Clarify the problem constraints (grid dimensions, input format, definition of connected region) and then explain a solution using either BFS/DFS or Union-Find. Walk through the algorithm step-by-step, analyze time and space complexity, and discuss potential optimizations or trade-offs.
Pro tip: At Amazon, emphasize scalability and real-world applications like image processing or network connectivity. Mention that you would handle large grids by using iterative BFS to avoid recursion depth limits and consider memory usage.
Ask about grid size, input format, whether diagonal connections count, and if the grid can be modified. Confirm that area is the number of cells in the region.
Decide between BFS/DFS (simpler, O(mn) time) and Union-Find (good for dynamic connectivity). For most interviews, BFS/DFS is sufficient and easier to implement.
Iterate through each cell; when a '1' is found, perform BFS/DFS to explore the connected component, count its size, and mark visited cells. Keep track of the maximum area.
State that time complexity is O(m*n) since each cell is visited once, and space complexity is O(m*n) in the worst case for the queue/stack or recursion.
Mention handling empty grid, all 0s, all 1s, and using iterative BFS to avoid stack overflow. Optionally, discuss Union-Find with path compression and union by rank.
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