Difference and Union of Models

Alanen, Marcus; Porres, Iván

doi:10.1007/978-3-540-45221-8_2

Cited by 178 publications

(151 citation statements)

References 5 publications

(3 reference statements)

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“…Note that the anonymous Transition objects lack such labels. In this case, the objects do not have an identity, and the difference algorithm will perform structural differencing (e.g., [20]), instead of semantic, model-based differencing [1]. Figure 2 shows two additional versions of the state machine of Fig.…”

Section: Overviewmentioning

confidence: 99%

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Origin Tracking $$+$$ Text Differencing $$=$$ Textual Model Differencing

Rozen

Storm

2015

Theory and Practice of Model Transformations

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Abstract. In textual modeling, models are created through an intermediate parsing step which maps textual representations to abstract model structures. Therefore, the identify of elements is not stable across different versions of the same model. Existing model differencing algorithms, therefore, cannot be applied directly because they need to identify model elements across versions. In this paper we present Textual Model Diff (TMDIFF), a technique to support model differencing for textual languages. TMDIFF requires origin tracking during text-to-model mapping to trace model elements back to the symbolic names that define them in the textual representation. Based on textual alignment of those names, TMDIFF can then determine which elements are the same across revisions, and which are added or removed. As a result, TMDIFF brings the benefits of model differencing to textual languages.

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Section: Overviewmentioning

confidence: 99%

“…Model differencing algorithms (e.g., [1]) determine which elements are added, removed or changed between revisions of a model. A crucial aspect of such algorithms that model elements need to be identified across versions.…”

Section: Introductionmentioning

confidence: 99%

Origin Tracking $$+$$ Text Differencing $$=$$ Textual Model Differencing

Rozen

Storm

2015

Theory and Practice of Model Transformations

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“…However, these solutions suffer an abstraction level mismatch, i.e., textbased techniques cannot grasp manipulations rationale at modelling level [KPP06]. For instance, serialisation procedures could produce textually different artefacts that however contain the same information [AP03]. Consequently, a number of techniques have been introduced for detecting, storing, and visualising [BP08] the evolution at modelling level.…”

Section: Model Versioningmentioning

confidence: 99%

“…In fact, differences and conflicts between versions of a same artefact are usually detected at file-level through line-oriented text comparison. However, even if taking into account model XMI serialisations, the mismatch between text and model levels of abstraction may lead to erroneous detection of differences and hence conflicts [AP03,KPP06]. Therefore, in the latest years a number of research works have been devoted to versioning models and metamodels at the appropriate level of abstraction, advancing the state of the art in (meta)model differencing, versioning, and related co-evolution problems.…”

Section: Introductionmentioning

confidence: 99%

A Solution for Concurrent Versioning of Metamodels and Models.

Cicchetti¹,

Ciccozzi²,

Leveque³

2012

JOT

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Model-Driven Engineering has been widely recognised as a powerful paradigm for shifting the focus of software development from coding to modelling in order to cope with the rising complexity of modern systems. Models become the main artefacts in the development process and therefore undergo evolutions performed in different ways until the final implementation is produced. Moreover, modelling languages are expected to evolve too and such evolutions have to be taken into account when dealing with model versioning. Since consistency between models and related metamodels is one of the pillars on which model-driven engineering relies, evolution of models and metamodels cannot be considered as independent events in a model versioning system. This article exploits model comparison and merging mechanisms to provide a solution to the issues related to model versioning when considering metamodel and model manipulations as concurrent and even misaligned. A scenario-based description of the challenges arising from versioning of models is given and a running example is exploited to demonstrate the proposed solutions.

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“…Alanen and Porres [12] formalise a definition of union and difference of models which can form the basis of an implementation of model version control, perhaps based on XML or XMI serialisation [3] of models. One challenge to overcome is the problem of visualising model differences.…”

Section: Version Control and Model Versioningmentioning

confidence: 99%

Using a Model Merging Language for Reconciling Model Versions

Engel

Paige

Kolovos

2006

Model Driven Architecture – Foundations and Applications

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Abstract.A difficult challenge in the industrialisation of Model-Driven Development is managing different versions of models. Different versions may arise at any time during the development process, due to different individuals or teams working on different parts of the overall model. To manage these versions it is necessary to be able to identify differences and reconcile these differences in a single, integrated model. We describe the use of model merging technology for managing different versions of a model in an industrial software development process. The use of automated model merging technology is contrasted with an alternative, semi-automated approach. The contributions of model merging to helping to solve this problem are outlined.

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Difference and Union of Models

Cited by 178 publications

References 5 publications

Origin Tracking $$+$$ Text Differencing $$=$$ Textual Model Differencing

Origin Tracking $$+$$ Text Differencing $$=$$ Textual Model Differencing

A Solution for Concurrent Versioning of Metamodels and Models.

Using a Model Merging Language for Reconciling Model Versions

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