An ontology-based framework for domain-specific modeling

Walter, Tobias; Parreiras, Fernando Silva; Staab, Steffen

doi:10.1007/s10270-012-0249-9

Cited by 43 publications

(28 citation statements)

References 34 publications

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“…A container is a standard operating environment for a component [8] , also is a composite meta-model and its model needs to be dependent on the connector. Define the container as a multivariate: Container = (ID, Conn, type, Attr), where ID is the unique identifier of the container; Conn is the set of connectors in the container; type is the type of container, Which can be divided into CPU containers, DSP containers and FPGA containers; Attr is used to describe the property information, including the type of connector, the number of each type.…”

Section: Connector Modelingmentioning

confidence: 99%

Design and Implementation of Portable Development Framework in Signal Processing Platform

Li¹,

Gao²,

Liu³

2017

dtcse

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Abstract. In order to solve the problem of the complex system, the hard development and the wide areas of high-speed signal processing platform, a portable development framework based on domain modeling is proposed. The meta-model is modeled in signal processing area and its template is designed based on Django, which can achieve the code generation automatically of software and hardware code combing with assembler file of meta-models. Finally, the framework code that connects processors into signal processing platform is automatically generated. In this paper, FPGA heartbeat package component development process as an example can verify the feasibility of the framework.

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Section: Connector Modelingmentioning

confidence: 99%

Design and Implementation of Portable Development Framework in Signal Processing Platform

Li¹,

Gao²,

Liu³

2017

dtcse

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“…Hence, using constraint solving techniques, the system proposed ways to complete a model so that it becomes a valid instance of a meta-model. In [36] the authors use ontologies in combination with domain-specific modelling, and hence can use ontology reasoners to provide reasoning services like model validation, inconsistency explanation, and services to help in the model construction phase. These approaches are not applicable in our context, since our purpose is to create a meta-model.…”

Section: Related Workmentioning

confidence: 99%

An Extensible Meta-Modelling Assistant

Mora-Segura

Pescador

Lara

et al. 2016

2016 IEEE 20th International Enterprise Distributed Object Computing Conference (EDOC)

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Meta-models play a pivotal role in Model-Driven Engineering (MDE). They are used to create domain-specific models, and to type model management operations like model transformations or code generators. However, even though creating meta-models is a common activity, it is currently mostly a manual activity, which does not profit from existing knowledge.In order to facilitate the meta-modelling task, we propose an extensible meta-modelling assistant. While primarily focussed on helping in the creation of meta-models, it can also help in creating models. The assistant permits the provision of heterogeneous data description sources (like ontologies, RDF data, XML schemas, database schemas and meta-models), and enables their uniform querying. Different kinds of queries are supported, and improved through synonym search. Query results are prioritized through sense disambiguation, can be graphically visualized, and incorporated into the (meta-)model being built.The assistant has been realized within Eclipse, and its architecture has been designed to be independent of the meta-modelling technology used. As a proof-of-concept, we show its integration within DSL-tao, a pattern-based meta-modelling tool built by our group, and two other tools developed by third-parties. The usefulness of the system is illustrated with a running example in the process modelling domain.

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“…The potential of ontology technologies applied to system engineering to formalise general modelling is outlined by Tetlow et al [37]. Walter et al [38] employ ontologies to improve the practice of domain-specific modelling. The authors develop a framework to validate models conformed to a certain domain-specific language employing ontology reasoning services (e.g.…”

Section: Related Workmentioning

confidence: 99%

Support for cross-domain composition of embedded systems using MARTE models

Vasilevskaya

Nadjm‐Tehrani

2015

SIGBED Rev.

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Abstract-Embedded systems have evolved from tailormade systems developed by specialist engineers to artefacts built from complex software/hardware components with many extrafunctional concerns. Ubiquity of embedded devices demands other facets such as security and safety to be brought to the forefront. At the same time, cost efficiency dictates building systems from reusable building blocks. However, integration of extrafunctional building blocks comes with a certain performance resource overhead that must be taken into consideration while designing resource-constraint embedded systems. This paper builds on the premise that functional models can be extended with platform modelling to help the application engineers to select the right extra-functional building blocks accounting for performance implications of their integration. We define a UML profile relating it to relevant parts of the MARTE profile in order to capture the performance analysis results for a reusable building block, and a generic notion of model-based compatibility analysis for platform models. Additionally, our approach rests on creation of ontologies to store MARTE description of hardware components, and is supported by a MagicDraw plugin developed for capturing the analysis results and performing the compatibility analysis.

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An ontology-based framework for domain-specific modeling

Cited by 43 publications

References 34 publications

Design and Implementation of Portable Development Framework in Signal Processing Platform

Design and Implementation of Portable Development Framework in Signal Processing Platform

An Extensible Meta-Modelling Assistant

Support for cross-domain composition of embedded systems using MARTE models

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