CS计算机代考程序代写 compiler Haskell algorithm Agda Static Assurance Phantom Types GADTs Type Families

Static Assurance Phantom Types GADTs Type Families
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Software System Design and Implementation
Static Assurance with Types
Christine Rizkallah
UNSW Sydney Term 2 2021

Static Assurance Phantom Types GADTs Type Families
Methods of Assurance
Static Hybrid Dynamic
Testing

Static Assurance Phantom Types GADTs Type Families
Methods of Assurance
assert()
Static Hybrid Dynamic
Testing

Static Assurance
Phantom Types GADTs Type Families
Methods of Assurance
Monitors, watchdogs
assert()
Static Hybrid Dynamic
Testing

Static Assurance
Phantom Types GADTs Type Families
Methods of Assurance
Monitors, watchdogs
assert()
Static Hybrid Dynamic
Types Testing

Static Assurance
Phantom Types GADTs Type Families
Methods of Assurance
Proofs
Static
Types
Hybrid
Monitors, watchdogs
assert()
Dynamic
Testing

Static Assurance
Phantom Types GADTs Type Families
Methods of Assurance
Static Analysers Proofs
Static
Types
Hybrid
Monitors, watchdogs
assert()
Dynamic
Testing

Static Assurance
Phantom Types GADTs Type Families
Methods of Assurance
Static Analysers Proofs
Static
Types
Model Checkers
Hybrid
Monitors, watchdogs
assert()
Dynamic
Testing

Static Assurance
Phantom Types GADTs Type Families
Methods of Assurance
Static Analysers Proofs
Static
Types
Model Checkers
Hybrid
Contracts
Monitors, watchdogs
assert()
Dynamic
Testing

Static Assurance
Phantom Types GADTs Type Families
Methods of Assurance
Static Analysers Proofs
Static
Types
Model Checkers
Monitors, watchdogs
Gradual Types
Hybrid
Contracts
assert()
Dynamic
Testing
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Static means of assurance analyse a program without running it.

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Static Assurance Phantom Types GADTs Type Families
Static vs. Dynamic
Static checks can be exhaustive.

Static Assurance Phantom Types GADTs Type Families
Static vs. Dynamic
Static checks can be exhaustive. Exhaustivity
An exhaustive check is a check that is able to analyse all possible executions of a program.
However, some properties cannot be checked statically in general (halting problem), or are intractable to feasibly check statically (state space explosion).
Dynamic checks cannot be exhaustive, but can be used to check some properties where static methods are unsuitable.
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Static Assurance Phantom Types GADTs Type Families
Compiler Integration
Most static and all dynamic methods of assurance are not integrated into the compilation process.

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Static Assurance Phantom Types GADTs Type Families
Compiler Integration
Most static and all dynamic methods of assurance are not integrated into the compilation process.
You can compile and run your program even if it fails tests.

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Static Assurance Phantom Types GADTs Type Families
Compiler Integration
Most static and all dynamic methods of assurance are not integrated into the compilation process.
You can compile and run your program even if it fails tests.
You can change your program to diverge from your model checker model.

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Static Assurance Phantom Types GADTs Type Families
Compiler Integration
Most static and all dynamic methods of assurance are not integrated into the compilation process.
You can compile and run your program even if it fails tests.
You can change your program to diverge from your model checker model. Your proofs can diverge from your implementation.

Static Assurance Phantom Types GADTs Type Families
Compiler Integration
Most static and all dynamic methods of assurance are not integrated into the compilation process.
You can compile and run your program even if it fails tests.
You can change your program to diverge from your model checker model. Your proofs can diverge from your implementation.
Types
Because types are integrated into the compiler, they cannot diverge from the source code. This means that type signatures are a kind of machine-checked documentation for your code.
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Static Assurance Phantom Types
GADTs Type Families
Types
Types are the most widely used kind of formal verification in programming today. They are checked automatically by the compiler.
They can be extended to encompass properties and proof systems with very high expressivity (covered next week).
They are an exhaustive analysis.

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Static Assurance Phantom Types
GADTs Type Families
Types
Types are the most widely used kind of formal verification in programming today. They are checked automatically by the compiler.
They can be extended to encompass properties and proof systems with very high expressivity (covered next week).
They are an exhaustive analysis.
This week, we’ll look at techniques to encode various correctness conditions inside Haskell’s type system.

Static Assurance Phantom Types GADTs Type Families
Phantom Types
Definition
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A type parameter is phantom if it does not appear in the right hand side of the type definition.
newtype Size x = S Int

Static Assurance Phantom Types GADTs Type Families
Phantom Types
Definition
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A type parameter is phantom if it does not appear in the right hand side of the type definition.
newtype Size x = S Int
Let’s examine each one of the following use cases:
We can use this parameter to track what data invariants have been established about a value.

Static Assurance Phantom Types GADTs Type Families
Phantom Types
Definition
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A type parameter is phantom if it does not appear in the right hand side of the type definition.
newtype Size x = S Int
Let’s examine each one of the following use cases:
We can use this parameter to track what data invariants have been established about a value.
We can use this parameter to track information about the representation (e.g. units of measure).

Static Assurance Phantom Types GADTs Type Families
Phantom Types
Definition
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A type parameter is phantom if it does not appear in the right hand side of the type definition.
newtype Size x = S Int
Let’s examine each one of the following use cases:
We can use this parameter to track what data invariants have been established about a value.
We can use this parameter to track information about the representation (e.g. units of measure).
We can use this parameter to enforce an ordering of operations performed on these values (type state).

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Static Assurance Phantom Types
GADTs
Type Families
data UG — empty type
data PG
data StudentID x = SID Int
Validation

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Static Assurance Phantom Types
GADTs
Type Families
data UG — empty type
data PG
data StudentID x = SID Int
We can define a smart constructor that specialises the type parameter: sid :: Int -> Either (StudentID UG)
(StudentID PG) (Recalling the following definition of Either)
data Either a b = Left a | Right b
Validation

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Static Assurance Phantom Types
GADTs
Type Families
data UG — empty type
data PG
data StudentID x = SID Int
We can define a smart constructor that specialises the type parameter: sid :: Int -> Either (StudentID UG)
(StudentID PG) (Recalling the following definition of Either)
data Either a b = Left a | Right b And then define functions:
enrolInCOMP3141 :: StudentID UG -> IO ()
lookupTranscript :: StudentID x -> IO String
Validation

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Static Assurance Phantom Types GADTs Type Families
Units of Measure
In 1999, software confusing units of measure (pounds and newtons) caused a mars orbiter to burn up on atmospheric entry.
data Kilometres
data Miles
data Value x = U Int
sydneyToMelbourne = (U 877 :: Value Kilometres)
losAngelesToSanFran = (U 383 :: Value Miles)

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Static Assurance Phantom Types GADTs Type Families
Units of Measure
In 1999, software confusing units of measure (pounds and newtons) caused a mars orbiter to burn up on atmospheric entry.
data Kilometres
data Miles
data Value x = U Int
sydneyToMelbourne = (U 877 :: Value Kilometres)
losAngelesToSanFran = (U 383 :: Value Miles)
In addition to tagging values, we can also enforce constraints on units:
data Square a
area :: Value m -> Value m -> Value (Square m)
area (U x) (U y) = U (x * y)
Note the arguments to area must have the same units.

Static Assurance Phantom Types
GADTs Type Families
Type State
Example
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A Socket can either be ready to recieve data, or busy. If the socket is busy, the user must first use the wait operation, which blocks until the socket is ready. If the socket is ready, the user can use the send operation to send string data, which will make the socket busy again.

Static Assurance Phantom Types
GADTs Type Families
Type State
Example
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A Socket can either be ready to recieve data, or busy. If the socket is busy, the user must first use the wait operation, which blocks until the socket is ready. If the socket is ready, the user can use the send operation to send string data, which will make the socket busy again.
data Busy
data Ready
newtype Socket s = Socket …
wait :: Socket Busy -> IO (Socket Ready)
send :: Socket Ready -> String -> IO (Socket Busy) What assumptions are we making here?

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Static Assurance Phantom Types GADTs Type Families
Linearity and Type State
The previous code assumed that we didn’t re-use old Sockets:
send2 :: Socket Ready -> String -> String
-> IO (Socket Busy)
send2 s x y = do s’ <- send s x s'' <- wait s' s''' <- send s'' y pure s''' 33 Static Assurance Phantom Types GADTs Type Families Linearity and Type State The previous code assumed that we didn’t re-use old Sockets: send2 :: Socket Ready -> String -> String
-> IO (Socket Busy)
send2 s x y = do s’ <- send s x s'' <- wait s' s''' <- send s'' y pure s''' But we can just re-use old values to send without waiting: send2' s x y = do _ <- send s x s' <- send s y pure s' Static Assurance Phantom Types GADTs Type Families Linearity and Type State The previous code assumed that we didn’t re-use old Sockets: send2 :: Socket Ready -> String -> String
-> IO (Socket Busy)
send2 s x y = do s’ <- send s x s'' <- wait s' s''' <- send s'' y pure s''' But we can just re-use old values to send without waiting: send2' s x y = do _ <- send s x s' <- send s y pure s' Linear type systems can solve this, but not in Haskell (yet). 34 35 Static Assurance Phantom Types GADTs Type Families Datatype Promotion data UG data PG data StudentID x = SID Int 36 Static Assurance Phantom Types GADTs Type Families Datatype Promotion data UG data PG data StudentID x = SID Int Defining empty data types for our tags is untyped. We can have StudentID UG, but also StudentID String. Static Assurance Phantom Types GADTs Type Families Datatype Promotion data UG data PG data StudentID x = SID Int Defining empty data types for our tags is untyped. We can have StudentID UG, but also StudentID String. Recall Haskell types themselves have types, called kinds. Can we make the kind of our tag types more precise than *? 37 Static Assurance Phantom Types GADTs Type Families Datatype Promotion data UG data PG data StudentID x = SID Int Defining empty data types for our tags is untyped. We can have StudentID UG, but also StudentID String. Recall Haskell types themselves have types, called kinds. Can we make the kind of our tag types more precise than *? The DataKinds language extension lets us use data types as kinds: {-# LANGUAGE DataKinds, KindSignatures #-} data Stream = UG | PG data StudentID (x :: Stream) = SID Int -- rest as before 38 Static Assurance Phantom Types GADTs Type Families Motivation: Evaluation data Expr = BConst Bool | IConst Int | Times Expr Expr | Less Expr Expr | And Expr Expr | If Expr Expr Expr data Value = BVal Bool | IVal Int Example Define an expression evaluator: eval :: Expr -> Value
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Static Assurance Phantom Types GADTs Type Families
Motivation: Partiality
Unfortunately the eval function is partial, undefined for input expressions that are not well-typed, like:
And (ICons 3) (BConst True)

Static Assurance Phantom Types GADTs Type Families
Motivation: Partiality
Unfortunately the eval function is partial, undefined for input expressions that are not well-typed, like:
And (ICons 3) (BConst True)
Recall
With any partial function, we can make it total by either expanding the co-domain (e.g. with a Maybe type), or constraining the domain.
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Static Assurance Phantom Types GADTs Type Families
Attempt: Phantom Types
Let’s try adding a phantom parameter to Expr, and defining typed constructors with precise types:

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Static Assurance Phantom Types GADTs Type Families
Attempt: Phantom Types
Let’s try adding a phantom parameter to Expr, and defining typed constructors with precise types:
data Expr t = …
bConst :: Bool -> Expr Bool
bConst = BConst
iConst :: Int -> Expr Int
iConst = IConst
times :: Expr Int -> Expr Int -> Expr Int
times = Times
less :: Expr Int -> Expr Int -> Expr Bool
less = Less
and :: Expr Bool -> Expr Bool -> Expr Bool
and = And
if’ ::ExprBool->Expra->Expra->Expra if’ = If

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Static Assurance Phantom Types GADTs Type Families
Attempt: Phantom Types
This makes invalid expressions into type errors (yay!):
— Couldn’t match Int and Bool
and (iCons 3) (bConst True)

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Static Assurance Phantom Types GADTs Type Families
Attempt: Phantom Types
This makes invalid expressions into type errors (yay!):
— Couldn’t match Int and Bool
and (iCons 3) (bConst True)
How about our eval function? What should its type be now?

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Static Assurance Phantom Types GADTs Type Families
Attempt: Phantom Types
This makes invalid expressions into type errors (yay!):
— Couldn’t match Int and Bool
and (iCons 3) (bConst True)
How about our eval function? What should its type be now?
eval :: Expr t ->

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Static Assurance Phantom Types GADTs Type Families
Attempt: Phantom Types
This makes invalid expressions into type errors (yay!):
— Couldn’t match Int and Bool
and (iCons 3) (bConst True)
How about our eval function? What should its type be now?
eval:: Exprt->t

Static Assurance Phantom Types GADTs Type Families
Attempt: Phantom Types
This makes invalid expressions into type errors (yay!):
— Couldn’t match Int and Bool
and (iCons 3) (bConst True)
How about our eval function? What should its type be now?
eval:: Exprt->t
Bad News
Inside eval, the Haskell type checker cannot be sure that we used our typed constructors, so in e.g. the IConst case:
eval :: Expr t -> t
eval (IConst i) = i — type error
We are unable to tell that the type t is definitely Int.
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Static Assurance Phantom Types
GADTs Type Families
GADTs
Generalised Algebraic Datatypes (GADTs) is an extension to Haskell that, among other things, allows data types to be specified by writing the types of their constructors:
{-# LANGUAGE GADTs, KindSignatures #-}
— Unary natural numbers, e.g. 3 is S (S (S Z)) data Nat = Z | S Nat
— is the same as
data Nat :: * where
Z :: Nat
S :: Nat -> Nat

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Static Assurance Phantom Types
GADTs Type Families
GADTs
Generalised Algebraic Datatypes (GADTs) is an extension to Haskell that, among other things, allows data types to be specified by writing the types of their constructors:
{-# LANGUAGE GADTs, KindSignatures #-}
— Unary natural numbers, e.g. 3 is S (S (S Z)) data Nat = Z | S Nat
— is the same as
data Nat :: * where
Z :: Nat
S :: Nat -> Nat
When combined with the type indexing trick of phantom types, this becomes very powerful!

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Static Assurance Phantom Types GADTs Type Families
Expressions as a GADT
data Expr :: * -> * where
BConst :: Bool -> Expr Bool
IConst :: Int -> Expr Int
Times :: Expr Int -> Expr Int -> Expr Int
Less :: Expr Int -> Expr Int -> Expr Bool
And :: Expr Bool -> Expr Bool -> Expr Bool
If ::ExprBool->Expra->Expra->Expra

Static Assurance Phantom Types GADTs Type Families
Expressions as a GADT
data Expr :: * -> * where
BConst :: Bool -> Expr Bool
IConst :: Int -> Expr Int
Times :: Expr Int -> Expr Int -> Expr Int
Less :: Expr Int -> Expr Int -> Expr Bool
And :: Expr Bool -> Expr Bool -> Expr Bool
If ::ExprBool->Expra->Expra->Expra
Observation
There is now only one set of precisely-typed constructors.
Inside eval now, the Haskell type checker accepts our previously problematic case:
eval :: Expr t -> t
eval (IConst i) = i — OK now
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Static Assurance Phantom Types
GADTs
Type Families
Lists
We could define our own list type using GADT syntax as follows:
data List (a :: *) :: * where
Nil :: List a
Cons :: a -> List a -> List a

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Static Assurance Phantom Types
GADTs
Type Families
Lists
We could define our own list type using GADT syntax as follows:
data List (a :: *) :: * where
Nil :: List a
Cons :: a -> List a -> List a
But, if we define head (hd) and tail (tl) functions, they’re partial (boo!):
hd (Cons x xs) = x
tl (Cons x xs) = xs

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Static Assurance Phantom Types
GADTs
Type Families
Lists
We could define our own list type using GADT syntax as follows:
data List (a :: *) :: * where
Nil :: List a
Cons :: a -> List a -> List a
But, if we define head (hd) and tail (tl) functions, they’re partial (boo!): hd (Cons x xs) = x
tl (Cons x xs) = xs
We will constrain the domain of these functions by tracking the length of the list on the type level.

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Static Assurance Phantom Types
GADTs Type Families
Vectors
As before, define a natural number kind to use on the type level:
data Nat = Z | S Nat

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Static Assurance Phantom Types
GADTs
Type Families
Vectors
As before, define a natural number kind to use on the type level:
data Nat = Z | S Nat
Now our length-indexed list can be defined, called a Vec:
data Vec (a :: *) :: Nat -> * where Nil ::VecaZ
Cons :: a -> Vec a n -> Vec a (S n)

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Static Assurance Phantom Types
GADTs
Type Families
Vectors
As before, define a natural number kind to use on the type level:
data Nat = Z | S Nat
Now our length-indexed list can be defined, called a Vec:
data Vec (a :: *) :: Nat -> * where Nil ::VecaZ
Cons :: a -> Vec a n -> Vec a (S n)
Now hd and tl can be total:
hd :: Vec a (S n) -> a
hd (Cons x xs) = x
tl :: Vec a (S n) -> Vec a n
tl (Cons x xs) = xs

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Static Assurance Phantom Types GADTs Type Families
Vectors, continued
Our map for vectors is as follows:
mapVec :: (a -> b) -> Vec a n -> Vec b n
mapVec f Nil = Nil
mapVec f (Cons x xs) = Cons (f x) (mapVec f xs)

Static Assurance Phantom Types GADTs Type Families
Vectors, continued
Our map for vectors is as follows:
mapVec :: (a -> b) -> Vec a n -> Vec b n
mapVec f Nil = Nil
mapVec f (Cons x xs) = Cons (f x) (mapVec f xs)
Properties
Using this type, it’s impossible to write a mapVec function that changes the length of the vector.
Properties are verified by the compiler!
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Static Assurance Phantom Types
GADTs Type Families
Tradeoffs
The benefits of this extra static checking are obvious, however:
It can be difficult to convince the Haskell type checker that your code is correct, even when it is.

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Static Assurance Phantom Types
GADTs Type Families
Tradeoffs
The benefits of this extra static checking are obvious, however:
It can be difficult to convince the Haskell type checker that your code is correct, even when it is.
Type-level encodings can make types more verbose and programs harder to understand.

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Static Assurance Phantom Types
GADTs Type Families
Tradeoffs
The benefits of this extra static checking are obvious, however:
It can be difficult to convince the Haskell type checker that your code is correct, even when it is.
Type-level encodings can make types more verbose and programs harder to understand.
Sometimes excessively detailed types can make type-checking very slow, hindering productivity.

Static Assurance Phantom Types
GADTs Type Families
Tradeoffs
The benefits of this extra static checking are obvious, however:
It can be difficult to convince the Haskell type checker that your code is correct, even when it is.
Type-level encodings can make types more verbose and programs harder to understand.
Sometimes excessively detailed types can make type-checking very slow, hindering productivity.
Pragmatism
We should use type-based encodings only when the assurance advantages outweigh the clarity disadvantages.
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Static Assurance Phantom Types GADTs Type Families
Appending Vectors
Example (Problem)
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appendV :: Vec a m -> Vec a n -> Vec a ???

Static Assurance Phantom Types GADTs Type Families
Appending Vectors
Example (Problem)
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appendV :: Vec a m -> Vec a n -> Vec a ???
We want to write m + n in the ??? above, but we do not have addition defined for
kind Nat.

Static Assurance Phantom Types GADTs Type Families
Appending Vectors
Example (Problem)
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appendV :: Vec a m -> Vec a n -> Vec a ???
We want to write m + n in the ??? above, but we do not have addition defined for
kind Nat.
We can define a normal Haskell function easily enough:
plus :: Nat -> Nat -> Nat
plus Z y = y
plus (S x) y = S (plus x y)

Static Assurance Phantom Types GADTs Type Families
Appending Vectors
Example (Problem)
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appendV :: Vec a m -> Vec a n -> Vec a ???
We want to write m + n in the ??? above, but we do not have addition defined for
kind Nat.
We can define a normal Haskell function easily enough:
plus :: Nat -> Nat -> Nat
plus Z y = y
plus (S x) y = S (plus x y)
This function is not applicable to type-level Nats, though.

Static Assurance Phantom Types GADTs Type Families
Appending Vectors
Example (Problem)
75
appendV :: Vec a m -> Vec a n -> Vec a ???
We want to write m + n in the ??? above, but we do not have addition defined for
kind Nat.
We can define a normal Haskell function easily enough:
plus :: Nat -> Nat -> Nat
plus Z y = y
plus (S x) y = S (plus x y)
This function is not applicable to type-level Nats, though. ⇒ we need a type level function.

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Static Assurance Phantom Types GADTs Type Families
Type Families
Type level functions, also called type families, are defined in Haskell like so:
{-# LANGUAGE TypeFamilies #-}
type family Plus (x :: Nat) (y :: Nat) :: Nat where
Plus Z y = y
Plus (S x) y = S (Plus x y)
We can use our type family to define appendV:
appendV :: Vec a m -> Vec a n -> Vec a (Plus m n)
appendV Nil ys = ys
appendV (Cons x xs) ys = Cons x (appendV xs ys)

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Static Assurance Phantom Types
GADTs Type Families
Recursion
If we had implemented Plus by recursing on the second argument instead of the first: {-# LANGUAGE TypeFamilies #-}
type family Plus’ (x :: Nat) (y :: Nat) :: Nat where
Plus’ x Z = x
Plus’ x (S y) = S (Plus’ x y)

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Static Assurance Phantom Types
GADTs Type Families
Recursion
If we had implemented Plus by recursing on the second argument instead of the first: {-# LANGUAGE TypeFamilies #-}
type family Plus’ (x :: Nat) (y :: Nat) :: Nat where
Plus’ x Z = x
Plus’ x (S y) = S (Plus’ x y)
Then our appendV code would not type check.
appendV :: Vec a m -> Vec a n -> Vec a (Plus’ m n) appendV Nil ys = ys
appendV (Cons x xs) ys = Cons x (appendV xs ys) Why?

Static Assurance Phantom Types
GADTs Type Families
Recursion
If we had implemented Plus by recursing on the second argument instead of the first: {-# LANGUAGE TypeFamilies #-}
type family Plus’ (x :: Nat) (y :: Nat) :: Nat where
Plus’ x Z = x
Plus’ x (S y) = S (Plus’ x y)
Then our appendV code would not type check.
appendV :: Vec a m -> Vec a n -> Vec a (Plus’ m n) appendV Nil ys = ys
appendV (Cons x xs) ys = Cons x (appendV xs ys) Why?
Answer
Consider the Nil case. We know m = Z, and must show that our desired return type Plus′ Z n equals our given return type n, but that fact is not immediately apparent from the equations.
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Static Assurance Phantom Types GADTs Type Families
Type-driven development
This lecture is only a taste of the full power of type-based specifications.
Languages supporting dependent types (Idris, Agda) completely merge the type and value level languages, and support machine-checked proofs about programs.
Haskell is also gaining more of these typing features all the time. Next week: Fancy theory about types!
Deep connections between types, logic and proof.
Algebraic type structure for generic algorithms and refactoring. Using polymorphic types to infer properties for free.

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Static Assurance Phantom Types GADTs Type Families
Participation Marks
1 As participation marks were not initially mentioned in the course outline, we decided to drop them.
2 Instead, we will provide one bonus mark to all students for the overall course mark, if we receive at least 50% course myExperience feedback. Another bonus point will be awarded to all students if we receive significant detailed feedback on the course forum (say 10% student response rate).

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Static Assurance Phantom Types GADTs Type Families
Homework and Marking
1 Some Assignment 1 submissions are not marked yet and are being review by UNSW’s student conduct unit for alleged plagiarism. See Curtis’ forum announcement for details on how this is handled.
2 Do not cheat. If you are struggling, ask for help.
3 Assignment 2 is released. Due on Friday 30th July, 12 PM.
4 The last programming exercise has been released, also due next Friday at 12pm.
5 This week’s quiz is also up, due in Friday of Week 9 at 6pm.

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