← Snowflake Interview Insights
I went with a two-pointer style single pass, left to right, tracking the last seen person or cake and updating a running minimum.
Start by clarifying the problem constraints (e.g., array size, whether multiple people/cakes exist, and if distance is absolute index difference). Then propose an efficient solution, such as a two-pass dynamic programming approach that tracks the nearest cake from left and right, or a BFS-like multi-source propagation. Compare with brute force and explain why the chosen approach is optimal.
Pro tip: Mention that you can solve it in O(n) time and O(1) extra space by scanning left-to-right and right-to-left while maintaining the last seen cake position, updating the minimum distance when encountering a person. This shows you can optimize beyond the obvious O(n^2) brute force.
Ask about array size, whether there can be multiple people and cakes, and if distance is defined as absolute index difference. Confirm edge cases like no person or no cake.
Explain that a naive approach would compare every person with every cake, resulting in O(n^2) time. This sets a baseline and shows you consider trade-offs.
Describe a two-pass method: first left-to-right to record distance to the nearest cake on the left, then right-to-left for the nearest cake on the right, taking the minimum. Alternatively, use a multi-source BFS if the problem were on a grid.
Trace the algorithm on a small array like [1,0,2,0,1] to demonstrate correctness and how the minimum distance is updated.
State that the solution runs in O(n) time and O(1) extra space (if using two variables) or O(n) if storing distances. Discuss handling of no valid pair, multiple cakes, and large inputs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.