Loli Burgueño

Formal specification and testing of model transformations

In this paper we present some of the key issues involved in model transformation specification and testing, discuss and classify some of the existing approaches, and introduce the concept of Tract, a generalization of model transformation contracts. We show how Tracts can be used for model transformation specification and black-box testing, and the kinds of analyses they allow. Some representative examples are used to illustrate this approach.

Static Fault Localization in Model Transformations

As the complexity of model transformations grows, there is an increasing need to count on methods, mechanisms, and tools for checking their correctness, i.e., the alignment between specifications and implementations. In this paper we present a light-weight and static approach for locating the faulty rules in model transformations, based on matching functions that automatically establish these alignments using the metamodel footprints, i.e., the metamodel elements used. The approach is implemented for the combination of Tracts and ATL, both residing in the Eclipse Modeling Framework, and is supported by the corresponding toolkit. An evaluation discussing the accuracy and the limitations of the approach is also provided. Furthermore, we identify the kinds of transformations which are most suitable for validation with the proposed approach and use mutation techniques to evaluate its effectiveness.

Testing M2T/T2M Transformations

Testing model-to-model M2M transformations is becoming a prominent topic in the current Model-driven Engineering landscape. Current approaches for transformation testing, however, assume having explicit model representations for the input domain and for the output domain of the transformation. This excludes other important transformation kinds, such as model-to-text M2T and text-to-model T2M transformations, from being properly tested since adequate model representations are missing either for the input domain or for the output domain. The contribution of this paper to overcome this gap is extending Tracts, a M2M transformation testing approach, for M2T/T2M transformation testing. The main mechanism we employ for reusing Tracts is to represent text within a generic metamodel. By this, we transform the M2T/T2M transformation specification problems into equivalent M2M transformation specification problems. We demonstrate the applicability of the approach by two examples and present how the approach is implemented for the Eclipse Modeling Framework EMF. Finally, we apply the approach to evaluate code generation capabilities of several existing UML tools.

On the concurrent execution of model transformations with Linda

Nowadays there exists a wide variety of model transformation languages. However, all of them present limitations, mainly performance issues, when the complexity and size of model transformations and models grow. The problems arise due to the in-memory allocation of large models as well as the time taken by the execution engines for producing the output models. This restricts the benefits of using model transformations in different application fields of model engineering where the complexity of the transformation tasks exceeds the capabilities of sequential execution engines. In this paper we tackle these limitations by introducing concurrency for model transformations to effectively improve the execution performance. Instead of reinventing the wheel, we base our approach on Linda, a mature coordination language for parallel processes. We explore how model transformations fit into Linda and show a set of basic mechanisms to enable concurrent model transformations. Initial results of applying our approach show a great potential of using Linda to improve the execution performance with respect to existing approaches.

Employing classifying terms for testing model transformations

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.

Towards systematic mutations for and with ATL model transformations

Model transformation is a key technique to automate software engineering tasks, such as generating implementations of software systems from higher-level models. To enable this automation, transformation engines are used to synthesize various types of software artifacts from models, where the rules according to which these artifacts are generated are implemented by means of dedicated model transformation languages. Hence, the quality of the generated software artifacts depends on the quality of the transformation rules applied to generate them. Thus, there is the need for approaches to certify their behavior for a selected set of test models. As mutation analysis has proven useful as a practical testing approach, we propose a set of mutation operators for the ATLAS Transformation Language (ATL) derived by a comprehensive language-centric synthesis approach. We describe the rationale behind each of the mutation operators and propose an automated process to generate mutants for ATL transformations based on a combination of generic mutation operators and higher-order transformations. Finally, we describe a cost-effective solution for executing the obtained mutants.

Handling non-functional requirements in Model-Driven Development: An ongoing industrial survey

Model-Driven Development (MDD) is no longer a novel development paradigm. It has become mature from a research perspective and recent studies show its adoption in industry. Still, some issues remain a challenge. Among them, we are interested in the treatment of non-functional requirements (NFRs) in MDD processes. Very few MDD approaches have been reported to deal with NFRs (and they do it in a limited way). However, it is clear that NFRs need to be considered somehow in the final product of the MDD process. To better understand how NFRs are integrated into the existing MDD approaches, we have initiated the NFR4MDD project, a multi-national empirical study, based on interviews with companies working on MDD projects. Our project aims at surveying the state of the practice for this topic. In this paper, we summarize our research protocol and present the current status of our study. The discussion will focus on the peculiarities of our studys context and organization involving about 20 researchers from 8 European countries.

Testing models and model transformations using classifying terms

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.

Managing Uncertain Complex Events in Web of Things Applications

A critical issue in the Web of Things (WoT) is the need to process and analyze the interactions of Web-interconnected real-world objects. Complex Event Processing (CEP) is a powerful technology for analyzing streams of information about real-time distributed events, coming from different sources, and for extracting conclusions from them. However, in many situations these events are not free from uncertainty, due to either unreliable data sources and networks, measurement uncertainty, or to the inability to determine whether an event has actually happened or not. This short research paper discusses how CEP systems can incorporate different kinds of uncertainty, both in the events and in the rules. A case study is used to validate the proposal, and we discuss the benefits and limitations of this CEP extension.

A Linda-based platform for the parallel execution of out-place model transformations

ContextThe performance and scalability of model transformations is gaining interest as industry is progressively adopting model-driven techniques and multicore computers are becoming commonplace. However, existing model transformation engines are mostly based on sequential and in-memory execution strategies, and thus their capabilities to transform large models in parallel and distributed environments are limited. ObjectiveThis paper presents a solution that provides concurrency and distribution to model transformations. MethodInspired by the concepts and principles of the Linda coordination language, and the use of data parallelism to achieve parallelization, a novel Java-based execution platform is introduced. It offers a set of core features for the parallel execution of out-place transformations that can be used as a target for high-level transformation language compilers. ResultsSignificant gains in performance and scalability of this platform are reported with regard to existing model transformation solutions. These results are demonstrated by running a model transformation test suite, and by its comparison against several state-of-the-art model transformation engines. ConclusionOur Linda-based approach to the concurrent execution of model transformations can serve as a platform for their scalable and efficient implementation in parallel and distributed environments.