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An abstraction-guided simulation approach using Markov models for microprocessor verification

机译:一种使用Markov模型进行微处理器验证的抽象引导仿真方法

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In order to combine the power of simulation-based and formal techniques, semi-formal methods have been widely explored. Among these methods, abstraction-guided simulation is a quite promising one. In this paper, we propose an abstraction-guided simulation approach aiming to cover hard-to-reach states in functional verification of microprocessors. A Markov model is constructed utilizing the high level functional specification, i.e. ISA. Such model integrates vector correlations. Furthermore, several strategies utilizing abstraction information are proposed as an effective guidance to the test generation. Experimental results on two complex microprocessors show that our approach is more efficient in covering hard-to-reach states than similar methods. Comparing with some work with other intelligent engines, our approach could guarantee higher hit ratio of target states without efficiency loss.
机译:为了结合基于仿真和形式技术的力量,已广泛探索半正式方法。 在这些方法中,抽象引导的模拟是一个非常有前途的模拟。 在本文中,我们提出了一种抽象引导的模拟方法,其旨在在微处理器的功能验证中涵盖难以达到的状态。 利用高电平函数规范,即ISA构建马尔可夫模型。 这种模型集成了矢量相关性。 此外,提出了利用抽象信息的若干策略作为对测试生成的有效指导。 两个复杂的微处理器上的实验结果表明,我们的方法在覆盖难以达到的状态方面比类似方法更有效。 与其他智能发动机的一些工作相比,我们的方法可以保证目标国家的较高比率而无需效率损失。

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