Netflix·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Netflix SWE interview with a matrix simulation problem. Nothing too wild but the gravity mechanic adds a layer that trips you up if you jump straight to the rotation.

Questions Asked (1)

You're given an m x n grid where each cell is a stone, an obstacle, or empty space. Apply gravity so stones fall and settle, then rotate the entire grid 90 degrees clockwise. Return the resulting matrix.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I went for the rotation first, which was a mistake.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases first, then propose an efficient solution that simulates gravity column by column and rotates the grid in a single pass. Discuss time and space complexity, and consider whether in-place rotation is possible or if a new matrix is acceptable.

Pro tip: Mention that you can combine gravity and rotation by processing columns from bottom to top and writing directly into the rotated positions, avoiding an extra pass. This shows you think about optimizing beyond the naive approach.

1. Clarify requirements and edge cases

Ask about grid dimensions, character representations, and whether rotation should be in-place. Confirm behavior for empty grids, all obstacles, or all stones.

2. Design gravity simulation

For each column, iterate from bottom to top, keeping a pointer for the next available empty slot. Move stones down to the lowest available empty cell, skipping obstacles.

3. Implement rotation

After gravity, rotate the grid 90 degrees clockwise. This can be done by creating a new matrix where new[i][j] = old[m-1-j][i], or in-place using transpose and reverse.

4. Optimize by combining steps

Instead of simulating gravity then rotating, process each column from bottom to top and directly place stones into the rotated matrix at the correct positions, reducing time and space overhead.

5. Analyze complexity and test

State time complexity O(m*n) and space complexity O(m*n) for the output (or O(1) extra if in-place). Walk through a small example to verify correctness.

Key Points to Mention

Time and space complexity analysis, including trade-offs between in-place and new matrix approaches.
Handling obstacles correctly: stones cannot pass through obstacles, so gravity must respect them.
Edge cases: empty grid, single row/column, all stones, all obstacles, no stones.
In-place rotation techniques: transpose + reverse rows or columns.
Combining gravity and rotation to avoid multiple passes over the data.
Choice of data structures: using arrays/lists for efficient indexing and mutation.

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