Start by clarifying the problem and constraints, then discuss a brute-force approach before optimizing. Implement the solution while explaining your thought process, and finally analyze time and space complexity, considering trade-offs.
Pro tip: While coding, verbalize your reasoning and edge cases; this shows collaboration and thoroughness. Also, after implementing, test with a few examples to catch bugs early.
Ask clarifying questions to confirm input/output formats, constraints, and edge cases. Restate the problem in your own words to ensure alignment.
Propose a brute-force solution first, then suggest optimizations. Explain the trade-offs between different approaches in terms of time and space.
Write clean, modular code while explaining each step. Use meaningful variable names and handle edge cases as you go.
Walk through your code with a few test cases, including edge cases. If you find a bug, debug it methodically and explain your fix.
State the time and space complexity of your solution, justifying each. Discuss potential improvements or trade-offs if relevant.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.