Multiperspective analysis and testing of expert systems

Abstract

The paper describes a technique which the author developed for testing expert systems. The technique, which he calls multiperspective testing, can be applied during both the knowledge engineering phase and the acceptance testing phase of developing an exppert system. The first step in multiperspective testing is to define a group of performance measures ('perspectives') that focus on the behavior of the knowledge base. For each such measure, the results of testing are summarized in four scores, which the author calls 'expansion,' 'detection,' 'discrimination,' and 'comprehension.' These scores have the advantage of providing more specific information about how the knowledge base should be updated or corrected.