Z3 and SMT in Industrial R&D

  • Nikolaj BjørnerEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10951)


Theorem proving has a proud history of elite academic pursuit and select industrial use. Impact, when predicated on acquiring the internals of a formalism or proof environment, is gated on skilled and idealistic users. In the case of automatic theorem provers known as Satisfiability Modulo Theories, SMT, solvers, the barrier of entry is shifted to tool builders and their domains. SMT solvers typically provide convenient support for domains that are prolific in software engineering and have in the past decade found widespread use cases in both academia and industry. We describe some of the background developing the Z3 solver, the factors that have played an important role in shaping its use, and an outlook on further development and use.


  1. 1.
    Barrett, C., Pascal, P., Tinelli, C.: The Satisfiability Modulo Theories Library (SMT-LIB) (2016).
  2. 2.
    de Moura, L., Bjørner, N.: Efficient E-matching for SMT solvers. In: Pfenning, F. (ed.) CADE 2007. LNCS (LNAI), vol. 4603, pp. 183–198. Springer, Heidelberg (2007). Scholar
  3. 3.
    Godefroid, P., Klarlund, N., Sen, K.: DART: directed automated random testing. In: Proceedings of the ACM SIGPLAN 2005 Conference on Programming Language Design and Implementation, Chicago, IL, USA, June 12–15, pp. 213–223 (2005)Google Scholar
  4. 4.
    Moskewicz, M.W., Madigan, C.F., Zhao, Y., Zhang, L., Malik, S.: Chaff: engineering an efficient SAT solver. In: Proceedings of the 38th Design Automation Conference, DAC 2001, Las Vegas, NV, USA, June 18–22, pp. 530–535 (2001)Google Scholar
  5. 5.
    Marques Silva, J.P., Sakallah, K.A.: GRASP: a search algorithm for propositional satisfiability. IEEE Trans. Comput. 48(5), 506–521 (1999)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Microsoft ResearchRedmondUSA

Personalised recommendations