Inference of monotonicity constraints in Datalog programs

Citation
A. Brodsky et Y. Sagiv, Inference of monotonicity constraints in Datalog programs, ANN MATH A, 26(1-4), 1999, pp. 29-57
Citations number
7
Categorie Soggetti
Engineering Mathematics
Journal title
ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE
ISSN journal
10122443 → ACNP
Volume
26
Issue
1-4
Year of publication
1999
Pages
29 - 57
Database
ISI
SICI code
1012-2443(1999)26:1-4<29:IOMCID>2.0.ZU;2-M
Abstract
Datalog (i.e., function-free logic) programs with monotonicity constraints on extensional predicates are considered. A monotonicity constraint states that one argument of a predicate or a constant is always less than another argument or a constant, according to some strict partial order. Relations o f an extensional database are required to satisfy the monotonicity constrai nts imposed on their predicates. More specifically, a strict partial order is defined on the domain (i.e., set of constants) of the database, and ever y tuple of each relation satisfies the monotonicity constraints imposed on its predicate. This paper focuses on the problem of entailment of monotonic ity constraints in the intensional database from monotonicity constraints i n the extensional database. The entailment problem is proven to be decidabl e, based on a suggested algorithm for computing sound and complete disjunct ions of monotonicity and equality constraints that hold in the intentional database. It is also shown that the entailment of monotonicity constraints in programs is a complete problem for exponential time. For linear programs , this problem is complete for polynomial space.