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Uber·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Phone screen for a software engineer role at Uber. The problem was essentially the robot/grid movement question that's been floating around 1point3acres for a while, just dressed up slightly differently.

Questions Asked (1)

Q1

Given a robot on a grid, navigate or simulate its movement according to a set of rules or instructions.

Algorithms & Data Structures
Author's notes

Seen this one before on prep forums so I wasn't totally blindsided.

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AI HintsAI Generated

Suggested Approach

Clarify the grid dimensions, movement rules, and whether the robot must navigate to a target or just simulate instructions. Then choose an appropriate representation (e.g., 2D array, coordinate system) and algorithm (e.g., simulation, BFS/DFS for pathfinding), and discuss time/space complexity.

Pro tip: At Uber, emphasize robustness: discuss handling invalid moves, obstacles, and edge cases like grid boundaries, and mention how you'd test your solution with unit tests.

1. Clarify Requirements

Ask about grid size, movement rules (e.g., directions, step size), obstacles, and whether the goal is to simulate or find a path. Confirm input/output format.

2. Choose Representation

Decide how to represent the grid (2D array, coordinate system) and robot state (position, direction). Consider using a set for obstacles if needed.

3. Design Algorithm

For simulation, iterate through instructions updating position. For pathfinding, use BFS/DFS/A* depending on grid size and obstacles. Handle boundary checks and invalid moves.

4. Analyze Complexity

State time and space complexity. For simulation, O(n) where n is number of instructions. For BFS, O(rows*cols).

5. Test and Edge Cases

Walk through examples, including edge cases like starting at boundary, obstacles blocking path, or instructions causing out-of-bounds moves.

Key Points to Mention

  • Grid representation (2D array vs. coordinate system)
  • Handling obstacles and boundaries
  • Simulation vs. pathfinding algorithms (BFS/DFS/A*)
  • Time and space complexity analysis
  • Edge cases: invalid moves, no path, large grids
  • Testing strategy: unit tests, example walkthroughs

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