Falsification of hybrid systems is attracting ever-growing attention in quality assurance of Cyber-Physical Systems (CPS) as a practical alternative to exhaustive formal verification. In falsification, one searches for a falsifying input that drives a given black-box model to output an undesired signal. In this paper, we identify input constraints---such as the constraint "the throttle and brake pedals should not pressed simultaneously" for an automotive powertrain model---as a key factor for the practical value of falsification methods. We propose three approaches for systematically addressing input constraints in optimization-based falsification, two among which come from the lexicographic method studied in the context of constrained multi-objective optimization. Our experiments show the approaches' effectiveness.

中文翻译：

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混合系统伪造中的约束反例：基于惩罚的方法

作为详尽形式验证的实用替代方案，混合系统的伪造在网络物理系统 (CPS) 的质量保证方面引起了越来越多的关注。在伪造中，人们搜索一个伪造输入，该输入驱动给定的黑盒模型输出不需要的信号。在本文中，我们确定了输入约束——例如汽车动力系统模型的“油门和制动踏板不应同时踩下”的约束——作为证伪方法实用价值的关键因素。我们提出了三种方法来系统地解决基于优化的证伪中的输入约束，其中两种来自在约束多目标优化的背景下研究的词典方法。我们的实验显示了这些方法的有效性。