Clarify the problem constraints and edge cases, then choose BFS or DFS to traverse the grid from the start, marking visited cells to avoid cycles. If a path is found, return true; otherwise, return false after exploring all reachable cells.
Pro tip: Discuss trade-offs between BFS and DFS: BFS finds the shortest path and is often preferred for grid problems, while DFS uses less memory but may be slower for large grids. Mention that you can optimize space by modifying the grid in-place if allowed.
Confirm grid dimensions, start and target coordinates, movement rules, and edge cases such as start or target being a wall or out of bounds.
Decide between BFS (queue) or DFS (stack/recursion) based on requirements like shortest path or memory constraints, and explain your choice.
Use a queue or stack to explore neighbors in four directions, checking bounds and walls, and mark visited cells to avoid revisiting.
Return true if the target is reached; if the traversal exhausts all reachable cells without finding the target, return false.
State time and space complexity: O(m*n) time and O(m*n) space in the worst case, and discuss potential optimizations.
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