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Heuristics for Deriving Adaptive Homing and Distinguishing Sequences for Nondeterministic Finite State Machines

机译:不确定性有限状态机的自适应归位和区分序列的启发式方法

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Distinguishing Sequences (DS) and Homing Sequences (HS) are used for state identification purposes in Finite State Machine (FSM) based testing. For deterministic FSMs, DS and HS related problems are well studied, for both preset and adaptive cases. There are also recent algorithms for checking the existence and constructing Adaptive DS and Adaptive HS for nondeterministic FSMs. However, most of the related problems are proven to be PSPACE-complete, while the worst case height of Adaptive DS and HS is known to be exponential. Therefore, novel heuristics and FSM classes where they can be applied need to be provided for effective derivation of such sequences. In this paper, we present a work in progress on the minimization of Adaptive DS and Adaptive HS for nondeterministic FSMs.
机译:区分序列(DS)和归位序列(HS)用于基于有限状态机(FSM)的测试中的状态识别。对于确定性FSM,对于预设和自适应情况,都对DS和HS相关问题进行了深入研究。最近还存在用于检查是否存在并为非确定性FSM构造自适应DS和自适应HS的算法。但是,大多数相关问题被证明是PSPACE完全的,而Adaptive DS和HS的最坏情况高度已知是指数级的。因此,需要提供可应用它们的新颖启发式和FSM类,以有效推导此类序列。在本文中,我们提出了关于将不确定性FSM的自适应DS和自适应HS最小化的工作。

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