Design-Time Validation of Runtime Reconfiguration Strategies: An Environmental-Driven Approach

Abstract

Validating the effectiveness of reconfiguration strategies of Self-Adaptive Systems (SAS) regarding their impact on runtime quality properties is a challenging problem at design time. Since quality properties, such as performance or reliability, are effectively observable at runtime, it is inherently difficult to validate reconfiguration strategies at design-time during their design (e.g., during the definition of the software architecture). Furthermore, engineering and validating SAS at design-time involves uncertainties that are difficult to manage due to a dynamic operating environment. Therefore, we propose a novel model-based analysis approach that is driven by a temporal probabilistic model which captures the stochastic nature of the operating environment. The sampled trajectories through the state space serve as a basis for validation. Software engineers benefit from the framework by validating their reconfiguration strategy regarding quality objectives before implementation. The validated strategy serves as starting point for further model-based analyses such as correctness verification of adaptation logic or scenario-based analysis for local optimization.