Title

Detecting anomalies in constraint-based systems

Keywords

Automated verification; Constraint satisfaction problem; Constraint-based systems; Constraint-directed reasoning; Software verification; Verification

Abstract

This paper addresses the problem of the automated verification of constraint-based systems. This issue has not been adequately covered in the research literature, as current expert-system verification methodologies and tools have largely focused on rule-based systems. As a result, these tools do not incorporate the methodologies necessary to verify constraint-based reasoning systems. However, there is great similarity as well as commonality of terms between rule-based systems and constraint-based systems. This suggests that verification techniques for rule-based expert systems can be successfully modified for application to constraint-based systems. The paper presents the authors' experience in verifying the internal consistency of a constraint-based reasoning system knowledge base. The approach is based on automatically identifying several anomalies in a constraint-based system knowledge base without having to execute the system. Many of these types of anomalies are derived directly or indirectly from those that are also found in traditional rule-based expert systems, but new ones specific to constraint-based systems are identified. Detection methods and possible repair strategies are discussed, and a test example is described and evaluated. © 1997 Elsevier Science Ltd. All rights reserved.

Publication Date

1-1-1997

Publication Title

Engineering Applications of Artificial Intelligence

Volume

10

Issue

3

Number of Pages

257-268

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/s0952-1976(96)00083-8

Socpus ID

0031164363 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0031164363

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