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Towards a Microservices-Based Product Line with Multi-Objective Evolutionary Algorithms

机译:面向具有多目标进化算法的基于微服务的产品线

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Microservices are small and independently deployable services. They can be developed on different platforms and communicate via lightweight protocols, what makes them highly interoperable. The interoperability between microservices, as well as their reuse and customization needs make this kind of systems adequate to constitute a Software Product Line. However, there is no automatic approach to support the designing of Microservices-Based Product Lines (MBPLs). To move towards the development of MBPLs, this work presents an approach, named MOEA4MBPL, to extract Feature Models (FMs) from a set of microservices-based systems. These FMs intent to leverage interoperability, enabling the practitioners to reason about reuse and/or customization of functionalities. The proposed approach is based on multi-objective evolutionary algorithms, optimizing three objectives, namely precision and recall of products denoted by an FM, and conformance with existing dependencies between microservices. MOEA4MBPL was evaluated with six microservices-based systems, using the algorithms NSGA-II and SPEA2. Our approach was capable of finding FMs with good trade-off values of precision and recall, satisfying all dependencies among the microservices. SPEA2 found better fronts of solutions than NSGA-II, but the latter always executed faster and could find single solutions closer to an ideal solution than the former.
机译:微服务是小型且可独立部署的服务。它们可以在不同的平台上开发并通过轻量级协议进行通信,这使它们具有高度的互操作性。微服务之间的互操作性以及它们的重用和定制需求使这种系统足以构成软件产品线。但是,没有自动的方法来支持基于微服务的产品线(MBPL)的设计。为了朝着MBPL的发展方向发展,这项工作提出了一种名为MOEA4MBPL的方法,该方法可以从一组基于微服务的系统中提取功能模型(FM)。这些FM旨在利用互操作性,使从业人员能够推理功能的重用和/或定制。所提出的方法基于多目标进化算法,优化了三个目标,即由FM表示的产品的精度和召回率,以及与微服务之间现有的依存关系的一致性。使用算法NSGA-II和SPEA2,使用六个基于微服务的系统对MOEA4MBPL进行了评估。我们的方法能够找到具有良好精度和召回率折衷值的FM,从而满足微服务之间的所有依赖关系。 SPEA2在解决方案方面比NSGA-II更好,但是后者总是执行得更快,并且可以找到比前者更接近理想解决方案的单个解决方案。

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