The Sat4j library, release 2.2 system description. Sat4j is a java library for solving boolean satisfaction and optimization problems. It can solve SAT, MAXSAT, Pseudo-Boolean, Minimally Unsatisfiable Subset (MUS) problems. Being in Java, the promise is not to be the fastest one to solve those problems (a SAT solver in Java is about 3.25 times slower than its counterpart in C++), but to be full featured, robust, user friendly, and to follow Java design guidelines and code conventions (checked using static analysis of the source code). The library is designed for flexibility, by using heavily the decorator and strategy design patterns. Furthermore, Sat4j is open source, under the dual business friendly Eclipse Public License and academic friendly GNU LGPL license.

References in zbMATH (referenced in 75 articles )

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  1. Cai, Shaowei; Lei, Zhendong: Old techniques in new ways: clause weighting, unit propagation and hybridization for maximum satisfiability (2020)
  2. Chen, Qian Matteo; Finzi, Alberto; Mancini, Toni; Melatti, Igor; Tronci, Enrico: MILP, pseudo-Boolean, and OMT solvers for optimal fault-tolerant placements of relay nodes in mission critical wireless networks (2020)
  3. Drechsler, Rolf (ed.); Soeken, Mathias (ed.): Advanced Boolean techniques. Selected papers from the 13th international workshop on Boolean problems, Bremen, Germany, September 19--21, 2018 (2020)
  4. Rocha, Thiago Alves; Martins, Ana Teresa; Ferreira, Francicleber Martins: Synthesis of a DNF formula from a sample of strings using Ehrenfeucht-Fraïssé games (2020)
  5. Showkatbakhsh, Mehrdad; Shoukry, Yasser; Diggavi, Suhas N.; Tabuada, Paulo: Securing state reconstruction under sensor and actuator attacks: theory and design (2020)
  6. Demirović, Emir; Musliu, Nysret; Winter, Felix: Modeling and solving staff scheduling with partial weighted maxSAT (2019)
  7. Ebner, Gabriel: Herbrand constructivization for automated intuitionistic theorem proving (2019)
  8. Liao, Xiaojuan; Koshimura, Miyuki; Nomoto, Kazuki; Ueda, Suguru; Sakurai, Yuko; Yokoo, Makoto: Improved WPM encoding for coalition structure generation under MC-nets (2019)
  9. Varshosaz, Mahsa; Luthmann, Lars; Mohr, Paul; Lochau, Malte; Mousavi, Mohammad Reza: Modal transition system encoding of featured transition systems (2019)
  10. Zha, Aolong; Koshimura, Miyuki; Fujita, Hiroshi: (N)-level modulo-based CNF encodings of pseudo-Boolean constraints for MaxSAT (2019)
  11. Beyersdorff, Olaf; Chew, Leroy; Mahajan, Meena; Shukla, Anil: Understanding cutting planes for QBFs (2018)
  12. Lagniez, Jean-Marie; Le Berre, Daniel; de Lima, Tiago; Montmirail, Valentin: An assumption-based approach for solving the Minimal S5-Satisfiability problem (2018)
  13. Nadel, Alexander: Solving MaxSAT with bit-vector optimization (2018)
  14. Ansótegui, Carlos; Gabàs, Joel: WPM3: an (in)complete algorithm for weighted partial MaxSAT (2017)
  15. Cohen, D.; Crampton, J.; Gutin, G.; Wahlström, M.: Parameterized complexity of the workflow satisfiability problem (2017)
  16. Demirović, Emir; Musliu, Nysret: maxSAT-based large neighborhood search for high school timetabling (2017)
  17. Feng, Yu; Martins, Ruben; Wang, Yuepeng; Dillig, Isil; Reps, Thomas W.: Component-based synthesis for complex APIs (2017)
  18. Giesl, Jürgen; Aschermann, Cornelius; Brockschmidt, Marc; Emmes, Fabian; Frohn, Florian; Fuhs, Carsten; Hensel, Jera; Otto, Carsten; Plücker, Martin; Schneider-Kamp, Peter; Ströder, Thomas; Swiderski, Stephanie; Thiemann, René: Analyzing program termination and complexity automatically with \textsfAProVE (2017)
  19. Hutter, Frank; Lindauer, Marius; Balint, Adrian; Bayless, Sam; Hoos, Holger; Leyton-Brown, Kevin: The configurable SAT solver challenge (CSSC) (2017)
  20. Ignatiev, Alexey; Morgado, Antonio; Marques-Silva, Joao: On tackling the limits of resolution in SAT solving (2017)

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