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A third reformulation that can increase efficiency is the addition of redundant constrains. If the programmer knows (by whatever means) that the solution of a problem satisfies a specific constraint, they can include that constraint to cause inconsistency of the constraint store as soon as possible. For example, if it is known beforehands that the evaluation of <code>B(X)</code> will result in a positive value for <code>X</code>, the programmer may add <code>X>0</code> before any occurrence of <code>B(X)</code>. As an example, <code>A(X,Y):-B(X),C(X)</code> will fail on the goal <code>A(-2,Z)</code>, but this is only found out during the evaluation of the subgoal <code>B(X)</code>. On the other hand, if the above clause is replaced by <code>A(X,Y):-X>0,A(X),B(X)</code>, the interpreter backtracks as soon as the constraint <code>X>0</code> is added to the constraint store, which happens before the evalation of <code>B(X)</code> even starts.
==History==
Constraint logic programming was introduced by Jaffar and Lassez in 1987. They generalized the observation that the term equations and disequations of [[Prolog II]] were a specific form of constraints, and generalized this idea to arbitrary constraint languages. The first implementations of this concept were [[Prolog III]], [[CLP(R)]], and [[CHIP programming language|CHIP]].
==References==
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==See also==
*[[GNU Prolog]]
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