How can i design a scheme in 3NF with FD's of the form
a -> t; b -> v; b -> w; {a, b} -> {z, k}; w ->y; w -> m; a ->s;
b ->j; w -> p;
FD1: a -> t;
FD2: b -> v;
FD3: b -> w;
FD4: a, b -> z, k;
FD5: w -> y;
FD6: w -> m;
FD7: a -> s;
FD8: b -> j;
FD9: w -> p;
Relation R(A,B,J,K,M,P,S,T,V,W,Y,Z); (A,B) is the primary key as it determines all other attributes by the rules of inference.
At least 2NF, no partial dependentcies on the on key attributes.
FDs with partial dependency on primary key are FD1, FD2, FD3, FD7 and FD8. After relation decomposition we have following set of relation which are at least in NF2:
R1(A,T,S) -- FD1 and FD7
R2(B,J,M,P,V,W,Y) -- FD2, FD3, FD5, FD6, FD8 and FD9
R3(A,B,K,Z) -- FD4
At least 3NF, no transitive dependencies on key attributes.
FD5, FD6 and FD9 are transitive dependencies so move them to a separate relation.
R1(A,T,S) -- FD1 and FD7
R21(B,J,V,W) -- FD2, FD3 and FD8
R22(W,M,P,Y) -- FD5, FD6 and FD9
R3(A,B,K,Z) -- FD4
Related
I've been trying to develop a component system in Purescript, using a Component typeclass which specifies an eval function. The eval function for can be recursively called by a component for each sub-component of the component, in essence fetching the input's values.
As components may wish to use run-time values, a record is also passed into eval. My goal is for the rows in the Record argument of the top-level eval to be required to include all the rows of every sub-component. This is not too difficult for components which do not use any rows themselves, but their single sub-component does, as we can simply pass along the sub-components rows to the component's. This is shown in evalIncrement.
import Prelude ((+), one)
import Data.Symbol (class IsSymbol, SProxy(..))
import Record (get)
import Prim.Row (class Cons, class Union)
class Component a b c | a -> b where
eval :: a -> Record c -> b
data Const a = Const a
instance evalConst :: Component (Const a) a r where
eval (Const v) r = v
data Var (a::Symbol) (b::Type) = Var
instance evalVar ::
( IsSymbol a
, Cons a b r' r) => Component (Var a b) b r where
eval _ r = get (SProxy :: SProxy a) r
data Inc a = Inc a
instance evalInc ::
( Component a Int r
) => Component (Inc a) Int r where
eval (Inc a) r = (eval a r) + one
All of the above code works correctly. However, once I try to introduce a component which takes multiple input components and merges their rows, I cannot seem to get it to work. For example, when trying to use the class Union from Prim.Row:
data Add a b = Add a b
instance evalAdd ::
( Component a Int r1
, Component b Int r2
, Union r1 r2 r3
) => Component (Add a b) Int r3 where
eval (Add a b) r = (eval a r) + (eval b r)
The following error is produced:
No type class instance was found for
Processor.Component a3
Int
r35
while applying a function eval
of type Component t0 t1 t2 => t0 -> { | t2 } -> t1
to argument a
while inferring the type of eval a
in value declaration evalAdd
where a3 is a rigid type variable
r35 is a rigid type variable
t0 is an unknown type
t1 is an unknown type
t2 is an unknown type
In fact, even modifying the evalInc instance to use a dummy Union with an empty row produces a similar error, like so:
instance evalInc :: (Component a Int r, Union r () r1)
=> Component (Increment a) Int r1 where
Am I using Union incorrectly? Or do I need further functional dependencies for my class - I do not understand them very well.
I am using purs version 0.12.0
r ∷ r3 but it is being used where an r1 and r2 are required, so there is a type mismatch. A record {a ∷ A, b ∷ B} cannot be given where {a ∷ A} or {b ∷ B} or {} is expected. However, one can say this:
f ∷ ∀ s r. Row.Cons "a" A s r ⇒ Record r → A
f {a} = a
In words, f is a function polymorphic on any record containing a label "a" with type A. Similarly, you could change eval to:
eval ∷ ∀ s r. Row.Union c s r ⇒ a → Record r → b
In words, eval is polymorphic on any record which contains at least the fields of c. This introduces a type ambiguity which you will have to resolve with a proxy.
eval ∷ ∀ proxy s r. Row.Union c s r ⇒ proxy c → a → Record r → b
The eval instance of Add becomes:
instance evalAdd ∷
( Component a Int r1
, Component b Int r2
, Union r1 s1 r3
, Union r2 s2 r3
) => Component (Add a b) Int r3 where
eval _ (Add a b) r = eval (RProxy ∷ RProxy r1) a r + eval (RProxy ∷ RProxy r2) b r
From here, r1 and r2 become ambiguous because they're not determined from r3 alone. With the given constraints, s1 and s2 would also have to be known. Possibly there is a functional dependency you could add. I am not sure what is appropriate because I am not sure what the objectives are of the program you are designing.
As the instance for Var is already polymorphic (or technically open?) due to the use of Row.Cons, ie
eval (Var :: Var "a" Int) :: forall r. { "a" :: Int | r } -> Int
Then all we have to is use the same record for the left and right evaluation, and the type system can infer the combination of the two without requiring a union:
instance evalAdd ::
( Component a Int r
, Component b Int r
) => Component (Add a b) Int r where
eval (Add a b) r = (eval a r) + (eval b r)
This is more obvious when not using typeclasses:
> f r = r.foo :: Int
> g r = r.bar :: Int
> :t f
forall r. { foo :: Int | r } -> Int
> :t g
forall r. { bar :: Int | r } -> Int
> fg r = (f r) + (g r)
> :t fg
forall r. { foo :: Int, bar :: Int | r } -> Int
I think the downside to this approach compared to #erisco's is that the open row must be in the definition of instances like Var, rather than in the definition of eval? It is also not enforced, so if a Component doesn't use open rows then a combinator such as Add no longer works.
The benefit is the lack of the requirement for the RProxies, unless they are not actually needed for eriscos implementation, I haven't checked.
Update:
I worked out a way of requiring eval instances to be closed, but it makes it quite ugly, making use of pick from purescript-record-extra.
I'm not really sure why this would be better over the above option, feels like I'm just re-implementing row polymorphism
import Record.Extra (pick, class Keys)
...
instance evalVar ::
( IsSymbol a
, Row.Cons a b () r
) => Component (Var a b) b r where
eval _ r = R.get (SProxy :: SProxy a) r
data Add a b = Add a b
evalp :: forall c b r r_sub r_sub_rl trash
. Component c b r_sub
=> Row.Union r_sub trash r
=> RL.RowToList r_sub r_sub_rl
=> Keys r_sub_rl
=> c -> Record r -> b
evalp c r = eval c (pick r)
instance evalAdd ::
( Component a Int r_a
, Component b Int r_b
, Row.Union r_a r_b r
, Row.Nub r r_nub
, Row.Union r_a trash_a r_nub
, Row.Union r_b trash_b r_nub
, RL.RowToList r_a r_a_rl
, RL.RowToList r_b r_b_rl
, Keys r_a_rl
, Keys r_b_rl
) => Component (Add a b) Int r_nub where
eval (Add a b) r = (evalp a r) + (evalp b r)
eval (Add (Var :: Var "a" Int) (Var :: Var "b" Int) ) :: { a :: Int , b :: Int } -> Int
eval (Add (Var :: Var "a" Int) (Var :: Var "a" Int) ) :: { a :: Int } -> Int
I am trying to define lexicographic ordering on strings over posets, but I'm not completely sure how to use the PartialOrder typeclass.
Require Import List RelationClasses.
Fail Inductive lex_leq {A : Type} `{po : PartialOrder A} : list A -> list A -> Prop :=
| lnil: forall l, lex_leq nil l
| lcons:
forall (hd1 hd2 : A) (tl1 tl2 : list A),
hd1 <= hd2 -> (* error *)
(hd1 = hd2 -> lex_leq tl1 tl2) ->
lex_leq (hd1 :: tl1) (hd2 :: tl2).
Partial output:
The term "hd1" has type "A" while it is expected to have type "nat".
Clearly <= is the wrong notation to use here; I'm wondering how I can obtain an ordering relation from my po instance.
One can bind the names explicitly to make things more obvious. Before we can do this we need to tell Coq not to complain about unbound variables using the Generalizable Variables command:
From Coq Require Import List RelationClasses.
Generalizable Variables A eqA R.
Inductive lex_leq `{PartialOrder A eqA R} : list A -> list A -> Prop :=
| lnil: forall l, lex_leq nil l
| lcons:
forall (hd1 hd2 : A) (tl1 tl2 : list A),
R hd1 hd2 ->
(hd1 = hd2 -> lex_leq tl1 tl2) ->
lex_leq (hd1 :: tl1) (hd2 :: tl2).
You can find more information in the manual (here).
if i am given following grammar
E->E W T|T
T->L S T|L
L->a|b|c
W->*
S->+|-
From following grammar i see that since + and - are deeper down the tree they have higher precedence then *, am i correct on that?
Also since this is left recursion i can assume left associativity?
Since operators can have different associativity i a confused how to tell which one has which one.
I guess what i am asking is how can i tell operator associativity based on grammar?
Start with
T->L S T|L
and consider a+b+c, which can be produced from T as follows:
T -> L S T
-> L S (L S T)
-> L S (L S (L))
-> L S (L S (c))
-> L S (b + (c))
-> L + (b + (c))
-> a + (b + (c))
(The parentheses are only there as a shorthand for the parse tree.)
That rightmost derivation is unique; T cannot match (a + b) + c because a + b is not an L.
Consequently, + and - are "right-associative".
By contrast, we have
E->E W T|T
so a*b*c will be produced as follows:
E -> E W T
-> E W L
-> E W c
-> E * c
-> (E W T) * c
-> (E W L) * c
-> (E W b) * c
-> (E * b) * c
-> ((T) * b) * c
-> ((L) * b) * c
-> ((a) * b) * c
Again, that parse is unambiguous.
I didn't do a+b*c, so it would be a good exercise.
I thought these two function were the same, but it seems that I was wrong.
I define two function f and g in this way:
let rec f n k =
match k with
|_ when (k < 0) || (k > n) -> 0
|_ when k = n -> 100
|_ -> (f n (k+1)) + 1
let rec g n k =
match k with
|_ when (k < 0) || (k > n) -> 0
| n -> 100
|_ -> (g n (k+1)) + 1
let x = f 10 5
let y = g 10 5
The results are:
val x : int = 105
val y : int = 100
Could anyone tell me what's the difference between these two functions?
EDIT
Why does it work here?
let f x =
match x with
| 1 -> 100
| 2 -> 200
|_ -> -1
List.map f [-1..3]
and we get
val f : x:int -> int
val it : int list = [-1; -1; 100; 200; -1]
The difference is that
match k with
...
when k = n -> 100
is a case that matches when some particular condition is true (k = n). The n used in the condition refers to the n that is bound as the function parameter. On the other hand
match k with
...
n -> 100
is a case that only needs to match k against a pattern variable n, which can always succeed. The n in the pattern isn't the same n as the n passed into the function.
For comparison, try the code
let rec g n k =
match k with
|_ when (k < 0) || (k > n) -> 0
| n -> n
|_ -> (g n (k+1)) + 1
and you should see that when you get to the second case, the value returned is the value of the pattern variable n, which has been bound to the value of k.
This behavior is described in the Variable Patterns section of the MSDN F# Language Reference, Pattern Matching:
Variable Patterns
The variable pattern assigns the value being matched to a variable
name, which is then available for use in the execution expression to
the right of the -> symbol. A variable pattern alone matches any
input, but variable patterns often appear within other patterns,
therefore enabling more complex structures such as tuples and arrays
to be decomposed into variables. The following example demonstrates a
variable pattern within a tuple pattern.
let function1 x =
match x with
| (var1, var2) when var1 > var2 -> printfn "%d is greater than %d" var1 var2
| (var1, var2) when var1 < var2 -> printfn "%d is less than %d" var1 var2
| (var1, var2) -> printfn "%d equals %d" var1 var2
function1 (1,2)
function1 (2, 1)
function1 (0, 0)
The use of when is described in more depth in Match Expressions.
The first function is ok, it calls recursively itself n-k times and returns 100 when matches with the conditional where k = n. So, it returns all the calls adding 1 n-k times. with your example, with n=10 and k=5 it is ok the result had been 105.
The problem is the second function. I tested here. See I changed the pattern n->100 to z->100 and it still matches there and never calls itself recursively. So, it always returns 100 if it does not fail in the first conditional. I think F# don't allow that kind of match so it is better to put a conditional to get what you want.
I really hate asking this kind of question but I'm at the end of my wits here. I am writing an incremental parser but for some reason, just cannot figure out how to implement functor instance for it. Here's the code dump:
Input Data Type
Input is data type yielded by parser to the coroutine. It contains the current list of input chars being operated on by coroutine and end of line condition
data Input a = S [a] Bool deriving (Show)
instance Functor Input where
fmap g (S as x) = S (g <$> as) x
Output Data Type
Output is data type yielded by coroutine to Parser. It is either a Failed message, Done [b], or Partial ([a] -> Output a b), where [a] is the current buffer passed back to the parser
data Output a b = Fail String | Done [b] | Partial ([a] -> Output a b)
instance Functor (Output a) where
fmap _ (Fail s) = Fail s
fmap g (Done bs) = Done $ g <$> bs
fmap g (Partial f) = Partial $ \as -> g <$> f as
The Parser
The parser takes [a] and yields a buffer [a] to coroutine, which yields back Output a b
data ParserI a b = PP { runPi :: [a] -> (Input a -> Output a b) -> Output a b }
Functor Implementation
It seems like all I have to do is fmap the function g onto the coroutine, like follows:
instance Functor (ParserI a) where
fmap g p = PP $ \as k -> runPi p as (\xs -> fmap g $ k xs)
But it does not type check:
Couldn't match type `a1' with `b'
`a1' is a rigid type variable bound by
the type signature for
fmap :: (a1 -> b) -> ParserI a a1 -> ParserI a b
at Tests.hs:723:9
`b' is a rigid type variable bound by
the type signature for
fmap :: (a1 -> b) -> ParserI a a1 -> ParserI a b
at Tests.hs:723:9
Expected type: ParserI a b
Actual type: ParserI a a1
As Philip JF declared, it's not possible to have an instance Functor (ParserI a). The proof goes by variance of functors—any (mathematical) functor must, for each of its arguments, be either covariant or contravariant. Normal Haskell Functors are always covariant which is why
fmap :: (a -> b) -> (f a -> f b)`
Haskell Contravariant functors have the similar
contramap :: (b -> a) -> (f a -> f b)`
In your case, the b index in ParserI a b would have to be both covariant and contravariant. The quick way of figuring this out is to relate covariant positions to + and contravariant to - and build from some basic rules.
Covariant positions are function results, contravariant are function inputs. So a type mapping like type Func1 a b c = (a, b) -> c has a ~ -, b ~ -, and c ~ +. If you have functions in output positions, you multiply all of the argument variances by +1. If you have functions in input positions you multiply all the variances by -1. Thus
type Func2 a b c = a -> (b -> c)
has the same variances as Func1 but
type Func3 a b c = (a -> b) -> c
has a ~ 1, b ~ -1, and c ~ 1. Using these rules you can pretty quickly see that Output has variances like Output - + and then ParserI uses Output in both negative and positive positions, thus it can't be a straight up Functor.
But there are generalizations like Contravariant. The particular generalization of interest is Profunctor (or Difunctors which you see sometimes) which goes like so
class Profunctor f where
promap :: (a' -> a) -> (b -> b') -> (f a b -> f a' b')
the quintessential example of which being (->)
instance Profunctor (->) where
promap f g orig = g . orig . f
i.e. it "extends" the function both after (like a usual Functor) and before. Profunctors f are thus always mathematical functors of arity 2 with variance signature f - +.
So, by generalizing your ParserI slightly, letting there be an extra parameter to split the ouput types in half, we can make it a Profunctor.
data ParserIC a b b' = PP { runPi :: [a] -> (Input a -> Output a b) -> Output a b' }
instance Profunctor (ParserIC a) where
promap before after (PP pi) =
PP $ \as k -> fmap after $ pi as (fmap before . k)
and then you can wrap it up
type ParserI a b = ParserIC a b b
and provide a slightly less convenient mapping function over b
mapPi :: (c -> b) -> (b -> c) -> ParserI a b -> ParserI a c
mapPi = promap
which really drives home the burden of having the variances go both ways---you need to have bidirectional maps!