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Intelligent Agent Based Mapping of Software Requirement Specification to Design Model

机译:基于智能代理的软件需求规范到设计模型的映射

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Automatically mapping a requirement specification to design model in Software Engineering is an open complex problem. Existing methods use a complex manual process that use the knowledge from the requirement specification/modeling and the design, and try to find a good match between them. The key task done by designers is to convert a natural language based requirement specification (or corresponding UML based representation) into a predominantly computer language based design model—thus the process is very complex as there is a very large gap between our natural language and computer language. Moreover, this is not just a simple language conversion, but rather a complex knowledge conversion that can lead to meaningful design implementation. In this paper, we describe an automated method to map Requirement Model to Design Model and thus automate/partially automate the Structured Design (SD) process. We believe, this is the first logical step in mapping a more complex requirement specification to design model. We call it IRTDM (Intelligent Agent based requirement model to design model mapping). The main theme of IRTDM is to use some AI (Artificial Intelligence) based algorithms, semantic representation using Ontology or Predicate Logic, design structures using some well known design framework and Machine Learning algorithms for learning over time. Semantics help convert natural language based requirement specification (and associated UML representation) into high level design model followed by mapping to design structures. AI method can also be used to convert high level design structures into lower level design which then can be refined further by some manual and/or semi automated process. We emphasize that automation is one of the key ways to minimize the software cost, and is very important for all, especially, for the “Design for the Bottom 90% People” or BOP (Base of the Pyramid People).
机译:在软件工程中自动将需求规范映射到设计模型是一个开放的复杂问题。现有方法使用了复杂的手动过程,该过程利用了需求规范/建模和设计中的知识,并试图在它们之间找到良好的匹配。设计人员完成的关键任务是将基于自然语言的需求规范(或相应的基于UML的表示形式)转换为主要基于计算机语言的设计模型-因此过程非常复杂,因为我们的自然语言与计算机之间的差距非常大语言。而且,这不仅是简单的语言转换,而且是复杂的知识转换,可以导致有意义的设计实现。在本文中,我们描述了一种自动方法,将需求模型映射到设计模型,从而实现了结构化设计(SD)流程的自动化/部分自动化。我们相信,这是将更复杂的需求规范映射到设计模型的第一步。我们将其称为IRTDM(基于智能代理的需求模型到设计模型的映射)。 IRTDM的主要主题是使用一些基于AI(人工智能)的算法,使用本体论或谓词逻辑的语义表示,使用一些众所周知的设计框架的设计结构以及用于随着时间的推移进行学习的机器学习算法。语义有助于将基于自然语言的需求规范(和相关的UML表示形式)转换为高级设计模型,然后映射到设计结构。 AI方法也可以用于将高级设计结构转换为低级设计,然后可以通过一些手动和/或半自动过程进一步完善。我们强调自动化是降低软件成本的关键方法之一,对所有人都非常重要,尤其是对于“底层90%人口设计”或BOP(金字塔底层人民)而言。

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