I knew BFS would work here but I fumbled the transition logic at first.
Model the grid as a graph where each cell is a node, and rolling from a cell in a direction leads to another cell (where the ball stops). Use BFS to explore all reachable stopping positions from the start, and check if the destination is among them. Alternatively, use DFS with memoization to avoid revisiting states.
Pro tip: Clarify that the ball must stop exactly at the destination, not just pass through it. Also, mention that you can precompute the next stopping cell for each cell and direction to optimize the solution.
Confirm that the ball rolls until it hits a wall or boundary, and must stop exactly at the destination. Identify the start and destination cells, and note that the ball cannot change direction mid-roll.
Treat each cell as a node. From a cell, rolling in a direction leads to another cell where the ball stops. These directed edges form the graph.
Use BFS to find the shortest path or DFS to check reachability. BFS is preferred for shortest path, but either works for reachability.
For a given cell and direction, simulate rolling until hitting a wall or boundary. Record the stopping cell. Use precomputation or on-the-fly calculation.
After traversal, check if the destination is visited. Handle cases where start equals destination, or destination is unreachable.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Switched from BFS to Dijkstra here and I think that was right, but I second-guessed myself out loud which probably looked bad.
Model the problem as a graph where each state represents the ball's position and velocity, then use BFS to find the shortest sequence of moves to reach the destination with zero velocity. Alternatively, if the ball moves continuously, use binary search on the distance to check if stopping is possible within that distance. Clearly state assumptions about the ball's motion and constraints.
Pro tip: Always clarify the problem constraints and edge cases (e.g., can the ball overshoot and come back? Are there obstacles?) before diving into a solution. This shows you think like a engineer who values correctness and completeness.
Ask questions to understand the ball's movement rules, the environment (grid, continuous space, obstacles), and what 'stop at destination' means (zero velocity at exact point).
Represent the state as (position, velocity) and define possible actions (e.g., accelerate left/right, apply force) that change the state.
For discrete states, use BFS to find shortest path to a goal state with zero velocity. For continuous, use binary search on distance with a feasibility check (e.g., can we stop within D?).
Code the solution, handle edge cases (e.g., unreachable destination), and discuss time/space complexity. Optimize if needed (e.g., bidirectional BFS, A*).
Walk through examples, test edge cases, and verify the solution returns the shortest distance. Discuss potential pitfalls and how to address them.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.