获取和重用功能性和非功能性需求知识:目标-对象模式方法

L. Chung, Sam Supakkul
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引用次数: 37

摘要

基于模式的方法已被证明是捕获和重用过去的经验和最佳实践的有效方法,以促进沟通并缩短软件建模所需的时间。然而,目前的知识获取主要局限于功能性知识。知识重用也经常是手工的,并且仅限于低比例的小模型片段。本文提出了一个目标-对象模式框架,它捕获了使用UML和面向目标的方法建模的功能性和非功能性需求知识。此框架中的模式是模型细化方法的集合,每个方法定义目标模型中的单个模型元素生成步骤。模式是模型驱动的,因为它们是使用UML元模型定义的,然后作为模型使用。该框架还支持增量知识捕获,因为大粒度模式可以由细粒度模式组成,而且与应用程序无关的模式可以专门化为特定于应用程序的模式。该框架使用一个简化的在线书店应用程序来说明大规模重用是如何可能的
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Capturing and Reusing Functional and Non-functional Requirements Knowledge: A Goal-Object Pattern Approach
Pattern-based approach has proven to be an effective means for capturing and reusing past experience and best practices to facilitate communication and shorten the time required for software modeling. However, current knowledge capture is limited to mostly functional knowledge. Knowledge reuse is also often manual and limited to low-scale small model fragments. This paper presents a goal-object pattern framework that captures both functional and non-functional requirements knowledge that is modeled using UML and a goal-oriented method. Patterns in this framework are a collection of model refinement methods, each defining a single model element generation step in the target model. The patterns are model-driven in that they are defined using a UML metamodel and then used as such. The framework also supports incremental knowledge capture in that large-grain patterns can be composed from fine-grain ones, and also application-independent patterns can be specialized into application-specific ones. The framework is illustrated using a simplified on-line bookstore application to demonstrate how large-scale reuse may be possible
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