Generic and reflective graph transformations for the checking and enforcement of modeling guidelines

Amelunxen, Carsten; Legros, E.; Schürr, Andy

doi:10.1109/vlhcc.2008.4639088

Cited by 7 publications

(6 citation statements)

References 4 publications

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“…This textual language provided advanced constructs for querying (e.g., recursive graph patterns [152]), unidirectional graph transformation rules for elementary model manipulations, and complex transformation programs captured by ASMs. As further key innovation, generic and metatransformations were introduced in [142,145] which are known nowadays as higher-order transformations [8,133]. Popular graph transformation tools developed in parallel with Viatra2 included AGG [49], ATOM3 [93], FUJABA [102], GReAT [14], GrGen.Net [55], MOFLON [7], VMTS [99].…”

Section: Key Innovations and Featuresmentioning

confidence: 99%

Road to a reactive and incremental model transformation platform: three generations of the VIATRA framework

Varró

Bergmann

Hegedüs³

et al. 2016

Softw Syst Model

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The current release of VIATRA provides opensource tool support for an event-driven, reactive model transformation engine built on top of highly scalable incremental graph queries for models with millions of elements and advanced features such as rule-based design space exploration complex event processing or model obfuscation. However, the history of the VIATRA model transformation framework dates back to over 16 years. Starting as an early academic research prototype as part of the M.Sc project of the the first author it first evolved into a Prolog-based engine followed by a family of open-source projects which by now matured into a component integrated into various industrial and open-source tools and deployed over multiple technologies. This invited paper briefly overviews the evolution of the VIATRA/IncQuery family by highlighting key features and illustrating main transformation concepts along an open case study influenced by an industrial project. Software tools in systems engineeringModel-driven engineering (MDE) plays an important role in the design of critical embedded and cyber-physical systems in various application domains such as automotive, avionics or telecommunication. MDE tools aim to simultaneously improve quality and decrease costs by early validation by highlighting conceptual design flaws well before traditional testing phases in accordance with the correct-by-construction principle. Furthermore, they improve productivity of engineers by automatically synthesizing different design artifacts (source code, configuration tables, test cases, fault trees, etc.) necessitated by certification standards (like DO-178C [117], DO-330 [116] or ISO 26262[78]).Certain shares in the software tool market of systems engineering are dominated by very few industrial tools (e.g., MATLAB Simulink, Dymola, DOORS, MagicDraw) each of which typically provides advanced support for certain development stages (requirements engineering, simulation, allocation, test generation, etc). To protect their intellectual property rights, these tools are of closed nature, which implies huge tool integration costs for system integrators (such as airframers or car manufacturers). On the other hand, recent initiatives (such as PolarSys, OpenModelica) have started to promote open language standards and the systematic use of open-source software components in tools for critical systems to reduce licensing costs and risks of vendor lock-in.Certification standards of critical cyber-physical systems require that software tools used for developing such critical system are validated with the same scrutiny as the system under design by software tool qualification [87,116], especially, when no further human checking is carried out on the outputs of such tools. Software tool qualification distinguishes between design tools which, by definition, may 123

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Section: Key Innovations and Featuresmentioning

confidence: 99%

Road to a reactive and incremental model transformation platform: three generations of the VIATRA framework

Varró

Bergmann

Hegedüs³

et al. 2016

Softw Syst Model

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“…For instance, in [ALS08], transformation rules can define String parameters with the name of classes, attributes and associations which are resolved at run-time. In [VP04], the type of the objects in a rule can be variables which are also resolved at run-time.…”

Section: Related Workmentioning

confidence: 99%

Flexible Model-to-Model Transformation Templates: An Application to ATL.

Cuadrado¹,

Guerra²,

Lara³

2012

JOT

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Model transformation is one of the core techniques in ModelDriven Engineering. Many transformation languages exist nowadays, but few offer mechanisms directed to the reuse of whole transformations or transformation fragments in different contexts.Taking inspiration from generic programming, in this paper we define model transformation templates. These templates are not defined over concrete meta-models, but on so-called meta-model concepts which later can be bound to specific meta-models. The binding mechanism is flexible as it permits mapping concepts and meta-models with certain kinds of structural heterogeneities. The approach is general and can be applied to any model transformation language. In this paper we report on its application to ATL.

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“…However, the type compatibility defined in this metamodel relies on a simple notion of model types as sets of metaclasses, but without any notion of model type substitutability. Other works [30,31] study the problem of generic model transformations using a mechanism of parameterization. However, these transformations do not apply to different metamodels but to a set of related models.…”

Section: Related Workmentioning

confidence: 99%

Reusable model transformations

et al. 2010

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Model transformations written for an input metamodel may often apply to other metamodels that share similar concepts. For example, a transformation written to refactor Java models can be applicable to refactoring UML class diagrams as both languages share concepts such as classes, methods, attributes, inheritance. Deriving motivation from this example, we present an approach to make model transformations reusable such that they function correctly across several similar metamodels. Our approach relies on these principal steps: (1) We analyze a transformation to obtain an effective subset of used concepts. We prune the input metamodel of the transformation to obtain an effective input metamodel containing the effective subset. The effective input metamodel represents the true input domain of transformation. (2) We adapt a target input metamodel by weaving it with aspects such as properties derived from the effective input metamodel to ultimately make it a subtype of the effective input metamodel. The subtype property ensures that the transformation can process models conforming to the target input metamodel without any change in the transformation itself. We validate our approach by adapting well-known refactoring transformations (Encapsulate Field, Move Method, and Pull Up Method) written for an in-house domain-specific modelling language (DSML) to three different industry standard metamodels (Java, MOF, and UML).

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Generic and reflective graph transformations for the checking and enforcement of modeling guidelines

Cited by 7 publications

References 4 publications

Road to a reactive and incremental model transformation platform: three generations of the VIATRA framework

Road to a reactive and incremental model transformation platform: three generations of the VIATRA framework

Flexible Model-to-Model Transformation Templates: An Application to ATL.

Reusable model transformations

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