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Managing the evolution of a software architecture at minimal cost under performance and reliability constraints

机译:在性能和可靠性约束下以最小的成本管理软件架构的发展

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Managing a software architecture after the deployment phase is a very complex task due to frequent changes in the software requirements and environment. The software architecture must evolve in order to tackle such changes. The goal of this paper is to provide support for the decisions that software architects make after deployment. This approach is based on an optimization model whose solution suggests the "best" actions to be taken according to a given change scenario (i.e., a set of new requirements that induce changes in the structural and behavioral aspects of the software architecture). The model aims to minimize the costs while keeping the reliability and the performance of the software architecture within certain thresholds. The approach has been implemented as a framework named SHEPhERd, which is composed of a UML case tool, a model builder and a model solver. We show how SHEPhERd works on a smartphone mobile application example, and we highlight its potential to drive architectural decisions through sensitivity analysis. The achieved results are compared with those obtained by two groups of (human) maintainers composed of experts and non-experts with respect to the system and the execution environment, and we show that SHEPhERd outperforms the human judgment-based approaches.
机译:由于软件需求和环境的频繁变化,在部署阶段之后管理软件体系结构是一项非常复杂的任务。为了应对这种变化,软件架构必须不断发展。本文的目的是为部署后的软件架构师的决策提供支持。该方法基于优化模型,该优化模型的解决方案建议根据给定的更改方案(即,引起软件体系结构和行为方面的更改的一组新要求)采取“最佳”措施。该模型旨在最大程度地降低成本,同时将软件体系结构的可靠性和性能保持在一定阈值内。该方法已实现为名为SHEPhERd的框架,该框架由UML案例工具,模型构建器和模型求解器组成。我们将展示SHEPhERd如何在智能手机移动应用程序示例中工作,并重点介绍其通过敏感性分析推动架构决策的潜力。将所获得的结果与由专家和非专家组成的两组(人类)维护者在系统和执行环境方面所获得的结果进行比较,并且我们证明SHEPhERd优于基于人类判断的方法。

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