Tree: Depth-First Search - Flatten Binary Tree to Linked List
What is the auxiliary space complexity of the recursive in-place flatten algorithm that uses reverse preorder traversal on a binary tree with height h?
What is the auxiliary space complexity of the recursive in-place flatten algorithm that uses reverse preorder traversal on a binary tree with height h?
medium🧠 Conceptual Q6 of Q15
Step-by-Step Solution
Solution:
Step 1: Analyze recursion stack depth
The algorithm uses recursion that goes as deep as the tree height h.Step 2: No extra data structures used
It does not use additional data structures like arrays or queues.Step 3: Space complexity conclusion
Thus, auxiliary space is O(h), where h is the height of the tree.Final Answer:
Option A -> Option AQuick Check:
Recursion depth equals tree height [OK]
Quick Trick: Recursion stack space equals tree height h [OK]
Common Mistakes:
MISTAKES- Assuming O(1) space ignoring recursion stack
- Confusing node count n with height h
- Thinking extra arrays are used
Trap Explanation:
PITFALL- Ignoring recursion stack leads to underestimating space complexity
Interviewer Note:
CONTEXT- Tests understanding of recursion space usage in tree algorithms
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