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首页> 外文期刊>IEICE Transactions on Information and Systems >Knowledge-Based Software Composition Using Rough Set Theory
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Knowledge-Based Software Composition Using Rough Set Theory

机译：基于粗糙集理论的基于知识的软件组合

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摘要

Software Composition is one of the major concerns in component based software development (CBSD). In this paper, we present a formal approach to construct software svs- tems from requirements models using available components. We focus on the knowledge resides in the requirements and the com- ponents in order to deal with those heterogeneous concepts. This approach consists of three steps. The first step is selecting adapt- able components to the requirements model. The requirements and the components are transformed into the form of ∑ algebra, and the component adaptability is evaluated by ∑ homomor- phism. Rough Set Theory (RST) is used to make carriers of two ∑ algebras common, which are derived from the requirements and the components. The second step is identifying the control structure of the requirements. Decision tables are used for rep- resenting the knowledge on the requirements, and RST is used to optimize the control structure. The third step is to implement the control structure as glue codes which would perform the components appropriately. This approach mainly focuses on enterprise back-office applications in this paper, however, it can be easily applied to other domains, since it assumes the require- ments to be expressed in Colored Petri Nets (CPN), and CPN can express various problem domains other than enterprise back- office applications.
机译：软件组成是基于组件的软件开发（CBSD）中的主要问题之一。在本文中，我们提出了一种使用可用组件从需求模型构建软件系统的正式方法。我们专注于知识存在于需求和组件中，以便处理那些异构概念。此方法包括三个步骤。第一步是选择适合需求模型的组件。需求和组成部分被转换成∑代数的形式，并且组件的适应性通过∑同态性进行评估。粗糙集理论（RST）用于使两个∑代数的载波通用，它们是从需求和组成部分派生而来的。第二步是确定需求的控制结构。决策表用于表示有关需求的知识，而RST用于优化控制结构。第三步是将控制结构实现为可适当执行组件的粘合代码。该方法在本文中主要针对企业后台应用程序，但是，由于它假设需要在彩色Petri网（CPN）中表达，并且CPN可以表达各种问题域，因此可以轻松地应用于其他领域。除了企业后台应用程序。

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