← Jane Street Interview Insights
Clarify the problem constraints and assumptions, then propose an efficient algorithm using hash maps to track column heights and row occupancies. Explain how to detect k consecutive pieces in rows and columns after each move, and discuss trade-offs between time and space complexity.
Pro tip: Mention that you would first confirm whether the grid is truly infinite and if k is fixed, as this affects data structure choices. Also, note that early termination can save time by checking only affected rows and columns.
Ask clarifying questions about the grid size, k, and move sequence format. Confirm that pieces stack from the bottom and that only horizontal and vertical runs count.
Use a hash map to track the height of each column (next empty row) and another to track the pieces in each row. Since the grid is infinite, only store occupied cells.
For each move, place the piece, update column height and row occupancy. Check for k consecutive pieces in the affected row and column, and if found, record the winner and move index.
Discuss time complexity: O(1) per move for updates and O(k) for checking runs, leading to O(n*k) total. Space complexity: O(n) for storing occupied cells. Mention alternative approaches like union-find or segment trees if k is large.
Consider cases where k=1, multiple winners in the same move, or no winner. Ensure the algorithm correctly identifies the first move where any player wins.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.