A New General Method to Generate Random Modal Formulae for Testing Decision Procedures

The recent emergence of heavily-optimized modal decision procedures has highlighted the key role of empirical testing in this domain. Unfortunately, the introduction of extensive empirical tests for modal logics is recent, and so far none of the proposed test generators is very satisfactory. To cope...

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Bibliographic Details
Published inThe Journal of artificial intelligence research Vol. 18; pp. 351 - 389
Main Authors Patel-Schneider, P. F., Sebastiani, R.
Format Journal Article
LanguageEnglish
Published San Francisco AI Access Foundation 01.01.2003
Subjects
Artificial intelligence
Decision analysis
Empirical analysis
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Summary:The recent emergence of heavily-optimized modal decision procedures has highlighted the key role of empirical testing in this domain. Unfortunately, the introduction of extensive empirical tests for modal logics is recent, and so far none of the proposed test generators is very satisfactory. To cope with this fact, we present a new random generation method that provides benefits over previous methods for generating empirical tests. It fixes and much generalizes one of the best-known methods, the random CNF_[]m test, allowing for generating a much wider variety of problems, covering in principle the whole input space. Our new method produces much more suitable test sets for the current generation of modal decision procedures. We analyze the features of the new method by means of an extensive collection of empirical tests.
ISSN:1076-9757
1076-9757
1943-5037
DOI:10.1613/jair.1166