Solving ../../benchmarks/smtlib/false/cons_not_null.smt2...

Inference procedure has parameters:
Ice fuel: 200
Timeout: Some(60.) (sec)
Teacher_type: Checks all clauses every time
Approximation method: remove every clause that can be safely removed



Learning problem is:

env: {
nat -> {s, z}  ;  natlist -> {cons, nil}
}
definition:
{
(not_null, P:
{
not_null(cons(x, ll)) <= True
False <= not_null(nil)
}
)
}

properties:
{
not_null(l1) <= not_null(cons(i, l1))
}


over-approximation: {}
under-approximation: {}

Clause system for inference is:

{
not_null(cons(x, ll)) <= True -> 0
not_null(l1) <= not_null(cons(i, l1)) -> 0
False <= not_null(nil) -> 0
}


Solving took 0.036980 seconds.
No: Contradictory set of ground constraints:
{
not_null(cons(z, nil)) <= True
not_null(nil) <= True
False <= not_null(nil)
}
-------------------
STEPS:
-------------------------------------------
Step 0, which took 0.005872 s (model generation: 0.005844,  model checking: 0.000028):

Clauses:
{
not_null(cons(x, ll)) <= True -> 0
not_null(l1) <= not_null(cons(i, l1)) -> 0
False <= not_null(nil) -> 0
}

Accumulated learning constraints:
{

}

Current best model:
|_
name: None

not_null ->
[
not_null : <natlist>
{
  
}
]



--
Equality automata are defined for: {nat, natlist}
_|




Answer of teacher:

not_null(cons(x, ll)) <= True  :
Yes: {

}

not_null(l1) <= not_null(cons(i, l1))  :
No: ()

False <= not_null(nil)  :
No: ()


-------------------------------------------
Step 1, which took 0.009092 s (model generation: 0.009047,  model checking: 0.000045):

Clauses:
{
not_null(cons(x, ll)) <= True -> 0
not_null(l1) <= not_null(cons(i, l1)) -> 0
False <= not_null(nil) -> 0
}

Accumulated learning constraints:
{
not_null(cons(z, nil)) <= True
}

Current best model:
|_
name: None

not_null ->
[
not_null : <natlist>
{
  not_null(cons(x_0_0, x_0_1)) <= True
}
]



--
Equality automata are defined for: {nat, natlist}
_|




Answer of teacher:

not_null(cons(x, ll)) <= True  :
No: ()

not_null(l1) <= not_null(cons(i, l1))  :
Yes: {
l1 -> nil
}

False <= not_null(nil)  :
No: ()


-------------------------------------------
Step 2, which took 0.010093 s (model generation: 0.010062,  model checking: 0.000031):

Clauses:
{
not_null(cons(x, ll)) <= True -> 0
not_null(l1) <= not_null(cons(i, l1)) -> 0
False <= not_null(nil) -> 0
}

Accumulated learning constraints:
{
not_null(cons(z, nil)) <= True
not_null(nil) <= True
}

Current best model:
|_
name: None

not_null ->
[
not_null : <natlist>
{
  not_null(cons(x_0_0, x_0_1)) <= True
  not_null(nil) <= True
}
]



--
Equality automata are defined for: {nat, natlist}
_|




Answer of teacher:

not_null(cons(x, ll)) <= True  :
No: ()

not_null(l1) <= not_null(cons(i, l1))  :
No: ()

False <= not_null(nil)  :
Yes: {

}


Total time: 0.036980
Learner time: 0.024953
Teacher time: 0.000104
Reasons for stopping: No: Contradictory set of ground constraints:
{
not_null(cons(z, nil)) <= True
not_null(nil) <= True
False <= not_null(nil)
}