EMFtoCSP: A tool for the lightweight verification of EMF models

González, Marcos; Buttner,; Clariso,; Cabot, Jordi

doi:10.1109/formsera.2012.6229788

Cited by 45 publications

(32 citation statements)

References 15 publications

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“…In principle all of these approaches can be used to automatically generate test input data in the presence of a data model. However, with the exception of Alloy, we found that the transformation tools that implement the techniques presented in most of these papers are not usable in practice, either because they are not available [Soeken et al 2011;Przigoda et al 2016] or they are outdated [González et al 2012]. The results achieved in this paper show that (1) Alloy can be effectively used as the underlying formalism to represent the data model in a format that can be processed by a constraint solver, and (2) the solution proposed in this paper makes the Alloy solver scale when complex input data has to be generated.…”

Section: Related Workmentioning

confidence: 87%

“…These techniques have been proven to be effective for testing software systems that process classical data structures like trees, but they may not scale once adopted to generate more complex structures like the ones required to test SES-DAQ. Other approaches generate class diagram instances that satisfy a set of given OCL constraints by executing appropriate constraint solvers after having transformed the OCL constraints into other formalisms such as Alloy models [Anastasakis et al 2007], constraint satisfaction programs [González et al 2012], SMT [Przigoda et al 2016], or SAT problems [Soeken et al 2011]. In principle all of these approaches can be used to automatically generate test input data in the presence of a data model.…”

Section: Related Workmentioning

confidence: 99%

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Augmenting Field Data for Testing Systems Subject to Incremental Requirements Changes

Nardo

Pastore

Briand

2017

ACM Trans. Softw. Eng. Methodol.

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When testing data processing systems, software engineers often use real world data to perform system level testing. However, in the presence of new data requirements software engineers may no longer benefit from having real world data with which to perform testing. Typically, new test inputs complying with the new requirements have to be manually written.We propose an automated model-based approach that combines data modelling and constraint solving to modify existing field data to generate test inputs for testing new data requirements. The approach scales in the presence of complex and structured data, thanks to both the reuse of existing field data and the adoption of an innovative input generation algorithm based on slicing the model into parts.We validated the scalability and effectiveness of the proposed approach using an industrial case study. The empirical study shows that the approach scales in the presence of large amounts of structured and complex data. The approach can produce, within a reasonable time, test input data that is over ten times larger in size than the data generated with constraint solving only. We also demonstrate that the generated test inputs achieve more code coverage than the test cases implemented by experienced software engineers.

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Section: Related Workmentioning

confidence: 87%

Section: Related Workmentioning

confidence: 99%

Augmenting Field Data for Testing Systems Subject to Incremental Requirements Changes

Nardo

Pastore

Briand

2017

ACM Trans. Softw. Eng. Methodol.

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“…The authors claim that as models and model transformations become larger, they also become error-prone. Thus, a fully automatic approach that will be responsible to identify and fix these errors would be useful to improve the reliability of MDE-based processes [145].…”

Section: Combining Mde With Logic Programmingmentioning

confidence: 99%

“…In [145], the EMFtoCSP tool 6 is proposed, which is used for the verification of EMF models annotated with OCL constraints. The authors claim that as models and model transformations become larger, they also become error-prone.…”

Section: Combining Mde With Logic Programmingmentioning

confidence: 99%

Type Inference in Flexible Model-Driven Engineering

Zolotas

Matragkas

Devlin

et al. 2015

Modelling Foundations and Applications

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Model-driven Engineering (MDE) is an approach to software development that promises increased productivity and product quality. Domain models that conform to metamodels, both of which are the core artefacts in MDE approaches, are manipulated to perform different development processes using specific MDE tools.However, domain experts, who have detailed domain knowledge, typically lack the technical expertise to transfer this knowledge using MDE tools. Flexible or bottom-up Model-driven Engineering is an emerging approach to domain and systems modelling that tackles this challenge by promoting the use of simple drawing tools to increase the involvement of domain experts in MDE processes. In this approach, no metamodel is created upfront but instead the process starts with the definition of example models that will be used to infer a draft metamodel. When complete knowledge of the domain is acquired, a final metamodel is devised and a transition to traditional MDE approaches is possible. However, the lack of a metamodel that encodes the semantics of conforming models and of tools that impose these semantics bears some drawbacks, among others that of having models with nodes that are unintentionally left untyped. In this thesis we propose the use of approaches that use algorithms from three different research areas, that of classification algorithms, constraint programming and graph similarity to help with the type inference of such untyped nodes. We perform an evaluation of the proposed approaches in a number of randomly generated example models from 10 different domains with results suggesting that the approaches could be used for type inference both in an automatic or a semi-automatic style. 3For my parents Despoina and Michalis

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“…This computation can be performed using any of the SAT-based or CSP-based solvers available. In particular, we use EMFtoCSP 1 [12] to generate the input test models. EMFtoCSP is an Eclipse 2 -integrated tool for the automatic verification of UML models and EMF models annotated with OCL constraints by means of reexpressing them as a constraint satisfaction problem.…”

Section: Overall Picturementioning

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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EMFtoCSP: A tool for the lightweight verification of EMF models

Cited by 45 publications

References 15 publications

Augmenting Field Data for Testing Systems Subject to Incremental Requirements Changes

Augmenting Field Data for Testing Systems Subject to Incremental Requirements Changes

Type Inference in Flexible Model-Driven Engineering

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

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