Metamodel-based model conformance and multiview consistency checking

Model-driven development, using languages such as UML and BON, often makes use of multiple diagrams (e.g., class and sequence diagrams) when modeling systems. These diagrams, presenting different views of a system of interest, may be inconsistent. A metamodel provides a unifying framework in which to ensure and check consistency, while at the same time providing the means to distinguish between valid and invalid models, that is, conformance. Two formal specifications of the metamodel for an object-oriented modeling language are presented, and it is shown how to use these specifications for model conformance and multiview consistency checking. Comparisons are made in terms of completeness and the level of automation each provide for checking multiview consistency and model conformance. The lessons learned from applying formal techniques to the problems of metamodeling, model conformance, and multiview consistency checking are summarized

Case study: Class diagram restructuring

This case study is an update-in-place refactoring transformation on UML class diagrams. Its aim is to remove clones of attributes from a class diagram, and to identify new classes which abstract groups of classes that share common data features. It is used as one of a general collection of transformations (such as the removal of redundant inheritance, or multiple inheritance) which aim to improve the quality of a specification or design level class diagram. The transformation is a typical example of a model refactoring, and illustrates the issues involved in such transformations.Comment: In Proceedings TTC 2013, arXiv:1311.753

A Quality Model in a Quality Evaluation Framework for MDWE methodologies

Nowadays, diverse development methodologies exist in the field of Model-Driven Web Engineering (MDWE), each of which covers different levels of abstraction on Model-Driven Architecture (MDA): CIM, PIM, PSM and Code. Given the high number of methodologies available, it is necessary to evaluate the quality of existing methodologies and provide helpful information to the developers. Furthermore, proposals are constantly appearing and the need may arise not only to evaluate the quality but also to find out how it can be improved. In this context, QuEF (Quality Evaluation Framework) can be employed to assess the quality of MDWE methodologies. This article presents the work being carried out and describes tasks to define a Quality Model component for QuEF. This component would be responsible for providing the basis for specifying quality requirements with the purpose of evaluating quality.Ministerio de Educación y Ciencia TIN2007-67843-C06-03Ministerio de Educación y Ciencia TIN2007-30391-

A unifying framework for the definition of syntactic measures over conceptual schema diagrams (extended version)

There are many approaches that propose the use of measures for assessing the quality of conceptual schemas. Many of these measures focus purely on the syntactic aspects of the conceptual schema diagrams, e.g. their size, their shape, etc. Similarities among different measures may be found both at the intra-model level (i.e., several measures over the same type of diagram are defined following the same layout) and at the inter-model level (i.e., measures over different types of diagrams are similar considering an appropriate metaschema correspondence). In this paper we analyse these similarities for a particular family of diagrams used in conceptual modelling, those that can be ultimately seen as a combination of nodes and edges of different types. We propose a unifying measuring framework for this family and illustrate its application on a particular type, namely business process diagrams.Preprin

Assessing and improving the quality of model transformations

Software is pervading our society more and more and is becoming increasingly complex. At the same time, software quality demands remain at the same, high level. Model-driven engineering (MDE) is a software engineering paradigm that aims at dealing with this increasing software complexity and improving productivity and quality. Models play a pivotal role in MDE. The purpose of using models is to raise the level of abstraction at which software is developed to a level where concepts of the domain in which the software has to be applied, i.e., the target domain, can be expressed e??ectively. For that purpose, domain-speci??c languages (DSLs) are employed. A DSL is a language with a narrow focus, i.e., it is aimed at providing abstractions speci??c to the target domain. This makes that the application of models developed using DSLs is typically restricted to describing concepts existing in that target domain. Reuse of models such that they can be applied for di??erent purposes, e.g., analysis and code generation, is one of the challenges that should be solved by applying MDE. Therefore, model transformations are typically applied to transform domain-speci??c models to other (equivalent) models suitable for di??erent purposes. A model transformation is a mapping from a set of source models to a set of target models de??ned as a set of transformation rules. MDE is gradually being adopted by industry. Since MDE is becoming more and more important, model transformations are becoming more prominent as well. Model transformations are in many ways similar to traditional software artifacts. Therefore, they need to adhere to similar quality standards as well. The central research question discoursed in this thesis is therefore as follows. How can the quality of model transformations be assessed and improved, in particular with respect to development and maintenance? Recall that model transformations facilitate reuse of models in a software development process. We have developed a model transformation that enables reuse of analysis models for code generation. The semantic domains of the source and target language of this model transformation are so far apart that straightforward transformation is impossible, i.e., a semantic gap has to be bridged. To deal with model transformations that have to bridge a semantic gap, the semantics of the source and target language as well as possible additional requirements should be well understood. When bridging a semantic gap is not straightforward, we recommend to address a simpli??ed version of the source metamodel ??rst. Finally, the requirements on the transformation may, if possible, be relaxed to enable automated model transformation. Model transformations that need to transform between models in di??erent semantic domains are expected to be more complex than those that merely transform syntax. The complexity of a model transformation has consequences for its quality. Quality, in general, is a subjective concept. Therefore, quality can be de??ned in di??erent ways. We de??ned it in the context of model transformation. A model transformation can either be considered as a transformation de??nition or as the process of transforming a source model to a target model. Accordingly, model transformation quality can be de??ned in two di??erent ways. The quality of the de??nition is referred to as its internal quality. The quality of the process of transforming a source model to a target model is referred to as its external quality. There are also two ways to assess the quality of a model transformation (both internal and external). It can be assessed directly, i.e., by performing measurements on the transformation de??nition, or indirectly, i.e., by performing measurements in the environment of the model transformation. We mainly focused on direct assessment of internal quality. However, we also addressed external quality and indirect assessment. Given this de??nition of quality in the context of model transformations, techniques can be developed to assess it. Software metrics have been proposed for measuring various kinds of software artifacts. However, hardly any research has been performed on applying metrics for assessing the quality of model transformations. For four model transformation formalisms with di??fferent characteristics, viz., for ASF+SDF, ATL, Xtend, and QVTO, we de??ned sets of metrics for measuring model transformations developed with these formalisms. While these metric sets can be used to indicate bad smells in the code of model transformations, they cannot be used for assessing quality yet. A relation has to be established between the metric sets and attributes of model transformation quality. For two of the aforementioned metric sets, viz., the ones for ASF+SDF and for ATL, we conducted an empirical study aiming at establishing such a relation. From these empirical studies we learned what metrics serve as predictors for di??erent quality attributes of model transformations. Metrics can be used to quickly acquire insights into the characteristics of a model transformation. These insights enable increasing the overall quality of model transformations and thereby also their maintainability. To support maintenance, and also development in a traditional software engineering process, visualization techniques are often employed. For model transformations this appears as a feasible approach as well. Currently, however, there are few visualization techniques available tailored towards analyzing model transformations. One of the most time-consuming processes during software maintenance is acquiring understanding of the software. We expect that this holds for model transformations as well. Therefore, we presented two complementary visualization techniques for facilitating model transformation comprehension. The ??rst-technique is aimed at visualizing the dependencies between the components of a model transformation. The second technique is aimed at analyzing the coverage of the source and target metamodels by a model transformation. The development of the metric sets, and in particular the empirical studies, have led to insights considering the development of model transformations. Also, the proposed visualization techniques are aimed at facilitating the development of model transformations. We applied the insights acquired from the development of the metric sets as well as the visualization techniques in the development of a chain of model transformations that bridges a number of semantic gaps. We chose to solve this transformational problem not with one model transformation, but with a number of smaller model transformations. This should lead to smaller transformations, which are more understandable. The language on which the model transformations are de??ned, was subject to evolution. In particular the coverage visualization proved to be bene??cial for the co-evolution of the model transformations. Summarizing, we de??ned quality in the context of model transformations and addressed the necessity for a methodology to assess it. Therefore, we de??ned metric sets and performed empirical studies to validate whether they serve as predictors for model transformation quality. We also proposed a number of visualizations to increase model transformation comprehension. The acquired insights from developing the metric sets and the empirical studies, as well as the visualization tools, proved to be bene??cial for developing model transformations

Assessment of IT Infrastructures: A Model Driven Approach

Several approaches to evaluate IT infrastructure architectures have been proposed, mainly by supplier and consulting firms. However, they do not have a unified approach of these architectures where all stakeholders can cement the decision-making process, thus facilitating comparability as well as the verification of best practices adoption. The main goal of this dissertation is the proposal of a model-based approach to mitigate this problem. A metamodel named SDM (System Definition Model) and expressed with the UML (Unified Modeling Language) is used to represent structural and operational knowledge on the infrastructures. This metamodel is automatically instantiated through the capture of infrastructures configurations of existing distributed architectures, using a proprietary tool and a transformation tool that was built in the scope of this dissertation. The quantitative evaluation is performed using the M2DM (Meta-Model Driven Measurement) approach that uses OCL (Object Constraint Language) to formulate the required metrics. This proposal is expected to increase the understandability of IT infrastructures by all stakeholders (IT architects, application developers, testers, operators and maintenance teams) as well as to allow expressing their strategies of management and evolution. To illustrate the use of the proposed approach, we assess the complexity of some real cases in the diachronic and synchronic perspective

Component-based software engineering: a quantitative approach

Dissertação apresentada para a obtenção do Grau de Doutor em Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaBackground: Often, claims in Component-Based Development (CBD) are only supported by qualitative expert opinion, rather than by quantitative data. This contrasts with the normal practice in other sciences, where a sound experimental validation of claims is standard practice. Experimental Software Engineering (ESE) aims to bridge this gap. Unfortunately, it is common to find experimental validation efforts that are hard to replicate and compare, to build up the body of knowledge in CBD. Objectives: In this dissertation our goals are (i) to contribute to evolution of ESE, in what concerns the replicability and comparability of experimental work, and (ii) to apply our proposals to CBD, thus contributing to its deeper and sounder understanding. Techniques: We propose a process model for ESE, aligned with current experimental best practices, and combine this model with a measurement technique called Ontology-Driven Measurement (ODM). ODM is aimed at improving the state of practice in metrics definition and collection, by making metrics definitions formal and executable,without sacrificing their usability. ODM uses standard technologies that can be well adapted to current integrated development environments. Results: Our contributions include the definition and preliminary validation of a process model for ESE and the proposal of ODM for supporting metrics definition and collection in the context of CBD. We use both the process model and ODM to perform a series experimental works in CBD, including the cross-validation of a component metrics set for JavaBeans, a case study on the influence of practitioners expertise in a sub-process of component development (component code inspections), and an observational study on reusability patterns of pluggable components (Eclipse plug-ins). These experimental works implied proposing, adapting, or selecting adequate ontologies, as well as the formal definition of metrics upon each of those ontologies. Limitations: Although our experimental work covers a variety of component models and, orthogonally, both process and product, the plethora of opportunities for using our quantitative approach to CBD is far from exhausted. Conclusions: The main contribution of this dissertation is the illustration, through practical examples, of how we can combine our experimental process model with ODM to support the experimental validation of claims in the context of CBD, in a repeatable and comparable way. In addition, the techniques proposed in this dissertation are generic and can be applied to other software development paradigms.Departamento de Informática of the Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa (FCT/UNL); Centro de Informática e Tecnologias da Informação of the FCT/UNL; Fundação para a Ciência e Tecnologia through the STACOS project(POSI/CHS/48875/2002); The Experimental Software Engineering Network (ESERNET);Association Internationale pour les Technologies Objets (AITO); Association forComputing Machinery (ACM

M2Flex: a process metamodel for flexibility at runtime

International audienceExisting design and development methods do not meet designers' and developers' needs. They are difficult to learn and to use; they are complex, sequential and rigid and thus far from being adapted, reliable and efficient. This paper presents M2Flex, a process metamodel for highly supporting flexibility. M2Flex is based on a recent definition of flexibility along four dimensions: (1) versatility, the ability of the metamodel to provide various equivalent choices, (2) granularability, the possibility of defining components with several levels of details, (3) completeness, the possibility of defining optional components and pre-defined reusable results and (4) distensibility, the capacity of the resulting process model to be extended or reduced at runtime. This paper shows how M2Flex is original by the flexibility it offers to designers and developers at runtime