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2010
ACM

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

8 years 5 months ago
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...
Anne Martens, Heiko Koziolek, Steffen Becker, Ralf
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where WOSP
Authors Anne Martens, Heiko Koziolek, Steffen Becker, Ralf Reussner
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