COPE – A Workbench for the Coupled Evolution of Metamodels and Models

Herrmannsdoerfer, Markus

doi:10.1007/978-3-642-19440-5_18

Cited by 33 publications

(50 citation statements)

References 9 publications

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“…Finally, in metamodel matching, like [4], [9], [12], versions of metamodels are compared and differences between them are used to semi-automatically infer a transformation that expresses models updates. Manual specification approach like Flock [21] is very expressive, concise, and correctness is also assured but finds difficulties with large metamodels since there is no tool support for analyzing the changes between original and evolved metamodels [22]. Operator based approaches like [13] ensure expressiveness, automaticity, and reuse [23], it was been perceived as strong in correctness, conciseness and understandability [22] but its lack is in determining which sequence of operations will produce a correct migration.…”

Section: Related Workmentioning

confidence: 99%

“…Manual specification approach like Flock [21] is very expressive, concise, and correctness is also assured but finds difficulties with large metamodels since there is no tool support for analyzing the changes between original and evolved metamodels [22]. Operator based approaches like [13] ensure expressiveness, automaticity, and reuse [23], it was been perceived as strong in correctness, conciseness and understandability [22] but its lack is in determining which sequence of operations will produce a correct migration. Analysis of existing model co-evolution approaches, and comparison results of some works [3], [24][25] has yielded guidance for defining some requirements to our approach.…”

Section: Related Workmentioning

confidence: 99%

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Hybrid Approach for Metamodel and Model Co-evolution

Anguel¹,

Amirat²,

Bounour³

2015

IFIP Advances in Information and Communication Technology

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.Evolution is an inevitable aspect which affects metamodels. When metamodels evolve, model conformity may be broken. Model co-evolution is critical in model driven engineering to automatically adapt models to the newer versions of their metamodels. In this paper we discuss what can be done to transfer models between versions of a metamodel. For this purpose we introduce hybrid approach for model and metamodel co-evolution, that first uses matching between two metamodels to discover changes and then applied evolution operators to migrate models. In this proposal, migration of models is done automatically; except, for non resolvable changes, where assistance is proposed to the users in order to co-evolve their models to regain conformity.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Hybrid Approach for Metamodel and Model Co-evolution

Anguel¹,

Amirat²,

Bounour³

2015

IFIP Advances in Information and Communication Technology

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“…Herrmannsdörfer [70]. The differences between models are not represented as models themselves, but rather as signatures, which serve as an input for an algorithm that computes the differences as operations in the EMF Modeling…”

Section: Editability Of Ecore-based Metamodels and Modelsmentioning

confidence: 99%

“…For Ecore metamodels, the most sophisticated approach is the Edapt tool by Herrmannsdörfer et al [70]. Edapt is a delta-based approach (see section 3.4), where refactoring steps to metamodels are explicitly defined by the user and recorded to generate adaptation scripts for existing models, and to estimate the impact of changes to metamodels on existing instances.…”

Section: Motivationmentioning

confidence: 99%

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Flexible views for view-based model-driven development

Bürger¹

2013

Proceedings of the 18th International Doctoral Symposium on Components and Architecture

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Modern software development faces growing size and complexity of the systems that are being developed. To cope with this complexity, several languages and modelling formalisms are used during the development of a system in order to describe it from various view points and at multiple levels of abstraction. These languages and modeling formalisms are specific to the domain of the system under development, to the paradigms that are followed, and to the developer tools being used. For example, in a component-based process, the software architecture may be defined using a component metamodel, while class diagrams are used for the object-oriented design of the system; performance and reliability models express the extra-functional properties; program code in a general-purpose programming language defines the execution semantics, and is used for the implementation of the system. Although all these artefacts follow different concepts and formalisms, they express the same system from various view points and can thus be understood as views on the system under development. The entirety of these views can be identified as a complete definition of the system. Although the usage of multiple formalisms offers the advantage that different developers can describe the system from different view points, and in languages and models that are specially designed for this purpose, it introduces the problem of fragmentation of information across heterogeneous artefacts in different formats, concepts, and languages. With increasing complexity of the systems, this makes navigation through the system description difficult for developers and other roles in the development process. Furthermore, since the concepts and formalisms are managed independently, they can share semantic overlaps, so that a piece of information about the system under i Abstract development can be expressed in several ways and contexts. For example, while a component model may be used to express the prescriptive software architecture of a system, the implementation in a general-purpose programming language also determines an implicit architecture of the system, which leads to redundancies in the system descriptions. The independent evolution of these artefacts can lead to inconsistencies, which cannot be identified automatically if the semantic correspondances between the artefacts are not modelled explicitly.View-based software development processes offer two fundamental principles of adressing this problem: While synthetic approaches integrate the information of heterogeneous models to form a complete system description, projective approaches introduce a common formalism in which all view points of the system can be represented, and generate the views from this central model. While the pure synthetic approach suffers from a quadratic increase of interdependencies between the view types, which become very numerous with a growing number of formalisms that have to be supported, the projective approach faces the problem of providing a common formalism that is ab...

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Classifying Approaches for Constructing Single Underlying Models

Meier

Werner

Klare

et al. 2020

Communications in Computer and Information Science

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Multi-view environments for software development allow different views of a software system to be defined to cover the requirements of different stakeholders. One way of ensuring consistency of overlapping information often contained in such views is to project them "on demand" from a Single Underlying Model (SUM). However, there are several ways to construct and adapt such SUMs. This paper presents four archetypal approaches and analyses their advantages and disadvantages based on several new criteria. In addition, guidelines are presented for selecting a suitable SUM construction approach for a specific project.

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COPE – A Workbench for the Coupled Evolution of Metamodels and Models

Cited by 33 publications

References 9 publications

Hybrid Approach for Metamodel and Model Co-evolution

Hybrid Approach for Metamodel and Model Co-evolution

Flexible views for view-based model-driven development

Classifying Approaches for Constructing Single Underlying Models

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