with increasing N or whether an optimal choice of N exists