Title

Performance Evaluation Of A Large Diagnostic Expert System Using A Heuristic Test Case Generator

Authors

Authors

A. J. Gonzalez; U. G. Gupta;R. B. Chianese

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

Eng. Appl. Artif. Intell.

Keywords

knowledge-based systems; validation and verification (V&V); heuristics; software testing; Automation & Control Systems; Computer Science, Artificial Intelligence; Engineering, Multidisciplinary; Engineering, Electrical & Electronic

Abstract

Validating the performance of a knowledge-based system is a critical step in its commercialization process. Without exception, buyers of systems intended for serious purposes require a certain level of guarantees about system performance. This is particularly true for diagnostic systems. Yet, many problems exist in the validation process, especially as it applies to large knowledge-based systems. One of the biggest challenges facing the developer when validating the system's performance is knowing how much testing is sufficient to show that the system is valid. Exhaustive testing of the system is almost always impractical due to the many possible test cases that can be generated, many of which are not useful. It would thus be highly desirable to have a means of defining a representative set of test cases that, if executed correctly by the system, would provide a high confidence in the system's validity. This paper describes the experiences of the development ream in validating the performance of a large commercial diagnostic knowledge-based system. The description covers the procedure employed to carry out this task, as well as the heuristic technique used for generating the representative set of test cases. Copyright (C) 1996 Elsevier Science Ltd

Journal Title

Engineering Applications of Artificial Intelligence

Volume

9

Issue/Number

3

Publication Date

1-1-1996

Document Type

Article

Language

English

First Page

275

Last Page

284

WOS Identifier

WOS:A1996UU56700005

ISSN

0952-1976

Share

COinS