Theory of linear and integer programming
Theory of linear and integer programming
Some relationships between unification, restricted unification, and matching
Proc. of the 8th international conference on Automated deduction
Complexity of matching problems
Journal of Symbolic Computation
Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
The complexity of linear problems in fields
Journal of Symbolic Computation
A transformation system for deductive database modules with perfect model semantics
Theoretical Computer Science
Unfolding-definition-folding, in this order, for avoiding unnecessary variables in logic programs
PLILP '91 Selected papers of the symposium on Programming language implementation and logic programming
Transformations of CLP modules
Theoretical Computer Science
Transforming constraint logic programs
Theoretical Computer Science
A Transformation System for Developing Recursive Programs
Journal of the ACM (JACM)
A Unification Algorithm for Associative-Commutative Functions
Journal of the ACM (JACM)
Proving properties of constraint logic programs by eliminating existential variables
ICLP'06 Proceedings of the 22nd international conference on Logic Programming
A Folding Rule for Eliminating Existential Variables from Constraint Logic Programs
Fundamenta Informaticae - Advances in Computational Logic (CIL C08)
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The existential variables of a clause in a constraint logic program are the variables which occur in the body of the clause and not in its head. The elimination of these variables is a transformation technique which is often used for improving program efficiency and verifying program properties. We consider a folding transformation rule which ensures the elimination of existential variables and we propose an algorithm for applying this rule in the case where the constraints are linear inequations over rational or real numbers. The algorithm combines techniques for matching terms modulo equational theories and techniques for solving systems of linear inequations. We show that an implementation of our folding algorithm performs well in practice.