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The theory of quantifier-free bit-vectors (QF_BV) is of paramount importancein software verification. The standard approach for satisfiability checkingreduces the bit-vector problem to a Boolean problem, leveraging the powerfulSAT solving techniques and their conflict-driven clause learning (CDCL)mechanisms. Yet, this bit-level approach loses the structure of the initialbit-vector problem. We propose a conflict-driven, word-level, combinableconstraints learning for the theory of quantifier-free bit-vectors. This workpaves the way to truly word-level decision procedures for bit-vectors, takingfull advantage of word-level propagations recently designed in CP and SMTcommunities.

CDCL-inspired Word-level Learning for Bit-vector Constraint Solving