Designing a software architecture that satisﬁes all quality requirements is a difﬁcult task. To determine whether the require- ments are achieved, it is necessary to quantitatively evaluate quality attributes on the architecture model. A good evaluation process should have proper answers for these questions: (1) how to feedback the evaluation results to the architecture model (i.e., improve the architecture based on the evaluation results), (2) how to analyze uncertainties in calculations, and (3) how to handle conﬂicts that may exist between the quality preferences of stakeholders. In this paper, we introduce SQME as a framework for automatic evaluation of software architecture models. The framework uses evolutionary algorithms for archi- tecture improvement, evidence theory for uncertainty handling, and EV/TOPSIS for making trade-off decisions. To validate the applicability of the framework, a case study is performed, and a software tool is developed to support the evaluation process. Keywords Software architecture · Software quality attributes · Evolutionary algorithms · Evidence theory · EV/TOPSIS 1 Introduction – Dependencies among quality attributes: software qual- ity attributes are not independent from each other, and Dealing with quality attributes such as performance, relia- there are complex relationships among them . In par- bility and security is
Software & Systems Modeling – Springer Journals
Published: May 31, 2018
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