z3py

I ran into a problem where Z3Py does not enumerate all possible solutions for the given Boolean clauses. I was wondering if anyone knows why this is happening. Here is the code I use for the Z3Py. There are 5 booleans: 1 2 3 4 and 5. from z3 import * a,b,c,d,e = Bools('1 2 3 4 5') solver = Solver() solver.add(Or(Not(a), Not(b))) solver.add(Or(Not(b), Not(c))) solver.add(Or(Not(c), Not(d))) solver.add(Or(Not(d), Not(e))) while solver.check() == sat: model = solver.model() block = [] for declaration in model: constant = declaration() block.append(constant != model[declaration]) solver.append(Or

As part of a reverse engineering exercise, I'm trying to write a Z3 solver to find a username and password that satisfy the program below. This is especially tough because the z3py tutorial that everyone refers to (rise4fun) is down. #include <iostream> #include <string> using namespace std; int main() { string name, pass; cout << "Name: "; cin >> name; cout << "Pass: "; cin >> pass; int sum = 0; for (size_t i = 0; i < name.size(); i++) { char c = name[i]; if (c < 'A') { cout << "Lose: char is less than A" << endl; return 1; } if (c > 'Z') { sum += c - 32; } else { sum += c; } } int r1 =

Let's say I have a z3 solver with a certain number of asserted constraints that are satisfiable. Let S be a set of constraints, I would like to verify for every constraint in S whether the formula is still satisfiable when adding the constraint to the solver. This can be easily done sequentially in such a fashion: results = [] for constraint in S: solver.push() solver.add(constraint) results.append(solver.check() == z3.sat) solver.pop() print all(results) Now, I would like to parallelize this to speed things up, but I'm not sure how to do it properly with z3. Here is an attempt. Consider the

Suppose that a is an integer of 8-bit of value 254 . If a is a signed integer, it is actually considered -2 . In contrary, if a is unsigned, it remains 254 . I am trying to model this signed/unsigned integer problem with BitVector theory with Z3, but it seems BitVector doesnt allow this. Is this true? Then any idea on how to model this in Z3py? Thanks so much. Z3 has APIs for the signed and unsigned interpretations. For example, in the C API, Z3_mk_bvslt creates the signed less than, and Z3_mk_bvult the unsigned one. In Z3Py, we overloaded < , <= , ... using the signed ones. For creating, the

How to generate multiple models for bit vector formula using z3 solver in smt2 format? While implementing IDEA Code for Bit Vector it is generating one model. How to generate all possible models for the same if exists? ex.smt2 file (set-logic QF_BV) (set-info :smt-lib-version 2.0) (declare-const A0 (_ BitVec 16)) (declare-const A1 (_ BitVec 16)) (declare-const A2 (_ BitVec 16)) (declare-const B0 (_ BitVec 16)) (declare-const B1 (_ BitVec 16)) (declare-const B2 (_ BitVec 16)) (declare-const C0 (_ BitVec 16)) (declare-const C1 (_ BitVec 16)) (declare-const C2 (_ BitVec 16)) (declare-const D0 (_

I'm trying to influence the randomness of results for model values generated by Z3. As far as I understand, the options for this are very limited: in case of linear arithmetic, the simplex solver does not allow for random results that still satisfy the given constraints. However, there is an option smt.arith.random_initial_value ("use random initial values in the simplex-based procedure for linear arithmetic (default: false)") which I don't seem to get working: from z3 import * set_option('smt.arith.random_initial_value',True) x = Int('x') y = Int('y') s = Solver() s.add( x+y > 0) s.check() s