Applying MDE to the (semi-)automatic development of model transformations

Bollati, Verónica Andrea; Vara, Juan M.; Jiménez, Álvaro; Marcos, Esperanza

doi:10.1016/j.infsof.2012.11.004

Cited by 40 publications

(18 citation statements)

References 48 publications

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“…AToMPM [53] MATA [60] MeTAGeM [15] MoTif [51] MoTMoT [56] PICS [9] QVT-R [36] Schmidt [39] transML [22] VMTL Syntax transparency is exhibited by MATA [60], PICS [9] and the MTL proposed by Schmidt [39], all of which deliberately shun expressive control flow in favor of avoiding conformance breaking augmentations to the host metamodel. However, none of these approaches also address both environment and execution transparency.…”

Section: St Ent Extmentioning

confidence: 99%

“…The recent emergence of transformation primitive libraries such as T-Core [52], along with their usage for implementing existing MTLs such as MoTif [51], indicates that this implementation style is viable. Execution transparency is also addressed in the context of the systematic development of model transformations by the transML [22] and MeTAGeM [15] tools.…”

Section: St Ent Extmentioning

confidence: 99%

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VMTL: a language for end-user model transformation

2016

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Section: St Ent Extmentioning

confidence: 99%

Section: St Ent Extmentioning

confidence: 99%

VMTL: a language for end-user model transformation

2016

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“…However, the proposed diagrams use a UML heavy extension and new notations that make it difficult to integrate with the existing UML tools which are usually adopted. MeTaGen [2] proposes metamodels for transformation design and tools generate code automatically or semi automatically. The main difference between this work and ours is that it focuses on design, not considering the requirement specification level and it uses textual language for transformation specification whereas we use a profile that is a visual language.…”

Section: Related Workmentioning

confidence: 99%

On the Specification of Model Transformations through a Platform Independent Approach

Magalhães

Andrade

Maciel

2015

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-Transformations are key artifacts in the MDD (Model Driven Development) approach: a software development project can be defined through a transformation chain converting source models into target models until code, enabling development process automation. Transformations can be complex and demand software processes, languages and techniques to improve their development in order to increase reuse, portability, correctness, and so on. In this context we propose a framework to develop model transformations using MDD. This paper presents a Model Transformation Profile (MTP) defined as the domain specific language of the framework.

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“…In addition to the areas of knowledge already mentioned, the implementation of the proposed methodology for the regeneration of the user interfaces at runtime in an evolutionary way will make use of others such as cloud computing [18], big data [2] or model transformation [1]. Continued access to distributed systems and the data generated by that connection justify the use of cloud computing and big data [16].…”

Section: Introductionmentioning

confidence: 99%

Evolving Mashup Interfaces Using a Distributed Machine Learning and Model Transformation Methodology

Fernández-García

Iribarne

Corral

et al. 2015

Lecture Notes in Computer Science

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Abstract. Nowadays users access information services at any time and in any place. Providing an intelligent user interface which adapts dynamically to the users' requirements is essential in information systems. Conventionally, systems are constructed at the design time according to an initial structure and requirements. The effect of the passage of time and changes in users, applications and environment is that the systems cannot always satisfy the user's requirements. In this paper a methodology is proposed to allow mashup user interfaces to be intelligent and evolve over time by using computational techniques like machine learning over huge amounts of heterogeneous data, known as big data, and model-driven engineering techniques as model transformations. The aim is to generate new ways of adapting the interface to the user's needs, using information about user's interaction and the environment.

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Applying MDE to the (semi-)automatic development of model transformations

Cited by 40 publications

References 48 publications

VMTL: a language for end-user model transformation

VMTL: a language for end-user model transformation

On the Specification of Model Transformations through a Platform Independent Approach

Evolving Mashup Interfaces Using a Distributed Machine Learning and Model Transformation Methodology

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