Cognitive support in software reengineering based on generic fuzzy reasoning nets
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. (C) 2003 Elsevier B.V. All rights reserved.
reengineering imperfect knowledge software reverse engineering computational intelligence soft computing gentric fuzzy reasoning nets