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Equational term graph rewriting
 Fundamenta Informaticae
, 1996
"... and their applications. SMC is sponsored by the Netherlands Organization for Scientific Research (NWO). CWI is a member of ..."
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and their applications. SMC is sponsored by the Netherlands Organization for Scientific Research (NWO). CWI is a member of
Confluence of Curried TermRewriting Systems
 Journal of Symbolic Computation
, 1995
"... Reduction Systems Definition 2.2. An Abstract Reduction System (short: ARS) consists of a set A and a sequence ! i of binary relations on A, labelled by some set I. We often drop the label if I is a singleton. We write A j= P if the ARS A = (A; ! i ; : : : ); i 2 I has the property P . Further we ..."
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Reduction Systems Definition 2.2. An Abstract Reduction System (short: ARS) consists of a set A and a sequence ! i of binary relations on A, labelled by some set I. We often drop the label if I is a singleton. We write A j= P if the ARS A = (A; ! i ; : : : ); i 2 I has the property P . Further we write A j= P Q iff A j= P and A j= Q. An ARS A = (A; !) has the diamond property , A j= \Sigma, iff /;! ` !;/. It has the ChurchRosser property (is confluent), A j= CR, iff (A; !!) j= \Sigma. Given an ARS A = (A; !), we write CR(t) as shorthand for (fu j t !! ug; !) j= CR. 4 Stefan Kahrs Under most circumstances, confluence is a useful property of ARSs, mainly because: if (A; !) j= CR, and if two elements x; y 2 A are equivalent w.r.t. the smallest equivalence containing !, then there is a z 2 A such that x!! z //y. Roughly: the ARS decides the equivalence. An ARS A = (A; ! a ; ! b ) commutes directly , A j= CD, iff / a ; ! b ` ! b ; / a . To prove confluence of an ARS, it is sometimes...
COMPUGRAPH II: A Survey of Research Goals and Main Results
, 1995
"... This is a survey of the main aims and results of the ESPRIT Basic Research Working Group COMPUTING BY GRAPH TRANSFORMATION II, 1992  1996, following up the first phase of COMPUGRAPH, 1989  1992. The research goals and main results are presented within the following three research areas: Foundation ..."
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This is a survey of the main aims and results of the ESPRIT Basic Research Working Group COMPUTING BY GRAPH TRANSFORMATION II, 1992  1996, following up the first phase of COMPUGRAPH, 1989  1992. The research goals and main results are presented within the following three research areas: Foundations, Concurrency, and Graph Transformations for Specification and Programming. 1 Introduction The research area of graph grammars or graph transformations is a relatively young discipline of computer science. Its origins date back to the early seventies. Nevertheless, methods, techniques, and results from the area of graph transformations have already been studied and applied in many fields of computer science such as formal language theory, pattern recognition and generation, compiler construction, software engineering, concurrent and distributed systems modeling, database design and theory, logical and functorial programming, AI etc. This wide applicability is due to the fact that graphs ar...
Bisimilarity in Term Graph Rewriting
 INFORMATION AND COMPUTATION
, 1998
"... We present a survey of confluence properties of (acyclic) term graph rewriting. Results and counterexamples are given for different kinds of term graph rewriting: besides plain applications of rewrite rules, extensions with the operations of collapsing and copying, and with both operations togethe ..."
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We present a survey of confluence properties of (acyclic) term graph rewriting. Results and counterexamples are given for different kinds of term graph rewriting: besides plain applications of rewrite rules, extensions with the operations of collapsing and copying, and with both operations together are considered. Collapsing and copying together constitute bisimilarity of term graphs. We establish sufficient conditions forand counterexamples toconfluence, confluence modulo bisimilarity and the ChurchRosser property modulo bisimilarity. Moreover, we address rewriting modulo bisimilarity, that is, rewriting of bisimilarity classes of term graphs.
Conditional Term Graph Rewriting
 In Proceedings of the 6th International Conference on Algebraic and Logic Programming
, 1997
"... . For efficiency reasons, term rewriting is usually implemented by graph rewriting. It is known that graph rewriting is a sound and complete implementation of (almost) orthogonal term rewriting systems; see [BEG + 87]. In this paper, we extend the result to properly oriented orthogonal conditional ..."
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. For efficiency reasons, term rewriting is usually implemented by graph rewriting. It is known that graph rewriting is a sound and complete implementation of (almost) orthogonal term rewriting systems; see [BEG + 87]. In this paper, we extend the result to properly oriented orthogonal conditional systems with strict equality. In these systems extra variables are allowed in conditions and righthand sides of rules. 1 Introduction Attempts to combine the functional and logic programming paradigms have recently been receiving increasing attention; see [Han94b] for an overview of the field. It has been argued in [Han95] that strict equality is the only sensible notion of equality for possibly nonterminating programs. In this paper, we adopt this point of viewso every functional logic program is regarded as an orthogonal conditional term rewriting system (CTRS) with strict equality. The standard operational semantics for functional (or equational) logic programming is conditional narr...
Describing systems of processes by means of highlevel replacement
 IN EHRIG ET AL
"... Graphs and graph transformations are natural means to describe systems of processes. Graphs represent structure of the system, and graph rewriting rules model dynamic behaviour. In this chapter, we illustrate the technique by describing Petri nets, statecharts, parallel logic programming, and system ..."
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Graphs and graph transformations are natural means to describe systems of processes. Graphs represent structure of the system, and graph rewriting rules model dynamic behaviour. In this chapter, we illustrate the technique by describing Petri nets, statecharts, parallel logic programming, and systems of processes. Whereas description of Petri nets is based on usual graphs, statecharts lead us to hierarchical graphs, and parallel logic programming needs jungles. Finally, we combine different approaches to describe systems of processes. Topological structure is represented by a hypergraph. Local states and communication channels correspond to nodes that are labelled with parts of a global jungle playing the role of a shared data structure. The formal model takes advantage of commacategory approach allowing to change both the structure of graph and the contents of nodes consistently and to treat different graph structures as well as different labelling mechanisms in
DoublePushout Hypergraph Rewriting through Free Completions
, 1996
"... A relationship between doublepushout rewriting of total and partial hypergraphs is established by means of free completions. Given a doublepushout transformation rule P of total hypergraphs, a corresponding doublepushout transformation rule P 0 of partial subhypergraphs can be found a priori su ..."
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A relationship between doublepushout rewriting of total and partial hypergraphs is established by means of free completions. Given a doublepushout transformation rule P of total hypergraphs, a corresponding doublepushout transformation rule P 0 of partial subhypergraphs can be found a priori such that doublepushout derivations by the application of P are free completions of doublepushout derivations by the application of P 0 . It allows a more efficient doublepushout rewriting of total hypergraphs by rewriting suitable partial hypergraphs and freely completing the resulting partial hypergraphs. The main results in this paper are actually established in the more general setting of hierarchical unary algebras. 1 Introduction The algebraic approach to graph transformation, both in doublepushout and singlepushout form, has evolved in the last few years from the transformation of total structures (i.e., graphs, hypergraphs, algebras) to the transformation of partial structures ...
Unification, Rewriting, and Narrowing on Term Graphs
 Electronic notes in Theoretical Computer Science 1
, 1995
"... The concept of graph substitution recently introduced by the authors is applied to term graphs, yielding a uniform framework for unification, rewriting, and narrowing on term graphs. The notion of substitution allows definitions of these concepts that are close to the corresponding definitions in th ..."
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The concept of graph substitution recently introduced by the authors is applied to term graphs, yielding a uniform framework for unification, rewriting, and narrowing on term graphs. The notion of substitution allows definitions of these concepts that are close to the corresponding definitions in the term world. The rewriting model obtained in this way is equivalent to "collapsed tree rewriting" and hence is complete for equational deduction. For term graph narrowing, a completeness result is established which corresponds to Hullot's classical result for term narrowing. The general motivation for using term graphs instead of terms is to improve efficiency: sharing common subterms saves space and avoids the repetition of computations. 1 Introduction In [8] we introduced graph substitutions by using hyperedges as graph variables and hyperedge replacement to substitute graphs for variables. Graph unification, graph matching and substitutionbased graph rewriting were introduced and studi...
Modularity of Termination for Disjoint Term Graph Rewrite Systems: A Simple Proof
 Bulletin of the European Association for Theoretical Computer Science
, 1998
"... Introduction It is wellknown that termination is not modular for disjoint term rewriting systems (TRSs). In Toyama's counterexample the combination of the terminating systems R 1 = fF (0; 1; x) ! F (x; x; x)g, and R 2 = fg(x; y) ! x; g(x; y) ! yg yields a nonterminating system because there ..."
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Introduction It is wellknown that termination is not modular for disjoint term rewriting systems (TRSs). In Toyama's counterexample the combination of the terminating systems R 1 = fF (0; 1; x) ! F (x; x; x)g, and R 2 = fg(x; y) ! x; g(x; y) ! yg yields a nonterminating system because there is the cyclic rewrite derivation 0 1 g 1 0 + 0 1 g 0 1 g g 0 1 0 1 g 0 1 g g 0 1 F F F In the last decade, many sufficient criteria for the modularity of termination have been given; see [Mid90, Ohl94, Gra96] for an overview. For instance, termination is modular for the classes of noncollapsing and nonduplicat
Implementing βReduction by Hypergraph Rewriting
, 1995
"... The aim of this paper is to implement the fireduction in the calculus with a hypergraph rewriting mechanism called collapsed tree rewriting. It turns out that collapsed tree rewriting is sound with respect to fireduction and complete with respect to the GrossKnuth strategy. As a consequence, t ..."
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The aim of this paper is to implement the fireduction in the calculus with a hypergraph rewriting mechanism called collapsed tree rewriting. It turns out that collapsed tree rewriting is sound with respect to fireduction and complete with respect to the GrossKnuth strategy. As a consequence, there exists a normal form for a collapsed tree if and only if there exists a normal form for the represented term.