Quality-aware Approach for Engineering Self-adaptive Software Systems
This work addresses challenges in engineering self-adaptive software systems to reduce manual maintenance costs, but it appears incremental as it builds on existing methods like Case-based Reasoning.
The paper tackles the problem of managing complexity and uncertainty in self-adaptive software systems by proposing an approach using Case-based Reasoning and utility functions, resulting in improved quality through efficient adaptation space management and handling of run-time uncertainty.
Self-adaptivity allows software systems to autonomously adjust their behavior during run-time to reduce the cost complexities caused by manual maintenance. In this paper, an approach for building an external adaptation engine for self-adaptive software systems is proposed. In order to improve the quality of self-adaptive software systems, this research addresses two challenges in self-adaptive software systems. The first challenge is managing the complexity of the adaptation space efficiently and the second is handling the run-time uncertainty that hinders the adaptation process. This research utilizes Case-based Reasoning as an adaptation engine along with utility functions for realizing the managed system's requirements and handling uncertainty.