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Cognitive support in software reengineering based on generic fuzzy reasoning nets

机译:基于通用模糊推理网的软件再造中的认知支持

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摘要

Modernizing heavily evolved and badly documented information systems is a central software engineering problem in our current IT industry. Often, existing legacy information systems cannot simply be replaced by new systems, because they maintain legacy data of critical importance to the company's mission. Thus, reverse engineering the design documentation of such legacy systems is often a necessity. Several interactive CASE tools have been developed to support this cognitive and human-intensive process. However, practical experience indicates that their applicability is limited because they do not consider imperfect knowledge about legacy systems. Our research tries to overcome this problem by integrating reverse engineering tools with formal theories for approximate reasoning. This article makes three main contributions: it elaborates on the necessary properties that such a theory should have for successful applications to software reverse engineering, it introduces Generic Fuzzy Reasoning Nets as an example of such a theory, and it presents an example application of this theory that clearly demonstrates the benefits of the approach.
机译:在当前的IT行业中,对高度发展且记录不佳的信息系统进行现代化改造是一个主要的软件工程问题。通常,现有遗留信息系统不能简单地用新系统代替,因为它们维护着对公司使命至关重要的遗留数据。因此,经常需要对此类传统系统的设计文档进行逆向工程。已经开发了几种交互式的CASE工具来支持这种认知和人类密集的过程。但是,实践经验表明,它们的适用性受到限制,因为他们没有考虑有关遗留系统的不完善的知识。我们的研究试图通过将逆向工程工具与形式化理论进行近似推理来克服此问题。本文做出了三个主要贡献:阐述了该理论在成功应用于软件逆向工程中应具备的必要特性,以通用模糊推理网作为该理论的示例,并提供了该理论的示例应用。清楚地证明了这种方法的好处。

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