CVC4 1.2 released

We are delighted to announce version 1.2 of CVC4, the open-source flagship SMT solver developed at New York University and the University of Iowa, available at

In version 1.2, real arithmetic now has three simplex solvers for exact precision linear arithmetic: the classical dual solver and two new solvers based on techniques for minimizing the sum of infeasibilities.  GLPK can now be used as a heuristic backup to the exact precision solvers.  See cvc4 --help for more information on enabling these solvers.

Additionally, this release:

  • adds support for “bit0″ and “bit1″ bitvector constants in SMT-LIB v1.2
  • has support for theory “alternates”: new ability to prototype new decision procedures that are selectable at runtime
  • includes important bug fixes and performance improvements over the previous stable release (version 1.1)

We welcome feedback, feature requests, contributions, and collaborations.  It is our hope that CVC4 will become a research platform for a broad and diverse set of users and developers.  If you are interested in getting involved with the project, please contact a member of the development team:

  •   Clark Barrett (NYU, project leader)
  •   Cesare Tinelli (U Iowa, project leader)
  •   Kshitij Bansal (NYU)
  •   François Bobot (Paris-Diderot University)
  •   Chris Conway (Google)
  •   Morgan Deters (NYU)
  •   Liana Hadarean (NYU)
  •   Dejan Jovanović (NYU)
  •   Tim King (NYU)
  •   Tianyi Liang (U Iowa)
  •   Andrew Reynolds (U Iowa)

The development of CVC4 is supported in part by the following organizations:

  • The Air Force Office of Scientific Research (award FA9550-09-1-0596)
  • Intel Corporation
  • The National Science Foundation (grants 0644299,  0914956, 1049495, 1228765, 1228768)
  • The Semiconductor Research Corporation (tasks 1850.001, 1850.002)

Downloads, documentation, tutorials, and more information are available at the CVC4 web site:

-The CVC4 team