Google·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate

Jun 2026

Summary

Google SWE coding round, got a matrix rotation problem. Pretty standard on the surface but the follow-up about in-place vs extra space is where things get interesting.

Questions Asked (1)

Given an n by m matrix, rotate it 90 degrees clockwise and return the result. Your solution should handle non-square dimensions. Follow-up: is O(1) extra space achievable, and does it matter whether n equals m?

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The base case wasn't bad, just transpose and reverse logic, but I fumbled the follow-up.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then propose a straightforward solution using extra space, and finally discuss the in-place O(1) space approach for square matrices, explaining why it doesn't generalize to non-square matrices. Emphasize the trade-offs between simplicity and space efficiency.

Pro tip: Demonstrate awareness that the in-place rotation is only possible for square matrices, and for non-square matrices, O(1) extra space is impossible without overwriting data. This shows deep understanding of the problem constraints.

1. Clarify the problem and edge cases

Ask about matrix dimensions, data types, and whether the rotation should be in-place or can return a new matrix. Discuss edge cases like empty matrix, 1x1, 1xN, Nx1.

2. Propose a simple solution with extra space

Create a new matrix of size m x n and map each element (i, j) to (j, n-1-i) in the new matrix. This is O(n*m) time and O(n*m) space.

3. Discuss in-place rotation for square matrices

For square matrices (n x n), rotate in-place by first transposing the matrix and then reversing each row. This uses O(1) extra space.

4. Explain why in-place is not possible for non-square matrices

For non-square matrices, the dimensions change (n x m becomes m x n), so the original matrix cannot hold the result without overwriting. Thus, O(1) extra space is impossible unless we allow modifying the input in a destructive way that loses data.

5. Summarize trade-offs and conclude

Compare the simple approach (easy, uses extra space) with the in-place approach (space-efficient but only for square matrices). Mention that for non-square, extra space is necessary.

Key Points to Mention

Time complexity: O(n*m) for both approaches.
Space complexity: O(n*m) for the simple approach, O(1) for in-place square rotation.
In-place rotation for square matrices: transpose then reverse rows.
Non-square matrices require extra space because dimensions change.
Edge cases: empty matrix, 1x1, 1xN, Nx1.
Clarify if the rotation should be in-place or return a new matrix.

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