Intervals - Merge Intervals
What is the auxiliary space complexity of the in-place merge intervals algorithm that sorts and merges intervals without creating a new list?
What is the auxiliary space complexity of the in-place merge intervals algorithm that sorts and merges intervals without creating a new list?
medium🪤 Complexity Trap Q6 of Q15
Step-by-Step Solution
Solution:
Step 1: Consider in-place merging
The algorithm modifies the input list without extra storage, so no additional O(n) space.Step 2: Consider sorting space
Sorting typically uses O(log n) auxiliary space due to recursion stack in quicksort or mergesort implementations.Final Answer:
Option D -> Option DQuick Check:
Auxiliary space is O(log n) due to sorting recursion stack [OK]
Quick Trick: In-place merge uses O(log n) space due to sorting recursion [OK]
Common Mistakes:
MISTAKES- Assuming O(1) ignoring sorting stack
- Assuming O(n) for merged list space
Trap Explanation:
PITFALL- Candidates often forget recursion stack space in sorting and claim constant space.
Interviewer Note:
CONTEXT- Tests understanding of auxiliary space including recursion stack in sorting.
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