Apple·Software Engineer·Technical Phone Screen·Senior

Senior

Apr 2026

Summary

Apple technical screen for a software engineer role, one meaty question about arbitrary-angle matrix rotation that ended up being more of a design conversation than a coding exercise. Took me a while to realize they cared more about the trade-off reasoning than the actual implementation.

Questions Asked (1)

Given an n x n matrix and an arbitrary rotation angle in degrees, rotate the matrix by that angle. The angle is not restricted to multiples of 90, so rotated cell centers land on non-integer coordinates. You need to decide and justify: the output grid shape (same size with crop/pad vs. expanded bounding box), the resampling method for non-integer source coordinates (nearest-neighbor, bilinear, bicubic), and how to handle out-of-bounds source cells. Then implement it and walk through the trade-offs.

Technical Trade-offsAlgorithms & Data StructuresSystem Design

Author's notes

I went straight to coding and the interviewer stopped me pretty fast.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and stating assumptions, then systematically compare the trade-offs of output shape, resampling methods, and boundary handling before committing to a design. Implement the chosen approach with clean, modular code and analyze its complexity and practical implications.

Pro tip: Demonstrate production awareness by mentioning that for large matrices, a separable two-pass rotation (horizontal then vertical) can be more cache-friendly and parallelizable, and that Apple's Accelerate framework (vImageRotate) is the go-to for real-world image rotation.

1. Clarify requirements and assumptions

Ask about the expected output size, quality vs. performance priorities, and whether the matrix represents an image. State your assumptions explicitly to guide the design.

2. Decide output grid shape

Compare same-size (crop/pad) vs. expanded bounding box: same-size preserves dimensions but loses corners; expanded preserves all data but changes size. Justify based on use case.

3. Choose resampling method

Evaluate nearest-neighbor (fast, blocky), bilinear (smooth, moderate cost), and bicubic (sharp, expensive). Select based on quality requirements and performance constraints.

4. Handle out-of-bounds source cells

Decide between zero-padding, edge clamping, or mirroring. Explain how this affects visual artifacts and choose based on desired behavior.

5. Implement and analyze

Write clean code using inverse mapping, then discuss time/space complexity, potential optimizations (e.g., separable passes, SIMD), and trade-offs made.

Key Points to Mention

Inverse mapping: iterate over destination pixels and compute source coordinates to avoid holes.
Rotation matrix and coordinate transformation, including center offset and angle in radians.
Trade-offs between nearest-neighbor, bilinear, and bicubic interpolation in terms of quality and performance.
Handling out-of-bounds with zero-padding, edge clamping, or mirroring and their visual effects.
Complexity analysis: O(n^2) time for n x n matrix, O(n^2) space for output.
Optimization techniques: separable rotation, SIMD, and using Apple's Accelerate framework for production.

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