Classification of Concrete Textual Syntax Mapping Approaches

Goldschmidt, Thomas; Becker, Steffen; Uhl, Axel

doi:10.1007/978-3-540-69100-6_12

Cited by 28 publications

(16 citation statements)

References 9 publications

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“…Bridging grammarware and modelware has received a lot of attention, especially in how to map grammar based formalisms to meta-modeling frameworks, see for instance in [8,13,22]. The use of textual representations of models is generally recognized as being beneficial for productivity and tool development [8].…”

Section: Discussion and Related Workmentioning

confidence: 99%

Model Transformation with Immutable Data

Klint

Storm

2016

Theory and Practice of Model Transformations

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Abstract.Mainstream model transformation tools operate on graph structured models which are described by class-based meta-models. In the traditional grammarware space, transformation tools consume and produce tree structured terms, which are described by some kind of algebraic datatype or grammar. In this paper we explore a functional style of model transformation using Rascal, a meta-programming language, that seamlessly integrates functional programming, flexible static typing, and syntax-based analysis and transformation. We represent metamodels as algebraic data types (ADTs), and models as immutable values conforming to those data types. Our main contributions are (a) REFS a simple encoding and API, to deal with cross references among model elements that are represented as ADTs; (b) a mapping from models to ADTs augmented with REFS; (c) evaluation of our encoding by implementing various well-known model transformations on state machines, meta-models, and activity diagrams. Our approach can be seen as a first step towards making existing techniques and tools from the modelware domain available for reuse within Rascal, and opening up Rascal's transformation capabilities for use in model driven engineering scenarios. Model Transformation with GrammarwareThere are strong analogies between modelware and grammarware, albeit that terminology is mostly disjoint. For example, in modelware, a state machine model can be described by a model described in Ecore and Ecore itself is described using the Ecore meta-model. In grammarware, a C program can be described by a grammar of the C language written in BNF notation and BNF notation itself is described by a BNF grammar. A key difference between these domains is how models are represented. In the modeling domain models and meta-models are represented and processed as mutable graphs while immutable, tree-based, representation prevails in the grammar domain. The focus of this paper is on analyzing and bridging the impedance mismatch between these graph-based and tree-based domains. This can bring various cross fertilization benefits:• The ecosystem of models and modeling tools becomes available for the grammar-based approaches, e.g., EMF 1 (including Ecore 2 and 1 See

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Section: Discussion and Related Workmentioning

confidence: 99%

Model Transformation with Immutable Data

Klint

Storm

2016

Theory and Practice of Model Transformations

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“…Finally, Object Grammars are clearly model-based: both grammars and schemas are themselves models, self-formatted and self-describing respectively. A comparative overview of systems to parse text into graph structures that conform to class-based meta-models can be found in [26].…”

Section: Discussionmentioning

confidence: 99%

“…Common to many of these languages is that references are resolved using globally unique, or hierarchically scoped names. Such names can be opaque Unique Universal Identifiers (UUIDs) to uniquely identify model elements or key attributes of the elements themselves [26]. The main difference between these approaches and Object Grammars is that Object Grammars replace the name-based strategy by allowing arbitrary paths through the model to find a referenced object.…”

Section: Grammars and Modelsmentioning

confidence: 99%

The design and implementation of Object Grammars

Storm

Cook

Loh

2014

Science of Computer Programming

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An Object Grammar is a variation on traditional BNF grammars, where the notation is extended to support declarative bidirectional mappings between text and object graphs. The two directions for interpreting Object Grammars are parsing and formatting. Parsing transforms text into an object graph by recognizing syntactic features and creating the corresponding object structure. In the reverse direction, formatting recognizes object graph features and generates an appropriate textual presentation. The key to Object Grammars is the expressive power of the mapping, which decouples the syntactic structure from the graph structure. To handle graphs, Object Grammars support declarative annotations for resolving textual names that refer to arbitrary objects in the graph structure. Predicates on the semantic structure provide additional control over the mapping. Furthermore, Object Grammars are compositional so that languages may be defined in a modular fashion. We have implemented our approach to Object Grammars as one of the foundations of the Ensō system and illustrate the utility of our approach by showing how it enables definition and composition of domain-specific languages (DSLs).

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“…More detailed and comparative overviews of most of the tools in this section and others can be found in [48] and [49].…”

Section: Related Workmentioning

confidence: 99%

Model-Based Language Engineering with EMFText

Heidenreich

Johannes

Karol

et al. 2013

Lecture Notes in Computer Science

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Abstract.Model-based techniques are in wide-spread use for the design and implementation of domain specific languages (DSLs) and their tooling. The Eclipse Modeling Framework (EMF) is a frequently used environment for model-based language engineering. With its underlying modelling language Ecore, its XML serialisation support and its versatile extensibility it provides a solid grounding for many task-specific language development tools. In this tutorial, we give an introduction to model-based language engineering using EMFText, which allows users to develop powerful textual editors for Ecore-based DSLs that are tightly integrated with the EMF.

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Classification of Concrete Textual Syntax Mapping Approaches

Cited by 28 publications

References 9 publications

Model Transformation with Immutable Data

Model Transformation with Immutable Data

The design and implementation of Object Grammars

Model-Based Language Engineering with EMFText

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