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Like in regular logic programming, evaluating a goal such as <code>A(X,1)</code> requires evaluating the body of the last clause with <code>Y=1</code>. Like in regular logic programming, this in turn requires proving the goal <code>B(X,1)</code>. Contrary to regular logic programming, this also requires a constraint to be satisfied: <code>X>0</code>, the constraint in the body of the last clause.
Whether a constraint is satisfied cannot always be determined when the constraint is encountered. In this case, for example, the value of <code>X</code> is not determined when the last clause is evaluated. As a result, the constraint <code>X>0</code> is not satisfied nor violated at this point. Rather than proceeding in the evaluation of <code>B(X,1)</code> and then checking whether the resulting value of <code>X</code> is positive afterwards, the interpreter stores the constraint <code>X>0</code> and then
In general, the evaluation of a constraint logic program proceeds like for a regular logic program, but constraint encountered during evaluation are placed in a set called constraint store. As an example, the evaluation of the goal <code>A(X,1)</code> proceeds by evaluating the body of the first clause with <code>Y=1</code>; this evaluation adds <code>X>0</code> to the constraint store and requires the goal <code>B(X,1)</code> to be proved. While trying to prove this goal, the first clause is applicable, but its evaluation adds <code>X<0</code> to the constraint store. This addition makes the constraint store unsatisfiable, and the interpreter backtracks, removing the last addition from the constraint store. The evaluation of the second clause adds <code>X=1</code> and <code>Y>0</code> to the constraint store. Since the constraint store is satisfiable and no other literal is left to prove, the interpreter stops with the solution <code>X=1, Y=1</code>.
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