Model the grid as a graph and use BFS to find the shortest path, since BFS explores level by level and guarantees the shortest path in unweighted graphs. Clearly define movement rules (e.g., 4-directional or 8-directional) and handle edge cases like obstacles or unreachable targets. Return the distance when the target is reached, or a sentinel value like -1 if the queue is exhausted.
Pro tip: Mention that BFS is optimal for unweighted grids, but if the grid has weighted cells, Dijkstra's algorithm would be needed. Also, discuss early termination when the target is found to save time.
Ask about movement rules (4 or 8 directions), obstacles, grid boundaries, and what value to return if unreachable. Confirm the start and target are valid cells.
Explain that BFS is ideal for unweighted shortest path problems because it explores nodes in increasing order of distance from the start.
Initialize a queue with the start cell and a visited set or distance matrix. While the queue is not empty, dequeue a cell, check if it's the target, and enqueue all valid unvisited neighbors with distance+1.
Consider cases where start equals target, start or target is blocked, or the grid is empty. Return 0 for same cell, -1 for unreachable.
State that time complexity is O(R*C) since each cell is visited at most once, and space complexity is O(R*C) for the queue and visited set.
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