The Effect of Program Behavior on Fault Observability

Fault observability based on the behavior of memory references is studied. Traditional studies view memory as one monolithic entity that must completely work to be considered reliable. The usage patterns of a particular program's memory are emphasized here. This paper develops a new model for the successful execution of a program taking into account the usage of the data by extending a cache memory performance model. Three variations, based on well known allocation schemes, are presented (i.e., whether the program's storage is preallocated, dynamically allocated, or constrained in allocation). This is contrasted to traditional memory reliability calculations to show that the actual mean time to failure may be more optimistic when program behavior is considered. It also develops expressions for the probability of unobserved faults. With several studies reporting correlations between increased workloads and increased failure rates, a new theory is proposed here that provides an explanation for this behavior. The model studies several program traces demonstrating that increased workloads could cause an increase of the observed failure rates in the range of 32% to 53%.