A collection operator for graph transformation

Grønmo, Roy; Krogdahl, Stein; Møller-Pedersen, Birger

doi:10.1007/s10270-011-0190-3

Cited by 6 publications

(3 citation statements)

References 31 publications

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“…The GReAT tool can use a group operator to apply delete, move or copy operations to each match of a rule [27]. A related conceptual approach aiming at transforming collections of similar subgraphs is presented in [28] by Grønmo et al The main conceptual difference is that we amalgamate rule instances whereas Grønmo et al replace all collection operators (multi-objects) in a rule by the mapped number of [29] where cloned nodes roughly correspond to multi-objects. Moreover, the graph transformation tools PROGRES [30] and FuJaBA [31] feature so-called set nodes which can be duplicated as often as necessary.…”

Section: Related Workmentioning

confidence: 99%

Formal foundation of consistent EMF model transformations by algebraic graph transformation

2011

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Model transformation is one of the key activities in model-driven software development. An increasingly popular technology to define modeling languages is provided by the Eclipse Modeling Framework (EMF). Several EMF model transformation approaches have been developed, focusing on different transformation aspects. To validate model transformations with respect to functional behavior and correctness, a formal foundation is needed. In this paper, we define consistent EMF model transformations as a restricted class of typed graph transformations using node type inheritance. Containment constraints of EMF model transformations are translated to a special kind of graph transformation rules such that their application leads to consistent transformation results only. Thus, consistent EMF model transformations behave like algebraic graph transformations and the rich theory of algebraic graph transformation can be applied to these EMF model transformations to show functional behavior and correctness. Furthermore, we propose parallel graph transformation as a suitable framework for modeling EMF model transformations with multi-object structures. Rules extended by multi-object structures can specify a flexible number of recurring structures. The actual number of recurring structures is dependent on the application context of such a rule. We illustrate our approach by selected refactorings of simplified statechart models. Finally, we discuss the implementation of our concepts in a tool environment for EMF model transformations.

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Section: Related Workmentioning

confidence: 99%

Formal foundation of consistent EMF model transformations by algebraic graph transformation

2011

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“…subgraph operators [3], collection operators [13], cloning rules [15] and set-valued transformations [10]. More recently, pattern rewriting [17] has been developed and applied in the context of chemical reactions [1].…”

Section: Related Workmentioning

confidence: 99%

How Much Are Your Geraniums? Taking Graph Conditions Beyond First Order

Rensink

2017

ModelEd, TestEd, TrustEd

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Previous work has shown how first-order logic can equivalently be expressed through nested graph conditions, also called condition trees, with surprisingly few ingredients. In this paper, we extend condition trees by adding set-based operators such as sums and products, calculated over operands that are themselves characterised by first-order logic formulas. This provides a greatly improved way to specify computations such as: given that the price of a geranium plant equals 2 per flower petal, return the average price of all geraniums with at least one flower .We claim the same level of expressive equivalence as before between (extended) condition trees and a certain class of logic formulas; we show that the latter go beyond what can be expressed in first-order logic.On the practical side, we evaluate the performance and usability of set-based operators by specifying and comparing the example geranium property, with and without set-based operators, in the graph transformation tool groove.1 Ehrig was also a leading researcher in algebraic data specification, i.e. [7]; in that capacity he was one of the founders of ACT-ONE, the data type specification language of LOTOS, the standardisation of which in [20] was one of Ed Brinksma's early scientific achievements.

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“…By contrast, the GReAT tool can use a group operator to apply delete, move or copy operations to each match of a rule (Balasubramanian et al 2007). Grønmo et al (2009) adopted a related conceptual approach, which aimed at the transformation of collections of similar subgraphs. In that work, all the collection operators (multi-objects) in a rule are replaced by the mapped number of collection match copies.…”

Section: Other Parallel Models Of Computation In Graph Transformationmentioning

confidence: 99%

Multi-amalgamation of rules with application conditions in -adhesive categories

Golas¹,

Habel²,

Ehrig³

2014

Math. Struct. Comp. Sci.

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Amalgamation is a well-known concept for graph transformations that is used to model synchronised parallelism of rules with shared subrules and corresponding transformations. This concept is especially important for an adequate formalisation of the operational semantics of statecharts and other visual modelling languages, where typed attributed graphs are used for multiple rules with nested application conditions. However, the theory of amalgamation for the double-pushout approach has so far only been developed on a set-theoretical basis for pairs of standard graph rules without any application conditions.For this reason, in the current paper we present the theory of amalgamation for$\mathcal{M}$-adhesive categories, which form a slightly more general framework than (weak) adhesive HLR categories, for a bundle of rules with (nested) application conditions. The two main results are the Complement Rule Theorem, which shows how to construct a minimal complement rule for each subrule, and the Multi-Amalgamation Theorem, which generalises the well-known Parallelism and Amalgamation Theorems to the case of multiple synchronised parallelism. In order to apply the largest amalgamated rule, we use maximal matchings, which are computed according to the actual instance graph. The constructions are illustrated by a small but meaningful running example, while a more complex case study concerning the firing semantics of Petri nets is presented as an introductory example and to provide motivation.

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A collection operator for graph transformation

Cited by 6 publications

References 31 publications

Formal foundation of consistent EMF model transformations by algebraic graph transformation

Formal foundation of consistent EMF model transformations by algebraic graph transformation

How Much Are Your Geraniums? Taking Graph Conditions Beyond First Order

Multi-amalgamation of rules with application conditions in -adhesive categories

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