Com os grandes avanços recentes dos sistemas computacionais, houve a possibilidade de ascensão de dispositivos inovadores, como os modernos telefones celulares e tablets com telas sensíveis ao toque. Para gerenciar adequadamente estas diversas interfaces é necessário utilizar o software dependente do hardware (HdS), que é responsável pelo controle e acesso a estes dispositivos. Além deste complexo arranjo de componentes, para atender a crescente demanda por mais funcionalidades integradas, o paradigma de multiprocessamento vem sendo adotado para aumentar o desempenho das plataformas. Devido à lacuna de produtividade de sistemas, tanto a indústria como a academia têm pesquisado processos mais eficientes para construir e simular sistemas cada vez mais complexos. A premissa dos trabalhos do estado da arte está em trabalhar com modelos com alto nível de abstração e de precisão que permitam ao projetista avaliar rapidamente o sistema, sem ter que depender de lentos e complexos modelos baseados em ISS. Neste trabalho é definido um conjunto de construtores para modelagem de plataformas baseadas em processadores, com suporte para desenvolvimento de HdS e reusabilidade dos componentes, técnicas para estimativa estática de tempo simulado em ambiente nativo de simulação e suporte para plataformas multiprocessadas. Foram realizados experimentos com aplica- ções de entrada e saída intensiva, computação intensiva e multiprocessada, com ganho médio de desempenho da ordem de 1.000 vezes e precisão de estimativas com erro médio inferior a 3%, em comparação com uma plataforma de referência baseada em ISS._________________________________________________________________________________________ ABSTRACT: The amazing advances of computer systems technology enabled the rise of innovative devices, such as modern touch sensitive cell phones and tablets. To properly manage these various interfaces, it is required the use of the Hardwaredependent Software (HdS) that is responsible for these devices control and access. Besides this complex arrangement of components, to meet the growing demand for more integrated features, the multiprocessing paradigm has been adopted to increase the platforms performance. Due to the system design gap, both industry and academia have been researching for more efficient processes to build and simulate systems with this increasingly complexity. The premise of the state of art works is the development of high level of abstraction and precise models to enable the designer to quickly evaluate the system, without having to rely on slow and complex models based on instruction set simulators (ISS). This work defined a set of constructors for processor-based platforms modeling, supporting HdS development and components reusability, techniques for static simulation timing estimation in native environment and support for multiprocessor platforms. Experiments were carried out with input and output intensive, compute intensive and multiprocessed applications leading to an average performance speed up of about 1,000 times and average timing estimation accuracy of less than 3%, when compared with a reference platform based on ISS.

Role-based modeling has been investigated for over 35 years as a promising paradigm to model complex, dynamic systems. Although current software systems are characterized by increasing complexity and context-dependence, all this research had almost no influence on current software development practice, still being discussed in recent literature. One reason for this is the lack of a coherent, comprehensive, readily applicable notion of roles. Researchers focused either on relational roles or context-dependent roles rather then combining both natures. Currently, there is no role-based modeling language sufficiently incorporating both the relational and context-dependent nature of roles together with the various proposed constraints. Hence, this paper formalizes a full-fledged role-based modeling language supporting both natures. To show its sufficiency and adequacy, a real world example is employed.

Since the year 1977, role modeling has been continuously investigated as promising paradigm to model complex, dynamic systems. However, this research had almost no influence on the design of todays increasingly complex and context-sensitive software systems. The reason for that is twofold. First, most modeling languages focused either on the behavioral, relational or context-dependent nature of roles rather than combining them. Second, there is a lack of tool support for the design, validation, and generation of role-based software systems. In particular, there exists no graphical role modeling editor supporting the three natures as well as the various proposed constraints. To overcome this deficiency, we introduce the Full-fledged Role Modeling Editor (FRaMED), a graphical modeling editor embracing all natures of roles and modeling constraints featuring generators for a formal representation and source code of a rolebased programming language. To show its applicability for the development of role-based software systems, an example from the banking domain is employed.

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Livestock grazing is the most important type of land-use in arid and semi-arid regions. In these regions, uncertain and highly variable climate conditions cause scarce and spatio-temporally variable resource availability. The major challenge to livestock grazing is the efficient utilisation of these resources without running the risk of degradation. Therefore, well adapted grazing strategies that consider both local environmental characteristics and the farmers' individual needs and perceptions are crucial for sustaining human livelihoods. Particularly, rotational grazing is presumed to render adaptation to spatio-temporal heterogeneities possible. A systematic investigation, however, that analyses the interrelations between the major components of rotational grazing systems on appropriate spatial and temporal scales was missing so far. This doctoral thesis investigates different management strategies for sustainable livestock grazing in semi-arid rangelands. Using an integrated modelling approach, it enters into the question: how to adapt grazing systems to spatio-temporal heterogeneous rangeland conditions, variable and changing climate conditions, and different individual needs and goals of livestock farmers? In order to address these issues, the taken approach tackles both methodical challenges and applied concerns. In the first part of this study, a generic modelling framework is developed that incorporates important components of grazing systems on appropriate spatial and temporal scales. To parameterise the model, a pattern-oriented approach is developed that uses qualitative patterns to derive a broad range of plausible parameter sets supporting a general model analysis. In the second part, a variety of management strategies is explored under different climatic, ecological, and economic conditions. The research focuses in particular on combined effects between and relative importance of different management components. The question how the results of different management strategies depend on the type of vegetation is investigated. Furthermore, the performance of rotational grazing strategies is analysed under different economic requirements and rainfall conditions. The study also identifies management strategies that are suitable to adapt a grazing system to spatio-temporally variable rangeland conditions. Overall, this thesis contributes to a general understanding of basic principles for adaptation to spatio-temporal heterogeneities as well as the interplay of different management components. The results allow an evaluation of management strategies for specific situations and the identification of strategies that are robust to a broad range of situations including different aspects of global change.