How do BFS and DFS differ in graph traversal order and use cases?

• A. BFS visits level by level; DFS explores as deep as possible before backtracking.
• B. BFS uses a stack; DFS uses a queue.
• C. BFS is depth-first; DFS breadth-first.
• D. They always produce the same results.

Answer: (A)

BFS and DFS differ in the order they visit nodes, which in turn shapes their best uses. In BFS you expand outward from the starting node level by level, processing all nodes at distance d before those at distance d+1. This is typically implemented with a queue and makes BFS excellent for finding the shortest path in unweighted graphs and for level-by-level traversal.

In DFS you push as far as possible along a branch before backtracking, which can be done with a stack or via recursion. This deep-first approach is handy for tasks like exploring a whole connected component, detecting cycles, producing topological orders, or locating a path when the exact shortest distance isn’t required.

So the statement that BFS visits level by level and DFS explores as deep as possible before backtracking captures the essential difference in how they traverse. The idea that BFS uses a stack and DFS uses a queue is opposite, and saying they are always producing the same results isn’t true since the traversal order and discovered paths can differ.