Weaving Variability into Domain Metamodels

International audienceDomain-Specific Modeling Languages (DSMLs) describe the concepts of a particular domain and their relationships, in a meta-model. From a given DSML, it is possible to describe a wide range of different models. These models often share a common base and vary on some parts. Current approaches tend to distinguish the variability language from the DSMLs themselves, implying greater learning curve for DSMLs stakeholders and a significant overhead in product line engineering of DSLs. We propose to consider variability concepts as an independent aspect to be woven into the DSML to introduce variability capabilities. In particular we detail how variability is woven and how to perform product line derivation. We validate our approach through the weaving of variability into two very different metamodels: Ecore and SmartAdapter, our aspect-oriented modelling weaver, thus adding exibility in the weaving process itself. These results emphasize how new abilities of the language can be provided by this means

Weaving Variability into Domain Metamodels

International audienceDomain-Specific Modeling Languages (DSMLs) describe the concepts of a particular domain and their relationships, in a meta-model. From a given DSML, it is possible to describe a wide range of different models. These models often share a common base and vary on some parts. Current approaches tend to distinguish the variability language from the DSMLs themselves, implying greater learning curve for DSMLs stakeholders and a significant overhead in product line engineering of DSLs. We propose to consider variability concepts as an independent aspect to be woven into the DSML to introduce variability capabilities. In particular we detail how variability is woven and how to perform product line derivation. We validate our approach through the weaving of variability into two very different metamodels: Ecore and SmartAdapter, our aspect-oriented modelling weaver, thus adding exibility in the weaving process itself. These results emphasize how new abilities of the language can be provided by this means

Generic Model Refactorings

Many modeling languages share some common concepts and principles. For example, Java, MOF, and UML share some aspects of the concepts\ud of classes, methods, attributes, and inheritance. However, model\ud transformations such as refactorings specified for a given language\ud cannot be readily reused for another language because their related\ud metamodels may be structurally different. Our aim is to enable a\ud flexible reuse of model transformations across various metamodels.\ud Thus, in this paper, we present an approach allowing the specification\ud of generic model transformations, in particular refactorings, so\ud that they can be applied to different metamodels. Our approach relies\ud on two mechanisms: (1) an adaptation based mainly on the weaving\ud of aspects; (2) the notion of model typing, an extension of object\ud typing in the model-oriented context. We validated our approach by\ud performing some experiments that consisted of specifying three well\ud known refactorings (Encapsulate Field, Move Method, and Pull Up Method)\ud and applying each of them onto three different metamodels (Java,\ud MOF, and UML)

A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen

XRound : A reversible template language and its application in model-based security analysis

Successful analysis of the models used in Model-Driven Development requires the ability to synthesise the results of analysis and automatically integrate these results with the models themselves. This paper presents a reversible template language called XRound which supports round-trip transformations between models and the logic used to encode system properties. A template processor that supports the language is described, and the use of the template language is illustrated by its application in an analysis workbench, designed to support analysis of security properties of UML and MOF-based models. As a result of using reversible templates, it is possible to seamlessly and automatically integrate the results of a security analysis with a model. (C) 2008 Elsevier B.V. All rights reserved

Variability management in a model-driven software product line

Variability management in Software Product Lines (SPLs) has two fundamental challenges: (1) the expression of common and variable features, and (2) the development of applications employing properly such features. In this paper, we present a Software Product Line based on Models (MD-SPL). We separate the concepts related to SPLs in different domains and we build core assets like feature models, metamodels, and three different types of transformation rules to transform models from a source domain to different (variable) models into a target domain. By using transformation rules, we are able to generate applications in an incremental process, guided by a set of features selected for each target domain. Thus, we manage to extend the SPLs scope, separate the domains diminishing the complexity to create applications with variable characteristics, and automatically generate applications using transformation rules. In order to illustrate our approach, we have built a MDSPL where the products are small applications used in programming computers teaching

Kevoree Modeling Framework (KMF): Efficient modeling techniques for runtime use

The creation of Domain Specific Languages(DSL) counts as one of the main goals in the field of Model-Driven Software Engineering (MDSE). The main purpose of these DSLs is to facilitate the manipulation of domain specific concepts, by providing developers with specific tools for their domain of expertise. A natural approach to create DSLs is to reuse existing modeling standards and tools. In this area, the Eclipse Modeling Framework (EMF) has rapidly become the defacto standard in the MDSE for building Domain Specific Languages (DSL) and tools based on generative techniques. However, the use of EMF generated tools in domains like Internet of Things (IoT), Cloud Computing or Models@Runtime reaches several limitations. In this paper, we identify several properties the generated tools must comply with to be usable in other domains than desktop-based software systems. We then challenge EMF on these properties and describe our approach to overcome the limitations. Our approach, implemented in the Kevoree Modeling Framework (KMF), is finally evaluated according to the identified properties and compared to EMF.Comment: ISBN 978-2-87971-131-7; N° TR-SnT-2014-11 (2014

Approaching the Model-Driven Generation of Feedback to Remove Software Performance Flaws

Abstract—The problem of interpreting results of perfor-mance analysis and providing feedback on software models to overcome performance flaws is probably the most critical open issue in the field of software performance engineering. Automation in this step would help to introduce perfor-mance validation as an integrated activity in the software lifecycle, without dramatically affecting the daily practices of software developers. In this paper we approach the problem with model-driven techniques, on which we build a general solution. Basing on the concept of performance antipatterns, that are bad practices in software modeling leading to performance flaws, we introduce metamodels and transformations that can support the whole process of flaw detection and solution. The approach that we propose is notation-independent and can be embedded in any (existing or future) concrete modeling notation by using weaving models and automatically generated model transformations. Finally, we discuss the issues opened from this work and the future achievements that are at the hand in this domain thanks to model-driven techniques