Model the grid as an unweighted graph and use BFS from the start cell to find the shortest path to the target, exploring only land cells in 4 directions. Track visited cells to avoid cycles and stop early when the target is reached. Then analyze time and space complexity based on the number of cells.
Pro tip: Mention that BFS is optimal for unweighted graphs and briefly compare with DFS or A* to show depth of understanding. Also, clarify edge cases like start or target being water, or unreachable target.
Confirm that movement is only through land cells (0) in 4 directions, and that start and target are valid land cells. Discuss edge cases like start equals target, start or target is water, or no path exists.
Explain that BFS is ideal for finding the shortest path in an unweighted graph, as it explores level by level. Mention that each cell is a node and edges connect adjacent land cells.
Initialize a queue with the start cell and a visited set. While the queue is not empty, dequeue a cell, check if it's the target, and enqueue all unvisited adjacent land cells. Track distance or parent pointers to reconstruct the path if needed.
Time complexity is O(N^2) since each cell is visited at most once. Space complexity is O(N^2) for the visited set and queue in the worst case.
Mention bidirectional BFS for faster performance, or A* with Manhattan distance heuristic if the grid is large. Note that DFS would not guarantee shortest path.
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