The base problem was easy and the follow-up wasn't exactly brutal either, but I still ran out of time.
Start by clarifying the problem and constraints, then walk through a simple example to confirm understanding. Implement the straightforward base case with clean code, test it, and then discuss how to extend it to the follow-up scenario by identifying the additional constraints and adapting your approach accordingly.
Pro tip: Always communicate your thought process and trade-offs, even if you don't finish coding. Google values problem-solving and collaboration over perfect syntax.
Ask clarifying questions to fully understand the base problem and the follow-up scenario. Confirm input/output formats, edge cases, and constraints.
Propose a simple, correct algorithm for the base case. Discuss time and space complexity, and consider alternative approaches.
Write clean, modular code for the base case. Walk through a small example to verify correctness and handle edge cases.
Analyze how the follow-up differs (e.g., larger input, additional constraints). Modify your solution or propose a new approach, discussing trade-offs.
Refine the extended solution for efficiency and clarity. Test with the follow-up scenario and discuss potential optimizations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.