A rewrite system is called uniformly normalising if all its steps are perpetual, i.e. are such that if s → t and s has an infinite reduction, then t has one too. For such systems termination (SN) is equivalent to normalisation (WN). A well-known fact is uniform normalisation of orthogonal non-erasing term rewrite systems, e.g. the λI-calculus. In the present paper both restrictions are analysed. Orthogonality is seen to pertain to the linear part and non-erasingness to the non-linear part of rewrite steps. Based on this analysis, a modular proof method for uniform normalisation is presented which allows to go beyond orthogonality. The method is shown applicable to biclosed first- and second-order term rewrite systems as well as to a λ-calcu...
Kennaway proved the remarkable result that every (almost) orthogonal term rewriting system admits a ...
In this paper we first study the difference between Weak Normalization (WN) and Strong Normalization...
In this paper we first study the difference between Weak Normalization (WN) and Strong Normalization...
A rewrite system is called uniformly normalising if all its steps are perpetual, i.e. are such that...
We study perpetuality of reduction steps, as well as perpetuality of redexes, in orthogonal rewrite ...
Weintroduce a modular property of equational proofs, called modularity of normalization, for the un...
AbstractExplicit substitutions (ES) were introduced as a bridge between the theory of rewrite system...
AbstractCurrying is a transformation of term rewrite systems which may contain symbols of arbitrary ...
Avoiding infinite loops is one of the obstacles most computer scientists must fight. Therefore the s...
Métivier (1983) proved that every confluent and terminating rewrite system can be transformed into ...
AbstractWe study perpetuality of reduction steps, as well as perpetuality of redexes, in orthogonal ...
In this paper we first study the difference between Weak Normalization (WN) and Strong Normalization...
AbstractKennaway proved the remarkable result that every (almost) orthogonal term rewriting system a...
. Term rewriting systems play an important role in various areas, e.g. in abstract data type specifi...
AbstractIn this paper we first study the difference between Weak Normalization (WN) and Strong Norma...
Kennaway proved the remarkable result that every (almost) orthogonal term rewriting system admits a ...
In this paper we first study the difference between Weak Normalization (WN) and Strong Normalization...
In this paper we first study the difference between Weak Normalization (WN) and Strong Normalization...
A rewrite system is called uniformly normalising if all its steps are perpetual, i.e. are such that...
We study perpetuality of reduction steps, as well as perpetuality of redexes, in orthogonal rewrite ...
Weintroduce a modular property of equational proofs, called modularity of normalization, for the un...
AbstractExplicit substitutions (ES) were introduced as a bridge between the theory of rewrite system...
AbstractCurrying is a transformation of term rewrite systems which may contain symbols of arbitrary ...
Avoiding infinite loops is one of the obstacles most computer scientists must fight. Therefore the s...
Métivier (1983) proved that every confluent and terminating rewrite system can be transformed into ...
AbstractWe study perpetuality of reduction steps, as well as perpetuality of redexes, in orthogonal ...
In this paper we first study the difference between Weak Normalization (WN) and Strong Normalization...
AbstractKennaway proved the remarkable result that every (almost) orthogonal term rewriting system a...
. Term rewriting systems play an important role in various areas, e.g. in abstract data type specifi...
AbstractIn this paper we first study the difference between Weak Normalization (WN) and Strong Norma...
Kennaway proved the remarkable result that every (almost) orthogonal term rewriting system admits a ...
In this paper we first study the difference between Weak Normalization (WN) and Strong Normalization...
In this paper we first study the difference between Weak Normalization (WN) and Strong Normalization...