Cheapest Flights Within K Stops

1. Clarify Constraints: Immediately confirm if k represents stops (edges minus one) or total edges, and verify if the graph is directed or weighted with negative values. 2. Select Algorithm: Propose Modified BFS for unweighted logic or Dijkstra with a priority queue storing [cost, u, stops]. Explain why Bellman-Ford might be too slow for large inputs but valid for small graphs. 3. Define State: Explicitly state that standard visited arrays are insufficient; you need to track the minimum cost to reach a node with exactly 's' stops, as a higher-cost path with fewer stops might yield a better final result. 4. Implement Logic: Describe iterating through neighbors, updating costs only if the new price is lower AND the stop count remains within k. 5. Optimize and Discuss: Mention pruning branches where stops exceed k and discuss time complexity O(E*K) versus O(E log V), highlighting how this scales for Amazon's massive flight networks.