Rule based expert systems provide a modular and uniform approach to representing knowledge, however it has been recognized that rule-based systems become increasingly difficult to understand and maintain as the number of rules grow. Expert systems today are developed on general purpose inference shells that offer general purpose paradigms which do not take into considerations the type of problems being solved. It is up to the users to create the meta level control to prevent rule interference, and for the rules to function properly. This task tends to become increasingly difficult in direct proportion to the size of the accumulated knowledge.The solution is in a new generation of Application Specific Expert System Tools that are designed with specific paradigms and knowledge representation methodology that meet the requirements of a specific domain. This concept is examplified in the work presented here that introduces a generic expert systems shell for diagnostic reasoning. Domain knowledge is represented as five different classes of objects. A paradigm for diagnostic reasoning is built into the inference algorithm to become part of the inference shell, replacing the usual general purpose forward or backward chaining algorithm.

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