Traceability for Mutation Analysis in Model Transformation

Aranega, Vincent; Mottu, Jean-Marie; Etien, Anne; Dekeyser, Jean-Luc

doi:10.1007/978-3-642-21210-9_25

Cited by 15 publications

(22 citation statements)

References 16 publications

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“…In [14], we used OCL-based queries to backwards debugging of model transformations using an explicit runtime model based on the trace model between the source and target models. Aranega et al [1] present an approach for situating transformations errors by exploiting also the traces between the source and target models. The dynamic approach is also used by [11] to build slices of model transformations.…”

Section: Related Workmentioning

confidence: 99%

Towards tracking "guilty" transformation rules

Burgueño

Wimmer

Vallecillo

2012

Proceedings of the First Workshop on the Analysis of Model Transformations

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Several approaches for specifying the requirements for model transformations have been proposed. Most of them define constraints on source and target models as well as on the relationships between them. A major advantage of these approaches is their independence from transformation implementation languages and transformation implementations. However, when these constraints are used for testing, identifying the model transformation rules that violate the constraints is not possible. In this paper we present an approach for automatically aligning specifications of model transformations and their implementations. Matching functions establish these alignments based on the used metamodel elements in the constraints and rules. We present our first results and outline further use cases where an alignment between constraints and rules is beneficial.

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Section: Related Workmentioning

confidence: 99%

Towards tracking "guilty" transformation rules

Burgueño

Wimmer

Vallecillo

2012

Proceedings of the First Workshop on the Analysis of Model Transformations

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“…Regarding dynamic approaches, for which the model transformation execution is needed and therefore input models, the authors in [35,60] present their contribution for debugging model transformations. Also, the work in [4] analyze the execution traces between the source and target models in order to find errors, and in [29] a white-box test model generation approach for testing the transformations is proposed. In this context, Tracts [59] are a complementary approach that establishes contracts between the source and target metamodels which define the transformation specification.…”

Section: Testing and Verifying Model Transformationsmentioning

confidence: 99%

Testing models and model transformations using classifying terms

et al. 2016

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This paper proposes the use of equivalence partitioning techniques for testing models and model transformations. In particular, we introduce the concept of classifying terms, which are general OCL terms on a class model enriched with OCL constraints. Classifying terms permit defining equivalence classes, in particular for partitioning the source and target model spaces of the transformation, defining for each class a set of equivalent models with regard to the transformation. Using these classes, a model validator tool is able to automatically construct object models for each class, which constitute relevant test cases for the transformation. We show how this approach of guiding the construction of test cases in an orderly, systematic and efficient manner can be effectively used in combination with Tracts for testing both directional and bidirectional model transformations and for analyzing their behavior.

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“…Regarding dynamic approaches, for which the model transformation execution is needed and therefore input models, the authors in [21] and [22] present their contribution for debugging model transformations. Also, the work in [23] analyse the execution traces between the source and target models in order to find errors, and in [24] a white-box test model generation approach for testing the transformations is proposed. In this context, Tracts [25] are a complementary approach that establishes contracts between the source and target metamodels which define the transformation specification.…”

Section: B Testing and Verifying Model Transformationsmentioning

confidence: 99%

Employing classifying terms for testing model transformations

Gogolla

Vallecillo

Burgueño

et al. 2015

2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS)

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Abstract-This contribution proposes a new technique for developing test cases for UML and OCL models. The technique is based on an approach that automatically constructs object models for class models enriched by OCL constraints. By guiding the construction process through so-called classifying terms, the built test cases in form of object models are classified into equivalence classes. A classifying term can be an arbitrary OCL term on the class model that calculates for an object model a characteristic value. From each equivalence class of object models with identical characteristic values one representative is chosen. The constructed test cases behave significantly different with regard to the selected classifying term. By building few diverse object models, properties of the UML and OCL model can be explored effectively. The technique is applied for automatically constructing relevant source model test cases for model transformations between a source and target metamodel.

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Traceability for Mutation Analysis in Model Transformation

Cited by 15 publications

References 16 publications

Towards tracking "guilty" transformation rules

Towards tracking "guilty" transformation rules

Testing models and model transformations using classifying terms

Employing classifying terms for testing model transformations

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