Difference between macro and quantifier in Z3 - z3

I would like to know what is the difference between following 2 statements -
Statement 1
(define-fun max_integ ((x Int) (y Int)) Int
(ite (< x y) y x))
Statement 2
(declare-fun max_integ ((Int)(Int)) Int)
(assert (forall ((x Int) (y Int)) (= (max_integ x y) (if (< x y) y x))))
I observed that when I use Statement1, my z3 constraints give me a result in 0.03 seconds. Whereas when I used Statement2, it does not finish in 2 minutes and I terminate the solver.
I would like also to know how achieve it using C-API.
Thanks !

Statement 1 is a macro. Z3 will replace every occurrence of max_integ with the ite expression. It does that during parsing time. In the second statement, by default, Z3 will not eliminate max_integ, and to be able to return sat it has to build an interpretation for the uninterpreted symbol max_integ that will satisfy the quantifier for all x and y.
Z3 has an option called :macro-finder, it will detect quantifiers that are essentially encoding macros, and will eliminate them. Here is an example (also available online here):
(set-option :macro-finder true)
(declare-fun max_integ ((Int)(Int)) Int)
(assert (forall ((x Int) (y Int)) (= (max_integ x y) (if (< x y) y x))))
(check-sat)
(get-model)
That being said, we can easily simulate macros in a programmatic API by writing a function that given Z3 expressions return a new Z3 expression. Here in an example using the Python API (also available online here):
def max(a, b):
# The function If builds a Z3 if-then-else expression
return If(a >= b, a, b)
x, y = Ints('x y')
solve(x == max(x, y), y == max(x, y), x > 0)
Yet another option is to use the C API: Z3_substitute_vars. The idea is to an expression containing free variables. Free variables are created using the API Z3_mk_bound. Each variable represents an argument. Then, we use Z3_substitute_vars to replace the variables with other expressions.

Related

Strange behaviour of seq.nth in exists-expression

Running z3 on this
(assert (< (seq.nth (seq.unit 0) 0) 0))
(check-sat)
has UNSAT as a result
But running
(assert (exists ((x Int))
(< (seq.nth (seq.unit 0) x) 0)))
(check-sat)
(get-model)
is SAT. Looking at the model
(model
(define-fun seq.nth_u ((x!0 Seq) (x!1 Int)) Int
(- 1))
)
So, doesn't this mean that seq.nth is treated like a variable over a Function?
Shouldn't it be a constant function (returning always the indexed value of seq)?
I would expect the second case also to be UNSAT. In order to achieve that, how can I make seq.nth a non-variable-function?
Help appreciated...
The function seq.nth is underspecified. That is, if you query an element that is out-of-bounds (i.e., either at a negative index or at at an index that is larger than the last), then it is free to return whatever value the solver wants. (And the solver will always pick a value to make your query satisfiable.)
This is typical of SMTLib, where underspecified functions can simply take any value when given arguments that are not in the domain of their arguments. So, z3 is telling you that there is such a model by indexing out-of-bounds using the sequence (seq.unit 0). i.e., we can index it at some negative value, or at some index larger than 0.
Note that the value of seq.nth_u given in the model (note the _u suffix!) is indicative of how the underflow/overflow behavior is modeled. It should not be confused with the value of the function seq.nth.
You can actually get z3 to display the value of the index x if you make it a top-level existential:
(declare-fun x () Int)
(assert (< (seq.nth (seq.unit 0) x) 0))
(check-sat)
(get-value (x))
For this, z3 says:
sat
((x (- 1)))
that is, index at location -1. But do not confuse this with the -1 that you see in the interpretation of seq.nth_u. In fact, if we also add:
(assert (> x 0))
then z3 says:
sat
((x 1))
However, if we add:
(assert (>= x 0))
(assert (< x 1))
then we get unsat as expected. And when working with sequences, you should add these sorts of constraints (if possible!) to avoid out-of-bounds accesses.

Decidable sqrt function in Z3

Since disabling unsound simplification of root objects, Z3 will now fail on this simple model involving a square root:
(define-fun sqrt ((x Real)) Real (^ x 0.5))
(declare-fun y () Real)
(declare-fun x () Real)
(assert (= y (sqrt x)))
(check-sat)
This returns sat with Z3 4.4.1, but unknown with master.
If I change the problem definition to use is_sqrt as defined by Nikolaj in this question, then Z3 master will return sat. The approach using is_sqrt shows that all real roots can be pushed into QF_NRA by introducing auxiliary variables, so I think Z3 should be able to solve all problems involving roots over the reals.
How can I define a square-root function in the reals that will result in a decidable theory, assuming the rest of the model is in QF_NRA?
There is a subtle difference between (assert (= y (^ x 0.5))) and (assert (and (= x (* y y)) (> y 0.0))). The difference comes from the requirement that all functions in Z3 (and SMT-LIB) are total. This means, for example, that y=1/x, x=0 is considered satisfiable. Given that ^ is total in Z3, (assert (and (= y (^ x 0.5)) (< x 0.0))) is considered satisfiable. We can't convert (= y (^ x 0.5)) to (and (= x (* y y)) (> y 0.0)), because if x < 0 then the former is considered satisfiable but the latter is unsatisfiable. Similarly, any sqrt function defined within SMT-LIB would also be total, so we cannot define a sqrt function by any other means such that (assert (= y (sqrt x))) is equivalent to (assert (and (= x (* y y)) (> y 0.0))). In addition to the above difference as to whether or not y = sqrt(x), x < 0 (pseudocode) is considered satisfiable, it is also the case that (assert (and (= x (* y y)) (> y 0.0))) is decidable (it is in QF_NRA), while (assert (= y (^ x 0.5))) is not.
The solution for my purpose is to not use a Z3 or SMT-LIB function definition for the square-root. Instead, I will use statements of the form (assert (and (= x (* y y)) (> y 0.0))) to indicate that y is the square-root of x. Such assertions are within QF_NRA, so models built in this way will be decidable. Furthermore, this has the advantage that y = sqrt(x), x < 0 (pseudocode) will return unsat if it is represented in SMT-LIB via the statements (assert (and (= x (* y y)) (> y 0.0))) and (assert (< x 0.0)). To return unsat for this example is more in-line with my use case.

Does z3 support rational arithmetic for its input constraints?

In fact, does the SMT-LIB standard have a rational (not just real) sort? Going by its website, it does not.
If x is a rational and we have a constraint x^2 = 2, then we should get back ``unsatisfiable''. The closest I could get to encoding that constraint is the following:
;;(set-logic QF_NRA) ;; intentionally commented out
(declare-const x Real)
(assert (= (* x x) 2.0))
(check-sat)
(get-model)
for which z3 returns a solution, as there is a solution (irrational) in the reals. I do understand that z3 has its own rational library, which it uses, for instance, when solving QF_LRA constraints using an adaptation of the Simplex algorithm. On a related note, is there an SMT solver that supports rationals at the input level?
I'm sure it's possible to define a Rational sort using two integers as suggested by Nikolaj -- I would be interested to see that. It might be easier to just use the Real sort, and any time you want a rational, assert that it's equal to the ratio of two Ints. For example:
(set-option :pp.decimal true)
(declare-const x Real)
(declare-const p Int)
(declare-const q Int)
(assert (> q 0))
(assert (= x (/ p q)))
(assert (= x 0.5))
(check-sat)
(get-value (x p q))
This quickly comes back with
sat
((x 0.5)
(p 1)
(q 2))

Why operators '/' and 'div' in Z3 give different results?

I was trying to represent a real number with two integer numbers as using them as the numerator and the denominator of the real number. I wrote the following program:
(declare-const a Int)
(declare-const b Int)
(declare-const f Real)
(assert (= f (/ a b)))
(assert (= f 0.5))
(assert (> b 2))
(assert (> b a))
(check-sat)
(get-model)
The program returned SAT result as follows:
sat
(model
(define-fun f () Real
(/ 1.0 2.0))
(define-fun b () Int
4)
(define-fun a () Int
2)
)
However, if I write '(assert (= f (div a b)))' instead of '(assert (= f (/ a b)))', then the result is UNSAT. Why does not div return the same result?
Moreover, and the main concern for me, I did not find a way to use operator '/' in z3 .Net API. I can see only function MkDiv, which actually for operator 'div'. Is there a way so that I can apply operator '/' in the case of z3 .Net API? Thank you in advance.
Strictly speaking neither of these formulas is SMT-LIB2 compliant, because / is a function that takes two Real inputs and produces a Real output, whereas div is a function that takes two Int inputs and produces an Int (see SMT-LIB Theories). Z3 is more relaxed and automatically converts those objects. If we enable the option smtlib2_compliant=true then it will indeed report an error in both cases.
The reason for the div version being unsatisfiable is that there is indeed no solution where f is an integer according to (= f (/ a b)), but there is indeed no integer that satisfies (= f 0.5)

Quantifier in Z3

Basically, I want to ask Z3 to give me an arbitrary integer whose value is greater than 10. So I write the following statements:
(declare-const x (Int))
(assert (forall ((i Int)) (> i 10)))
(check-sat)
(get-value(x))
How can I apply this quantifier to my model? I know you can write (assert (> x 10)) to achieve this. But I mean I want a quantifier in my model so every time I declare an integer constant whose value is guaranteed to be over 10. So I don't have to insert statement (assert (> x 10)) for every integer constant that I declared.
When you use (assert (forall ((i Int)) (> i 10))), i is a bounded variable and the quantified formula is equivalent to a truth value, which is false in this case.
I think you want to define a macro using quantifiers:
(declare-fun greaterThan10 (Int) Bool)
(assert (forall ((i Int)) (= (greaterThan10 i) (> i 10))))
And you can use them to avoid code repetition:
(declare-const x (Int))
(declare-const y (Int))
(assert (greaterThan10 x))
(assert (greaterThan10 y))
(check-sat)
It is essentially the way to define macros using uninterpreted functions when you're working with Z3 API. Note that you have to set (set-option :macro-finder true) in order that Z3 replaces universal quantifiers with bodies of those functions.
However, if you're working with the textual interface, the macro define-fun in SMT-LIB v2 is an easier way to do what you want:
(define-fun greaterThan10 ((i Int)) Bool
(> i 10))

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