Automatic, Model-Based Software Performance Improvement for Component-based Software Designs

Formal performance prediction methods, based on queueing network models, allow evaluating software architectural designs for performance. Existing methods provide prediction results such as response times and throughputs, but do not guide the software architect on how to improve the design. We propose a novel approach to optimise the expected performance of component-based software designs by automatically generating and evaluating design alternatives. The design space spanned by different design options (e.g. available components and configuration options) is systematically explored using metaheuristic search techniques and performance-domain heuristics. The gap between applying formal performance predictions and actually improving the design of a system can thus be closed. This paper presents a formal description and a prototypical implementation of our approach with a proof-of-concept case study.