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ABSTRACT
Over the last decade, first-order constraints have been efficiently used in the constraint programming world to model many kinds of complex problems such as: scheduling, resource allocation, computer graphics and bio-informatics. Recently, a new property called "decomposability" has been introduce and many first-order theories have been proved to be decomposable: finite or infinite trees, rational and real numbers, linear dense order, ... etc. A decision procedure in the form of 5 rewriting rules has also been developed but this later can only decide if a formula without free variables is true or not in any decomposable theory T. Unfortunately, this decision procedure is not enough when we want to find the values of the free variables of any first-order constraint ϕ so that ϕ is true in any decomposable theory T. These kind of problems are generally known as first-order constraint satisfaction problems. We present in this paper not only a decision procedure but a full first-order constraint solver for any decomposable theory T. Our solver is given in the form of six rewriting rules which transform any first-order constraint (which can possibly contain free variables) into an equivalent solved formula which is either the formula true, or the formula false or a formula having at least one free variable and written in a very simple and explicit solved form. We also show the efficiency of our solver by solving complex first-order constraints containing a huge number of imbricated quantifiers and negations. This is the first full first-order constraint solver over any decomposable theory. REFERENCES
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