Learning GR(1) Specifications from Traces
This work addresses the problem of automatically mining synthesizable GR(1) specifications from system execution traces by introducing GR1MINE, an efficient and specialized mining framework. GR1MINE integrates GR(1) temporal skeleton analysis, incremental formula enumeration, and conflict-driven clause learning, leveraging SAT solving to prune redundant search paths and substantially improve both efficiency and coverage of mined specifications. As the first dedicated framework for the GR(1) fragment, GR1MINE achieves a speedup of over 30× compared to general-purpose LTL mining tools on the Syntech benchmark suite and recovers more than twice as many realizable specifications on non-GR(1) instances from SYNTCOMP.
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