Usage-Based Online Testing for Proactive Adaptation of Service-Based Applications

Increasingly, service-based applications (SBAs) are composed of third-party services available over the Internet. Even if third-party services have shown to work during design-time, they might fail during the operation of the SBA due to changes in their implementation, provisioning, or the communication infrastructure. As a consequence, SBAs need to dynamically adapt to such failures during run-time to ensure that they maintain their expected functionality and quality. Ideally the need for an adaptation is proactively identified, i.e., failures are predicted before they can lead to consequences such as costly compensation and roll-back activities. Currently, approaches to predict failures are based on monitoring. Due to its passive nature, however, monitoring might not cover all relevant service executions, which can diminish the ability to correctly predict failures. In this paper we demonstrate how online testing, as an active approach, can improve failure prediction by considering a broader range of service executions. Specifically, we introduce a framework and prototypical implementation that exploits synergies between monitoring, online testing and quality prediction. For online test selection and assessment we adapt usage-based testing strategies. We experimentally evaluate the strengths of our approach in predicting the need for an adaptation of an SBA.