Davide Arcelli, V. Cortellessa, Mattia D’emidio, Daniele Di Pompeo
Multi-objective optimization has demonstrated, in the last few years, to be an effective paradigm to tackle different architectural problems, such as service selection, composition and deployment. In particular, multi-objective approaches for searching architectural configurations that optimize quality properties (such as performance, reliability and cost) have been introduced in the last decade. However, a relevant amount of complexity is introduced in this context when performance are considered, often due to expensive iterative generation of performance models and interpretation of results. In this paper we introduce EASIER (Evolutionary Approach for multi-objective Software archItecturE Refactoring), that is an approach for optimizing architecture refactoring based on performance and on the intensity of changes. We focus on the actionable aspects of architectural optimization, instead of merely searching over a set of alternatives. We also start to investigate on the potential influence of performance antipatterns on such process. We have implemented our approach on AEmilia ADL, so to carry out performance analysis and architecture refactoring within the same environment. We demonstrate the effectiveness and applicability of our approach through its experimentation on a case study.
在过去几年中，多目标优化已被证明是一种有效的范例，可用于解决不同的体系结构问题，例如服务选择、组合和部署。特别是，在过去十年中引入了用于搜索优化质量属性(如性能、可靠性和成本)的体系结构配置的多目标方法。然而，当考虑性能时，在这种情况下会引入相关的复杂性，这通常是由于性能模型的昂贵迭代生成和结果的解释。本文介绍了一种基于性能和变化强度对架构重构进行优化的方法，即easy (Evolutionary Approach for multi-objective Software archItecturE Refactoring)。我们关注架构优化的可操作方面，而不仅仅是在一组备选方案中搜索。我们还开始研究性能反模式对此类过程的潜在影响。我们已经在AEmilia ADL上实现了我们的方法，以便在同一环境中执行性能分析和架构重构。我们通过案例研究的实验证明了我们的方法的有效性和适用性。
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