A User-Oriented Software Reliability Model

TLDR

Reliable service can be provided in software systems even when errors exist, provided the requested service does not use defective parts, so service reliability depends on component reliability and the probabilistic distribution of component utilization, with future refinements discussed. The paper defines a user‑oriented software reliability figure of merit to measure system reliability relative to a user environment. The model uses a user profile to influence reliability, formulates a simple Markov model based on module reliabilities and inter‑module transition probabilities, and applies sensitivity analysis to identify critical modules. The developed model measures service reliability for a user community and is applied to devise cost‑effective testing strategies and estimate expected penalty costs of failures.

Abstract

A user-oriented reliability model has been developed to measure the reliability of service that a system provides to a user community. It has been observed that in many systems, especially software systems, reliable service can be provided to a user when it is known that errors exist, provided that the service requested does not utilize the defective parts. The reliability of service, therefore, depends both on the reliability of the components and the probabilistic distribution of the utilization of the components to provide the service. In this paper, a user-oriented software reliability figure of merit is defined to measure the reliability of a software system with respect to a user environment. The effects of the user profile, which summarizes the characteristics of the users of a system, on system reliability are discussed. A simple Markov model is formulated to determine the reliability of a software system based on the reliability of each individual module and the measured intermodular transition probabilities as the user profile. Sensitivity analysis techniques are developed to determine modules most critical to system reliability. The applications of this model to develop cost-effective testing strategies and to determine the expected penalty cost of failures are also discussed. Some future refinements and extensions of the model are presented.