895 resultados para Model Driven Software Development, Arduino, Meta-Modeling, Domain Specific Languages, Software Factory


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The increasing amount of data available about software systems poses new challenges for re- and reverse engineering research, as the proposed approaches need to scale. In this context, concerns about meta-modeling and analysis techniques need to be augmented by technical concerns about how to reuse and how to build upon the efforts of previous research. MOOSE is an extensive infrastructure for reverse engineering evolved for over 10 years that promotes the reuse of engineering efforts in research. MOOSE accommodates various types of data modeled in the FAMIX family of meta-models. The goal of this half-day workshop is to strengthen the community of researchers and practitioners who are working in re- and reverse engineering, by providing a forum for building future research starting from MOOSE and FAMIX as shared infrastructure.

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Development of homology modeling methods will remain an area of active research. These methods aim to develop and model increasingly accurate three-dimensional structures of yet uncrystallized therapeutically relevant proteins e.g. Class A G-Protein Coupled Receptors. Incorporating protein flexibility is one way to achieve this goal. Here, I will discuss the enhancement and validation of the ligand-steered modeling, originally developed by Dr. Claudio Cavasotto, via cross modeling of the newly crystallized GPCR structures. This method uses known ligands and known experimental information to optimize relevant protein binding sites by incorporating protein flexibility. The ligand-steered models were able to model, reasonably reproduce binding sites and the co-crystallized native ligand poses of the β2 adrenergic and Adenosine 2A receptors using a single template structure. They also performed better than the choice of template, and crude models in a small scale high-throughput docking experiments and compound selectivity studies. Next, the application of this method to develop high-quality homology models of Cannabinoid Receptor 2, an emerging non-psychotic pain management target, is discussed. These models were validated by their ability to rationalize structure activity relationship data of two, inverse agonist and agonist, series of compounds. The method was also applied to improve the virtual screening performance of the β2 adrenergic crystal structure by optimizing the binding site using β2 specific compounds. These results show the feasibility of optimizing only the pharmacologically relevant protein binding sites and applicability to structure-based drug design projects.

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The climate during the Cenozoic era changed in several steps from ice-free poles and warm conditions to ice-covered poles and cold conditions. Since the 1950s, a body of information on ice volume and temperature changes has been built up predominantly on the basis of measurements of the oxygen isotopic composition of shells of benthic foraminifera collected from marine sediment cores. The statistical methodology of time series analysis has also evolved, allowing more information to be extracted from these records. Here we provide a comprehensive view of Cenozoic climate evolution by means of a coherent and systematic application of time series analytical tools to each record from a compilation spanning the interval from 4 to 61 Myr ago. We quantitatively describe several prominent features of the oxygen isotope record, taking into account the various sources of uncertainty (including measurement, proxy noise, and dating errors). The estimated transition times and amplitudes allow us to assess causal climatological-tectonic influences on the following known features of the Cenozoic oxygen isotopic record: Paleocene-Eocene Thermal Maximum, Eocene-Oligocene Transition, Oligocene-Miocene Boundary, and the Middle Miocene Climate Optimum. We further describe and causally interpret the following features: Paleocene-Eocene warming trend, the two-step, long-term Eocene cooling, and the changes within the most recent interval (Miocene-Pliocene). We review the scope and methods of constructing Cenozoic stacks of benthic oxygen isotope records and present two new latitudinal stacks, which capture besides global ice volume also bottom water temperatures at low (less than 30°) and high latitudes. This review concludes with an identification of future directions for data collection, statistical method development, and climate modeling.

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Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs. In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement. We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).

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Embedded systems are commonly designed by specifying and developing hardware and software systems separately. On the contrary, the hardware/software (HW/SW) co-development exploits the trade-offs between hardware and software in a system through their concurrent design. HW/SW Codevelopment techniques take advantage of the flexibility of system design to create architectures that can meet stringent performance requirements with a shorter design cycle. This paper presents the work done within the scope of ESA HWSWCO (Hardware-Software Co-design) study. The main objective of this study has been to address the HW/SW co-design phase to integrate this engineering task as part of the ASSERT process (refer to [1]) and compatible with the existing ASSERT approach, process and tool, Advances in the automation of the design of HW and SW and the adoption of the Model Driven Architecture (MDA) [9] paradigm make possible the definition of a proper integration substrate and enables the continuous interaction of the HW and SW design paths.

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Software Product Line Engineering (SPLE) has proved to have significant advantages in family-based software development, but also implies the up¬front design of a product-line architecture (PLA) from which individual product applications can be engineered. The big upfront design associated with PLAs is in conflict with the current need of "being open to change". However, the turbulence of the current business climate makes change inevitable in order to stay competitive, and requires PLAs to be open to change even late in the development. The trend of "being open to change" is manifested in the Agile Software Development (ASD) paradigm, but it is spreading to the domain of SPLE. To reduce the big upfront design of PLAs as currently practiced in SPLE, new paradigms are being created, one being Agile Product Line Engineering (APLE). APLE aims to make the development of product-lines more flexible and adaptable to changes as promoted in ASD. To put APLE into practice it is necessary to make mechanisms available to assist and guide the agile construction and evolution of PLAs while complying with the "be open to change" agile principle. This thesis defines a process for "the agile construction and evolution of product-line architectures", which we refer to as Agile Product-Line Archi-tecting (APLA). The APLA process provides agile architects with a set of models for describing, documenting and tracing PLAs, as well as an algorithm to analyze change impact. Both the models and the change impact analysis offer the following capabilities: Flexibility & adaptability at the time of defining software architectures, enabling change during the incremental and iterative design of PLAs (anticipated or planned changes) and their evolution (unanticipated or unforeseen changes). Assistance in checking architectural integrity through change impact analysis in terms of architectural concerns, such as dependencies on earlier design decisions, rationale, constraints, and risks, etc.Guidance in the change decision-making process through change im¬pact analysis in terms of architectural components and connections. Therefore, APLA provides the mechanisms required to construct and evolve PLAs that can easily be refined iteration after iteration during the APLE development process. These mechanisms are provided in a modeling frame¬work called FPLA. The contributions of this thesis have been validated through the conduction of a project regarding a metering management system in electrical power networks. This case study took place in an i-smart software factory and was in collaboration with the Technical University of Madrid and Indra Software Labs. La Ingeniería de Líneas de Producto Software (Software Product Line Engi¬neering, SPLE) ha demostrado tener ventajas significativas en el desarrollo de software basado en familias de productos. SPLE es un paradigma que se basa en la reutilización sistemática de un conjunto de características comunes que comparten los productos de un mismo dominio o familia, y la personalización masiva a través de una variabilidad bien definida que diferencia unos productos de otros. Este tipo de desarrollo requiere el diseño inicial de una arquitectura de línea de productos (Product-Line Architecture, PLA) a partir de la cual los productos individuales de la familia son diseñados e implementados. La inversión inicial que hay que realizar en el diseño de PLAs entra en conflicto con la necesidad actual de estar continuamente "abierto al cam¬bio", siendo este cambio cada vez más frecuente y radical en la industria software. Para ser competitivos es inevitable adaptarse al cambio, incluso en las últimas etapas del desarrollo de productos software. Esta tendencia se manifiesta de forma especial en el paradigma de Desarrollo Ágil de Software (Agile Software Development, ASD) y se está extendiendo también al ámbito de SPLE. Con el objetivo de reducir la inversión inicial en el diseño de PLAs en la manera en que se plantea en SPLE, en los último años han surgido nuevos enfoques como la Ingeniera de Líneas de Producto Software Ágiles (Agile Product Line Engineering, APLE). APLE propone el desarrollo de líneas de producto de forma más flexible y adaptable a los cambios, iterativa e incremental. Para ello, es necesario disponer de mecanismos que ayuden y guíen a los arquitectos de líneas de producto en el diseño y evolución ágil de PLAs, mientras se cumple con el principio ágil de estar abierto al cambio. Esta tesis define un proceso para la "construcción y evolución ágil de las arquitecturas de lineas de producto software". A este proceso se le ha denominado Agile Product-Line Architecting (APLA). El proceso APLA proporciona a los arquitectos software un conjunto de modelos para de¬scribir, documentar y trazar PLAs, así como un algoritmo para analizar vel impacto del cambio. Los modelos y el análisis del impacto del cambio ofrecen: Flexibilidad y adaptabilidad a la hora de definir las arquitecturas software, facilitando el cambio durante el diseño incremental e iterativo de PLAs (cambios esperados o previstos) y su evolución (cambios no previstos). Asistencia en la verificación de la integridad arquitectónica mediante el análisis de impacto de los cambios en términos de dependencias entre decisiones de diseño, justificación de las decisiones de diseño, limitaciones, riesgos, etc. Orientación en la toma de decisiones derivadas del cambio mediante el análisis de impacto de los cambios en términos de componentes y conexiones. De esta manera, APLA se presenta como una solución para la construcción y evolución de PLAs de forma que puedan ser fácilmente refinadas iteración tras iteración de un ciclo de vida de líneas de producto ágiles. Dicha solución se ha implementado en una herramienta llamada FPLA (Flexible Product-Line Architecture) y ha sido validada mediante su aplicación en un proyecto de desarrollo de un sistema de gestión de medición en redes de energía eléctrica. Dicho proyecto ha sido desarrollado en una fábrica de software global en colaboración con la Universidad Politécnica de Madrid e Indra Software Labs.

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Semantic Sensor Web infrastructures use ontology-based models to represent the data that they manage; however, up to now, these ontological models do not allow representing all the characteristics of distributed, heterogeneous, and web-accessible sensor data. This paper describes a core ontological model for Semantic Sensor Web infrastructures that covers these characteristics and that has been built with a focus on reusability. This ontological model is composed of different modules that deal, on the one hand, with infrastructure data and, on the other hand, with data from a specific domain, that is, the coastal flood emergency planning domain. The paper also presents a set of guidelines, followed during the ontological model development, to satisfy a common set of requirements related to modelling domain-specific features of interest and properties. In addition, the paper includes the results obtained after an exhaustive evaluation of the developed ontologies along different aspects (i.e., vocabulary, syntax, structure, semantics, representation, and context).

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How to create or integrate large Smart Spaces (considered as mash-ups of sensors and actuators) into the paradigm of ?Web of Things? has been the motivation of many recent works. A cutting-edge approach deals with developing and deploying web-enabled embedded devices with two major objectives: 1) to integrate sensor and actuator technologies into everyday objects, and 2) to allow a diversity of devices to plug to Internet. Currently, developers who want to use this Internet-oriented approach need have solid understanding about sensorial platforms and semantic technologies. In this paper we propose a Resource-Oriented and Ontology-Driven Development (ROOD) methodology, based on Model Driven Architecture (MDA), to facilitate to any developer the development and deployment of Smart Spaces. Early evaluations of the ROOD methodology have been successfully accomplished through a partial deployment of a Smart Hotel.

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Personalized health (p-health) systems can contribute significantly to the sustainability of healthcare systems, though their feasibility is yet to be proven. One of the problems related to their development is the lack of well-established development tools for this domain. As the p-health paradigm is focused on patient self-management, big challenges arise around the design and implementation of patient systems. This paper presents a reference platform created for the development of these applications, and shows the advantages of its adoption in a complex project dealing with cardio-vascular diseases.

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Software architecture is a key factor to scale up Agile Software Development ASD in large softwareintensive systems. Currently, software architectures are more often approached through mechanisms that enable to incrementally design and evolve software architectures aka. agile architecting. Agile architecting should be a light-weight decision-making process, which could be achieved by providing knowledge to assist agile architects in reasoning about changes. This paper presents the novel solution of using change-impact knowledge as the main driver for agile architecting. The solution consists of a Change Impact Analysis technique and a set of models to assist agile architects in the change -decision-making- process by retrieving the change-impact architectural knowledge resulting from adding or changing features iteration after iteration. To validate our approach, we have put our solution into practice by running a project of a metering management system in electric power networks in an i-smart software factory.

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The DNDC (DeNitrification and DeComposition) model was first developed by Li et al. (1992) as a rain event-driven process-orientated simulation model for nitrous oxide, carbon dioxide and nitrogen gas emissions from the agricultural soils in the U.S. Over the last 20 years, the model has been modified and adapted by various research groups around the world to suit specific purposes and circumstances. The Global Research Alliance Modelling Platform (GRAMP) is a UK-led initiative for the establishment of a purposeful and credible web-based platform initially aimed at users of the DNDC model. With the aim of improving the predictions of soil C and N cycling in the context of climate change the objectives of GRAMP are to: 1) to document the existing versions of the DNDC model; 2) to create a family tree of the individual DNDC versions; 3) to provide information on model use and development; and 4) to identify strengths, weaknesses and potential improvements for the model.

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We describe a domain ontology development approach that extracts domain terms from folksonomies and enrich them with data and vocabularies from the Linked Open Data cloud. As a result, we obtain lightweight domain ontologies that combine the emergent knowledge of social tagging systems with formal knowledge from Ontologies. In order to illustrate the feasibility of our approach, we have produced an ontology in the financial domain from tags available in Delicious, using DBpedia, OpenCyc and UMBEL as additional knowledge sources.

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The development of mixed-criticality virtualized multi-core systems poses new challenges that are being subject of active research work. There is an additional complexity: it is now required to identify a set of partitions, and allocate applications to partitions. In this job, a number of issues have to be considered, such as the criticality level of the application, security and dependability requirements, time requirements granularity, etc. MultiPARTES [11] toolset relies on Model Driven Engineering (MDE), which is a suitable approach in this setting, as it helps to bridge the gap between design issues and partitioning concerns. MDE is changing the way systems are developed nowadays, reducing development time. In general, modelling approaches have shown their benefits when applied to embedded systems. These benefits have been achieved by fostering reuse with an intensive use of abstractions, or automating the generation of boiler-plate code.

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La tesis está focalizada en la resolución de problemas de optimización combinatoria, haciendo uso de las opciones tecnológicas actuales que ofrecen las tecnologías de la información y las comunicaciones, y la investigación operativa. Los problemas de optimización combinatoria se resuelven en general mediante programación lineal y metaheurísticas. La aplicación de las técnicas de resolución de los problemas de optimización combinatoria requiere de una elevada carga computacional, y los algoritmos deben diseñarse, por un lado pensando en la efectividad para encontrar buenas soluciones del problema, y por otro lado, pensando en un uso adecuado de los recursos informáticos disponibles. La programación lineal y las metaheurísticas son técnicas de resolución genéricas, que se pueden aplicar a diferentes problemas, partiendo de una base común que se particulariza para cada problema concreto. En el campo del desarrollo de software, los frameworks cumplen esa función de comenzar un proyecto con el trabajo general ya disponible, con la opción de cambiar o extender ese comportamiento base o genérico, para construir el sistema concreto, lo que permite reducir el tiempo de desarrollo, y amplía las posibilidades de éxito del proyecto. En esta tesis se han desarrollado dos frameworks de desarrollo. El framework ILP permite modelar y resolver problemas de programación lineal, de forma independiente al software de resolución de programación lineal que se utilice. El framework LME permite resolver problemas de optimización combinatoria mediante metaheurísticas. Tradicionalmente, las aplicaciones de resolución de problemas de optimización combinatoria son aplicaciones de escritorio que permiten gestionar toda la información de entrada del problema y resuelven el problema en local, con los recursos hardware disponibles. Recientemente ha aparecido un nuevo paradigma de despliegue y uso de aplicaciones que permite compartir recursos informáticos especializados por Internet. Esta nueva forma de uso de recursos informáticos es la computación en la nube, que presenta el modelo de software como servicio (SaaS). En esta tesis se ha construido una plataforma SaaS, para la resolución de problemas de optimización combinatoria, que se despliega sobre arquitecturas compuestas por procesadores multi-núcleo y tarjetas gráficas, y dispone de algoritmos de resolución basados en frameworks de programación lineal y metaheurísticas. Toda la infraestructura es independiente del problema de optimización combinatoria a resolver, y se han desarrollado tres problemas que están totalmente integrados en la plataforma SaaS. Estos problemas se han seleccionado por su importancia práctica. Uno de los problemas tratados en la tesis, es el problema de rutas de vehículos (VRP), que consiste en calcular las rutas de menor coste de una flota de vehículos, que reparte mercancías a todos los clientes. Se ha partido de la versión más clásica del problema y se han hecho estudios en dos direcciones. Por un lado se ha cuantificado el aumento en la velocidad de ejecución de la resolución del problema en tarjetas gráficas. Por otro lado, se ha estudiado el impacto en la velocidad de ejecución y en la calidad de soluciones, en la resolución por la metaheurística de colonias de hormigas (ACO), cuando se introduce la programación lineal para optimizar las rutas individuales de cada vehículo. Este problema se ha desarrollado con los frameworks ILP y LME, y está disponible en la plataforma SaaS. Otro de los problemas tratados en la tesis, es el problema de asignación de flotas (FAP), que consiste en crear las rutas de menor coste para la flota de vehículos de una empresa de transporte de viajeros. Se ha definido un nuevo modelo de problema, que engloba características de problemas presentados en la literatura, y añade nuevas características, lo que permite modelar los requerimientos de las empresas de transporte de viajeros actuales. Este nuevo modelo resuelve de forma integrada el problema de definir los horarios de los trayectos, el problema de asignación del tipo de vehículo, y el problema de crear las rotaciones de los vehículos. Se ha creado un modelo de programación lineal para el problema, y se ha resuelto por programación lineal y por colonias de hormigas (ACO). Este problema se ha desarrollado con los frameworks ILP y LME, y está disponible en la plataforma SaaS. El último problema tratado en la tesis es el problema de planificación táctica de personal (TWFP), que consiste en definir la configuración de una plantilla de trabajadores de menor coste, para cubrir una demanda de carga de trabajo variable. Se ha definido un modelo de problema muy flexible en la definición de contratos, que permite el uso del modelo en diversos sectores productivos. Se ha definido un modelo matemático de programación lineal para representar el problema. Se han definido una serie de casos de uso, que muestran la versatilidad del modelo de problema, y permiten simular el proceso de toma de decisiones de la configuración de una plantilla de trabajadores, cuantificando económicamente cada decisión que se toma. Este problema se ha desarrollado con el framework ILP, y está disponible en la plataforma SaaS. ABSTRACT The thesis is focused on solving combinatorial optimization problems, using current technology options offered by information technology and communications, and operations research. Combinatorial optimization problems are solved in general by linear programming and metaheuristics. The application of these techniques for solving combinatorial optimization problems requires a high computational load, and algorithms are designed, on the one hand thinking to find good solutions to the problem, and on the other hand, thinking about proper use of the available computing resources. Linear programming and metaheuristic are generic resolution techniques, which can be applied to different problems, beginning with a common base that is particularized for each specific problem. In the field of software development, frameworks fulfill this function that allows you to start a project with the overall work already available, with the option to change or extend the behavior or generic basis, to build the concrete system, thus reducing the time development, and expanding the possibilities of success of the project. In this thesis, two development frameworks have been designed and developed. The ILP framework allows to modeling and solving linear programming problems, regardless of the linear programming solver used. The LME framework is designed for solving combinatorial optimization problems using metaheuristics. Traditionally, applications for solving combinatorial optimization problems are desktop applications that allow the user to manage all the information input of the problem and solve the problem locally, using the available hardware resources. Recently, a new deployment paradigm has appeared, that lets to share hardware and software resources by the Internet. This new use of computer resources is cloud computing, which presents the model of software as a service (SaaS). In this thesis, a SaaS platform has been built for solving combinatorial optimization problems, which is deployed on architectures, composed of multi-core processors and graphics cards, and has algorithms based on metaheuristics and linear programming frameworks. The SaaS infrastructure is independent of the combinatorial optimization problem to solve, and three problems are fully integrated into the SaaS platform. These problems have been selected for their practical importance. One of the problems discussed in the thesis, is the vehicle routing problem (VRP), which goal is to calculate the least cost of a fleet of vehicles, which distributes goods to all customers. The VRP has been studied in two directions. On one hand, it has been quantified the increase in execution speed when the problem is solved on graphics cards. On the other hand, it has been studied the impact on execution speed and quality of solutions, when the problem is solved by ant colony optimization (ACO) metaheuristic, and linear programming is introduced to optimize the individual routes of each vehicle. This problem has been developed with the ILP and LME frameworks, and is available in the SaaS platform. Another problem addressed in the thesis, is the fleet assignment problem (FAP), which goal is to create lower cost routes for a fleet of a passenger transport company. It has been defined a new model of problem, which includes features of problems presented in the literature, and adds new features, allowing modeling the business requirements of today's transport companies. This new integrated model solves the problem of defining the flights timetable, the problem of assigning the type of vehicle, and the problem of creating aircraft rotations. The problem has been solved by linear programming and ACO. This problem has been developed with the ILP and LME frameworks, and is available in the SaaS platform. The last problem discussed in the thesis is the tactical planning staff problem (TWFP), which is to define the staff of lower cost, to cover a given work load. It has been defined a very rich problem model in the definition of contracts, allowing the use of the model in various productive sectors. It has been defined a linear programming mathematical model to represent the problem. Some use cases has been defined, to show the versatility of the model problem, and to simulate the decision making process of setting up a staff, economically quantifying every decision that is made. This problem has been developed with the ILP framework, and is available in the SaaS platform.

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Several languages have been proposed for the task of describing networks of systems, either to help on managing, simulate or deploy testbeds for testing purposes. However, there is no one specifically designed to describe the honeynets, covering the specific characteristics in terms of applications and tools included in the honeypot systems that make the honeynet. In this paper, the requirements of honeynet description are studied and a survey of existing description languages is presented, concluding that a CIM (Common Information Model) match the basic requirements. Thus, a CIM like technology independent honeynet description language (TIHDL) is proposed. The language is defined being independent of the platform where the honeynet will be deployed later, and it can be translated, either using model-driven techniques or other translation mechanisms, into the description languages of honeynet deployment platforms and tools. This approach gives flexibility to allow the use of a combination of heterogeneous deployment platforms. Besides, a flexible virtual honeynet generation tool (HoneyGen) based on the approach and description language proposed and capable of deploying honeynets over VNX (Virtual Networks over LinuX) and Honeyd platforms is presented for validation purposes.