Refinements 101 (contd.)
Hopefully, the previous article gave you a basic idea about what refinement types look like. Several folks had interesting questions, that are worth discussing in a separate post, since they throw a lot of light on the strengths (or weaknesses, depending on your point of view!) of LiquidHaskell.
22: module Refinements101Reax where
How to relate outputs and inputs¶
Recall the function divide
31: {@ divide :: Int > {v: Int  v /= 0 } > Int @} 32: divide :: Int > Int > Int 33: (GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV != 0)} > (GHC.Types.Int)divide (GHC.Types.Int)n 0 = [(GHC.Types.Char)] > {VV : (GHC.Types.Int)  false}error {VV : [(GHC.Types.Char)]  (len([VV]) >= 0)}"divide by zero" 34: divide n d = {VV : (GHC.Types.Int)  (VV = n)}n x:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x / y))}`div` {VV : (GHC.Types.Int)  (VV != 0)}d
and abz
was the absolute value function
40: abz :: Int > Int 41: x:(GHC.Types.Int) > {VV : (GHC.Types.Int)  ((VV = 0) <=> (x = 0)),(0 <= VV)}abz (GHC.Types.Int)n  {VV : (GHC.Types.Int)  (VV = (0 : int))}0 x:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Bool)  ((? Prop([VV])) <=> (x < y))}< {VV : (GHC.Types.Int)  (VV = n)}n = {VV : (GHC.Types.Int)  (VV = n)}n 42:  otherwise = {VV : (GHC.Types.Int)  (VV = (0 : int))}0 x:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x  y))} {VV : (GHC.Types.Int)  (VV = n)}n
nanothief remarked
that LiquidHaskell was unable to verify the safety of the following call to
divide
(i.e. was unable to show that x
was nonzero at the callsite).
50: {@ f :: Int > Int @} 51: (GHC.Types.Int) > (GHC.Types.Int)f (GHC.Types.Int)x  x:(GHC.Types.Int) > {VV : (GHC.Types.Int)  ((VV = 0) <=> (x = 0)),(0 <= VV)}abz {VV : (GHC.Types.Int)  (VV = x)}x x:{VV : (GHC.Types.Int)  (VV >= 0),(0 <= VV)} > y:{VV : (GHC.Types.Int)  (VV >= 0),(0 <= VV)} > {VV : (GHC.Types.Bool)  ((? Prop([VV])) <=> (x = y))}== {VV : (GHC.Types.Int)  (VV = (0 : int))}0 = x:(GHC.Prim.Int#) > {VV : (GHC.Types.Int)  (VV = (x : int))}3 52:  otherwise = {VV : (GHC.Types.Int)  (VV = (3 : int))}3 (GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV != 0)} > (GHC.Types.Int)`divide` {VV : (GHC.Types.Int)  (VV = x)}x
Nanothief correctly argues that the code is clearly safe as "abz x == 0
being false implies x /= 0
".
Indeed, the code is safe, however, the reason that LiquidHaskell
rejected it has nothing to do with its inability
to "track the constraints of values based on tests using new values derived from that value" as Nanothief surmised,
but instead, because LiquidHaskell supports modular verification
where the only thing known about abz
at a use site is
whatever is specified in its type.
Concretely speaking, the type
64: abz :: Int > {v: Int  0 <= v }
is too anemic to verify f
above, as it tells us nothing
about the relationship between the output and input  looking at it,
we have now way of telling that when the output (of abz
) is
nonzero, the input must also have been nonzero.
Instead, we can write a stronger type which does capture this information, for example
73: abz :: x:Int > {v:Int  v = (if (x > 0) then x else (0  x))}
where
77: v = (if p then e1 else e2)
is an abbreviation for the formula
81: (p => v == e1) && ((not p) => v = e2)
With this specification for abz
, LiquidHaskell is able to reason that
when abz x
is nonzero, x
is also nonzero. Of course, abz
is trivial
enough that we can very precisely capture its exact semantics in the
refinement type, but thats is rarely the case.
Nevertheless, even here, you could write a somewhat weaker specification,
that still had enough juice to allow the verification of the divide
call
in f
. In particular, we might write
94: {@ abz :: x:Int > {v:Int  ((0 <= v) && ((v = 0) <=> (x = 0))) } @}
which states the output is 0
if and only if the input is 0
.
LiquidHaskell will happily verify that abz
implements this specification,
and will use it to verify the safety of f
above.
(BTW, follow the link above to demo this code yourself.)
How to tell a Fib¶
Chris Done asked
why LiquidHaskell refused to verify the following definition of fib
.
110: {@ fib :: n:Int > { b:Int  (n >= 0 && b >= n) } @} 111: fib :: Int > Int 112: n:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV >= n),(n >= 0)}fib 0 = x:(GHC.Prim.Int#) > {VV : (GHC.Types.Int)  (VV = (x : int))}0 113: fib 1 = x:(GHC.Prim.Int#) > {VV : (GHC.Types.Int)  (VV = (x : int))}1 114: fib n = n:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV >= n),(n >= 0)}fib ((GHC.Types.Int)nx:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x  y))}{VV : (GHC.Types.Int)  (VV = (1 : int))}1) x:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x + y))}+ n:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV >= n),(n >= 0)}fib ((GHC.Types.Int)nx:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x  y))}{VV : (GHC.Types.Int)  (VV = (2 : int))}2)
Indeed, the both the specification and the implementation look pretty legit, so what gives? It turns out that there are two different reasons why.
Reason 1: Assumptions vs. Guarantees
What we really want to say over here is that the input n
is nonnegative. However, putting the refinement n >= 0
in
the output constraint means that it becomes something that
LiquidHaskell checks that the function fib
guarantees
(or ensures).
That is, the type states that we can pass fib
any value
n
(including negative values) and yet, fib
must return
values b
such that b >= n
and n >= 0
.
The latter requirement is a rather tall order when an arbitrary n
is passed in as input. fib
can make no such guarantees since
it was given the value n
as a parameter. The only way n
could
be nonnegative was that if the caller had sent in a nonnegative value.
Thus, we want to put the burden of proof on the right entity here,
namely the caller.
To assign the burden of proof appropriately, we place the nonnegative refinement on the input type
142: {@ fib' :: n:{v:Int  v >= 0} > {b:Int  (n >= 0 && b >= n) } @} 143: fib' :: Int > Int 144: n:{VV : (GHC.Types.Int)  (VV >= 0)} > {VV : (GHC.Types.Int)  (VV >= n),(n >= 0)}fib' 0 = x:(GHC.Prim.Int#) > {VV : (GHC.Types.Int)  (VV = (x : int))}0 145: fib' 1 = x:(GHC.Prim.Int#) > {VV : (GHC.Types.Int)  (VV = (x : int))}1 146: fib' n = n:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV >= n),(n >= 0)}fib ({VV : (GHC.Types.Int)  (VV >= 0)}nx:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x  y))}{VV : (GHC.Types.Int)  (VV = (1 : int))}1) x:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x + y))}+ n:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV >= n),(n >= 0)}fib ({VV : (GHC.Types.Int)  (VV >= 0)}nx:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x  y))}{VV : (GHC.Types.Int)  (VV = (2 : int))}2)
where now at calls to fib'
LiquidHaskell will check that the argument
is nonnegative, and furthermore, when checking fib'
LiquidHaskell will
assume that the parameter n
is indeed nonnegative. So now the
constraint n >= 0
on the output is somewhat redundant, and the
nonnegative n
guarantee holds trivially.
Reason 2: The Specification is a Fib
If you run the above in the demo, you will see that LiquidHaskell still doth protest loudly, and frankly, one might start getting a little frustrated at the stubbornness and petulance of the checker.
However, if you stare at the implementation, you will see that it in fact, does not meet the specification, as
162: fib' 2 == fib' 1 + fib' 0 163: == 0 + 1 164: == 1
LiquidHaskell is reluctant to prove things that are false. Rather than anthropomorphize frivolously, lets see why it is unhappy.
First, recall the somewhat simplified specification
171: fib' :: n:Int > { b:Int  (b >= n) }
As we saw in the discussion about abz
, at each recursive callsite
the only information LiquidHaskell uses about the returned value,
is that described in the output type for that function call.
Thus, LiquidHaskell reasons that the expression:
179: fib' (n1) + fib' (n2)
has the type
183: {b: Int  exists b1, b2. b == b1 + b2 184: && b1 >= n1 185: && b2 >= n2 }
where the b1
and b2
denote the values returned by the
recursive calls  we get the above by plugging the parameters
n1
and n2
in for the parameter n
in output type for fib'
.
The SMT solver simplifies the above to
193: {b: Int  b >= 2n  3}
Finally, to check the output guarantee is met, LiquidHaskell asks the SMT solver to prove that
197: (b >= 2n  2) => (b >= n)
The SMT solver will refuse, of course, since the above implication is
not valid (e.g. when n
is 2
) Thus, via SMT, LiquidHaskell proclaims
that the function fib'
does not implement the advertised type and hence
marks it unsafe.
Fixing The Code¶
How then, do we get Chris' specification to work out? It seems like it
should hold (except for that pesky case where n=2
. Indeed,
let's rig the code, so that all the base cases return 1
.
213: {@ fibOK :: n:Int > {b:Int  ((b >= n) && (b >= 1))} @} 214: fibOK :: Int > Int 215: n:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV >= 1),(VV >= n)}fibOK 0 = x:(GHC.Prim.Int#) > {VV : (GHC.Types.Int)  (VV = (x : int))}1 216: fibOK 1 = x:(GHC.Prim.Int#) > {VV : (GHC.Types.Int)  (VV = (x : int))}1 217: fibOK n = n:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV >= 1),(VV >= n)}fibOK ((GHC.Types.Int)nx:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x  y))}{VV : (GHC.Types.Int)  (VV = (1 : int))}1) x:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x + y))}+ n:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV >= 1),(VV >= n)}fibOK ((GHC.Types.Int)nx:(GHC.Types.Int) > y:(GHC.Types.Int) > {VV : (GHC.Types.Int)  (VV = (x  y))}{VV : (GHC.Types.Int)  (VV = (2 : int))}2)
Here' we specify that not only is the output greater than the input, it is
also greater than 1
.
Now in the recursive case, LiquidHaskell reasons that the value being output is
224: {b: Int  exists b1, b2. b == b1 + b2 225: && b1 >= n1 && b1 >= 1 226: && b2 >= n2 && b2 >= 1 }
which reduces to
230: {b: Int  b = 2n  3 && n >= 2 }
which, the SMT solver is happy to verify, is indeed a subtype
234: of (i.e. implies the refinement of) the specified output 235: {b: Int  b >= n && b >= 1 }
Conclusion¶
There are several things to take away.

We need to distinguish between assumptions and guarantees when writing specifications for functions.

For modularity, LiquidHaskell, like every type system, uses only the (refinement) type of each function at each use site, and not the function's body.

Some seemingly intuitive specifications often aren't; in future work it would be useful to actually generate tests as counterexamples that illustrate when a specification fails.