The story framing threw me off for a second.
Model the story as a directed graph and perform a full traversal (DFS or BFS) from the start node, tracking visited nodes to avoid infinite loops. Collect all ending nodes encountered during the traversal, then analyze the time and space complexity based on the number of nodes and edges.
Pro tip: Explicitly discuss how you handle cycles (e.g., using a visited set) and mention that the traversal must explore all branches, not just one path. Also, clarify whether the graph is a DAG or may contain cycles, as this affects the approach and complexity.
Confirm that each node's options are directed edges, and that you must traverse all reachable nodes. Ask about input format (adjacency list, etc.) and whether cycles are possible.
Select DFS (recursive or iterative) or BFS. Use a visited set to avoid revisiting nodes and infinite loops. Ensure all branches are explored.
During traversal, whenever you encounter a node with no outgoing edges (an ending node), add it to a result set. Return the set of all reachable endings.
Time: O(V + E) where V is number of nodes and E is number of edges, since each node and edge is visited once. Space: O(V) for the visited set and recursion stack (DFS) or queue (BFS), plus O(V) for the result set.
Consider empty graph, start node is an ending, disconnected components, and very large graphs. Compare DFS vs BFS in terms of memory and suitability.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.