Using Models to Validate Unanticipated, Fine-Grained Adaptations at Runtime

An increasing number of modern software systems need to be adapted at runtime while they are still executing. It becomes crucial to validate each adaptation before it is deployed to the running system. Models are used to ease software maintenance and can, therefore, be used to manage dynamic software adaptations. For example, models are used to manage coarse-grained anticipated adaptations for self-adaptive systems. However, the need for both fine-grained and unanticipated adaptations is becoming increasingly common, and their validation is also becoming more crucial. This paper proposes an approach to validate unanticipated, fine-grained adaptations performed on models before the adaptations are deployed into the running system. The proposed approach exploits model execution where model representations of the test suites of a software system are executed. The proposed approach is demonstrated and evaluated within the Fine Grained Adaptation (FiGA) framework.