Term graph rewriting

Barendregt, Henk; Eekelen, M.C.J.D. van; Glauert, John; Kennaway, Richard; Plasmeijer, M.J.; Sleep, M. R.

doi:10.1007/3-540-17945-3_8

Cited by 211 publications

(141 citation statements)

References 4 publications

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“…Several definitions of graph rewriting are available, using different kinds of graphs and rewriting rules (see, for instance, [14,22,9,35,10,27]). In this paper we consider port graph rewriting systems [1,3,4], of which interaction nets [27] are a particular case.…”

Section: Background: Port Graph Rewritingmentioning

confidence: 99%

A Strategy Language for Graph Rewriting

Fernández¹,

Kirchner²,

Namet³

2012

Logic-Based Program Synthesis and Transformation

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Abstract. We give a formal semantics for a graph-based programming language, where a program consists of a collection of graph rewriting rules, a user-defined strategy to control the application of rules, and an initial graph to be rewritten. The traditional operators found in strategy languages for term rewriting have been adapted to deal with the more general setting of graph rewriting, and some new constructs have been included in the language to deal with graph traversal and management of rewriting positions in the graph. This language is part of the graph transformation and visualisation environment PORGY.

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Section: Background: Port Graph Rewritingmentioning

confidence: 99%

A Strategy Language for Graph Rewriting

Fernández¹,

Kirchner²,

Namet³

2012

Logic-Based Program Synthesis and Transformation

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“…It uses both unification and matching constraints, leading to a term-graph representation in an equational style. This calculus is more general than classical term graph rewriting [18,3], which can be simulated in it. We feel that our work can serve as a first basis for creating a reduction system for a proof assistant based on the ρ g -calculus.…”

Section: Related Workmentioning

confidence: 99%

A Single-Step Term-Graph Reduction System for Proof Assistants

Mol

Eekelen

Plasmeijer

2008

Applications of Graph Transformations With Industrial Relevance

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Abstract. In this paper, we will define a custom term-graph reduction system for a simplified lazy functional language. Our custom system is geared towards flexibility, which is accomplished by leaving the choice of redex free and by making use of single-step reduction. It is therefore more suited for formal reasoning than the well-established standard reduction systems, which usually fix a single redex and realize multi-step reduction only. We will show that our custom system is correct with respect to the standard systems, by proving that it is confluent and allows standard lazy functional evaluation as a possible reduction path. Our reduction system is used in the foundation of Sparkle. Sparkle is the dedicated proof assistant for Clean, a lazy functional programming language based on term-graph rewriting. An important reasoning step in Sparkle is the replacement of an expression with one of its reducts. The flexibility of our underlying reduction mechanism ensures that as many reduction options as possible are available for this reasoning step, which improves the ease of reasoning. Because our reduction system is based on a simplified lazy functional language, our results can be applied to any other functional language based on term-graph rewriting as well.

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“…In TGRS's, such duplications are avoided by c o pying references t o t h e objects instead o f c o p ying the objects themselves. Term g r aph rewrite systems have been introduced in Barendregt et al (1987), see also Barendsen and Smetsers (1994). The objects in TGRS's are directed graphs in which each node is labelled with a symbol.…”

Section: Term Graph Rewritingmentioning

confidence: 99%

“…Instead of using drawings, or 4-tuples (see Barendregt et al (1987) and Barendsen and Smetsers (1994)), we specify graphs in an equational style (cf. Barendregt e t a l. (1987), Ariola and Klop (1996)).…”

Section: Term Graph Rewritingmentioning

confidence: 99%

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Graph rewriting semantics for functional programming languages

Eekelen

Smetsers

Plasmeijer

1997

Computer Science Logic

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Abstract. The lambda calculus forms without any q uestion *the* theoretical backbone o f f u n ctional programming languages. For the design and implementation of the lazy functional language Concurrent C l e a n w e have used a related computational model: Term Graph Rewriting Systems (TGRS's). T h is paper wraps up our main conclusions after 10 years of experience with graph rewriting semantics for functional programming languages. TGRS's are not a direct extension of the l a m bdacalculus, so one sometimes has to re-establish known theoretical results. But T G R S 's are that much closer to the world of functional programming t h at its use has been proven to be very worthwhile. In TGRS's functions h a ve names, there are constants, pattern matching and one can choose to either share expressions or copy t h e m . Graph reduction very accurately models the essential behaviour o f m ost implementations of functional languages and therefore it forms a g o o d base for reasoning about reduction properties as well as the time and space consumption of functional applications. With uniqueness typing important information can be derived for ecient i m plementation and for purely functional interfacing w i t h i m perative programs.

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Term graph rewriting

Cited by 211 publications

References 4 publications

A Strategy Language for Graph Rewriting

A Strategy Language for Graph Rewriting

A Single-Step Term-Graph Reduction System for Proof Assistants

Graph rewriting semantics for functional programming languages

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