Efficient Graph Rewriting and Its Implementation

Dörr, Heiko; Leeuwen, Jan van; Hartmanis, Juris; Goos, G.

doi:10.1007/bfb0031909

Cited by 41 publications

(9 citation statements)

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“…This makes for a simple algorithm at the expense of performance. A more performance focussed implementation might use a search plan [4,21] in which a graph morphism is built incrementally by adding both nodes and edges to an existing partial morphism, back-tracking if no suitable candidate can be found.…”

Section: Discussionmentioning

confidence: 99%

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A Reference Interpreter for the Graph Programming Language GP 2

Bak¹,

Faulkner²,

Plump³

et al. 2015

Electron. Proc. Theor. Comput. Sci.

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GP 2 is an experimental programming language for computing by graph transformation. An initial interpreter for GP 2, written in the functional language Haskell, provides a concise and simply structured reference implementation. Despite its simplicity, the performance of the interpreter is sufficient for the comparative investigation of a range of test programs. It also provides a platform for the development of more sophisticated implementations.

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Section: Discussionmentioning

confidence: 99%

“…. , h k m ] that match l k with respect to label matching and rootedness 4 An environment is paired with each host node. The result is a list of lists [[h 1 1 , .…”

Section: Graph Matchingmentioning

confidence: 99%

A Reference Interpreter for the Graph Programming Language GP 2

Bak¹,

Faulkner²,

Plump³

et al. 2015

Electron. Proc. Theor. Comput. Sci.

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“…This could be useful, for example, for temporal graphs [21]; we would be interested in exploring this direction further to tackle suitable real-world applications. Another potential application area is inside graph rewriting systems [10]. Here, the pattern graphs are considered "fixed", rather than being part of the input, which has implications for the theoretical complexity of the problem.…”

Section: Future Directionsmentioning

confidence: 99%

The Glasgow Subgraph Solver: Using Constraint Programming to Tackle Hard Subgraph Isomorphism Problem Variants

McCreesh

Prosser

Trimble

2020

Lecture Notes in Computer Science

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The Glasgow Subgraph Solver provides an implementation of state of the art algorithms for subgraph isomorphism problems. It combines constraint programming concepts with a variety of strong but fast domain-specific search and inference techniques, and is suitable for use on a wide range of graphs, including many that are found to be computationally hard by other solvers. It can also be equipped with side constraints, and can easily be adapted to solve other subgraph matching problem variants. We outline its key features from the view of both users and algorithm developers, and discuss future directions.

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“…As a consequence, linear-time graph algorithms in imperative languages may be slowed down to polynomial time when they are recast as rule-based programs. To speed up matching, GP 2 supports 'rooted' graph transformation where graphs in rules and host graphs are equipped with socalled root nodes, originally developed by Dörr [41]. Roots in rules must match roots in the host graph so that matches are restricted to the neighbourhood of the host graph's roots.…”

Section: Rooted Gp 2 Programsmentioning

confidence: 99%

Improving the GP 2 Compiler

Campbell,

Romo,

Plump

2020

Preprint

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GP 2 is an experimental programming language based on graph transformation rules which aims to facilitate program analysis and verification. Writing efficient programs in such a language is hard because graph matching is expensive, however GP 2 addresses this problem by providing rooted rules which, under mild conditions, can be matched in constant time using the GP 2 to C compiler. In this report, we document various improvements made to the compiler; most notably the introduction of node lists to improve iteration performance for destructive programs, meaning that binary DAG recognition by reduction need only take linear time where the previous implementation required quadratic time.

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Efficient Graph Rewriting and Its Implementation

Cited by 41 publications

References 0 publications

A Reference Interpreter for the Graph Programming Language GP 2

A Reference Interpreter for the Graph Programming Language GP 2

The Glasgow Subgraph Solver: Using Constraint Programming to Tackle Hard Subgraph Isomorphism Problem Variants

Improving the GP 2 Compiler

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