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  • Deterministic Executable Models Verified Efficiently at Runtime: An Architecture for Robotic and Embedded Systems

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    Author(s)
    Estivill-Castro, Vladimir
    Hexel, Rene
    Griffith University Author(s)
    Hexel, Rene
    Year published
    2017
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    Abstract
    We show an architecture that enables runtime verification. Runtime verification focusses on the design of formal languages for the specification of properties that must hold during runtime. In this paper, we take matters one step further and describe a uniform modelling and development paradigm for software systems that can monitor the quality of software systems as they execute, set-up, tear-down and enforce quality behaviour on the fly. Our paradigm for modelling behaviour enables efficient execution, validation, simulation, and runtimeverification. The models are executable and efficient because they are compiled (not ...
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    We show an architecture that enables runtime verification. Runtime verification focusses on the design of formal languages for the specification of properties that must hold during runtime. In this paper, we take matters one step further and describe a uniform modelling and development paradigm for software systems that can monitor the quality of software systems as they execute, set-up, tear-down and enforce quality behaviour on the fly. Our paradigm for modelling behaviour enables efficient execution, validation, simulation, and runtimeverification. The models are executable and efficient because they are compiled (not interpreted). Moreover, they can be developed using test-driven development, where tests are models derived from requirements. We illustrate the approach with case studies from robotics and embedded systems.
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    Conference Title
    MODELSWARD: PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON MODEL-DRIVEN ENGINEERING AND SOFTWARE DEVELOPMENT
    Volume
    2017-January
    DOI
    https://doi.org/10.5220/0006116700290040
    Copyright Statement
    © 2017 ScitePress. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
    Subject
    Autonomous agents and multiagent systems
    Intelligent robotics
    Mixed initiative and human-in-the-loop
    Social robotics
    Reinforcement learning
    Publication URI
    http://hdl.handle.net/10072/355318
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    • Conference outputs

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