It's one of those problems that shows up so often in Uber prep lists that you'd feel embarrassed not knowing it.
Clarify the problem constraints and edge cases, then discuss a brute-force solution before optimizing with appropriate data structures. For Uber's high-frequency problems, focus on graph algorithms (e.g., shortest path, topological sort) or dynamic programming, and analyze time/space complexity.
Pro tip: Uber often values clean, production-ready code with proper error handling and edge case checks. Write modular code with meaningful variable names and test with examples, including edge cases like empty input or large graphs.
Restate the problem in your own words, ask clarifying questions about input size, constraints, and expected output format. Confirm edge cases like empty input or disconnected graphs.
Start with a brute-force solution, then propose an optimized approach using suitable data structures (e.g., heaps, queues, hash maps). Explain trade-offs and choose the best based on constraints.
Write clean, modular code with clear variable names. Handle edge cases and use helper functions if needed. Comment on key steps.
Walk through the code with a sample input, including edge cases. Verify correctness and discuss potential bugs or improvements.
State the time and space complexity of your solution. Discuss if further optimization is possible or necessary.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.