How do you solve Find Elements in a Contaminated Binary Tree on LeetCode?

Find Elements in a Contaminated Binary Tree (LeetCode #1261) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: The recovery of the tree values follows a specific mathematical pattern based on the parent value.

What is the brute force solution for Find Elements in a Contaminated Binary Tree?

The brute force approach for Find Elements in a Contaminated Binary Tree is Brute Force, with O(n²) time complexity and O(n) space complexity. In the brute force approach, we can traverse the tree and recover the values by using a recursive function. We will then check if the target exists in the list of recovered values. This is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n).

What are the interview tips for Find Elements in a Contaminated Binary Tree?

Explain your thought process clearly while coding. Consider edge cases, such as an empty tree. Discuss the trade-offs of different data structures you might use.

What are common mistakes when solving Find Elements in a Contaminated Binary Tree?

Not using a HashSet for fast lookups, leading to O(n) time complexity for each find call. Failing to correctly implement the recovery logic based on the tree structure.

#1261

Find Elements in a Contaminated Binary Tree

Medium

Hash TableTreeDepth-First SearchBreadth-First SearchDesignBinary TreeHash MapTree Traversal

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

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Intuition

Time O(n)Space O(n)

The optimal approach uses a Depth-First Search (DFS) to recover the tree values and stores them in a HashSet for O(1) average time complexity during the find operation. This is efficient because we only traverse the tree once.

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Algorithm

3 steps

1Step 1: Initialize a HashSet to store recovered values.
2Step 2: Use a recursive DFS function to recover the tree values based on the rules.
3Step 3: For each call to find(target), check if the target exists in the HashSet.

solution.py14 lines

1class FindElements:
2    def __init__(self, root):
3        self.recovered = set()
4        self.recover(root, 0)
5
6    def recover(self, node, value):
7        if node:
8            node.val = value
9            self.recovered.add(value)
10            self.recover(node.left, 2 * value + 1)
11            self.recover(node.right, 2 * value + 2)
12
13    def find(self, target):
14        return target in self.recovered

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Complexity note: The time complexity is O(n) because we traverse the tree once to recover the values. The space complexity is O(n) due to the HashSet storing the recovered values.

1The recovery of the tree values follows a specific mathematical pattern based on the parent value.
2Using a HashSet allows for efficient lookups.

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