Spectrum-Based Fault Localization in Model Transformations

Model transformations play a cornerstone role in Model-Driven Engineering (MDE), as they provide the essential mechanisms for manipulating and transforming models. The correctness of software built using MDE techniques greatly relies on the correctness of model transformations. However, it is challenging and error prone to debug them, and the situation gets more critical as the size and complexity of model transformations grow, where manual debugging is no longer possible. Spectrum-Based Fault Localization (SBFL) uses the results of test cases and their corresponding code coverage information to estimate the likelihood of each program component (e.g., statements) of being faulty. In this article we present an approach to apply SBFL for locating the faulty rules in model transformations. We evaluate the feasibility and accuracy of the approach by comparing the effectiveness of 18 different stateof- the-art SBFL techniques at locating faults in model transformations. Evaluation results revealed that the best techniques, namely Kulcynski2, Mountford, Ochiai, and Zoltar, lead the debugger to inspect a maximum of three rules to locate the bug in around 74% of the cases. Furthermore, we compare our approach with a static approach for fault localization in model transformations, observing a clear superiority of the proposed SBFL-based method.Comisión Interministerial de Ciencia y Tecnología TIN2015-70560-RJunta de Andalucía P12-TIC-186

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

A Feature Model for an IDE4OCL

An Integrated OCL Development Environment (IDE4OCL) can significantly improve the pragmatics and practice of OCL. Therefore we started a comprehensive requirement analysis with the long term vision of a multisite IDE4OCL project. In this paper we present a feature model for the IDE4OCL vision based on this analysis. In an earlier work we identified domain concepts, tool–level interactions with IDE4OCL, and use cases for OCL developers including a set predefined features. In the second step, we asked the OCL community members for their feedback on our proposal. Around 100 researchers, tool developers and practitioners who gained experience with OCL have voted in an online–survey. The results gave us a valuable insight in the needs of OCL usage both in usual and advanced OCL applications. One of the important results is a collection of features that have been proposed additionally to our predefined features. We analysed all the comments of the participants of the survey and consolidated them into an extended set of IDE4OCL features and eventually into a feature model

Highlighting model elements to improve OCL comprehension

Models, metamodels, and model transformations play a central role in Model-Driven Development (MDD). Object Constraint Language (OCL) was initially proposed as part of the Unified Modeling Language (UML) standard to add the precision and validation capabilities lacking in its diagrams, and to express well-formedness rules in its metamodel. OCL has several other applications, such as defining design metrics, code-generation templates, or validation rules for model transformations, required in MDD. Learning OCL as part of a UML course at the university would seem natural but is still the exception rather than the rule. We believe that this is mainly due to a widespread perception that OCL is hard to learn, as gleaned from claims made in the literature. Based on data gathered over the past school years from numerous undergraduate students of di↵erent Software Engineering courses, we analyzed how learning design by contract clauses with UML+OCL compares with several other Software Engineering Body Of Knowledge (SWEBOK) topics. The outcome of the learning process was collected in a rigorous setup, supported by an e-learning platform. We performed inferential statistics on that data to support our conclusions and identify the relevant explanatory variables for students’ success/failure. The obtained findings lead us to extend an existing OCL tool with two novel features: one is aimed at OCL apprentices and goes straight to the heart of the matter by allowing to visualize how OCL expressions traverse UML class diagrams; the other is intended for researchers and allows to compute OCL complexity metrics, making it possible to replicate a research study like the one we are presenting.Modelos, metamodelos e transformações de modelo desempenham um papel central em MDD. OCL foi inicialmente proposta como parte da UML para adicionar os recursos de precisão e validação que faltavam nestes diagramas, e também para expressar regras de boa formação no metamodelo. OCL possui outras aplicações, tais como definir métricas de desenho, modelos de geração de código ou regras de validação para transformações de modelo, exigidas em MDD. Aprender OCL como parte de um curso de UML na universidade parecia portanto natural, não sendo no entanto o que se verifica. Acreditamos que isso se deva a uma percepção generalizada de que OCL é difícil de aprender, tendo em conta afirmações feitas na literatura. Com base em dados recolhidos em anos letivos anteriores de vários alunos de licenciatura de diferentes cursos de Engenharia de Software, analisámos como a aprendizagem por cláusulas contratuais de UML + OCL se compara a outros tópicos do SWEBOK. O resultado do processo de aprendizagem foi recolhido de forma rigorosa, apoiado por uma plataforma de e-learning. Realizámos estatísticas inferenciais sobre os dados para apoiar as nossas conclusões, de forma a identificar as variáveis explicativas relevantes para o sucesso / fracasso dos alunos. As conclusões obtidas levaram-nos a estender uma ferramenta OCL com duas novas funcionalidades: a primeira é voltada para os estudantes de OCL e permite visualizar como as expressões percorrem um diagrama de classes UML; a segunda é voltada para investigadores e permite calcular métricas de complexidade OCL, habilitando a réplica de um estudo semelhante ao apresentado

A model transformation framework to increase OCL usability

The usability of a modeling language has a direct relationship with several factors of models constructed with the modeling language, such as time required and accuracy. Object Constraint Language (OCL) is the most prevalent language to document system constraints that are annotated in the Unified Modeling Language (UML). OCL is reputed as a modeling language with difficult syntax, and prior knowledge of OCL is needed to use the language. These obstacles result in the low usability of OCL. Therefore, the current research proposes a model to automatically transform system constraints formed in English sentences to OCL specifications. The proposed model is based on the Model-Driven Architecture (MDA) approach. The Linear Temporal Logic (LTL) properties of the proposed model are verified by the Maude model checker. To validate the proposed model and compare it with the existing work, the En2OCL (English2OCL) application is developed. This application is tested by three evaluation metrics: precision, recall, and f-measure. The En2OCL application is further compared with the NL2OCLviaSBVR application, which is the existing work on OCL generation from English sentences. The comparison shows a considerable improvement in precision, recall, and f-measure.Web of Science281261