Designing a Testing Strategy for Expert Systems

Testing programs with tractable algorithms is one area in which software engineers have made numerous advances over the past few decades. Testing rule-based expert systems, however, is a new area in software engineering which requires new testing techniques. For the most part, traditional software engineering testing strategies assume modular program development. This is assumption impractical to make for expert system development, for the knowledge base of an expert system is quite simply a huge non-modular program. It consists almost entirely of non-ordered, multi-branching decision statements. In traditional programming, the module interfaces are limited and well defined. For rule-based expert systems, the interaction among rules is combinatoric and highly data-driven. Thus, the testing of a completed expert system via traditional path analysis is impractical. The design of a testing strategy for expert systems focuses on the generic phases of expert system development. Briefly, these phases include system definition, incremental system implementation, and system maintenance. Using this simplified breakdown of the expert system development process as a guide, certain testing techniques can be generalized enough to work for any expert system application.