Efficient conflict analysis for finding all satisfying assignments of a boolean circuit

  • Authors:

  • HoonSang Jin;HyoJung Han;Fabio Somenzi

  • Affiliations:

  • University of Colorado at Boulder;University of Colorado at Boulder;University of Colorado at Boulder

  • Venue:
  • TACAS'05 Proceedings of the 11th international conference on Tools and Algorithms for the Construction and Analysis of Systems
  • Year:
  • 2005

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Abstract

Finding all satisfying assignments of a propositional formula has many applications to the synthesis and verification of hardware and software. An approach to this problem that has recently emerged augments a clause-recording propositional satisfiability solver with the ability to add “blocking clauses.” One generates a blocking clause from a satisfying assignment by taking its complement. The resulting clause prevents the solver from visiting the same solution again. Every time a blocking clause is added the search is resumed until the instance becomes unsatisfiable. Various optimization techniques are applied to get smaller blocking clauses, since enumerating each satisfying assignment would be very inefficient. In this paper, we present an improved algorithm for finding all satisfying assignments for a generic Boolean circuit. Our work is based on a hybrid SAT solver that can apply conflict analysis and implications to both CNF formulae and general circuits. Thanks to this capability, reduction of the blocking clauses can be efficiently performed without altering the solver's state (e.g., its decision stack). This reduces the overhead incurred in resuming the search. Our algorithm performs conflict analysis on the blocking clause to derive a proper conflict clause for the modified formula. Besides yielding a valid, nontrivial backtracking level, the derived conflict clause is usually more effective at pruning the search space, since it may encompass both satisfiable and unsatisfiable points. Another advantage is that the derived conflict clause provides more flexibility in guiding the score-based heuristics that select the decision variables. The efficiency of our new algorithm is demonstrated by our preliminary results on SAT-based unbounded model checking of VIS benchmark models.