Which approach guarantees an optimal solution with O(n) time and O(h) space complexity, where h is the tree height?
easy🔍 Pattern Recognition Q11 of Q15
Tree: Depth-First Search - Flatten Binary Tree to Linked List
You are given a binary tree and asked to transform it into a singly linked list in-place such that the linked list follows the preorder traversal of the tree. Which approach guarantees an optimal solution with O(n) time and O(h) space complexity, where h is the tree height?
AUse a reverse preorder traversal (right subtree first, then left) with a global pointer to rewire nodes in-place.
BPerform a preorder traversal, store nodes in a list, then rebuild the linked list from the list.
CUse a bottom-up postorder traversal to reconstruct the linked list from leaves to root.
DApply a greedy approach that always attaches the left subtree to the rightmost node of the right subtree.
Step-by-Step Solution
Solution:
Step 1: Understand traversal order needed
The linked list must follow preorder traversal (root, left, right).
Step 2: Identify approach that rewires in-place efficiently
Reverse preorder traversal (right, left) with a global pointer allows rewiring nodes in-place without extra storage, achieving O(n) time and O(h) space due to recursion stack.
Final Answer:
Option A -> Option A
Quick Check:
Reverse preorder traversal with global pointer rewires nodes in correct order [OK]
Quick Trick:Reverse preorder traversal with global pointer is optimal [OK]
Common Mistakes:
MISTAKES
Using extra space to store nodes before rebuilding
Confusing traversal order causing incorrect linked list
Trying greedy rewiring without correct traversal order
Trap Explanation:
PITFALL
Option A looks correct but uses extra space, violating in-place requirement. Option C uses postorder which does not preserve preorder sequence. Option D is a greedy heuristic that fails on complex trees.
Interviewer Note:
CONTEXT
Tests if candidate recognizes the optimal traversal pattern and in-place rewiring strategy.
Master "Flatten Binary Tree to Linked List" in Tree: Depth-First Search
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