Good afternoon! Here's our prompt for today.

Assume we're using a binary tree in writing a video game via Binary Space Partitioning. We need to identify the bottom left leaf, that is-- the leftmost value in the lowest row of the binary tree.

In this example, the bottom left leaf is 3:

1/*
2    4
3   / \
4  3   5
5*/

Assuming the standard node definition of:

1function Node(val) {
2  this.val = val;
3  this.left = this.right = null;
4}

It would be called as such:

1const root = new Node(4);
2root.left = new Node(3);
3root.right = new Node(5);
4
5function bottomLeftNodeVal(root) { return; };
6bottomLeftNodeVal(root);
7// 3

Here's another example. Let's assume that there's at least the root node available in all binary trees passed as parameters.

1/*
2      4
3     / \
4    1   3
5       / \
6      5   9
7*/
8
9const root = new Node(4);
10root.left = new Node(1);
11root.right = new Node(3);
12root.right.left = new Node(5);
13root.right.right = new Node(9);
14
15bottomLeftNodeVal(root);
16// 5

Constraints

• Nodes in the binary tree <= 100000
• The values in the nodes will be in the range -1000000000 and 1000000000
• Expected time complexity : O(n)
• Expected space complexity : O(n)

Try to solve this here or in Interactive Mode.

How do I practice this challenge?

xxxxxxxxxx

  console.log('PASSED: ' + 'assert.equal(bottomLeftNodeVal(tree4), 1);');

var assert = require('assert');

​

function Node(val) {

  this.val = val;

  this.left = this.right = null;

}

​

function bottomLeftNodeVal(root) {

  // Fill in this method

  return root;

}

​

// const root = new Node(4);

// root.left = new Node(1);

// root.right = new Node(3);

// root.right.left = new Node(5);

// root.right.right = new Node(9);

​

// console.log(bottomLeftNodeVal(root));

​

function Node(val) {

  this.val = val;

  this.left = null;

  this.right = null;

}

​

// Regular binary trees

var tree1 = new Node(4);

tree1.left = new Node(1);

Tired of reading? Watch this video explanation!

To change the speed of the video or see it in full screen, click the icons to the right of the progress bar.

Here's how we would solve this problem...

How do I use this guide?