63,182 research outputs found

    Spinal Test Suites for Software Product Lines

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    A major challenge in testing software product lines is efficiency. In particular, testing a product line should take less effort than testing each and every product individually. We address this issue in the context of input-output conformance testing, which is a formal theory of model-based testing. We extend the notion of conformance testing on input-output featured transition systems with the novel concept of spinal test suites. We show how this concept dispenses with retesting the common behavior among different, but similar, products of a software product line.Comment: In Proceedings MBT 2014, arXiv:1403.704

    Integrated Design Tools for Embedded Control Systems

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    Currently, computer-based control systems are still being implemented using the same techniques as 10 years ago. The purpose of this project is the development of a design framework, consisting of tools and libraries, which allows the designer to build high reliable heterogeneous real-time embedded systems in a very short time at a fraction of the present day costs. The ultimate focus of current research is on transformation control laws to efficient concurrent algorithms, with concerns about important non-functional real-time control systems demands, such as fault-tolerance, safety,\ud reliability, etc.\ud The approach is based on software implementation of CSP process algebra, in a modern way (pure objectoriented design in Java). Furthermore, it is intended that the tool will support the desirable system-engineering stepwise refinement design approach, relying on past research achievements ¿ the mechatronics design trajectory based on the building-blocks approach, covering all complex (mechatronics) engineering phases: physical system modeling, control law design, embedded control system implementation and real-life realization. Therefore, we expect that this project will result in an\ud adequate tool, with results applicable in a wide range of target hardware platforms, based on common (off-theshelf) distributed heterogeneous (cheap) processing units

    Fast Damage Recovery in Robotics with the T-Resilience Algorithm

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    Damage recovery is critical for autonomous robots that need to operate for a long time without assistance. Most current methods are complex and costly because they require anticipating each potential damage in order to have a contingency plan ready. As an alternative, we introduce the T-resilience algorithm, a new algorithm that allows robots to quickly and autonomously discover compensatory behaviors in unanticipated situations. This algorithm equips the robot with a self-model and discovers new behaviors by learning to avoid those that perform differently in the self-model and in reality. Our algorithm thus does not identify the damaged parts but it implicitly searches for efficient behaviors that do not use them. We evaluate the T-Resilience algorithm on a hexapod robot that needs to adapt to leg removal, broken legs and motor failures; we compare it to stochastic local search, policy gradient and the self-modeling algorithm proposed by Bongard et al. The behavior of the robot is assessed on-board thanks to a RGB-D sensor and a SLAM algorithm. Using only 25 tests on the robot and an overall running time of 20 minutes, T-Resilience consistently leads to substantially better results than the other approaches

    Modular Networks: Learning to Decompose Neural Computation

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    Scaling model capacity has been vital in the success of deep learning. For a typical network, necessary compute resources and training time grow dramatically with model size. Conditional computation is a promising way to increase the number of parameters with a relatively small increase in resources. We propose a training algorithm that flexibly chooses neural modules based on the data to be processed. Both the decomposition and modules are learned end-to-end. In contrast to existing approaches, training does not rely on regularization to enforce diversity in module use. We apply modular networks both to image recognition and language modeling tasks, where we achieve superior performance compared to several baselines. Introspection reveals that modules specialize in interpretable contexts.Comment: NIPS 201

    Torque control strategy for an axial flux switched reluctance machine

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    This paper reflects the work done to design a torque control strategy for an axial flux switched reluctance machine. The general electrical model is first presented but as the switched reluctance machine behaves nonlinearly1 a (three-dimensional) finite element method characterization is performed, so the nonlinearity may be considered. Once the machine is characterized in FEM a Simulink model is developed where a torque control strategy is proposed. Then, both the machine and the control are experimentally tested. The control setting, and the obtained real performance results are also presented in this document. Finally, the most outstanding conclusions about the control strategy are captured. Main difficulties encountered during the implementation of the control strategy are also collected

    A Case Study on Formal Verification of Self-Adaptive Behaviors in a Decentralized System

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    Self-adaptation is a promising approach to manage the complexity of modern software systems. A self-adaptive system is able to adapt autonomously to internal dynamics and changing conditions in the environment to achieve particular quality goals. Our particular interest is in decentralized self-adaptive systems, in which central control of adaptation is not an option. One important challenge in self-adaptive systems, in particular those with decentralized control of adaptation, is to provide guarantees about the intended runtime qualities. In this paper, we present a case study in which we use model checking to verify behavioral properties of a decentralized self-adaptive system. Concretely, we contribute with a formalized architecture model of a decentralized traffic monitoring system and prove a number of self-adaptation properties for flexibility and robustness. To model the main processes in the system we use timed automata, and for the specification of the required properties we use timed computation tree logic. We use the Uppaal tool to specify the system and verify the flexibility and robustness properties.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432
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