An Introduction to Model Versioning

Brosch, Petra; Kappel, Gerti; Langer, Philip; Seidl, Martina; Wieland, Konrad; Wimmer, Manuel

doi:10.1007/978-3-642-30982-3_10

Cited by 51 publications

(31 citation statements)

References 73 publications

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“…There are different ways to identify an element within a model: static identitybased matching (unique identifiers), signature-based matching [30], similaritybased matching, and custom language-specific matching [10], [23]. This is needed, for example, to detect changes in a model, and to merge and compare models.…”

Section: A Path To Reach Elements In the Modeling Spacementioning

confidence: 99%

“…In a deep prediction, the strategy leverages the history of the customer to predict its consumption habits. Both approaches perform a linear regression to predict the future consumption using two scales: large (100 meters) and small (10). Results and time reduction factors are presented in the table 1.…”

Section: Kpi-2: Impact On Time Required For Exploration In Versions Amentioning

confidence: 99%

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A Native Versioning Concept to Support Historized Models at Runtime

Hartmann

Fouquet

Nain

et al. 2014

Lecture Notes in Computer Science

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Abstract. Models@run.time provides semantically rich reflection layers enabling intelligent systems to reason about themselves and their surrounding context. Most reasoning processes require not only to explore the current state, but also the past history to take sustainable decisions e.g. to avoid oscillating between states. Models@run.time and model-driven engineering in general lack native mechanisms to efficiently support the notion of history, and current approaches usually generate redundant data when versioning models, which reasoners need to navigate. Because of this limitation, models fail in providing suitable and sustainable abstractions to deal with domains relying on history-aware reasoning. This paper tackles this issue by considering history as a native concept for modeling foundations. Integrated, in conjunction with lazy load/storage techniques, into the Kevoree Modeling Framework, we demonstrate onto a smart grid case study, that this mechanisms enable a sustainable reasoning about massive historized models.

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Section: A Path To Reach Elements In the Modeling Spacementioning

confidence: 99%

Section: Kpi-2: Impact On Time Required For Exploration In Versions Amentioning

confidence: 99%

A Native Versioning Concept to Support Historized Models at Runtime

Hartmann

Fouquet

Nain

et al. 2014

Lecture Notes in Computer Science

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“…Our approach is built atop existing model versioning technologies in order to use their capabilities in identifying the differences between versions of an architectural model (e.g. [1,9,10]), and obtaining an initial merged model in which non-conflicting changes are merged (see [2] for a review of existing model merging techniques). We guide the software architects to resolve inconsistencies found in the initial merging by a combination of three methods: (a) reversing the nonconflicting changes which have been applied; (b) applying a (non-conflicting) subsets of conflicting changes; and (c) making further "new" changes to the model.…”

Section: Principlementioning

confidence: 99%

“…However, they only address structural models and do not deal with inconsistencies during the merging process. Those techniques are part of the large literature on model merging (see [2] for a recent survey and the online bibliography compiling an extensive list of relevant publications in this field [14]), on which our approach leverages to compute the differences between model versions and create an initial merged model (steps 1 & 2 in section V).…”

Section: B Correctnessmentioning

confidence: 99%

“…However, since models are complex, rich data structures of interconnected elements, traditional text-based versioning techniques and tools such as Git, Subversion, and CVS have not been successfully applied to model versioning [2]. Without adequate tool support, model merging may result in a syntactically and/or semantically inconsistent merged version.…”

Section: Introductionmentioning

confidence: 99%

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Inconsistency Resolution in Merging Versions of Architectural Models

Dam

Reder

Egyed

2014

2014 IEEE/IFIP Conference on Software Architecture

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Abstract-State-of-the-art optimistic model versioning systems, which are critical to enable efficient team-based development of architectural models, are able to detect and help resolve basic conflicts arising during the merging of model versions. However, it is often overlooked that model merging may also cause severe syntactical and semantic inconsistencies. In this paper, we propose an approach to guide the resolution of inconsistencies detected in a merged architectural model. Our approach automatically finds and presents to the software architects all solutions for resolving all inconsistencies arisen during the merging of model versions. For inconsistencies that preexist in the model, our approach is able to suggest exactly which model elements should be changed to resolve them. Our approach is built upon a repair generation which can quickly derive resolutions for an inconsistency by examining its static and dynamic structure and forming concrete repair actions from changes in the versions to be merged. An empirical validation on a range of industrial models has demonstrated that our approach is scalable to both large models and large differences between model versions.

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A Configuration Management Strategy for Modelbased Product Line Engineering in Aircraft Systems Development

Epp,

Robert,

Ruch

et al. 2024

INCOSE International Symp

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Aircraft systems development is complex and time‐consuming. Model‐based Product Line Engineering (MBPLE) aims to reuse assets between projects to accelerate the development of systems at their early stage. Despite guidance from standards, MBPLE practitioners still face the challenge of deploying an appropriate configuration management strategy. This paper presents and demonstrates a configuration management strategy to support practitioners deploying MBPLE for aircraft systems development. We developed this strategy to comply with ISO/IEC 26580 and address pending standard ambiguities using best practices from product lines for systems, software, business processes, and systems of systems. The proposed strategy supports long‐term product line evolution, management of different asset types, and independent product environments.

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An Introduction to Model Versioning

Cited by 51 publications

References 73 publications

A Native Versioning Concept to Support Historized Models at Runtime

A Native Versioning Concept to Support Historized Models at Runtime

Inconsistency Resolution in Merging Versions of Architectural Models

A Configuration Management Strategy for Modelbased Product Line Engineering in Aircraft Systems Development

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