I jumped straight to prefix sums because that felt natural, and the interviewer nudged me toward thinking about space.
First, clarify the problem statement and constraints, as the question is ambiguous. Then, propose a two-pointer solution that maintains a sliding window or partitions the array in-place, achieving O(n) time and O(1) extra space. Explain how this avoids the O(n) space of prefix sums while meeting the requirements.
Pro tip: Always restate the problem in your own words and confirm assumptions with the interviewer before coding; this demonstrates clarity and prevents solving the wrong problem.
Ask questions to understand the exact requirement: what operation should the two pointers perform? For example, is it to find a subarray with a given sum, partition the array, or compute something else? Confirm input properties (non-negative integers) and expected output.
Compare the two-pointer approach with prefix sums: prefix sums use O(n) space but allow O(1) subarray sum queries; two pointers use O(1) space but may only work for specific problems (e.g., non-negative numbers). Highlight that the choice depends on the problem constraints.
Outline the two-pointer logic: initialize left and right pointers, maintain a running sum or condition, and move pointers based on the condition. Ensure the algorithm handles edge cases (empty array, single element, no solution).
State that the time complexity is O(n) because each element is visited at most twice, and space complexity is O(1) as only a few variables are used. Contrast with prefix sum's O(n) space.
Write clean code with meaningful variable names, then walk through a small example to verify correctness. Mention potential pitfalls like integer overflow or infinite loops.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.