I knew it was BFS the second I read it, which almost made it worse because I got overconfident and skipped thinking through edge cases.
Model the grid as an unweighted graph and use BFS to find the shortest path from start to goal. Reconstruct the path by storing parent pointers during traversal, or simply return the distance when the goal is reached.
Pro tip: Clarify upfront whether the path or just the length is needed, and discuss trade-offs between BFS and A* if the grid is large or has obstacles. Mention that BFS guarantees the shortest path in unweighted grids, while A* can be faster with a good heuristic.
Ask whether to return the path or just the length, and confirm movement rules, grid size, and whether diagonal moves are allowed. This ensures you solve the exact problem.
Explain that BFS explores level by level, guaranteeing the shortest path in an unweighted grid. Mention that each cell is a node and edges connect adjacent non-wall cells.
Describe using a queue, a visited set or 2D array, and parent pointers to reconstruct the path. Track distance as you go if only the length is needed.
Discuss cases like start equals goal, unreachable goal, or empty grid. State time and space complexity: O(R*C) for both, where R and C are grid dimensions.
Mention that A* with Manhattan distance can be more efficient for large grids, and bidirectional BFS can reduce search space. Note that BFS is optimal for unweighted grids.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.