942 resultados para Model-driven Web engineering
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática
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Dissertação para obtenção do Grau de Doutor em Engenharia Informática
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Open Source (OS) community offers numerous eLearning platforms of both types: Learning Management Systems (LMS) and Learning Content Systems (LCS). General purpose OS intermediaries such as SourceForge, ObjectWeb, Apache or specialized intermediaries like CampusSource reduce the cost to locate such eLearning platforms. Still, it is impossible to directly compare the functionalities of those OS software products without performing detailed testing on each product. Some articles available from eLearning Wikipedia show comparisons between eLearning platforms which can help, but at the end they barely serve as documentation which are becoming out of date quickly [1]. The absence of integration activities between OS eLearning platforms - which are sometimes quite similar in terms of functionalities and implementation technologies - is sometimes critical since most of the OS projects possess small financial and human resources. This paper shows a possible solution for these barriers of OS eLearning platforms. We propose the Model Driven Architecture (MDA) concept to capture functionalities and to identify similarities between available OS eLearning platforms. This contribution evolved from a fruitful discussion at the 2nd CampusSource Developer Conference at the University of Muenster (27th August 2004).
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Advances in electronics nowadays facilitate the design of smart spaces based on physical mash-ups of sensor and actuator devices. At the same time, software paradigms such as Internet of Things (IoT) and Web of Things (WoT) are motivating the creation of technology to support the development and deployment of web-enabled embedded sensor and actuator devices with two major objectives: (i) to integrate sensing and actuating functionalities into everyday objects, and (ii) to easily allow a diversity of devices to plug into the Internet. Currently, developers who are applying this Internet-oriented approach need to have solid understanding about specific platforms and web technologies. In order to alleviate this development process, this research proposes a Resource-Oriented and Ontology-Driven Development (ROOD) methodology based on the Model Driven Architecture (MDA). This methodology aims at enabling the development of smart spaces through a set of modeling tools and semantic technologies that support the definition of the smart space and the automatic generation of code at hardware level. ROOD feasibility is demonstrated by building an adaptive health monitoring service for a Smart Gym.
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The Software Engineering (SE) community has historically focused on working with models to represent functionality and persistence, pushing interaction modelling into the background, which has been covered by the Human Computer Interaction (HCI) community. Recently, adequately modelling interaction, and specifically usability, is being considered as a key factor for success in user acceptance, making the integration of the SE and HCI communities more necessary. If we focus on the Model-Driven Development (MDD) paradigm, we notice that there is a lack of proposals to deal with usability features from the very first steps of software development process. In general, usability features are manually implemented once the code has been generated from models. This contradicts the MDD paradigm, which claims that all the analysts? effort must be focused on building models, and the code generation is relegated to model to code transformations. Moreover, usability features related to functionality may involve important changes in the system architecture if they are not considered from the early steps. We state that these usability features related to functionality can be represented abstractly in a conceptual model, and their implementation can be carried out automatically.
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Over the past years, the paradigm of component-based software engineering has been established in the construction of complex mission-critical systems. Due to this trend, there is a practical need for techniques that evaluate critical properties (such as safety, reliability, availability or performance) of these systems. In this paper, we review several high-level techniques for the evaluation of safety properties for component-based systems and we propose a new evaluation model (State Event Fault Trees) that extends safety analysis towards a lower abstraction level. This model possesses a state-event semantics and strong encapsulation, which is especially useful for the evaluation of component-based software systems. Finally, we compare the techniques and give suggestions for their combined usage
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Constructing and executing distributed systems that can adapt to their operating context in order to sustain provided services and the service qualities are complex tasks. Managing adaptation of multiple, interacting services is particularly difficult since these services tend to be distributed across the system, interdependent and sometimes tangled with other services. Furthermore, the exponential growth of the number of potential system configurations derived from the variabilities of each service need to be handled. Current practices of writing low-level reconfiguration scripts as part of the system code to handle run time adaptation are both error prone and time consuming and make adaptive systems difficult to validate and evolve. In this paper, we propose to combine model driven and aspect oriented techniques to better cope with the complexities of adaptive systems construction and execution, and to handle the problem of exponential growth of the number of possible configurations. Combining these techniques allows us to use high level domain abstractions, simplify the representation of variants and limit the problem pertaining to the combinatorial explosion of possible configurations. In our approach we also use models at runtime to generate the adaptation logic by comparing the current configuration of the system to a composed model representing the configuration we want to reach. © 2008 Springer-Verlag Berlin Heidelberg.
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A self-adaptive system adjusts its configuration to tolerate changes in its operating environment. To date, requirements modeling methodologies for self-adaptive systems have necessitated analysis of all potential system configurations, and the circumstances under which each is to be adopted. We argue that, by explicitly capturing and modelling uncertainty in the operating environment, and by verifying and analysing this model at runtime, it is possible for a system to adapt to tolerate some conditions that were not fully considered at design time. We showcase in this paper our tools and research results. © 2012 IEEE.
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Engineering adaptive software is an increasingly complex task. Here, we demonstrate Genie, a tool that supports the modelling, generation, and operation of highly reconfigurable, component-based systems. We showcase how Genie is used in two case-studies: i) the development and operation of an adaptive flood warning system, and ii) a service discovery application. In this context, adaptation is enabled by the Gridkit reflective middleware platform.
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This paper presents a vision that allows the combined use of model-driven engineering, run-time monitoring, and animation for the development and analysis of components in real-time embedded systems. Key building block in the tool environment supporting this vision is a highly-customizable code generation process. Customization is performed via a configuration specification which describes the ways in which input is provided to the component, the ways in which run-time execution information can be observed, and how these observations drive animation tools. The environment is envisioned to be suitable for different activities ranging from quality assurance to supporting certification, teaching, and outreach and will be built exclusively with open source tools to increase impact. A preliminary prototype implementation is described.
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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2015.
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The majority of the organizations store their historical business information in data warehouses which are queried to make strategic decisions by using online analytical processing (OLAP) tools. This information has to be correctly assured against unauthorized accesses, but nevertheless there are a great amount of legacy OLAP applications that have been developed without considering security aspects or these have been incorporated once the system was implemented. This work defines a reverse engineering process that allows us to obtain the conceptual model corresponding to a legacy OLAP application, and also analyses and represents the security aspects that could have established. This process has been aligned with a model-driven architecture for developing secure OLAP applications by defining the transformations needed to automatically apply it. Once the conceptual model has been extracted, it can be easily modified and improved with security, and automatically transformed to generate the new implementation.
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We study the exact ground state of the two-dimensional random-field Ising model as a function of both the external applied field B and the standard deviation ¿ of the Gaussian random-field distribution. The equilibrium evolution of the magnetization consists in a sequence of discrete jumps. These are very similar to the avalanche behavior found in the out-of-equilibrium version of the same model with local relaxation dynamics. We compare the statistical distributions of magnetization jumps and find that both exhibit power-law behavior for the same value of ¿. The corresponding exponents are compared.