Start by restating the problem in your own words and asking clarifying questions to pin down constraints and edge cases. Then break the problem into smaller subproblems, discuss brute-force and optimized solutions, and analyze trade-offs. Finally, walk through your chosen solution with test cases and complexity analysis.
Pro tip: Verbalize your thought process continuously, including dead ends, because Google evaluates problem-solving approach as much as the final answer. If stuck, simplify the problem (e.g., reduce dimensions or assume small input) to gain insight.
Restate the problem, ask about input size, constraints, edge cases, and expected output format. Confirm assumptions before proceeding.
Work through small examples manually to identify patterns, invariants, or special cases. Use these to validate your understanding.
Propose a brute-force solution first, then consider optimizations using data structures or algorithmic paradigms (e.g., divide and conquer, dynamic programming, greedy). Discuss trade-offs.
Outline your chosen algorithm step-by-step, then write clean pseudocode or actual code. Explain key decisions and handle edge cases.
Walk through test cases (including edge cases), verify correctness, and analyze time and space complexity. Discuss potential improvements.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.