Abstract models of system-level behaviour have applications in design exploration, analysis, testing and verification. We describe a new algorithm for automatically extracting useful models, as automata, from execution traces of a HW/SW system driven by software exercising a use-case of interest. Our algorithm leverages modern program synthesis techniques to generate predicates on automaton edges, succinctly describing system behaviour. It employs trace segmentation to tackle complexity for long traces. We learn concise models capturing transaction-level, system-wide behaviour--experimentally demonstrating the approach using traces from a variety of sources, including the x86 QEMU virtual platform and the Real-Time Linux kernel.

中文翻译：

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从长执行跟踪中学习简洁模型

系统级行为的抽象模型在设计探索、分析、测试和验证中具有应用。我们描述了一种新算法，用于从由执行感兴趣用例的软件驱动的 HW/SW 系统的执行轨迹中自动提取有用的模型作为自动机。我们的算法利用现代程序综合技术在自动机边缘上生成谓词，简洁地描述系统行为。它采用跟踪分割来解决长跟踪的复杂性。我们学习了捕获事务级、系统范围行为的简洁模型——使用来自各种来源的跟踪来实验性地演示该方法，包括 x86 QEMU 虚拟平台和实时 Linux 内核。