Microsoft·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jul 2026

Summary

Microsoft SWE interview with a classic array merging problem. Pretty standard algorithmic stuff but they pushed on complexity analysis which tripped me up a bit.

Questions Asked (1)

You're given two sorted arrays. Merge them into one sorted array with no duplicate values. Walk through your approach and analyze the time and space complexity.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The merge part I had down pretty quickly, two pointers, advance whichever side is smaller, done.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., sorted ascending, duplicates within each array, output format) and then propose a two-pointer approach that merges while skipping duplicates. Walk through a small example to illustrate, then analyze time and space complexity, mentioning edge cases and potential optimizations.

Pro tip: Explicitly state that you would handle duplicates by comparing the current element with the last added element in the result, and mention that if the arrays are very large, you might consider a streaming approach to avoid storing the entire output in memory.

1. Clarify requirements and constraints

Ask about input size, whether arrays are sorted ascending or descending, if duplicates exist within each array, and the expected output format (e.g., new array, in-place, or stream).

2. Outline the two-pointer approach

Explain that you will use two pointers, one for each array, to traverse them in order, comparing elements and advancing the pointer of the smaller element.

3. Handle duplicates

Describe how to skip duplicates by checking if the current element equals the last added element in the result, and only adding if it's different.

4. Walk through an example

Choose a small example with duplicates (e.g., [1,3,5] and [2,3,6]) and step through the algorithm to demonstrate correctness.

5. Analyze complexity and edge cases

State that time complexity is O(m+n) and space complexity is O(m+n) for the output (or O(1) extra if done in-place with one array having extra space). Mention edge cases like empty arrays, all duplicates, or one array exhausted early.

Key Points to Mention

Two-pointer technique for merging sorted arrays
Duplicate removal by comparing with the last added element
Time complexity: O(m+n) where m and n are array lengths
Space complexity: O(m+n) for the output array (or O(1) extra if in-place)
Edge cases: empty arrays, one array exhausted, all elements duplicates
Potential optimization: early termination if one array is exhausted and no more duplicates

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.