Analyzing model evolution

Wenzel, Sven; Kelter, Udo

doi:10.1145/1368088.1368214

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…Wenzel et al [19] present a view that the evolution history of models can be traced into modelling elements and visualise the change metrics. When large amounts of data are being processed, again it is important to be able to extract the relevant information to compare with each other.…”

Section: Threats To Validitymentioning

confidence: 99%

Specifying and detecting meaningful changes in programs

Tun

Nuseibeh

2011

2011 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011)

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Section: Threats To Validitymentioning

confidence: 99%

Specifying and detecting meaningful changes in programs

Tun

Nuseibeh

2011

2011 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011)

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“…Sriplakich et al [9] identify simple changes in terminal models conforming to any metamodel. Wenzel et al [10] present an approach which discovers fine-grained traces between versions of modeling languages, e.g., UML models, schemas, web service description languages, and domain specific languages. The EMF Compare tool [11] reports simple changes between terminal model pairs or metamodel pairs.…”

Section: Related Workmentioning

confidence: 99%

“…Similarly to [10][18], our approach computes equivalences and differences between any pair of metamodels (e.g., representing schemas, UML models, ontologies, grammars) . 2.…”

Section: Related Workmentioning

confidence: 99%

Managing Model Adaptation by Precise Detection of Metamodel Changes

Garcés

Jouault

Cointe

et al. 2009

Lecture Notes in Computer Science

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Abstract. Technological and business changes influence the evolution of software systems. When this happens, the software artifacts may need to be adapted to the changes. This need is rapidly increasing in systems built using the Model-Driven Engineering (MDE) paradigm. An MDE system basically consists of metamodels, terminal models, and transformations. The evolution of a metamodel may render its related terminal models and transformations invalid. This paper proposes a three-step solution that automatically adapts terminal models to their evolving metamodels. The first step computes the equivalences and (simple and complex) changes between a given metamodel, and a former version of the same metamodel. The second step translates the equivalences and differences into an adaptation transformation. This transformation can then be executed in a third step to adapt to the new version any terminal model conforming to the former version. We validate our ideas by implementing a prototype based on the AtlanMod Model Management Architecture (AMMA) platform. We present the accuracy and performance that the prototype delivers on two concrete examples: a Petri Net metamodel from the research literature, and the Netbeans Java metamodel.

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“…Grammar comparison, as it is part of grammar convergence, can be loosely compared with schema matching in ER/relational modeling (Do and Rahm, 2007;Rahm and Bernstein, 2001) as well as model and metamodel matching or comparison in model-driven engineering (Falleri et al, 2008;Wenzel and Kelter, 2008;Xing and Stroulia, 2006) (specifically in the context of model/metamodel evolution). However, our current approach to comparison (as of §2.1) is relatively trivial, and does not make any contribution to this subject, not even remotely.…”

Section: Schema/metamodel Comparisonmentioning

confidence: 99%

Recovering grammar relationships for the Java Language Specification

Lämmel

Zaytsev²

2010

Software Qual J

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Grammar convergence is a method that helps discovering relationships between different grammars of the same language or different language versions. The key element of the method is the operational, transformation-based representation of those relationships. Given input grammars for convergence, they are transformed until they are structurally equal. The transformations are composed from primitive operators; properties of these operators and the composed chains provide quantitative and qualitative insight into the relationships between the grammars at hand.We describe a refined method for grammar convergence, and we use it in a major study, where we recover the relationships between all the grammars that occur in the different versions of the Java Language Specification (JLS). The relationships are represented as grammar transformation chains that capture all accidental or intended differences between the JLS grammars. This method is mechanized and driven by nominal and structural differences between pairs of grammars that are subject to asymmetric, binary convergence steps.We present the underlying operator suite for grammar transformation in detail, and we illustrate the suite with many examples of transformations on the JLS grammars. We also describe the extraction effort, which was needed to make the JLS grammars amenable to automated processing. We include substantial metadata about the convergence process for the JLS so that the effort becomes reproducible and transparent.

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Analyzing model evolution

Cited by 7 publications

References 4 publications

Specifying and detecting meaningful changes in programs

Specifying and detecting meaningful changes in programs

Managing Model Adaptation by Precise Detection of Metamodel Changes

Recovering grammar relationships for the Java Language Specification

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