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Rule groupings: A software engineering approach towards verification of expert systemsCurrently, most expert system shells do not address software engineering issues for developing or maintaining expert systems. As a result, large expert systems tend to be incomprehensible, difficult to debug or modify and almost impossible to verify or validate. Partitioning rule based systems into rule groups which reflect the underlying subdomains of the problem should enhance the comprehensibility, maintainability, and reliability of expert system software. Attempts were made to semiautomatically structure a CLIPS rule base into groups of related rules that carry the same type of information. Different distance metrics that capture relevant information from the rules for grouping are discussed. Two clustering algorithms that partition the rule base into groups of related rules are given. Two independent evaluation criteria are developed to measure the effectiveness of the grouping strategies. Results of the experiment with three sample rule bases are presented.
Document ID
19910016311
Acquisition Source
Legacy CDMS
Document Type
Contractor Report (CR)
Authors
Mehrotra, Mala
(Vigyan Research Associates, Inc. Hampton, VA, United States)
Date Acquired
September 6, 2013
Publication Date
May 1, 1991
Publication Information
Publisher: NASA
Subject Category
Computer Programming And Software
Report/Patent Number
HQ91-015
NASA-CR-4372
NAS 1.26:4372
Report Number: HQ91-015
Report Number: NASA-CR-4372
Report Number: NAS 1.26:4372
Accession Number
91N25625
Funding Number(s)
PROJECT: RTOP 549-03-31-03
CONTRACT_GRANT: NAS1-18585
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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