Automatically improve software architecture models for performance, reliability, and cost using evolutionary algorithms

Quantitative prediction of quality properties (i.e. extrafunctional properties such as performance, reliability, and cost) of software architectures during design supports a systematic software engineering approach. Designing architectures that exhibit a good trade-off between multiple quality criteria is hard, because even after a functional design has been created, many remaining degrees of freedom in the software architecture span a large, discontinuous design space. In current practice, software architects try to find solutions manually, which is time-consuming, can be errorprone and can lead to suboptimal designs. We propose an automated approach to search the design space for good solutions. Starting with a given initial architectural model, the approach iteratively modifies and evaluates architectural models. Our approach applies a multi-criteria genetic algorithm to software architectures modelled with the Palladio Component Model. It supports quantitative performance, reliabi...

• Type: Conference
• Year: 2010
• Where: WOSP
• Authors: Anne Martens, Heiko Koziolek, Steffen Becker, Ralf Reussner
• Keywords: Architecture, Software, Software Architectures, Software Engineering, WOSP 2010