Progressive Reliability Forecasting of Service-Oriented Software

Abstract

Reliability is an essential quality requirement for service-oriented systems. A number of models have been developed for predicting reliability of traditional software, in which code-based defects are the main concern for the causes of failures. Service-oriented software, however, shares many common characteristics with distributed systems and web applications. In addition to residual defects, the reliabilities of these types of systems can be affected by their execution context, message transmission media, and their usages. We present a case study to demonstrate that the reliability of a service varies on an hourly basis, and reliability forecasts should be recalibrated accordingly. In this study, the failure behavior of a required external service, used by a provided service, was monitored for two months to compute the initial estimates, which then continuously re-computed based on the learning of the new failure patterns. These reliabilities are integrated with the reliability of the component in the provided service. The results show that with this progressive re-calibration we provide more accurate reliability forecasts for the service.