Z3

问题 Is there any way to convert between BitVector and FP in SMTLIB2, something like the int2bv and bv2int functions? To clarify, I am looking for a raw representation of the bits, not e.g., a rounded integer in BitVec form. 回答1: To be precise, there is no standard for floating point arithmetic in SMTLIB yet. There is a draft for this which will be finalized at a later point in time; this draft does not contain such functions at the moment. However, Z3 does support such conversion functions when

问题 I've seen some online materials for defining algebraic datatypes like an IntList in Z3. I'm wondering how to define an algebraic datatype with logical constraints. For example, how to define a PosSort that stands for positive integers. 回答1: Total functions in SMT Functions are always total in SMT, which raises the question how to encode partial functions such a data type constructor for PosSort . Thus, I would be surprised if Z3's/SMT's built-in support for algebraic data types supports

问题 I'm a new guy to work with the Z3. Would like to know how I can calculate the maximum value of a set and two different sets. For example: [1, 6, 5] - The greater is 6 [1, 6, 5] e [10, 7, 2] - The greater is 6 I use the following code to set: (declare-sort Set 0) (declare-fun contains (Set Int) bool) ( declare-const set Set ) ( declare-const distinct_set Set ) ( declare-const A Int ) ( declare-const B Int ) ( declare-const C Int ) ( assert ( = A 0 ) ) ( assert ( = B 1 ) ) ( assert ( = C 2 ) )

问题 I am very new to z3py. I am trying to code the following logarithmic expressions in z3py . log(x,y) I did search stack overflow a lot and came across a similar question, but unfortunately I could not get a satisfactory enough answer. Please help me! 回答1: More generally, how can we define logs with Z3? The only way I have gotten any traction at all is to use an approximate value for e , define exp(x) as (^ e x) , and then define log as a total function that is the inverse of exp . In SMT-LIB 2

问题 In Complex numbers in Z3 Leonardo de Moura was able to introduce and to compute with complex numbers in Z3. Using the code proposed by Leonardo I am introducing and computing with quaternion numbers in Z3 according with the code presented here . Using this "quaternion " code I am solving the following problem: x = Quaternion("x") s = Tactic('qfnra-nlsat').solver() s.add(x*x + 30 == 0, x.i3 > 0, x.i2 >0, x.i1 > 0) print(s.check()) m = s.model() print m and the corresponding output is: sat [x.r

问题 I've got several questions about Z3 tactics, most of them concern simplify . I noticed that linear inequalites after applying simplify are often negated. For example (> x y) is transformed by simplify into (not (<= x y)) . Ideally, I would want integer [in]equalities not to be negated, so that (not (<= x y)) is transformed into (<= y x) . I can I ensure such a behavior? Also, among <, <=, >, >= it would be desirable to have only one type of inequalities to be used in all integer predicates in

问题 I saw a post which spoke about how Z3's python API can be used to get suboptimal solution for a minimization problem I have a MAXSMT problem, and I want to know how Z3 command line tool can be used to find a suboptimal solution when timeout is specified? Is using -t:timeout option alone suppose to give me a suboptimal solution? The Z3 solver took 150 seconds to find an optimal solution for my MaxSMT problem I used z3 -t:140000 smt2 <filename> to set the timeout as 140 seconds. But the z3

问题 I am using Z3 to solve the path conditions produced by a symbolic executor, which explores the state space in depth-first order, quite similarly to CUTE, DART or (possibly) SAGE. We are experimenting different ways of using Z3. At one extreme, we send every query to Z3 and (reset) it right after. At the other, we (push) every additional branch constraint, and (pop) (pop) upon backtrack the minimum necessary to correctly weaken the path condition. The problem is, no strategy seems to work

问题 So basically I am trying to solve the following SMT constraint with a generic constraint solver like Z3: >>> from z3 import * >>> a = BitVec("a", 32) >>> b = BitVec("b", 32) >>> c1 = (a + 32) & (b & 0xff) >>> c2 = (b & 0xff) >>> s = Solver() >>> s.add(c1 == c2) >>> s.check() sat >>> s.model() [b = 0, a = 4294967199] Note that obviously, the constraint should be sat whenever b falls within the range of [0x00000000, 0xffffff00] . So here is my question, is it in general feasible for a SMT

问题 Closed . This question is opinion-based. It is not currently accepting answers. Want to improve this question? Update the question so it can be answered with facts and citations by editing this post. Closed 12 months ago . Sorry that this question is subjective, but given that the Stack Overflow has the largest Z3 user base, I want to give it a try. I have a big constraint satisfaction problem that consists of many integer propositional logic formulas and a few first order logic formulas that