Validation in model-driven engineering: testing model transformations

Fleurey, Franck; Steel, Jim; Baudry, Benoît

doi:10.1109/modeva.2004.1425846

Cited by 67 publications

(83 citation statements)

References 12 publications

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“…Another interesting direction for further research is to apply emerging model transformation testing techniques [16,31] on the method presented in this paper. For example, it is important to test whether the UML to Alloy transformation rules can generate a syntactically incorrect Alloy model.…”

Section: Discussionmentioning

confidence: 99%

On challenges of model transformation from UML to Alloy

et al. 2008

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The Unified Modeling Language (UML) is the de facto language used in the industry for software specifications. Once an application has been formally specified, Model Driven Architecture (MDA) techniques can be applied to generate code from such specifications. Since implementing a system based on a faulty design requires additional cost and effort, it is important to analyse the UML models at earlier stages of the software development lifecycle. This paper focuses on utilizing MDA techniques to deal with the analysis of UML models and identify design faults within a specification. Specifically, we show how UML models can be automatically transformed into Alloy which, in turn, can be automatically analysed by the Alloy Analyzer. The proposed approach relies on MDA techniques to transform UML models to Alloy. This paper reports on the challenges of the model transformation from UML class diagrams and OCL to Alloy. Those issues are caused by fundamental differences in design philosophy of UML and Alloy. To facilitate better representation of Alloy concepts in the UML, the paper draws on the lessons learnt and presents a UML profile for Alloy.

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Section: Discussionmentioning

confidence: 99%

On challenges of model transformation from UML to Alloy

et al. 2008

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“…Currently, the majority of approaches facing this challenge are based on black-box techniques [11,9,10,16,21,22,3,6,20,8,13]. As far as we know only two white-box approaches for transformation testing have been proposed [9,15]. Both address the identification of the relevant parts of the input metamodel to be exercised by the tests: by looking at the transformation definition they detect the subset of the metamodel (and possible relevant values for the metamodel attributes) that is accessed during the transformation and thus focus the generation of tests on that subset.…”

Section: Related Workmentioning

confidence: 99%

ATLTest: A White-Box Test Generation Approach for ATL Transformations

González

Cabot

2012

Model Driven Engineering Languages and Systems

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Abstract. MDE is being applied to the development of increasingly complex systems that require larger model transformations. Given that the specification of such transformations is an error-prone task, techniques to guarantee their quality must be provided. Testing is a wellknown technique for finding errors in programs. In this sense, adoption of testing techniques in the model transformation domain would be helpful to improve their quality. So far, testing of model transformations has focused on black-box testing techniques. Instead, in this paper we provide a white-box test model generation approach for ATL model transformations.

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“…However, in [8], they also propose an adaptation of bacteriologic algorithm to model transformation testing. The bacteriologic algorithm [4] is designed to automatically improve the quality of a test data set.…”

Section: Related Workmentioning

confidence: 99%

Traceability for Mutation Analysis in Model Transformation

Aranega

Mottu

Etien

et al. 2011

Models in Software Engineering

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Abstract. Model transformation can't be directly tested using program techniques. Those have to be adapted to model characteristics. In this paper we focus on one test technique: mutation analysis. This technique aims to qualify a test data set by analyzing the execution results of intentionally faulty program versions. If the degree of qualification is not satisfactory, the test data set has to be improved. In the context of model, this step is currently relatively fastidious and manually performed. We propose an approach based on traceability mechanisms in order to ease the test model set improvement in the mutation analysis process. We illustrate with a benchmark the quick automatic identification of the input model to change. A new model is then created in order to raise the quality of the test data set.

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Validation in model-driven engineering: testing model transformations

Cited by 67 publications

References 12 publications

On challenges of model transformation from UML to Alloy

On challenges of model transformation from UML to Alloy

ATLTest: A White-Box Test Generation Approach for ATL Transformations

Traceability for Mutation Analysis in Model Transformation

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