Utilizing Criteria to Reduce a Set of Test Cases for Expert System Validation

In practice it is important to provide assurances of performance for a developed system. This can only be done if its quality can be guaranteed. Validity is one fundamental requirement to assure a system's quality. Considering the problems of Knowledge Acquisition as the first AI--Bottleneck the difficulties arising during the validation process can be considered as a second one in the commercialisation of expert systems (XPS). A complete system validation would imply the examination of all imaginable situations (cases). Such an exhaustive check would be a complete and real, but unfortunately unfeasible proof of a system's quality. Even the use of a quasi--exhaustive set of test cases (QUEST ) is impracticable due the huge cardinality of QUEST . The focus of this paper will be set on the objective of a criteria--driven reduction of a given set of test cases being a quasi--exhaustive description of the XPS's domain ([2], [3]). This reduction has to be carried out properly and without ri..