Using Transformation-Aspects in Model-Driven Software Product Lines

International audienceModel-Driven Software Product Lines (MD-SPL) are configured by using configuration models and Problem Space metamodels that capture product line scope. Products are derived by means of successive model transformations, starting from problem space models and based on the configuration models. Fine-variations of MD-SPLs correspond to characteristics that afect particular elements of models involved in the model transformations. In this paper, we present an approach to create MD-SPL including fine-variations. We configure products creating fine-feature configurations. Then, based on such configurations, we create MD-SPLs using principles of Aspects Oriented Development. Thus, our approach allows to derive products including fine-grained details of configuration

A Systematic Review of Tracing Solutions in Software Product Lines

Software Product Lines are large-scale, multi-unit systems that enable massive, customized production. They consist of a base of reusable artifacts and points of variation that provide the system with flexibility, allowing generating customized products. However, maintaining a system with such complexity and flexibility could be error prone and time consuming. Indeed, any modification (addition, deletion or update) at the level of a product or an artifact would impact other elements. It would therefore be interesting to adopt an efficient and organized traceability solution to maintain the Software Product Line. Still, traceability is not systematically implemented. It is usually set up for specific constraints (e.g. certification requirements), but abandoned in other situations. In order to draw a picture of the actual conditions of traceability solutions in Software Product Lines context, we decided to address a literature review. This review as well as its findings is detailed in the present article.Comment: 22 pages, 9 figures, 7 table

Evolving multi-tenant SaaS cloud applications using model-driven engineering

Cloud computing promotes multi-tenancy for efficient resource utilization by sharing hardware and software infrastructure among multiple clients. Multi-tenant applications running on a cloud infrastructure are provided to clients as Software-as-a-Service (SaaS) over the network. Despite its benefits, multi-tenancy introduces additional challenges, such as p artitioning, extensibility, and customizability during the application development. Over time, after the application deployment, new requirements of clients and changes in business environment result application evolution. As the application evolves, its complexity also increases. In multi-tenancy, evolution demanded by individual clients should not affect availability , security , and performance of the application for other clients. Thus, the multi- tenancy concerns add more complexity by causing variability in design decisions. Managing this complexity requires adequate approaches and tools. In this paper, we propose modeling techniques from software product lines (SPL) and model-driven engineering (MDE) to manage variability and support evolution of multi-tenant applications and their requirements. Specifically, SPL was ap p lied to define technological and concep tual variabilities during the application design, where MDE was suggested to manage these variabilities. We also present a process of how MDE can address evolution of multi-tenant applications using variability models

Capturing variability in Model Based Systems Engineering

International audienceAutomotive model-based systems engineering needs to be dapted to the industry specific needs, in particular by implementing appropriate means of representing and operating with variability. We rely on existing modeling techniques as an opportunity to provide a description of variability adapted to a systems en- gineering model. However, we also need to take into account requirements related to backwards compatibility with current practices, given the industry experience in mass customization. We propose to adopt the product line paradigm in model-based systems engineering by extending the orthogonal variability model, and adapting it to our specific needs. This brings us to an expression closer to a description of constraints, related to both orthogonal variability, and to SysML system models. We introduce our approach through a discussion on the different aspects that need to be covered for expressing variability in systems engineering. We explore these aspects by observing an automotive case study, and relate them to a list of contextual requirements for variability management

Parallel Execution of ATL Transformation Rules

International audienceIndustrial environments that make use of Model-Driven Engineering (MDE) are starting to see the appearance of very large models, made by millions of elements. Such models are produced automatically (e.g., by reverse engineering complex systems) or manually by a large number of users (e.g., from social networks). The success of MDE in these application scenarios strongly depends on the scalability of model manipulation tools. While parallelization is one of the traditional ways of making computation systems scalable, developing parallel model transformations in a general-purpose language is a complex and error-prone task. In this paper we show that rule-based languages like ATL have strong parallelization properties. Transformations can be developed without taking into account concurrency concerns, and a transformation engine can automatically parallelize execution. We describe the implementation of a parallel transformation engine for the current version of the ATL language and experimentally evaluate the consequent gain in scalability

Uma solução de implantação auto-adaptativa para plataformas Android

Orientador: Cecília Mary Fischer RubiraDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Os dispositivos móveis, hoje em dia, fornecem recursos semelhantes aos de um computador pessoal de uma década atrás, permitindo o desenvolvimento de aplicações complexas. Consequentemente, essas aplicações móveis podem exigir tolerar falhas em tempo de execução. No entanto, a maioria das aplicações móveis de hoje são implantados usando configurações estáticas, tornando difícil tolerar falhas durante a sua execução. Nós propomos uma infraestrutura de implantação auto-adaptativa para lidar com este problema. A nossa solução oferece um circuito autônomo que administra o modelo de configuração atual da aplicação usando um modelo de características dinâmico associado com o modelo arquitetônico da mesma. Em tempo de execução, de acordo com a seleção dinâmica de características, o modelo arquitetônico implantado na plataforma se re-configura para fornecer uma nova solução. Uma aplicação Android foi implementada utilizando a solução proposta, e durante sua execução, a disponibilidade de serviços foi alterada, de tal forma que sua configuração corrente foi dinamicamente alterada para tolerar a indisponibilidade dos serviçosAbstract: Mobile devices, nowadays, provide similar capabilities as a personal computer of a decade ago, allowing the development of complex applications. Consequently, these mobile applications may require tolerating failures at runtime. However, most of the today¿s mobile applications are deployed using static configurations, making difficult to tolerate failure during their execution. We propose an adaptive deployment infrastructure to deal with this problem. Our solution offers an autonomic loop that manages the current configuration model of the application using a dynamic feature model associated with the architectural model. During runtime, according to the dynamic feature selection, the deployed architectural model can be modified to provide a new deployment solution. An Android application was implemented using the proposed solution, and during its execution, the services availability was altered so that its current configuration was changed dynamically in order to tolerate the unavailability of servicesMestradoCiência da ComputaçãoMestre em Ciência da Computação131830/2013-9CNP

Consistency-Preserving Evolution Planning on Feature Models

A software product line (SPL) enables large-scale reuse in a family of related software systems through configurable features. SPLs represent a long-term investment so that their ongoing evolution becomes paramount and requires careful planning. While existing approaches enable to create an evolution plan for an SPL on feature-model (FM) level, they assume the plan to be rigid and do not support retroactive changes. In this paper, we present a method that enables to create and retroactively adapt an FM evolution plan while preventing undesired impacts on its structural and logical consistency. This method is founded in structural operational semantics and linear temporal logic. We implement our method using rewriting logic, integrate it within an FM tool suite and perform an evaluation using a collection of existing FM evolution scenarios