The first four parts are basically public knowledge at this point if you've been lurking the usual prep forums.
Start by clarifying the problem constraints and assumptions for each sub-question, then choose the appropriate algorithm (BFS for shortest path, DFS for any path) and discuss trade-offs. Progressively build from basic traversal to optimized solutions, explaining time/space complexity and edge cases at each step.
Pro tip: Demonstrate strong communication by thinking aloud and proactively discussing trade-offs between BFS and DFS, and mention how you would handle large mazes or dynamic obstacles. This shows you consider real-world scalability and not just correctness.
Ask about maze representation (grid, graph), start/end points, movement rules (4-directional vs 8-directional), and whether the maze is static or dynamic. Confirm if the goal is to find any path or the shortest path.
For shortest path, use BFS; for any path or memory-constrained scenarios, consider DFS. Explain why BFS guarantees shortest path in unweighted grids and discuss trade-offs.
Discuss handling of no path, start equals end, large mazes, and obstacles. Mention techniques like bidirectional BFS or A* for optimization if needed.
State time and space complexity (O(R*C) for BFS/DFS). For sub-questions, adapt to constraints like multiple queries or dynamic changes, suggesting precomputation or incremental updates.
Walk through a small example to verify the algorithm, and discuss how to test edge cases. Mention potential pitfalls like infinite loops in DFS without visited tracking.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.