Preprocessing in Incremental SAT

  • Alexander Nadel
  • Vadim Ryvchin
  • Ofer Strichman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7317)


Preprocessing of CNF formulas is an invaluable technique when attempting to solve large formulas, such as those that model industrial verification problems. Unfortunately, the best combination of preprocessing techniques, which involve variable elimination combined with subsumption, is incompatible with incremental satisfiability. The reason is that soundness is lost if a variable is eliminated and later reintroduced. Look-ahead is a known technique to solve this problem, which simply blocks elimination of variables that are expected to be part of future instances. The problem with this technique is that it relies on knowing the future instances, which is impossible in several prominent domains. We show a technique for this realm, which is empirically far better than the known alternatives: running without preprocessing at all or applying preprocessing separately at each step.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bacchus, F., Winter, J.: Effective Preprocessing with Hyper-Resolution and Equality Reduction. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 341–355. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Le Berre, D.: Exploiting the real power of unit propagation lookahead. Electronic Notes in Discrete Mathematics 9, 59–80 (2001)CrossRefGoogle Scholar
  3. 3.
    Eén, N., Biere, A.: Effective Preprocessing in SAT Through Variable and Clause Elimination. In: Bacchus, F., Walsh, T. (eds.) SAT 2005. LNCS, vol. 3569, pp. 61–75. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  4. 4.
    Eén, N., Sörensson, N.: An Extensible SAT-solver. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 502–518. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  5. 5.
    Eén, N., Sörensson, N.: Temporal induction by incremental SAT solving. Electr. Notes Theor. Comput. Sci. 89(4), 543–560 (2003)CrossRefGoogle Scholar
  6. 6.
    Franzén, A., Cimatti, A., Nadel, A., Sebastiani, R., Shalev, J.: Applying smt in symbolic execution of microcode. In: FMCAD, pp. 121–128 (2010)Google Scholar
  7. 7.
    Kupferschmid, S., Lewis, M.D.T., Schubert, T., Becker, B.: Incremental preprocessing methods for use in BMC. Formal Methods in System Design 39(2), 185–204 (2011)CrossRefGoogle Scholar
  8. 8.
    Nadel, A., Ryvchin, V., Strichman, O.: Preprocessing in incremental SAT. Technical Report IE/IS-2012-02, Industrial Engineering, Technion (2012),
  9. 9.
    Shtrichman, O.: Pruning Techniques for the SAT-Based Bounded Model Checking Problem. In: Margaria, T., Melham, T.F. (eds.) CHARME 2001. LNCS, vol. 2144, pp. 58–70. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  10. 10.
    Whittemore, J., Kim, J., Sakallah, K.: SATIRE: a new incremental satisfiability engine. In: IEEE/ACM Design Automation Conference, DAC (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alexander Nadel
    • 1
  • Vadim Ryvchin
    • 1
    • 2
  • Ofer Strichman
    • 2
  1. 1.Design Technology Solutions GroupIntel CorporationHaifaIsrael
  2. 2.Information Systems Engineering, IETechnionHaifaIsrael

Personalised recommendations