CAC based data mining workflow to test and re-engineer software agents

Abstract

In the past couple of decades, agent-oriented technology has been arisen in order to assist in developing intelligent software that is able to solve challenging problems. Numerous methodologies for developing agent-based systems have been proposed in the literature. Though these methodologies are maturing rapidly, they emphasis only on analysis, design and implementation phase of development process. There is no complete and potential testing technique to build, verify and validate agent based system. Customer satisfaction and cost are the most important factors that a development methodology must emphasis on. So in this paper we present a re-engineering based agent oriented software development methodology to build a powerful agent based system. We also present here a Classification and Clustering (CAC) based data mining workflow to test and re-engineer an agent based system such that we achieve a customer satisfaction rating of 89% for meeting quality expectations and an average project budget variation of just 3%. Both figures are ranging far higher than industry standards. © 2012 Springer-Verlag.