Display quantified-out formula - z3

how do I display the result of quantifier elimination ?
z3 seems to be happy with the following input
(set-option :elim-quantifiers true)
(declare-fun y () Real)
(simplify (exists ((x Real)) (>= x y)))
but it returns it the same as output.
Thanks

Z3 3.x has a new front-end for the SMT-LIB 2.0 input format.
In the new front-end, the command simplify is not an “umbrella” for all simplifications and pre-processing steps available in Z3.
The “do-all” approach used in Z3 2.x had several problems.
So, in Z3 3.x, we started using a fine-grain approach where the user can specify tactics/strategies for solving and/or simplifying formulas.
For example, one can write:
(declare-const x Int)
(assert (not (or (<= x 0) (<= x 2))))
(apply (and-then simplify propagate-bounds))
This new infrastructure is working in progress.
For example, Z3 3.2 does not have commands/tactics for eliminating quantifiers in the new front-end.
The commands/tactics for quantifier elimination will be available in Z3 3.3.
In the meantime, you can use the old SMT-LIB front-end for eliminating quantifiers.
You must provide the command line option -smtc to force Z3 to use the old front-end.
Moreover, the old front-end is not fully compliant with SMT-LIB 2.0. So, you must write:
(set-option ELIM_QUANTIFIERS true)
(declare-fun y () Real)
(simplify (exists ((x Real)) (>= x y)))

Related

Get fractional part of real in QF_UFNRA

Using smtlib I would like to make something like modulo using QF_UFNRA. This disables me from using mod, to_int, to_real an such things.
In the end I want to get the fractional part of z in the following code:
(set-logic QF_UFNRA)
(declare-fun z () Real)
(declare-fun z1 () Real)
(define-fun zval_1 ((x Real)) Real
x
)
(declare-fun zval (Real) Real)
(assert (= z 1.5));
(assert (=> (and (<= 0.0 z) (< z 1.0)) (= (zval z) (zval_1 z))))
(assert (=> (>= z 1.0) (= (zval z) (zval (- z 1.0)))))
(assert (= z1 (zval z)))
Of course, as I am asking this question here, implies, that it didn't work out.
Has anybody got an idea how to get the fractional part of z into z1 using logic QF_UFNRA?
This is a great question. Unfortunately, what you want to do is not possible in general if you restrict yourself to QF_UFNRA.
If you could encode such functionality, then you can decide arbitrary Diophantine equations. You would simply cast a given Diophantine equation over reals, compute the "fraction" of the real solution with this alleged method, and assert that the fraction is 0. Since reals are decidable, this would give you a decision procedure for Diophantine equations, accomplishing the impossible. (This is known as Hilbert's 10th problem.)
So, as innocent as the task looks, it is actually not doable. But that doesn't mean you cannot encode this with some extensions, and possibly have the solver successfully decide instances of it.
If you allow quantifiers and recursive functions
If you allow yourself quantifiers and recursive-functions, then you can write:
(set-logic UFNRA)
(define-fun-rec frac ((x Real)) Real (ite (< x 1) x (frac (- x 1))))
(declare-fun res () Real)
(assert (= (frac 1.5) res))
(check-sat)
(get-value (res))
To which z3 responds:
sat
((res (/ 1.0 2.0)))
Note that we used the UFNRA logic allowing quantification, which is required here implicitly due to the use of the define-fun-rec construct. (See the SMTLib manual for details.) This is essentially what you tried to encode in your question, but instead using the recursive-function-definition facilities instead of implicit encoding. There are several caveats in using recursive functions in SMTLib however: In particular, you can write functions that render your system inconsistent rather easily. See Section 4.2.3 of http://smtlib.cs.uiowa.edu/papers/smt-lib-reference-v2.5-draft.pdf for details.
If you can use QF_UFNIRA
If you move to QF_UFNIRA, i.e., allow mixing reals and integers, the encoding is easy:
(set-logic QF_UFNIRA)
(declare-fun z () Real)
(declare-fun zF () Real)
(declare-fun zI () Int)
(assert (= z (+ zF zI)))
(assert (<= 0 zF))
(assert (< zF 1))
(assert (= z 1.5))
(check-sat)
(get-value (zF zI))
z3 responds:
sat
((zF (/ 1.0 2.0))
(zI 1))
(You might have to be careful about the computation of zI when z < 0, but the idea is the same.)
Note that just because the encoding is easy doesn't mean z3 will always be able to answer the query successfully. Due to mixing of Real's and Integer's, the problem remains undecidable as discussed before. If you have other constraints on z, z3 might very well respond unknown to this encoding. In this particular case, it happens to be simple enough so z3 is able to find a model.
If you have sin and pi:
This is more of a thought experiment than a real alternative. If SMTLib allowed for sin and pi, then you can check whether sin (zI * pi) is 0, for a suitably constrained zI. Any satisfying model to this query would ensure that zI is integer. You can then use this value to extract the fractional part by subtracting zI from z.
But this is futile as SMTLib neither allows for sin nor pi. And for good reason: Decidability would be lost. Having said that, maybe some brave soul can design a logic that supported sin, pi, etc., and successfully answered your query correctly, while returning unknown when the problem becomes too hard for the solver. This is already the case for nonlinear arithmetic and the QF_UFNIRA fragment: The solver may give up in general, but the heuristics it employs might solve problems of practical interest.
Restriction to Rationals
As a theoretical aside, it turns out that if you restrict yourself to rationals only (instead of actual reals) then you can indeed write a first-order formula to recognize integers. The encoding is not for the faint of heart, however: http://math.mit.edu/~poonen/papers/ae.pdf. Furthermore, since the encoding involves quantifiers, it's probably quite unlikely that SMT solvers will do well with a formulation based on this idea.
[Incidentally, I should extend thanks to my work colleagues; this question made for a great lunch-time conversation!]

Using Z3 QFNRA tactic with datatypes: interaction or inlining

In Non-linear arithmetic and uninterpreted functions, Leonardo de Moura states that the qfnra-nlsat tactic hasn't been fully integrated with the rest of Z3 yet. I thought that the situation has changed in two years, but apparently the integration is still not very complete.
In the example below, I use datatypes purely for "software engineering" purposes: to organize my data into records. Even though there are no uninterpreted functions, Z3 still fails to give me a solution:
(declare-datatypes () (
(Point (point (point-x Real) (point-y Real)))
(Line (line (line-a Real) (line-b Real) (line-c Real)))))
(define-fun point-line-subst ((p Point) (l Line)) Real
(+ (* (line-a l) (point-x p)) (* (line-b l) (point-y p)) (line-c l)))
(declare-const p Point)
(declare-const l Line)
(assert (> (point-y p) 20.0))
(assert (= 0.0 (point-line-subst p l)))
(check-sat-using qfnra-nlsat)
(get-model)
> unknown
(model
)
However, if I manually inline all the functions, Z3 finds a model instantly:
(declare-const x Real)
(declare-const y Real)
(declare-const a Real)
(declare-const b Real)
(declare-const c Real)
(assert (> y 20.0))
(assert (= 0.0 (+ (* a x) (* b y) c)))
(check-sat-using qfnra-nlsat)
(get-model)
> sat
(model
(define-fun y () Real
21.0)
(define-fun a () Real
0.0)
(define-fun x () Real
0.0)
(define-fun b () Real
0.0)
(define-fun c () Real
0.0)
)
My question is, is there a way to perform such an inlining automatically? I'm fine with either one of these workflows:
Launch Z3 with a tactic that says "Inline first, then apply qfnra-nlsat. I haven't found a way to do so, but maybe I wasn't looking well enough.
Launch Z3 using some version of simplify to do the inlining. Launch Z3 the second time on the result of the first invocation (the inlined version).
In other words, how to make qfnra-nlsat work with tuples?
Thank you!
That's correct, the NLSAT solver is still not integrated with the other theories. At the moment, we can only use it if we eliminate all datatypes (or elements of other theories) before running it. I believe there is no useful existing tactic inside of Z3 at the moment though, so this would have to be done beforehand. In general it's not hard to compose tactics, e.g., like this:
(check-sat-using (and-then simplify qfnra-nlsat))
but the simplifier is not strong enough to eliminate the datatype constants in this problem. (The respective implementation files are datatype_rewriter.cpp and datatype_simplifier_plugin.cpp.)

Does Z3 support Real-to-Int conversions?

In Z3 you have to_real to obtain the Real equivalent of an Int. Is there some support to the inverse conversions, i.e., to truncation, rounding or like? In the negative case, what could be the most Z3-friendly way of defining them, if any? Many thanks to everyone will answer.
Yes, Z3 has a to_int function that converts a Real into an integer. The semantics of to_int is defined in the SMT 2.0 standard. Here is an example: http://rise4fun.com/Z3/uJ3J
(declare-fun x () Real)
(assert (= (to_int x) 2))
(assert (not (= x 2.0)))
(check-sat)
(get-model)

z3 produces unknown for assertions without quantifiers

I have some simple constraints involving multiplication of reals in z3 that are producing unknown. The problem seems to be that they are wrapped in a datatype, as the unwrapped version produces sat.
Here is a simplified case:
(declare-datatypes () ((T (NUM (n Real)))))
(declare-const a T)
(declare-const b T)
(declare-const c T)
(assert (is-NUM a))
(assert (is-NUM b))
(assert (is-NUM c))
(assert (= c (NUM (* (n a) (n b)))))
(check-sat)
;unknown
And without the datatype:
(declare-const a Real)
(declare-const b Real)
(declare-const c Real)
(assert (= c (* a b)))
(check-sat)
;sat
I'm using z3 3.2, but this also is reproducible in the web interface.
Yes, Z3 can return unknown in quantifier-free problems.
Here are the main reasons:
Run out of time or memory
The quantifier-free fragment is undecidable (e.g., nonlinear integer arithmetic)
The quantifier-free fragment is too expensive, and/or the procedure implemented in Z3 is incomplete.
Your problems are in a decidable fragment, and the unknown is due to the incomplete procedure for nonlinear arithmetic used in Z3. Z3 4.0 has a complete procedure for nonlinear real arithmetic, but it is still not integrated with the other theories. So, it will not help in the first problem.
The different in behavior in the first and second queries is due to different strategies used for each query. Z3 has a new framework for defining custom strategies. You can get sat for the first query by using the command
(check-sat-using (then simplify solve-eqs smt))
instead of
(check-sat)
The first command forces Z3 to eliminate variables by solving equalities (i.e., tactic solve-eqs). It will eliminate the equality (= c (NUM (* (n a) (n b)))). This tactic is automatically used in the second problem in Z3 3.x. Note that this tactic will not help if we replace the equality with (>= c (NUM (* (n a) (n b)))).
Moreover, the second problem contains only nonlinear arithmetic. So, in Z3 4.0, the new (and complete) solver for nonlinear real arithmetic will be automatically used.
You can learn about the new strategy framework at http://rise4fun.com/Z3/tutorial/strategies, http://rise4fun.com/Z3Py/tutorial/strategies
Your examples are in non-linear arithmetic. Z3 4.0 is able to solve problems with only non-linear arithmetic assertions, but not along with uninterpreted functions and other theories. That explains why it produces unknown in the first example. This limitation is likely to be addressed in Z3's future versions.

Non-linear arithmetic and uninterpreted functions

(declare-const x Real)
(declare-fun f (Real) Real)
(assert (= (f 1.0) 0.0))
(assert (= (* x x) (* 1.0 1.0)))
(check-sat)
(get-model)
I have two independent assertions one in non-linear arithmetic and other uninterpreted functions. Z3 gives a "model is not available" to the problem above. Is there a way to set the logic to something that can handle both at the same time? Thank you.
The new nonlinear solver is not integrated with other theories (arrays, unintepreted functions, bit-vectors) yet. In Z3 4.0, it can only be used to solve problems that contain only nonlinear arithmetic assertions. This is will change in future versions.

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