Start by clarifying the problem and constraints, then discuss a brute-force solution before optimizing. Walk through a concrete example to validate your approach, and finally present clean, efficient code with complexity analysis.
Pro tip: Communicate your thought process continuously, even when stuck; interviewers value problem-solving skills and how you handle challenges over just getting the right answer.
Ask clarifying questions to confirm input/output formats, edge cases, and constraints. Restate the problem in your own words to ensure alignment.
Discuss a brute-force solution first, then identify bottlenecks and propose optimizations using appropriate data structures or algorithms.
Choose a representative example, including edge cases, and step through your algorithm to verify correctness and catch flaws.
Write clean, modular code with meaningful variable names. Test with the example and additional edge cases, fixing any issues.
State time and space complexity, discuss trade-offs, and suggest potential improvements or alternative solutions.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.