Semantic-based Analysis of Rules for Decision Support for Software Maintenance

Abstract

Decision support systems assist users in making suitable and competent decisions regarding variety of issues. They embed knowledge about facts and features related to topics that are subjects of decision-making processes and use this knowledge to identify most appropriate alternatives. Representation of knowledge could take multiple forms. Quite often, if-then rules are used, as they are perceived as one of the easiest ways of capturing knowledge. In general, multiple methods can be employed to construct rulessome of them are fully depended on the experts' knowledge, some on available data, yet some on a combination of both approaches. The paper introduces a methodology for identifying most suitable and representative if-then rules. Semanticbased analysis of these rules is described. All rules are evaluated based on their classification performance, as well as their ability to represent knowledge. This constitutes a step towards an automatic construction of rule-based decision-making systems.