从手段-目的分析到主动的手段-目的推理

L. Sabatucci, M. Cossentino
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引用次数: 40

摘要

自适应是开发复杂分布式软件系统的一个重要特性。处理自适应的重要方法是运行时目标模型构件。目标在整个系统生命周期中通常是不变的,但包含了允许系统在许多可选行为中做出决定的可变性点。这项工作调查了如何可能在运行时提供不包含任务的目标模型,即如何处理目标的描述,从而打破任务和目标之间的设计时联系,通常是目的分析的结果。在这个愿景中,系统将决定如何结合其可用的功能:主动手段-目的推理。这条研究路线的影响是实现一种目标导向的自适应形式,目标模型可以在运行时注入。本文还介绍了用户驱动服务自适应中间件MUSA。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From Means-End Analysis to Proactive Means-End Reasoning
Self-adaptation is a prominent property for developing complex distributed software systems. Notable approaches to deal with self-adaptation are the runtime goal model artifacts. Goals are generally invariant along the system lifecycle but contain points of variability for allowing the system to decide among many alternative behaviors. This work investigates how it is possible to provide goal models at run-time that do not contain tasks, i.e. The description of how to address goals, thus breaking the design-time tie up between Tasks and Goals, generally outcome of a means-end analysis. In this vision the system is up to decide how to combine its available Capabilities: the Proactive Means-End Reasoning. The impact of this research line is to implement a goal-oriented form of self-adaptation where goal models can be injected at runtime. The paper also introduces MUSA, a Middleware for User-driven Service self-Adaptation.
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