How do you solve Find Mode in Binary Search Tree on LeetCode?

Find Mode in Binary Search Tree (LeetCode #501) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(1) space complexity. Key insight: In-order traversal is key for BST problems.

What is the brute force solution for Find Mode in Binary Search Tree?

The brute force approach for Find Mode in Binary Search Tree is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves traversing the entire tree and counting the occurrences of each value. This can be done using a simple traversal method, but it is inefficient due to the repeated counting. The optimal Optimal Solution approach improves this to O(n).

What are the interview tips for Find Mode in Binary Search Tree?

Explain your thought process while coding. Consider edge cases, like all nodes being the same. Practice writing clean and efficient code.

What are common mistakes when solving Find Mode in Binary Search Tree?

Not using in-order traversal for BSTs. Confusing frequency counting with value tracking.

#501

Find Mode in Binary Search Tree

Easy

TreeDepth-First SearchBinary Search TreeBinary TreeHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(n)Space O(1)

The optimal solution uses an in-order traversal to count occurrences while keeping track of the current value and its frequency. This allows us to find the modes in a single traversal of the tree, making it efficient.

⚙️

Algorithm

3 steps

1Step 1: Perform an in-order traversal of the tree while counting occurrences of each value.
2Step 2: Keep track of the current value and its frequency during traversal.
3Step 3: Update the modes list when a new maximum frequency is found.

solution.py25 lines

1# Full working Python code
2from collections import defaultdict
3
4def findMode(root):
5    def inorder(node):
6        nonlocal current_val, current_count, max_count, modes
7        if not node:
8            return
9        inorder(node.left)
10        if node.val == current_val:
11            current_count += 1
12        else:
13            current_val = node.val
14            current_count = 1
15        if current_count > max_count:
16            max_count = current_count
17            modes = [current_val]
18        elif current_count == max_count:
19            modes.append(current_val)
20        inorder(node.right)
21
22    current_val, current_count, max_count = None, 0, 0
23    modes = []
24    inorder(root)
25    return modes

ℹ

Complexity note: This complexity is optimal because we only traverse the tree once, making it O(n), where n is the number of nodes. We use constant space for the mode tracking, not counting the output space.

1In-order traversal is key for BST problems.
2Tracking state (current value and count) helps optimize the solution.

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