Construct Binary Search Tree from Preorder Traversal

Problem is here: https://leetcode.com/problems/construct-binary-search-tree-from-preorder-traversal/

Return the root node of a binary search tree that matches the given preorder traversal.
(Recall that a binary search tree is a binary tree where for every node, any descendant of node.left has a value < node.val, and any descendant of node.right has a value > node.val.  Also recall that a preorder traversal displays the value of the node first, then traverses node.left, then traverses node.right.)

Example 1:
Input: [8,5,1,7,10,12]
Output: [8,5,10,1,7,null,12]


Note: 
  1. 1 <= preorder.length <= 100
  2. The values of preorder are distinct.

This is a relatively simple problem, although labeled as Medium. The definition of a binary search tree is even given in the problem description. A recursive solution does the trick: add the first node, then call recursively for the left by creating a sub-array with the smaller elements, and similar to the right. That should do it. Conversion of linked-lists to arrays in C# is not the most efficient operation, hence the execution time slows down a bit. Code is below, cheers, ACC.


public class Solution
{
 public TreeNode BstFromPreorder(int[] preorder)
 {
  if (preorder == null || preorder.Length == 0) return null;
  TreeNode tree = new TreeNode(preorder[0]);
  LinkedList left = new LinkedList();
  int i = 1;
  for (; i < preorder.Length && preorder[i] < preorder[0]; i++)
  {
   left.AddLast(preorder[i]);
  }
  LinkedList right = new LinkedList();
  for (; i < preorder.Length; i++)
  {
   right.AddLast(preorder[i]);
  }
  tree.left = BstFromPreorder(left.ToArray());
  tree.right = BstFromPreorder(right.ToArray());
  return tree;
 }
}

Comments

  1. Neat! I've used a very similar approach, which runs a lot faster on any non-C# languages it seems like (Python code below runs in 36s and beats 100% of other submissions) :) Seriously speaking though, I think the reason for the slow runtime of your submission is usage of LinkedList - I bet just by replacing it with ArrayList you'd get a significantly better performance. LinkedList has a terrible effect on caches (non-contiguous memory) and uses more memory (thanks to pointers). LinkedLists are so bad that many advocate for their removal from standard libraries :)

    class Solution:
    def bstFromPreorder(self, preorder: List[int]) -> TreeNode:
    if not preorder:
    return None
    root = TreeNode(preorder[0])
    first_right_child_idx = len(preorder)
    for idx, node in enumerate(preorder):
    if node > root.val:
    first_right_child_idx = idx
    break
    root.left = self.bstFromPreorder(preorder[1:first_right_child_idx])
    root.right = self.bstFromPreorder(preorder[first_right_child_idx:])
    return root


    https://gist.github.com/ttsugriy/849ae99d210ff775a0b094ec03beb361

    ReplyDelete

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