Got the return type right but the actual values were wrong.
First, clarify the problem by asking questions about the expected input types, output data structure, and edge cases. Then, outline a solution using appropriate data structures and algorithms, discussing time and space complexity. Finally, implement the code cleanly and test with examples.
Pro tip: Communicate your thought process continuously and write modular, readable code with meaningful variable names. This demonstrates strong engineering practices and makes it easier for the interviewer to follow your logic.
Ask clarifying questions to confirm the exact requirements, input constraints, and expected output format. Restate the problem in your own words to ensure alignment.
Discuss potential data structures and algorithms, weighing trade-offs. Choose the most efficient and straightforward solution, and explain your reasoning.
Write clean, well-structured code with comments. Use descriptive names and handle edge cases as you go.
Walk through your code with sample inputs, including edge cases. Verify correctness and fix any issues.
State the time and space complexity of your solution, and discuss potential optimizations if needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.