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Automatic Derivation of a Product Performance Model from a Software Product Line Model

机译:从软件产品线模型自动推导产品性能模型

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We propose to integrate performance analysis in the early phases of the model-driven development process for Software Product Lines (SPL). We start with a multi-view UML model of the core family assets representing the commonality and variability between different products, which we call the SPL model. We add another perspective to the SPL model, annotating it with generic performance specifications expressed in the standard UML profile MARTE, recently adopted by OMG. The runtime performance of a product is affected by factors contained in the UML model of the product (derived from the SPL model), but also by external factors depending on the implementation and execution environments. The external factors not contained in the SPL model need to be eventually represented in the performance model. In order to do so, we propose to represent the variability space of different possible implementation and execution environments through a so called "performance completion (PC) feature model". These PC features are mapped to MARTE performance-related stereotypes and attributes attached to the SPL model elements. A first model transformation realized in the Atlas Transformation Language (ATL) derives the UML model of a specific product with concrete MARTE annotations from the SPL model. A second transformation generates a Layered Queueing Network (LQN) performance model for the given product by applying an existing transformation named PUMA, developed in previous work. The proposed technique is illustrated with an e-commerce case study. A LQN model is derived for a product and the impact of different levels of secure communication channels on its performance is analyzed by using the LQN model.
机译:我们建议在模型驱动的软件产品线(SPL)开发过程的早期阶段集成性能分析。我们从核心家族资产的多视图UML模型开始,该模型代表不同产品之间的共性和可变性,我们称之为SPL模型。我们向SPL模型添加了另一个视角,并以OMG最近采用的标准UML概要文件MARTE中表示的通用性能规范对其进行了注释。产品的运行时性能受产品的UML模型(源自SPL模型)中包含的因素的影响,还受取决于实施和执行环境的外部因素的影响。 SPL模型中未包含的外部因素最终需要在性能模型中表示。为此,我们建议通过所谓的“性能完成(PC)功能模型”来表示不同可能的实现和执行环境的可变性空间。这些PC功能映射到MARTE性能相关的构造型和附加到SPL模型元素的属性。在Atlas转换语言(ATL)中实现的第一个模型转换从SPL模型获得具有具体MARTE注释的特定产品的UML模型。第二个转换通过应用在先前工作中开发的现有转换PUMA生成给定产品的分层排队网络(LQN)性能模型。电子商务案例研究说明了所提出的技术。推导了产品的LQN模型,并使用LQN模型分析了不同级别的安全通信通道对其性能的影响。

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