Went with BFS, which felt like the right call.
Model the grid as a graph where each cell is a node and edges connect adjacent non-blocked cells. Use BFS to find the shortest path in terms of number of steps, since all edges have equal weight. If movement costs vary, use Dijkstra's algorithm with a priority queue.
Pro tip: Clarify with the interviewer whether diagonal moves are allowed and whether the grid has uniform movement costs. Mentioning edge cases like unreachable destination or empty grid shows thoroughness.
Ask about grid size, movement directions (4-way or 8-way), and whether all moves have equal cost. Confirm if the destination is guaranteed reachable.
For unweighted grids, BFS is optimal. For weighted grids, use Dijkstra's algorithm. Mention A* if heuristic is available.
Use a queue for BFS or a priority queue for Dijkstra. Track visited cells to avoid cycles and store parent pointers to reconstruct the path.
Check if source or destination is blocked, if the grid is empty, or if no path exists. Return -1 or appropriate indicator.
For BFS, time complexity is O(V+E) = O(mn) for an m x n grid. Space complexity is O(mn) for the queue and visited set.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Model the problem as a shortest path on a graph where each node has a cost of 1 if blocked and 0 otherwise. Use 0-1 BFS with a deque to find the path from source to destination that minimizes the total cost, which is the number of blocked nodes traversed. Return the minimum cost.
Pro tip: Mention that 0-1 BFS is optimal for binary edge weights and runs in O(V+E), which is more efficient than Dijkstra with a priority queue. Also, clarify that if blocked nodes cannot be traversed at all, the problem changes to finding a path avoiding them entirely, which is a different problem.
Confirm whether blocked nodes can be traversed (with a cost) or must be avoided. Also check if the graph is weighted or unweighted, directed or undirected, and if there are any constraints on the path length.
Assign a cost of 1 to edges entering blocked nodes and 0 to edges entering unblocked nodes. This transforms the problem into finding a path with minimum total cost.
Since edge weights are 0 or 1, use 0-1 BFS with a deque: push 0-weight edges to the front and 1-weight edges to the back. This finds the shortest path in O(V+E) time.
Maintain a distance array initialized to infinity, set distance[source] = 0, and update distances as you traverse. Return distance[destination] as the minimum number of blocked nodes.
Discuss time and space complexity (O(V+E) time, O(V) space). Handle edge cases like source equals destination, no path exists, or multiple paths with the same cost.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.