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Writing Specifications

This section documents how you can actually annotate new or existing code with refinement types, leveraging the full power of LiquidHaskell. There are a lot of different ways to annotate your code, and so we've included a brief summary of each here.

  • {-@ inline <binding-name> @-} copies a Haskell definition to the refinement logic. (Jump to: Inlines)
    • All parts of the definition must already be available to the refinement logic.
    • The definition cannot be recursive.
  • {-@ measure <function-name>[ <refinement-type>] @-} copies a Haskell function to the refinement logic, adds an inferred refinement type to the constructor of the function's first argument, and emits an inferred global invariant related to the refinement. (Jump to: Measures)
    • All parts of the definition must already be available to the refinement logic.
    • The function must have only one argument and it must pattern match on the constructors of the type.
    • The function may structurally recurse on the single argument.
  • {-@ reflect <function-name> @-} creates an uninterpreted function of the same name in the refinement logic, copies the implementation to a refinement type alias, and adds a refinement to the type of the uninterpreted function that specifies the type alias as a post-condition. (See more: Section 2.2 of this paper)
    • All parts of the definition must already be available to the refinement logic.
    • The function may be recursive.
  • {-@ type <type-alias-head> = <refinement-type> @-} introduces a type alias that looks like Haskell syntax but can contain refinements and may be parameterized over both types and values. (Jump to: Type Aliases)
  • {-@ predicate .. @-} introduces something like {-@ type .. @-}. (Deprecated, use inline instead, Jump to: Predicate Aliases)
  • {-@ invariant <refinement-type> @-} introduces a globally available refinement which may be used by Liquid Haskel, but is not checked. (Unchecked, Deprecated, Jump to: Invariants)
  • {-@ data <data-type-head><termination-measure>[ <data-type-body] @-} introduces a refined datatype, and introduces measures for each field of a record datatype. (Jump to: Data Refinements)
    • Optionally you may also add refinements to datatype fields.
    • Optionally you may also add a termination measure to the datatype.
  • {-@ assume <binding-signature-with-refinement-type> @-} introduces a refinement type for the named Haskell definition. (Unchecked)
    • For a function, the refinements become pre and post conditions for the functions use.
  • {-@ <binding-signature-with-refinement-type> @-} introduces a refinement type for the named Haskell definition.
    • For a function, the refinements become pre and post conditions for the functions use.
    • This is probably the most used Liquid Haskell annotation!

The following sections detail more variety for the uses of the above annotations.

Modules WITHOUT code

See the installation section, which cointains a link to a walkthrough document that describes how to add refinements for external packages (cfr. "Providing Specifications for Existing Packages")

Modules WITH code: Data

Write the specification directly into the .hs or .lhs file, above the data definition. See, for example, tests/pos/Map.hs:

data Map k a <l :: k -> k -> Prop, r :: k -> k -> Prop>
  = Tip
  | Bin (sz    :: Size)
        (key   :: k)
        (value :: a)
        (left  :: Map <l, r> (k <l key>) a)
        (right :: Map <l, r> (k <r key>) a)
data Map k a = Tip
             | Bin Size k a (Map k a) (Map k a)

You can also write invariants for data type definitions together with the types. For example, see tests/pos/record0.hs:

data LL a = BXYZ { size  :: {v: Int | v > 0 }
                 , elems :: {v: [a] | (len v) = size }

You can also specify a decreasing size for each data. For example, see tests/pos/FancyMutualTerm.hs:

{-@ measure tsize :: Tree a -> Nat @-}
{-@ data size (Tree a) tsize @-}

{-@ data Tree a where 
      Leaf :: a -> {t:Tree a  | tsize t == 0 } 
      Node :: f:(Int -> Tree a) -> Tree a  @-}

The annotation data size (Tree a) tsize ensures that each Tree a in the fields of Tree has tsize less than the result Tree. The data size annotation can be used for mutually defined types as data size (M1 a, M2 a) msize.

Finally you can specify the variance of type variables for data types. For example, see tests/pos/Variance.hs, where data type Foo has four type variables a, b, c, d, specified as invariant, bivariant, covariant and contravariant, respectively.

{-@ data variance Foo invariant bivariant covariant contravariant @-}
data Foo a b c d

Modules WITH code: Functions

Write the specification directly into the .hs or .lhs file, above the function definition. For example:

{-@ incr :: x:{v: Int | v > 0} -> {v: Int | v > x} @-}
incr   :: Int -> Int
incr x = x + 1

Modules WITH code: Type Classes

Write the specification directly into the .hs or .lhs file. The constrained variable must match the one from the class definition. A class must have at least one refinement signature (even if it's a trivial one) to be lifted to the refinement logic. For example:

class Semigroup a where
    {-@ mappend :: a -> a -> a @-}
    mappend :: a -> a -> a
    sconcat :: NonEmpty a -> a

class Semigroup a => VSemigroup a where
    {-@ lawAssociative :: v:a -> v':a -> v'':a ->
          {mappend (mappend v v') v'' == mappend v (mappend v' v'')} @-}
    lawAssociative :: a -> a -> a -> ()

Without the extra signature for mappend, the above example would not work.

Instances can be defined without any special annotations:

data PNat = Z | S PNat

instance Semigroup PNat where
  mappend Z     n = n
  mappend (S m) n = S (mappend m n)
  sconcat (NonEmpty h t) = foldlList mappend h t

instance VSemigroup PNat where
  lawAssociative Z     _ _ = ()
  lawAssociative (S p) m n = lawAssociative p m n

The example above inlines the proofs directly into the instance definition. This requires the --aux-inline flag.

Modules WITH code: Type Classes (Legacy)

Write the specification directly into the .hs or .lhs file, above the type class definition. For example:

{-@ class Sized s where
      size :: forall a. x:s a -> {v:Int | v = (size x)}
class Sized s where
  size :: s a -> Int

Any measures used in the refined class definition will need to be generic (see Specifying Measures).

As an alternative, you can refine class instances. For example:

instance Compare Int where

{-@ instance Compare Int where
    cmax :: Odd -> Odd -> Odd

cmax y x = if x >= y then x else y

When cmax method is used on Int, liquidHaskell will give it the refined type Odd -> Odd -> Odd.

Note that currently liquidHaskell does not allow refining instances of refined classes.

Modules WITH code: QuasiQuotation

Instead of writing both a Haskell type signature and a LiquidHaskell specification for a function, the lq quasiquoter in the LiquidHaskell module can be used to generate both from just the LiquidHaskell specification.

module Nats (nats) where

{-@ nats :: [{v:Int | 0 <= v}] @-}
nats :: [Int]
nats = [1,2,3]

can be written as

{-# LANGUAGE QuasiQuotes #-}
module Nats (nats) where

import LiquidHaskell

[lq| nats :: [{v:Int | 0 <= v}] |]
nats = [1,2,3]

and the lq quasiquoter will generate the plain nats :: [Int] when GHC compiles the module.

Refined type aliases (see the next section) can also be written inside lq; for example:

{-# LANGUAGE QuasiQuoters #-}
module Nats (Nat, nats) where

[lq| type Nat = {v:Int | 0 <= v} |]

[lq| nats :: [Nat] |]
nats = [1,2,3]

Here, the lq quasiquoter will generate a plain Haskell type synonym for Nat as well as the refined one.

Note that this is still an experimental feature, and currently requires that one depend on LiquidHaskell as a build dependency for your project; the quasiquoter will be split out eventually into an independent, dependency-light package. Also, at this time, writing a type inside lq which refers to a refined type alias for which there is not a plain Haskell type synonym of the same name will result in a "not in scope" error from GHC.

Standalone Specifications for Internal Modules

Recall that the .spec mechanism is only for modules whose code is absent; if code is present then there can be multiple, possibly conflicting specifications. Nevertheless, you may want, for one reason or another, to write (assumed) specifications outside the file implementing the module.

You can do this as follows.


module Lib (foo) where

foo a = a

now, instead of a .spec file, just use a haskell module, e.g. LibSpec.hs

module LibSpec ( module Lib ) where

import Lib

-- Don't forget to qualify the name!

{-@ :: {v:a | false} -> a @-}

and then here's Client.hs

module Client where

import Lib      -- use this if you DON'T want the spec
import LibSpec  -- use this if you DO want the spec, in addition to OR instead of the previous import.

bar = foo 1     -- if you `import LibSpec` then this call is rejected by LH

Inductive Predicates

Status: very_experimental

LH recently added support for Inductive Predicates in the style of Isabelle, Coq etc. These are encoded simply as plain Haskell GADTs but suitably refined.

Apologies for the minimal documentation; see the following examples for details:

Implicit Arguments

Status: experimental

There is experimental support for implicit arguments, solved for with congruence closure. For example, consider Implicit1.hs:

{-@ type IntN N = {v:Int | v = N} @-}

{-@ foo :: n:Int ~> (() -> IntN n) -> IntN {n+1} @-}
foo f = 1 + f ()

{-@ test1 :: IntN 11 @-}
test1 = foo (\_ -> 10)

Here, the refinement on (\_ -> 10) :: Int -> { v:Int | v = 10 } allows us to solve for n = 10, the implicit argument to foo.

Refinement Type Aliases

Predicate Aliases

Often, the propositions in the refinements can get rather long and verbose. You can write predicate aliases like so:

{-@ predicate Lt X Y = X < Y        @-}
{-@ predicate Ge X Y = not (Lt X Y) @-}

and then use the aliases inside refinements, for example

{-@ incr :: x:{v:Int | (Pos v)} -> { v:Int | ((Pos v) && (Ge v x))} @-}
incr :: Int -> Int
incr x = x + 1

See Data.Map for a more substantial and compelling example.

Syntax: The key requirements for type aliases are:

  • Value parameters are specified in uppercase: X, Y, Z etc.

Failing Specifications

The fail b declaration checks that the definition of b is unsafe. E.g., the following is SAFE.

{-@ fail unsafe @-}
{-@ unsafe :: () -> { 0 == 1 } @-}
unsafe :: () -> () 
unsafe _ = ()

An error is created if fail definitions are safe or binders defined as fail are used by (failing or not) definitions.

Type Aliases

Similarly, it is often quite tedious to keep writing

{v: Int | v > 0}

Thus, LiquidHaskell supports refinement-type aliases of the form:

{-@ type Gt      N = {v: Int | N <  v} @-}
{-@ type GeNum a N = {v: a   | N <= v} @-}


{-@ type SortedList a = [a]<{\fld v -> (v >= fld)}> @-}


{-@ type OMap k a = Map <{\root v -> v < root}, {\root v -> v > root}> k a @-}


{-@ type MinSPair a = (a, OSplay a) <\fld -> {v : Splay {v:a|v>fld} | 0=0}> @-}

and then use the above in signatures like:

{-@ incr: x: Int -> GeNum Int x @-}


{-@ incr: x: Int -> Gt x @-}


{-@ assert insert :: (Ord a) => a -> SortedList a -> SortedList a @-}

see tests/pos/ListSort.hs


{-@ assert insert :: (Ord k) => k -> a -> OMap k a -> OMap k a @-}

see tests/pos/Map.hs

Syntax: The key requirements for type aliases are:

  1. Type parameters are specified in lowercase: a, b, c etc.
  2. Value parameters are specified in uppercase: X, Y, Z etc.

Infix Operators

You can define infix types and logical operators in logic Haskell's infix notation. For example, if (+++) is defined as a measure or reflected function, you can use it infix by declaring

{-@ infixl 9 +++ @-}

Note: infix operators cannot contain the dot character ..

If (==>) is a Haskell infix type (see)

infixr 1 ==>

then to use it as infix in the refinements types you need to add the refinement infix notation.

{-@ infixr 1 ==> @-}
{-@ test :: g:(f ==> g) -> f x -> f y -> ()  @-}

Specifying Measures

They can be placed in a .spec file or in a .hs/.lhs file wrapped around {-@ @-}.

Value measures: GHC/Base.spec

measure len :: forall a. [a] -> GHC.Types.Int
len ([])     = 0
len (y:ys)   = 1 + len(ys)

Propositional measures: tests/pos/LambdaEval.hs

measure isValue      :: Expr -> Bool
isValue (Const i)    = true
isValue (Lam x e)    = true
isValue (Var x)      = false
isValue (App e1 e2)  = false
isValue (Plus e1 e2) = false
isValue (Fst e)      = false
isValue (Snd e)      = false
isValue (Pair e1 e2) = ((? (isValue(e1))) && (? (isValue(e2))))

Raw measures: tests/pos/meas8.hs

{-@ measure rlen :: [a] -> Int
rlen ([])   = {v | v = 0}
rlen (y:ys) = {v | v = (1 + rlen(ys))}

Generic measures: tests/pos/Class.hs

{-@ class measure size :: a -> Int @-}
{-@ instance measure size :: [a] -> Int
    size ([])   = 0
    size (x:xs) = 1 + (size xs)
{-@ instance measure size :: Tree a -> Int
    size (Leaf)       = 0
    size (Node x l r) = 1 + (size l) + (size r)

Note: Measure names do not have to be the same as field name, e.g. we could call the measure sz in the above as shown in tests/pos/Class2.hs.

Haskell Functions as Measures (beta): tests/pos/HaskellMeasure.hs

Inductive Haskell Functions from Data Types to some type can be lifted to logic

{-@ measure llen @-}
llen        :: [a] -> Int
llen []     = 0
llen (x:xs) = 1 + llen xs

The above definition:

  • refines list's data constructors types with the llen information, and
  • specifies a singleton type for the haskell function llen :: xs:[a] -> {v:Int | v == llen xs}. If the user specifies another type for llen, say llen :: xs:[a] -> {v:Int | llen xs >= 0}, then the auto generated singleton type is overwritten.


The inline lets you use a Haskell function in a type specification.

{-@ inline max @-}
{-@ max :: Int -> Int -> Int @-}
max :: Int -> Int -> Int
max x y = if x > y then x else y

For example, if you write the above you can then write a function:

{-@ floor :: x:Int -> {v:Int | max 0 x} @-}
floor :: Int -> Int
floor x 
  | x <= 0    = 0
  | otherwise = x

That is, you can use the haskell max in the refinement type and it will automatically get “expanded” out to the full definition. This makes it useful e.g. to reuse plain Haskell code to compose specifications, and to share definitions common to refinements and code.

However, as they are expanded at compile time, inline functions cannot be recursive. The can call other (non-recursive) inline functions.

If you want to talk about arbitrary (recursive) functions inside your types, then you need to use reflect described in the blog.


Sometimes, we require specifications that allow inner components of a type to refer to the outer components, typically, to measure-based properties of outer components. For example, the following invariant about Maybe values

{-@ type IMaybe a = {v0 : Maybe {v : a | ((isJust v0) && v = (fromJust v0))} | 0 = 0 } @-}

states that the inner a enjoys the property that the outer container is definitely a Just and furthermore, the inner value is exactly the same as the fromJust property of the outer container.

As another example, suppose we have a measure:

measure listElts :: [a] -> (Set a)
listElts([])   = {v | (? Set_emp(v))}
listElts(x:xs) = {v | v = Set_cup(Set_sng(x), listElts(xs)) }

Now, all lists enjoy the property

{-@ type IList a = {v0 : List  {v : a | (Set_mem v (listElts v0)) } | true } @-}

which simply states that each inner element is indeed, a member of the set of the elements belonging to the entire list.

One often needs these circular or self invariants to connect different levels (or rather, to reify the connections between the two levels.) See this test for a simple example and hedgeUnion and Data.Map.Base for a complex one.

Abstract and Bounded Refinements

This is probably the best example of the abstract refinement syntax:

Unfortunately, the best documentation for these two advanced features is the relevant papers at:

The bounds correspond to Horn implications between abstract refinements, which, as in the classical setting, correspond to subtyping constraints that must be satisfied by the concrete refinements used at any call-site.

Dependent Pairs

Dependent Pairs are expressed by binding the initial tuples of the pair. For example incrPair defines an increasing pair.

{-@ incrPair :: Int -> (x::Int, {v:Int | x <= v}) @-}
incrPair i = (i, i+1)

Internally dependent pairs are implemented using abstract refinement types. That is (x::a, {v:b | p x}) desugars to (a,b)<\x -> {v:b | p x}>.


LH lets you locally associate invariants with specific data types.

For example, in tests/measure/pos/Using00.hs every list is treated as a Stream. To establish this local invariant one can use the using declaration

{-@ using ([a]) as  {v:[a] | (len v > 0)} @-}

denoting that each list is not empty.

Then, LiquidHaskell will prove that this invariant holds, by proving that all calls to List's constructors (ie., : and []) satisfy it, and will assume that each list element that is created satisfies this invariant.

With this, at the above test LiquidHaskell proves that taking the head of a list is safe. But, at tests/measure/neg/Using00.hs the usage of [] falsifies this local invariant resulting in an "Invariant Check" error.

WARNING: There is an older global invariant mechanism that attaches a refinement to a datatype globally. Do not use this mechanism -- it is unsound and about to deprecated in favor of something that is actually sound

For example, the length of a list cannot be negative

{-@ invariant {v:[a] | (len v >= 0)} @-}

LiquidHaskell can prove that this invariant holds, by proving that all List's constructors (ie., : and []) satisfy it.(TODO!) Then, LiquidHaskell assumes that each list element that is created satisfies this invariant.


Status: experimental

You use the rewriteWith annotation to indicate equalities that PLE will apply automatically. For example, suppose that you have proven associativity of ++ for lists.

{-@ assoc :: xs:[a] -> ys:[a] -> zs:[a] 
          -> { xs ++ (ys ++ zs) == (xs ++ ys) ++ zs } @-}

Using the rewriteWith annotation, PLE will automatically apply the equality for associativity whenever it encounters an expression of the form xs ++ (ys ++ zs) or (xs ++ ys) ++ zs. For example, you can prove assoc2 for free.

{-@ rewriteWith assoc2 [assoc] @-} 
{-@ assoc2 :: xs:[a] -> ys:[a] -> zs:[a] -> ws:[a]
          -> { xs ++ (ys ++ (zs ++ ws)) == ((xs ++ ys) ++ zs) ++ ws } @-}
assoc2 :: [a] -> [a] -> [a] -> [a] -> ()
assoc2 xs ys zs ws = () 

You can also annotate a function as being a global rewrite rule by using the rewrite annotation, in which case PLE will apply it across the entire module.

{-@ rewrite assoc @-}
{-@ assoc :: xs:[a] -> ys:[a] -> zs:[a] 
          -> { xs ++ (ys ++ zs) == (xs ++ ys) ++ zs } @-}


Currently, rewriting does not work if the equality that uses the rewrite rule includes parameters that contain inner refinements (test).

Rewriting works by pattern-matching expressions to determine if there is a variable substitution that would allow it to match against either side of a rewrite rule. If so, that substitution is applied to the opposite side and the corresponding equality is generated. If one side of the equality contains any parameters that are not bound on the other side, it will not be possible to generate a rewrite in that direction, because those variables cannot be instantiated. Likewise, if there are free variables on both sides of an equality, no rewrite can be generated at all (test).

It's possible in theory for rewriting rules to diverge. We have a simple check to ensure that rewriting rules that will always diverge do not get instantiated. However, it's possible that applying a combination of rewrite rules could cause divergence.

Formal Grammar of Refinement Predicates


c := 0, 1, 2, ...


v := x, y, z, ...


e := v                      -- variable
   | c                      -- constant
   | (e + e)                -- addition
   | (e - e)                -- subtraction
   | (c * e)                -- multiplication by constant
   | (v e1 e2 ... en)       -- uninterpreted function application
   | (if p then e else e)   -- if-then-else


r := ==               -- equality
   | /=               -- disequality
   | >=               -- greater than or equal
   | <=               -- less than or equal
   | >                -- greater than
   | <                -- less than


p := (e r e)          -- binary relation
   | (v e1 e2 ... en) -- predicate (or alias) application
   | (p && p)         -- and
   | (p || p)         -- or
   | (p => p)         -- implies
   | (not p)          -- negation
   | true
   | false

Specifying Qualifiers

There are several ways to specify qualifiers.

By Separate .hquals Files

You can write qualifier files e.g. Prelude.hquals..

If a module is called or imports


Then the system automatically searches for


By Including .hquals Files

Additional qualifiers may be used by adding lines of the form:

{-@ include <path/to/file.hquals> @-}

to the Haskell source. See, this for example.

In Haskell Source or Spec Files

Finally, you can specifiers directly inside source (.hs or .lhs) or spec (.spec) files by writing as shown here

{-@ qualif Foo(v:Int, a: Int) : (v = a + 100)   @-}

Note In addition to these, LiquidHaskell scrapes qualifiers from all the specifications you write i.e.

  1. all imported type signatures,
  2. measure bodies and,
  3. data constructor definitions.

Termination Metrics

In recursive functions the first algebraic or integer argument should be decreasing.

The default decreasing measure for lists is length and Integers its value.

Default Termination Metrics

The user can specify the size of a data-type in the data definition

{-@ data L [llen] a = Nil | Cons { x::a, xs:: L a} @-}

In the above, the measure llen, which needs to be defined by the user (see below), is defined as the default metric for the type L a. LH will use this default metric to automatically prove that the following terminates:

append :: L a -> L a -> L a  
append N           ys = ys
append (Cons x xs) ys = Cons x (append xs ys)

as, by default the first (non-function) argument with an associated size metric is checked to be strictly terminating and non-negative at each recursive call.

A default termination metric is a Haskell function that is proved terminating using structural induction. To deactivate structional induction check on the termination metric, use the --trust-sizes flag.

Explicit Termination Metrics

However, consider the function reverse:

reverseAcc :: L a -> L a -> L a  
reverseAcc acc N           = acc
reverseAcc acc (Cons x xs) = reverseAcc (Cons x acc) xs

Here, the first argument does not decrease, instead the second does. We can tell LH to use the second argument using the explicit termination metric

reverseAcc :: L a -> xs:L a -> L a / [llen xs]  

which tells LH that the llen of the second argument xs is what decreases at each recursive call.

Decreasing expressions can be arbitrary refinement expressions, e.g.,

{-@ merge :: Ord a => xs:L a -> ys:L a -> L a / [llen xs + llen ys] @-}

states that at each recursive call of merge the sum of the lengths of its arguments will decrease.

Lexicographic Termination Metrics

Some functions do not decrease on a single argument, but rather a combination of arguments, e.g. the Ackermann function.

{-@ ack :: m:Int -> n:Int -> Nat / [m, n] @-}
ack m n
  | m == 0          = n + 1
  | m > 0 && n == 0 = ack (m-1) 1
  | m > 0 && n >  0 = ack (m-1) (ack m (n-1))

In all but one recursive call m decreases, in the final call m does not decrease but n does. We can capture this notion of m normally decreases, but if it does not, n will decrease with a lexicographic termination metric [m, n].

An alternative way to express this specification is by annotating the function's type with the appropriate numeric decreasing expressions. As an example, you can give ack a type

{-@ ack :: m:Nat -> n:Nat -> Nat / [m,n] @-}

stating that the numeric expressions [m, n] are lexicographically decreasing.

Mutually Recursive Functions

When dealing with mutually recursive functions you may run into a situation where the decreasing parameter must be measured across a series of invocations, e.g.

even :: Int -> Bool
even 0 = True
even n = odd (n-1)

odd :: Int -> Bool
odd  n = not (even n)

In this case, you can introduce a ghost parameter that orders the functions

{-@ isEven :: n:Nat -> Bool / [n, 0] @-}
isEven :: Int -> Bool
isEven 0 = True
isEven n = isOdd (n-1)

{-@ isOdd :: n:Nat -> Bool / [n, 1] @-}
isOdd :: Int -> Bool
isOdd  n = not $ isEven n

thus recovering a decreasing measure for the pair of functions, the pair of arguments. This can be encoded with the lexicographic termination annotation as shown above. See tests/pos/mutrec.hs for the full example.

Automatic Termination Metrics

Apart from specifying a specific decreasing measure for an Algebraic Data Type, the user can specify that the ADT follows the expected decreasing measure by

{-@ autosize L @-}

Then, LH will define an instance of the function autosize for L that decreases by 1 at each recursive call and use autosize at functions that recurse on L.

For example, autosize L will refine the data constructors of L a with the autosize :: a -> Int information, such that

Nil  :: {v:L a | autosize v = 0}
Cons :: x:a -> xs:L a -> {v:L a | autosize v = 1 + autosize xs}

Also, an invariant that autosize is non negative will be generated

invariant  {v:L a| autosize v >= 0 }

This information is all LiquidHaskell needs to prove termination on functions that recurse on L a (on ADTs in general.)

Disabling Termination Checking

To disable termination checking for foo that is, to assume that it is terminating (possibly for some complicated reason currently beyond the scope of LH) you can write

{-@ lazy foo @-}

Relational Types

Status: experimental

LH supports relational specifications that automatically compare two expressions. The implementation is based on an algorithmic subsystem of Relational Higher-Order Logic.

Example: Proving Monotonicity of Increment

In this example, we are going to prove monotonicity of an increment function. First, we define a function:

incr :: Int -> Int 
incr = (+ 1)

Monotonicity states that for any x1, x2 :: Int such that x1 < x2, inequality incr x1 < incr x2 holds. This can be expressed as a comparison property on incr.

{-@ relational incr ~ incr :: { x1:Int -> Int 
                              ~ x2:Int -> Int 
                              | x1 < x2 :=> r1 x1 < r2 x2 } @-}

Relational signature starts with the keyword relational. Next, it contains two functions being compared incr ~ incr. To prove monotonicity, we compare incr to itself. In the general case, it is possible to compare two different functions.

Related expressions are followed by their type signatures x1:Int -> Int and x2:Int -> Int separated with a tilde. The last component of the signature is a predicate x1 < x2 :=> r1 x1 < r2 x2.

Binders x1 and x2 refer to the functions' arguments. Keywords r1 and r2 are aliases for lhs incr and rhs incr respectively. The predicate is logically equivalent to x1 < x2 => r1 x1 < r2 x2. Implication symbol :=> separates the precondition on the arguments from the postcondition on the return values.

Relational Predicate Syntax

A relational predicate is a sequence of clauses separated by top-level implication connectives :=> (logically equivalent to =>):

x1 < x2 :=> y1 < y2 :=> r1 x1 y1 < r2 x2 y2
^^^^^^^     ^^^^^^^     ^^^^^^^^^^^^^^^^^^^
  1st         2nd            3rd clause               
  • Number of Clauses

    The number of clauses must match the number of arguments of each of the compared expressions. Hence, a relational signature can only be assigned to two expressions with the same number of arguments.

    ```haskell plus :: Int -> Int -> Int plus = (+)

    -- clauses == arguments + 1

    {-@ relational plus ~ plus :: { x1:Int -> y1:Int -> Int ~ x2:Int -> y2:Int -> Int | x1 < x2 :=> y1 < y2 :=> r1 x1 y1 < r2 x2 y2 } @-} ^^^^^^^ ^^^^^^^ ^^^^^^^^^^^^^^^^^^^

    For example, function incr has 1 argument. Its relational predicate has 1 implication that separates the precondition from the postcondition: x1 < x2 :=> r1 x1 < r2 x2.

    Nested, non-top-level implications are allowed, e.g. (true => x1 < x2) :=> (r1 x1 < r2 x2).

  • Argument Scopes

    Similar to the number of clauses, the order of the argument introduction must match that of the compared functions. A binder that appears in ith clause of the predicate must appear on ith position in the function argument list or earlier.

    These relational signatures are syntactically invalid: ```haskell -- ERROR: clauses < arguments + 1

    {-@ relational plus ~ plus :: { x1:Int -> y1:Int -> Int ~ x2:Int -> y2:Int -> Int | x1 < x2 && y1 < y2 :=> r1 x1 y1 < r2 x2 y2 } @-}

    -- ERROR: y1 and y2 used before their introduction

    {-@ relational plus ~ plus :: { x1:Int -> y1:Int -> Int ~ x2:Int -> y2:Int -> Int | y1 < y2 :=> x1 < x2 :=> r1 x1 y1 < r2 x2 y2 } @-}


    Correct versions could look like this: ```haskell {-@ relational plus ~ plus :: { x1:Int -> y1:Int -> Int ~ x2:Int -> y2:Int -> Int | x1 < x2 :=> y1 < y2 :=> r1 x1 y1 < r2 x2 y2 } @-}

    {-@ relational plus ~ plus :: { x1:Int -> y1:Int -> Int ~ x2:Int -> y2:Int -> Int | true :=> x1 < x2 && y1 < y2 :=> r1 x1 y1 < r2 x2 y2 } @-}

    {-@ relational plus ~ plus :: { x1:Int -> y1:Int -> Int ~ x2:Int -> y2:Int -> Int | true :=> true :=> x1 < x2 => y1 < y2 => r1 x1 y1 < r2 x2 y2 } @-} ```

Provided Guarantees

For all possible inputs of the two compared functions, it is guaranteed that the relational predicate holds.

Running Relational Checks

Enable reflection.

In the command line:

liquid --reflection path/to/File.hs

Or in a Haskell source file:

{-@ LIQUID --reflection @-}

Current limitations

  • No support for abstract refinements. All abstract refinements are erased before relational typechecking. Notably, this happens for the standard list [a] and tuple (a, b) types!

  • Limited support for higher-order relational signatures. Use !=> instead of :=> after the function arguments to enable higher-order checking.