Change propagation and bidirectionality in internal transformation DSLs

Hinkel, Georg; Bürger, Erik

doi:10.1007/s10270-017-0617-6

Cited by 19 publications

(21 citation statements)

References 45 publications

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“…With regard to theoretical considerations, least change and incremental synchronization have also been actively investigated in other approaches, in particular when using lenses, e.g., [15,[31][32][33]56]. The approach by Wang et al [56] seems to be the most similar one to ours.…”

Section: Related Workmentioning

confidence: 70%

“…Various bidirectional transformation (bx) approaches [3,14] for models have been suggested to deal with model (view) synchronization and consistency. Across these different approaches the following are important research topics [13,15,26,[31][32][33]47]: incrementality, i.e., achieving runtime/complexity dependent on the size of the model change, not on the model size, and least change, i.e., keeping the resulting model as similar as possible to the original one while restoring consistency. In this work, we extend synchronization approaches based on triple graph grammars by specific repair rules to increase incrementality and efficiency and to decrease the amount of change that occurs during synchronization.…”

Section: Introductionmentioning

confidence: 99%

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Avoiding unnecessary information loss: correct and efficient model synchronization based on triple graph grammars

Fritsche

Kosiol

Schürr

et al. 2020

Int J Softw Tools Technol Transfer

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Model synchronization, i.e., the task of restoring consistency between two interrelated models after a model change, is a challenging task. Triple graph grammars (TGGs) specify model consistency by means of rules that describe how to create consistent pairs of models. These rules can be used to automatically derive further rules, which describe how to propagate changes from one model to the other or how to change one model in such a way that propagation is guaranteed to be possible. Restricting model synchronization to these derived rules, however, may lead to unnecessary deletion and recreation of model elements during change propagation. This is inefficient and may cause unnecessary information loss, i.e., when deleted elements contain information that is not represented in the second model, this information cannot be recovered easily. Short-cut rules have recently been developed to avoid unnecessary information loss by reusing existing model elements. In this paper, we show how to automatically derive (short-cut) repair rules from short-cut rules to propagate changes such that information loss is avoided and model synchronization is accelerated. The key ingredients of our rule-based model synchronization process are these repair rules and an incremental pattern matcher informing about suitable applications of them. We prove the termination and the correctness of this synchronization process and discuss its completeness. As a proof of concept, we have implemented this synchronization process in eMoflon, a state-of-the-art model transformation tool with inherent support of bidirectionality. Our evaluation shows that repair processes based on (short-cut) repair rules have considerably decreased information loss and improved performance compared to former model synchronization processes based on TGGs.

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Section: Related Workmentioning

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Avoiding unnecessary information loss: correct and efficient model synchronization based on triple graph grammars

Fritsche

Kosiol

Schürr

et al. 2020

Int J Softw Tools Technol Transfer

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show abstract

“…NMF expressions are extensible with specific incrementalized algorithms, which take preference over the generic change propagation mechanism, in order to enable user-defined optimizations. NMF has been used for bidirectional model transformations in [28][29][30]. The scalability of NMF has been studied from a model analysis perspective but not in a model transformation setting.…”

Section: Incrementality In Bidirectional Mtmentioning

confidence: 99%

Incremental execution of rule-based model transformation

Boronat

2020

Int J Softw Tools Technol Transfer

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When model transformations are used to implement consistency relations between very large models, incrementality plays a cornerstone role in detecting and resolving inconsistencies efficiently when models are updated. Given a directed consistency relation between two models, the problem studied in this work consists in propagating model changes from a source model to a target model in order to ensure consistency while minimizing computational costs. The mechanism that enforces such consistency is called consistency maintainer and, in this context, its scalability is a required non-functional requirement. State-of-the-art model transformation engines with support for incrementality normally rely on an observer pattern for linking model changes, also known as deltas, to the application of model transformation rules, in so-called dependencies, at run time. These model changes can then be propagated along an already executed model transformation. Only a few approaches to model transformation provide domain-specific languages for representing and storing model changes in order to enable their use in asynchronous, event-based execution environments. The principal contribution of this work is the design of a forward change propagation mechanism for incremental execution of model transformations, which decouples dependency tracking from change propagation using two innovations. First, the observer pattern-based model is replaced with dependency injection, decoupling domain models from consistency maintainers. Second, a standardized representation of model changes is reused, enabling interoperability with EMF-compliant tools, both for defining model changes and for processing them asynchronously. This procedure has been implemented in a model transformation engine, whose performance has been evaluated experimentally using the VIATRA CPS benchmark. In the experiments performed, the new transformation engine shows gains in the form of several orders of magnitude in the initial phase of the incremental execution of the benchmark model transformation and change propagation is performed in real time for those model sizes that are processable by other tools and, in addition, is able to process much larger models.

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“…They explain that external MTLs can only be extended ("if at all") with a specific general-purpose language (C71). Internal model transformation languages of course do not suffer from this problem since they can be extended using the host language [21,32,46].…”

Section: Extendabilitymentioning

confidence: 99%

Claimed advantages and disadvantages of (dedicated) model transformation languages: a systematic literature review

2020

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There exists a plethora of claims about the advantages and disadvantages of model transformation languages compared to general-purpose programming languages. With this work, we aim to create an overview over these claims in the literature and systematize evidence thereof. For this purpose, we conducted a systematic literature review by following a systematic process for searching and selecting relevant publications and extracting data. We selected a total of 58 publications, categorized claims about model transformation languages into 14 separate groups and conceived a representation to track claims and evidence through the literature. From our results, we conclude that: (i) the current literature claims many advantages of model transformation languages but also points towards certain deficits and (ii) there is insufficient evidence for claimed advantages and disadvantages and (iii) there is a lack of research interest into the verification of claims.

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Change propagation and bidirectionality in internal transformation DSLs

Cited by 19 publications

References 45 publications

Avoiding unnecessary information loss: correct and efficient model synchronization based on triple graph grammars

Avoiding unnecessary information loss: correct and efficient model synchronization based on triple graph grammars

Incremental execution of rule-based model transformation

Claimed advantages and disadvantages of (dedicated) model transformation languages: a systematic literature review

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