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Chapter 5
Foundation and Application of Expert System Verification and Validation

Anca I. Vermesan


CONTENTS

1. Introduction
1.1 Historical Overview and Terminology
1.2. V&V in Conventional Software and V&V of Expert Systems
2. Theoretical Foundation of Expert System Veritifcation and Validation
2.1. Logical Foundation of Rule-Based Anomalies
2.1.1. Redundancy
    2.1.2. Ambivalence
    2.1.3. Circularity
    2.1.4. Deficiency
2.2. Foundation of Object-Oriented Expert Systems
2.2.1. Subsumption
    2.2.2. Implicit Pair-Subsumption
    2.2.3. Implicit Cross-Sumsumption
    2.2.4. Circular Inference Structure
    2.2.5. Conclusions
3. Application of Expert System Verification and Validation
3.1. Components of Verification and Validation
3.2. Methods and Techniques
3.2.1. Nonmethod-Specific Techniques
    3.2.2. Method-Specific Techniques
3.3. Expert System Development Methodologies
3.4. Verification and Validation Systems
3.4.1. KRUST
    3.4.2. COVADIS
    3.4.3. IMPROVER
    3.4.4. CONKRET
    3.4.5. IN-DEPTH
    3.4.6. Conclusions
4. Industrial Requirements
4.1. Establishing a Quality Culture
4.2. Independent Verification and Validation
4.3. V&V in Support of Certification for Critical Systems
4.4. How Much V&V?
5. Research Initiatives
6. Future Trends and Summary
6.1. Hybrid Intelligent Systems
6.2. Conclusion: Current State and Open Problems
References

1. INTRODUCTION

In the current practice of producing expert systems, much effort is expended in attempting to assure that the finished system does what it is supposed to do. The spectrum of effort is quite broad: debugging and testing, symbolic execution, proofs of specification's properties, as well as systematic techniques forming parts of well-defined methodologies for expert system construction. Recently, verification and validation (V&V) of expert systems has emerged as a distinct research field.

Many examples in the literature show the need for building reliable and dependable expert systems. As these systems become more and more complex, new and efficient techniques are needed to cope with their complexity.

The purpose of this chapter is to highlight the main issues associated with the V&V of expert systems and to describe practical solutions to the problems of expert system V & V. These issues first include discussion of the terminology used and a comparison between verification and validation as found in traditional software engineering and V&V of expert systems, pointing out what is special about the latter as compared with the former. The core of this chapter will then proceed as follows: we first define the theoretical foundation of expert system verification and validation, focusing on two principal methods for knowledge representation, i.e., production rules and object representation. Then, the characteristics of expert systems that pose special problems for V&V are discussed, along with techniques and methods currently used to overcome these problems. We proceed with descriptions of several verification and validation systems, followed by industrial requirements related to V&V. Finally, we point out some current and future research initiatives and provide a summary discussion.


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