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Enriching Context-Oriented Programming with Structured Context Representation

机译：以结构化的上下文表示丰富面向上下文的编程

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Context-oriented Programming (COP) has been proposed as a new promising paradigm for programming context-aware applications in pervasive environments. However, the expressive power of the layer abstraction in current COP extensions is limited, as layers are only suitable for expressing context with boolean or nominal values and lack support for describing temporal property of context. Besides, partial methods of COP are defined only on top of each single layer but not on a combination of layers, and the behavior of an invoked method is unpredictable as it is determined by the layer activation order. In this paper, we enriches COP by replacing layers with well-structured context entries. Each context entry specifies a piece of context information as well as its temporal property, and a context is represented as a set of many context entries. Many new operations are introduced to manipulate context more conveniently. Furthermore, partial methods are now defined on the notion of situation which is expressed as a combination of multiple context entries, and the evaluation order of multiple active partial methods can be explicitly specified so that the behavior of an invoked method becomes predictable. An implementation on top of ContextJ* and experiments for evaluating it in term of time overhead are also presented in this paper.
机译：面向上下文的编程（COP）已被提议作为用于编程在普遍存在环境中的上下文感知应用程序的新有前景范例。然而，当前COP扩展中的图层抽象的表现力是有限的，因为图层仅适用于用布尔或标称值表达上下文，并且缺少描述上下文的时间属性的支持。此外，COP的部分方法仅在每个单层的顶部定义，但不在层的组合上定义，并且调用方法的行为是不可预测的，因为它由层激活顺序确定。在本文中，我们通过用结构良好的上下文条目替换图层来丰富警察。每个上下文条目指定一段上下文信息以及其时间属性，并且上下文表示为许多上下文条目。引入许多新操作以更方便地操纵上下文。此外，现在在表达为多个上下文条目的组合的情况下定义部分方法，并且可以明确地指定多个活动部分方法的评估顺序，以便调用方法的行为变得可预测。本文还介绍了上下文中ContextJ *的实验和评估它的实验。

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