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Quantitative prediction of non-functional properties, such as performance, reliability, and costs, of software architectures supports systematic software engineering. Even though there usually is a rough idea on bounds for quality of service, the exact required values may be unclear and subject to trade-o s. Designing architectures that exhibit such good trade-off between multiple quality attributes is hard. Even with a given functional design, many degrees of freedom in the software architecture (e.g., component deployment or server configuration) span a large design space. Automated approaches search the design space with multi-objective metaheuristics such as evolutionary algorithms.
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