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Z3 was open sourced in the beginning of 2015. [3] The source code is licensed under MIT License and hosted on GitHub. [4] The solver can be built using Visual Studio, a makefile or using CMake and runs on Windows, FreeBSD, Linux, and macOS. The default input format for Z3 is SMTLIB2.
cvc5.github.io In computer science and mathematical logic , Cooperating Validity Checker (CVC) is a family of satisfiability modulo theories (SMT) solvers. The latest major versions of CVC are CVC4 and CVC5 (stylized cvc5); earlier versions include CVC, CVC Lite, and CVC3. [ 2 ]
The Viper verification infrastructure encodes verification conditions to Z3. The sbv library provides SMT-based verification of Haskell programs, and lets the user choose among a number of solvers such as Z3, ABC, Boolector, cvc5, MathSAT and Yices. There are also many verifiers built on top of the Alt-Ergo SMT solver. Here is a list of mature ...
For information about the SMT problem, see: Satisfiability modulo theories. Pages in category "Satisfiability modulo theories solvers" The following 3 pages are in this category, out of 3 total.
[1] [2] [3] At a high level, the algorithm works by transforming an SMT problem into a SAT formula where atoms are replaced with Boolean variables. The algorithm repeatedly finds a satisfying valuation for the SAT problem, consults a theory solver to check consistency under the domain-specific theory, and then (if a contradiction is found ...
Alt-Ergo, an automatic solver for mathematical formulas, is mainly used in formal program verification. It operates on the principle of satisfiability modulo theories (SMT). Development was undertaken by researchers at the Paris-Sud University , Laboratoire de Recherche en Informatique, Inria Saclay Ile-de-France, and CNRS .
The Isabelle [a] automated theorem prover is a higher-order logic (HOL) theorem prover, written in Standard ML and Scala.As a Logic for Computable Functions (LCF) style theorem prover, it is based on a small logical core (kernel) to increase the trustworthiness of proofs without requiring, yet supporting, explicit proof objects.
Generally, automated theorem provers focus on supporting full first-order logic with quantifiers, whereas SMT solvers focus more on supporting various theories (interpreted predicate symbols). ATPs excel at problems with lots of quantifiers, whereas SMT solvers do well on large problems without quantifiers. [23]