Derivational Complexity and Context-Sensitive Rewriting.

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Title: Derivational Complexity and Context-Sensitive Rewriting.
Authors: Lucas, Salvador1 slucas@dsic.upv.es
Source: Journal of Automated Reasoning. Dec2021, Vol. 65 Issue 8, p1191-1229. 39p.
Subjects: Rewriting systems (Computer science), Programming languages, Polynomials, Computational complexity, Natural numbers
Abstract: Context-sensitive rewriting is a restriction of rewriting where reduction steps are allowed on specific arguments μ (f) ⊆ { 1 , ... , k } of k-ary function symbols f only. Terms which cannot be further rewritten in this way are called μ -normal forms. For left-linear term rewriting systems (TRSs), the so-called normalization via μ -normalization procedure provides a systematic way to obtain normal forms by the stepwise computation and combination of intermediate μ -normal forms. In this paper, we show how to obtain bounds on the derivational complexity of computations using this procedure by using bounds on the derivational complexity of context-sensitive rewriting. Two main applications are envisaged: Normalization via μ -normalization can be used with non-terminating TRSs where the procedure still terminates; on the other hand, it can be used to improve on bounds of derivational complexity of terminating TRSs as it discards many rewritings. [ABSTRACT FROM AUTHOR]
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Abstract:Context-sensitive rewriting is a restriction of rewriting where reduction steps are allowed on specific arguments μ (f) ⊆ { 1 , ... , k } of k-ary function symbols f only. Terms which cannot be further rewritten in this way are called μ -normal forms. For left-linear term rewriting systems (TRSs), the so-called normalization via μ -normalization procedure provides a systematic way to obtain normal forms by the stepwise computation and combination of intermediate μ -normal forms. In this paper, we show how to obtain bounds on the derivational complexity of computations using this procedure by using bounds on the derivational complexity of context-sensitive rewriting. Two main applications are envisaged: Normalization via μ -normalization can be used with non-terminating TRSs where the procedure still terminates; on the other hand, it can be used to improve on bounds of derivational complexity of terminating TRSs as it discards many rewritings. [ABSTRACT FROM AUTHOR]
ISSN:01687433
DOI:10.1007/s10817-021-09603-1