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models of system-level behaviour have applications in designexploration, analysis, testing and verification. We describe a new algorithmfor automatically extracting useful models, as automata, from execution tracesof a HW/SW system driven by software exercising a use-case of interest. Ouralgorithm leverages modern program synthesis techniques to generate predicateson automaton edges, succinctly describing system behaviour. It employs tracesegmentation to tackle complexity for long traces. We learn concise modelscapturing transaction-level, system-wide behaviour--experimentallydemonstrating the approach using traces from a variety of sources, includingthe x86 QEMU virtual platform and the Real-Time Linux kernel.

Learning Concise Models from Long Execution Traces