The result is sat (satisfiable) if a solution was found. The method check() solves the asserted constraints. We say the constraints have been asserted in the solver. Constraints can be added using the method add. The command Solver() creates a general purpose solver. pop () print s print "Solving restored set of constraints." print s. add ( y < 11 ) print s print "Solving updated set of constraints." print s. add ( x > 10, y = x + 2 ) print s print "Solving constraints in the solver s. X = Int ( 'x' ) y = Int ( 'y' ) s = Solver () print s s. Let us start with the following simple example: Please send feedback, comments and/or corrections to comments are very valuable. Other cool front-ends for Z3 include Scala^Z3 and SBV. The source code also demonstrates how to use new features in Z3 4.0. The Z3 distribution, feel free to modify it to meet your needs. There are many excellent free resources for doing so ( Python Tutorial). However, it is useful to learn Python (a fun language!) at some point, and No Python background is needed to read this tutorial. This tutorial demonstrates the main capabilities of Z3Py: the Z3 API in Python. Security, biology (in silico analysis), and geometrical problems. Z3 is used in many applications such as: software/hardware verification and testing, constraint solving, analysis of hybrid systems, Z3 is a high performance theorem prover developed at Microsoft Research. Basics Strategies Fixpoints Advanced Z3 API in Python
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