type BSTree a = BinaryTree a
data BinaryTree a = Null | Node (BinaryTree a) a (BinaryTree a)
deriving Show
flattenTree :: BinaryTree a -> [a]
flattenTree tree = case tree of
Null -> []
Node left val right -> (flattenTree left) ++ [val] ++ (flattenTree right)
isBSTree :: (Ord a) => BinaryTree a -> Bool
isBSTree btree = case btree of
Null -> False
tree -> (flattenTree tree) == sort (flattenTree tree)
What I want to do is to write a function to determine whether the given tree is a binary search tree, my method is to group all of the values in a list and import Data.List
and then sort the list to find whether they are equal, but it is a little complicated. Can we do this without importing other module?
To see if a binary tree is a binary search tree, check: If a node is a left child, then its key and the keys of the nodes in its right subtree are less than its parent's key. If a node is a right child, then its key and the keys of the nodes in its left subtree are greater than its parent's key.
In a complete balanced binary tree, the first empty node should come after the last populated node, in a left-to-right breadth-first search. This simply checks that.
AVL Trees are binary search trees with a balance condition. The balance condition ensures that the height of the tree is bounded.
Here's a way to do it without flattening the tree.
From the definition, here,
data BinaryTree a = Null | Node (BinaryTree a) a (BinaryTree a)
deriving Show
one can see that traversing the tree left to right, ignoring Node
and parentheses, gives you an alternating sequence of Null
s and a
s. That is, between every two values, there is a Null
.
My plan is to check that each subtree satisfies suitable requirements: we can refine the requirements at each Node
, remembering which values we are between, then test them at each Null
. As there is a Null
between every in order pair of values, we will have tested that all in order (left-to-right) pairs are non-decreasing.
What is a requirement? It's a loose lower and upper bound on the values in the tree. To express requirements, including those at the leftmost and rightmost ends, we may extend any ordering with Bot
tom and Top
elements, as follows:
data TopBot a = Bot | Val a | Top deriving (Show, Eq, Ord)
Now let us check that a given tree satisfies the requirements of being both in order and between given bounds.
ordBetween :: Ord a => TopBot a -> TopBot a -> BinaryTree a -> Bool
-- tighten the demanded bounds, left and right of any Node
ordBetween lo hi (Node l x r) = ordBetween lo (Val x) l && ordBetween (Val x) hi r
-- check that the demanded bounds are in order when we reach Null
ordBetween lo hi Null = lo <= hi
A binary search tree is a tree that is in order and between Bot
and Top
.
isBSTree :: Ord a => BinaryTree a -> Bool
isBSTree = ordBetween Bot Top
Computing the actual extremal values in each subtree, bubbling them outwards, gives you more information than you need, and is fiddly in the edge cases where a left or right subtree is empty. Maintaining and checking the requirements, pushing them inwards, is rather more uniform.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With