Applications of rule-base coverage measures to expert system evaluation

Authors:
Valerie Barr
Affiliations:
Department of Computer Science, Hofstra University, Hempstead, NY
Venue:
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Year:
1997

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Abstract

Often a rule-based system is tested by checking its performance on a number of test cases with known solutions, modifying the system until it gives the correct results for all or a sufficiently high proportion of the test cases. This method cannot guarantee that the rule-base has been adequately or completely covered during the testing process. We introduce an approach to testing of rule-based systems which uses coverage measures to guide and evaluate the testing process. In addition, the coverage measures can be used to assist rule-base pruning and identification of class dependencies, and serve as the foundation for a set of test data selection heuristics. We also introduce a complexity metric for rule-bases.