Abstract
Higher-order lazy narrowing is a general method for solving E-unification problems in theories presented as sets of rewrite rules. In this paper we study the possibility of improving the search for normalized solutions of a higher-order lazy narrowing calculus LN. We introduce a new calculus, LNff, obtained by extending LN and define an equation selection strategy S n such that LNff with strategy S n is complete. The main advantages of using LNff with strategy S n instead of LN include the possibility of restricting the application of outermost narrowing at variable position, and the computation of more specific solutions because of additional inference rules for solving flex-flex equations. We also show that for orthogonal pattern rewrite systems we can adopt an eager variable elimination strategy that makes the calculus LNff with strategy S n even more deterministic.
This work is partially supported by Grant-in-Aid for Scientific Research on Priority Areas ”Research on the Principles for Constructing Software with Evolutionary Mechanisms”, Grant-in-Aid for Scientific Research (B) 10480053, and Grant-in-Aid for Encouragement of Young Scientists 11780204, Ministry of Education, Science, Sports and Culture, Government of Japan.
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Marin, M., Ida, T., Suzuki, T. (1999). On Reducing the Search Space of Higher-Order Lazy Narrowing. In: Middeldorp, A., Sato, T. (eds) Functional and Logic Programming. FLOPS 1999. Lecture Notes in Computer Science, vol 1722. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10705424_21
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DOI: https://doi.org/10.1007/10705424_21
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