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A Concept for Testing Robustness and Safety of the Context-Aware Behaviour of Autonomous Systems

机译:用于测试自主系统的环境感知行为的鲁棒性和安全性的概念

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Autonomous systems are used nowadays in more and more sectors from vehicles to domestic robots. They can make decisions on their own or interact with humans, thus their robustness and safety are properties of crucial importance. Due to the adaptive and context-aware nature of these systems, the testing of such properties is especially challenging. In this paper, we propose a model-based testing approach to capture the context and requirements of such systems, to automatically generate test data representing complex situations, and to evaluate test traces and compute test coverage metrics.
机译:现在,自动系统在越来越多的车辆到国内机器人。他们可以自己做出决定或与人类进行互动,因此他们的稳健性和安全性是至关重要的性质。由于这些系统的自适应和背景感知性质,这些属性的测试尤其具有挑战性。在本文中,我们提出了一种基于模型的测试方法来捕获这种系统的上下文和要求,自动生成代表复杂情况的测试数据,并评估测试迹线和计算测试覆盖度量。

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