Electronic Communications of the EASST (European Association of Software Science and Technology)
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Model Instantiation and Type Checking in UMLX
Full text linkOMG's MDA initiative encourages the use of meta-model based transformations and re-usable specifications. We discuss how Graphical Transformation Notations such as UMLX reduce opportunities for errors in this programming domain
PML: a Language for Platform Modeling
No full textModeling the computational platforms is necessary to analyze the execution
characteristics of systems developed using a model-based approach.
In this paper, we introduce a novel platform modeling language: PML
that is based on (a) transformational concepts borrowed from graph
transformation languages, and (b) generative concepts from platform modeling,
like 'kernel skeleton'. PML relies on higher-level, compact constructs that
represent a special case of model transformations, and which are then used to
specify platform semantics.
The paper also illustrates how PML constructs can be compiled into lower-level
constructs of more traditional model transformational languages, such as GReAT
Using Semantic Anchoring to Verify Behavior Preservation in Graph Transformations
Full text linkGraph transformation is often used to transform domain models from one domain specific language (DSML) to another. In some cases, the DSMLs are based on a formalism that has many implementation variants, such as Statecharts. For instance, it could be necessary to transform iLogix Statechart models into Matlab Stateflow models. The preservation of behavior of the models is crucial in such transformations. Bisimulation has previously been demonstrated as an approach to verifying behavior preservation, and semantic anchoring is an approach to specifying the dynamic semantics of DSMLs. We propose a method to verify behavior preservation, using bisimulation in conjunction with semantic anchoring. We will consider two hypothetical variants of the Statecharts formalism, and specify the operational semantics of each variant by semantic anchoring, using Abstract State Machines as a common semantic framework. We then establish bisimulation properties to verify if the behavior models of the source and target Statechart models are equivalent for a particular execution of the transformation
Realizing QVT with Graph Rewriting-Based Model Transformation
Full text linkModel-based development is an increasingly applied method in producing software artifacts that is driven by model transformation. For instance, OMG's Model-Driven Architecture as a model-based approach to software development facilitates the synthesis of application programs from models created using customized, domain-specific model processors. Meta Object Facility 2.0 Query/ Views/ Transformation (QVT) is the OMG's standard for specifying model queries, views, and transformations. Extensive research of graph transformation provides a strong formal background for model transformation. The main contribution of this paper is to show how high-level constraint constructs facilitate to realize transformations specified in QVT with metamodel-based model transformation. As a result we can reuse the graph transformation constructs, and its formal background, which facilitates to make QVT transformations validated
Towards Translating Graph Transformation Approaches by Model Transformations
Full text linkRecently, many researchers are working on semantics preserving model transformation. In the field of graph transformation one can think of translating graph grammars written in one approach to a behaviourally equivalent graph grammar in another approach. In this paper we translate graph grammars developed with the GROOVE tool to AGG graph grammars by first investigating the set of core graph transformation concepts supported by both tools. Then, we define what it means for two graph grammars to be behaviourally equivalent, and for the regarded approaches we actually show how to handle different definitions of both - application conditions and graph structures. The translation itself is explained by means of intuitive examples
Incremental Graph Pattern Matching: Data Structures and Initial Experiments
Full text linkDespite the large variety of existing graph transformation tools, the implementation of their pattern matching engine typically follows the same principle. First a matching occurrence of the left-hand side of the graph transformation rule is searched by some graph pattern matching algorithm. Then potential negative application conditions are checked that might eliminate the previous occurrence. However, when a new transformation step is started, all the information on previous matchings is lost, and the complex graph pattern matching phase is restarted from scratch each time. In the paper, we present the foundational data structures and initial experiments for an incremental graph pattern matching engine which keeps track of existing matchings in an incremental way to reduce the execution time of graph pattern matching