Towards Runtime Testing of Dynamically Adaptive Systems based on Behavioral Properties

Dynamically Adaptive Systems (DAS) support adaptations to deal with changes in the user requirements and the environments constraints at runtime. A DAS can have high dynamicity of its configurations at runtime, so a major challenge is to perform quality assurance activities. In the literature, approaches that perform runtime testing mostly uses the DAS operational context to generate test plans, then missing other relevant runtime data (e.g., violation of behavioral properties) in the process. Therefore, this master thesis proposes an approach that monitors behavioral properties and use its results to improve the selection and execution of tests at runtime. Thus, the main contribution is the identification of failures in the adaptation mechanism during the DAS execution.

Validating Autonomic Services

Autonomic service-driven applications represent a new realm of software that can discover new capabilities, automatically integrate with other systems, and adapt to changing system environmental conditions. For the past many years, researchers and practitioners have been investigating, prototyping, and evaluating these self-configuring, self-healing, self-optimizing, and self-protecting systems. Although validation is expected to play a key role in the success of autonomic systems, there are few works that address this topic. Dynamic adaptation in autonomic software results in structural and behavioral runtime changes, which cannot be validated offline at design-time. Runtime testing has therefore emerged as a possible solution to validating dynamic adaptations in autonomic software. This chapter summarizes the state-of-the-art in runtime testing of autonomic systems, describes key challenges associated with runtime testing, and provides guidelines for integrating runtime testing approaches into autonomic software using self-testing architectures. Finally, directions for future research for validation of autonomic components are discussed.

Validating Autonomic Services

Autonomic service-driven applications represent a new realm of software that can discover new capabilities, automatically integrate with other systems, and adapt to changing system environmental conditions. For the past many years, researchers and practitioners have been investigating, prototyping, and evaluating these self-configuring, self-healing, self-optimizing, and self-protecting systems. Although validation is expected to play a key role in the success of autonomic systems, there are few works that address this topic. Dynamic adaptation in autonomic software results in structural and behavioral runtime changes, which cannot be validated offline at design-time. Runtime testing has therefore emerged as a possible solution to validating dynamic adaptations in autonomic software. This chapter summarizes the state-of-the-art in runtime testing of autonomic systems, describes key challenges associated with runtime testing, and provides guidelines for integrating runtime testing approaches into autonomic software using self-testing architectures. Finally, directions for future research for validation of autonomic components are discussed.