How do you solve Find Bottom Left Tree Value on LeetCode?

Find Bottom Left Tree Value (LeetCode #513) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(h) space complexity. Key insight: Using depth-first search allows us to efficiently find the leftmost value without storing all nodes.

What is the brute force solution for Find Bottom Left Tree Value?

The brute force approach for Find Bottom Left Tree Value is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves traversing the entire tree level by level and storing the values of the leftmost nodes. Finally, we return the last leftmost value found. This is simple but inefficient. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Find Bottom Left Tree Value?

Find Bottom Left Tree Value uses the following concepts: Tree, Depth-First Search, Breadth-First Search, Binary Tree. The recommended patterns to study are: Depth-First Search, Breadth-First Search.

What are the interview tips for Find Bottom Left Tree Value?

Clarify the problem statement and ask about edge cases before jumping into coding. Think about the data structure you are using and how it affects performance. Always explain your thought process and approach to the interviewer as you code.

What are common mistakes when solving Find Bottom Left Tree Value?

Confusing depth-first search with breadth-first search, leading to incorrect traversal order. Not considering edge cases like a single-node tree.

#513

Find Bottom Left Tree Value

Medium

TreeDepth-First SearchBreadth-First SearchBinary TreeDepth-First SearchBreadth-First Search

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(h)

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Intuition

Time O(n)Space O(h)

The optimal solution uses a depth-first search (DFS) approach to traverse the tree. By tracking the depth of each node, we can directly identify the leftmost value at the deepest level without needing to store all nodes.

⚙️

Algorithm

4 steps

1Step 1: Initialize a variable to store the leftmost value and a variable to track the maximum depth.
2Step 2: Use a recursive DFS function that takes the current node and its depth as parameters.
3Step 3: If the current depth is greater than the maximum depth, update the leftmost value and maximum depth.
4Step 4: Traverse the left subtree first, then the right subtree.

solution.py17 lines

1# Full working Python code
2
3def findBottomLeftValue(root):
4    def dfs(node, depth):
5        nonlocal leftmost_value, max_depth
6        if not node:
7            return
8        if depth > max_depth:
9            max_depth = depth
10            leftmost_value = node.val
11        dfs(node.left, depth + 1)
12        dfs(node.right, depth + 1)
13
14    leftmost_value = root.val
15    max_depth = 0
16    dfs(root, 1)
17    return leftmost_value

ℹ

Complexity note: The time complexity is O(n) because we visit each node exactly once. The space complexity is O(h) due to the recursion stack, where h is the height of the tree.

1Using depth-first search allows us to efficiently find the leftmost value without storing all nodes.
2The order of traversal matters; always explore the left child before the right child to ensure we find the leftmost node.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.