MiniSat

An extensible SAT-solver. MiniSat is a minimalistic, open-source SAT solver, developed to help researchers and developers alike to get started on SAT. It is released under the MIT licence, and is currently used in a number of projects (see ”Links”). On this page you will find binaries, sources, documentation and projects related to MiniSat, including the Pseudo-boolean solver MiniSat+ and the CNF minimizer/preprocessor SatELite. Together with SatELite, MiniSat was recently awarded in the three industrial categories and one of the ”crafted” categories of the SAT 2005 competition.


References in zbMATH (referenced in 470 articles , 1 standard article )

Showing results 1 to 20 of 470.
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  1. Biere, Armin; Kröning, Daniel: SAT-based model checking (2018)
  2. Blanchette, Jasmin Christian; Fleury, Mathias; Lammich, Peter; Weidenbach, Christoph: A verified SAT solver framework with learn, forget, restart, and incrementality (2018)
  3. Cerutti, Federico; Vallati, Mauro; Giacomin, Massimiliano: On the impact of configuration on abstract argumentation automated reasoning (2018)
  4. Cheng, Xi; Zhou, Min; Song, Xiaoyu; Gu, Ming; Sun, Jiaguang: Parallelizing SMT solving: lazy decomposition and conciliation (2018)
  5. Eggensperger, Katharina; Lindauer, Marius; Hoos, Holger H.; Hutter, Frank; Leyton-Brown, Kevin: Efficient benchmarking of algorithm configurators via model-based surrogates (2018)
  6. Ignatiev, Alexey; Morgado, Antonio; Marques-Silva, Joao: PySAT: A Python toolkit for prototyping with SAT oracles (2018)
  7. Marques-Silva, Joao; Malik, Sharad: Propositional SAT solving (2018)
  8. Zese, Riccardo; Bellodi, Elena; Riguzzi, Fabrizio; Cota, Giuseppe; Lamma, Evelina: Tableau reasoning for description logics and its extension to probabilities (2018)
  9. Abramé, André; Habet, Djamal; Toumi, Donia: Improving configuration checking for satisfiable random $k$-SAT instances (2017)
  10. Al-Saedi, Balasim; Fourdrinoy, Olivier; Grégoire, Éric; Mazure, Bertrand; Saïs, Lakhdar: About some UP-based polynomial fragments of SAT (2017)
  11. Audemard, Gilles; Lagniez, Jean-Marie; Szczepanski, Nicolas; Tabary, Sébastien: A distributed version of Syrup (2017)
  12. Berg, Jeremias; Järvisalo, Matti: Cost-optimal constrained correlation clustering via weighted partial maximum satisfiability (2017)
  13. Bhattacharyya, Anirban; Mokhov, Andrey; Pierce, Ken: An empirical comparison of formalisms for modelling and analysis of dynamic reconfiguration of dependable systems (2017)
  14. Cabodi, G.; Camurati, P. E.; Mishchenko, A.; Palena, M.; Pasini, P.: SAT solver management strategies in IC3: an experimental approach (2017)
  15. Chakraborty, Supratik; Khasidashvili, Zurab; Seger, Carl-Johan H.; Gajavelly, Rajkumar; Haldankar, Tanmay; Chhatani, Dinesh; Mistry, Rakesh: Symbolic trajectory evaluation for word-level verification: theory and implementation (2017)
  16. Chihani, Zakaria; Marre, Bruno; Bobot, François; Bardin, Sébastien: Sharpening constraint programming approaches for bit-vector theory (2017)
  17. Dekker, Jip J.; Björdal, Gustav; Carlsson, Mats; Flener, Pierre; Monette, Jean-Noël: Auto-tabling for subproblem presolving in minizinc (2017)
  18. Devriendt, Jo; Bogaerts, Bart; Bruynooghe, Maurice: Symmetric explanation learning: effective dynamic symmetry handling for SAT (2017)
  19. Deza, Michel-Marie; Dutour Sikirić, Mathieu: Lego-like spheres and tori (2017)
  20. Egly, Uwe; Kronegger, Martin; Lonsing, Florian; Pfandler, Andreas: Conformant planning as a case study of incremental QBF solving (2017)

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Further publications can be found at: http://minisat.se/Papers.html