Uber·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Uber SWE interview with a grid simulation problem that looked deceptively straightforward but had a lot of edge cases hiding underneath. The kind of question where you think you're done and then they ask about holes in the pattern and you realize you missed half the problem.

Questions Asked (1)

You have an n-by-m grid and a list of binary tile patterns. For each pattern in order, scan the grid row by row to find the first valid top-left position where the pattern fits without going out of bounds and without overlapping already-filled cells. If found, place it and mark those cells with the pattern's index (1-based). If not, skip it. Output the final grid. Discuss scanning order, tie-breaking, complexity, and edge cases like holey patterns or patterns bigger than the grid.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I spent the first few minutes just restating the problem back to make sure I had the scanning order right, which actually helped because I initially assumed you'd place greedily without caring about holes.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints and assumptions, then walk through a concrete example to illustrate the scanning and placement logic. Discuss the algorithm step-by-step, covering scanning order, tie-breaking, complexity, and edge cases, and finally propose optimizations or alternative approaches.

Pro tip: Emphasize that the scanning order (row-major) and tie-breaking (first valid position) are explicitly defined, so no ambiguity exists; instead, focus on optimizing the search using techniques like precomputed pattern bounding boxes or skipping invalid positions.

1. Clarify requirements and constraints

Ask about grid dimensions, pattern sizes, pattern shapes (including holes), and whether patterns can be placed partially outside. Confirm the scanning order and tie-breaking rules.

2. Outline the brute-force approach

Describe scanning the grid row by row, and for each cell, checking if the pattern fits without overlap or out-of-bounds. If valid, place it and mark cells with the pattern index; otherwise, continue scanning.

3. Analyze complexity and edge cases

Discuss time complexity: O(P * n * m * k) where P is number of patterns and k is pattern area. Cover edge cases: patterns larger than grid, holey patterns, empty patterns, and patterns that cannot be placed.

4. Propose optimizations

Suggest improvements like precomputing pattern bounding boxes, using a hash set for filled cells, or skipping rows/columns based on pattern dimensions to reduce unnecessary checks.

5. Summarize and conclude

Reiterate the algorithm, its correctness, and trade-offs. Mention that the solution is straightforward but can be optimized for large inputs.

Key Points to Mention

Scanning order: row-major (top to bottom, left to right) and tie-breaking: first valid position.
Pattern representation: binary matrix, possibly with holes (0s) that don't require empty cells? Actually, holes mean pattern has 0s that don't need to match? Clarify: typically 1s are filled cells, 0s are empty in pattern, so only 1s must be placed on empty grid cells.
Complexity: O(P * n * m * k) time, O(n*m) space for grid.
Edge cases: pattern larger than grid, pattern with all zeros (always fits?), overlapping patterns, patterns that don't fit due to existing placements.
Optimization: precompute pattern's bounding box and only check positions where bounding box fits.
Data structures: use a 2D array for grid, and for each pattern, iterate over its 1s to check validity.

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