Software dependability models under memory faults with application to a digital system in nuclear power plants

In this work, software dependability under memory faults in the operational phase is predicted by two models: an analytic model and the stochastic activity network (SAN) model. The analytic model is based on the simple reliability theory and the graph theory, which represents the software as a graph composed of nodes and arcs. Through proper transformation, the graph can be reduced to a simple two-node graph from which software reliability can be derived. The SAN model permits the representation of concurrency, timeliness, fault tolerance, and degradable performance of the system and provides a means for determining the stochastic behavior of a software.Using these models, we predict the reliability of an application software in a digital system, Interposing Logic System (ILS), in a nuclear power plant and show the sensitivity of software reliability to major physical parameters which affect software failure in the normal operation phase. It is found that the effects of hardware faults on software failure should be considered for the accurate prediction of software dependability in the operation phase.