Which traversal method can be more memory efficient in sparse graphs?

Which traversal method can be more memory efficient in sparse graphs?

Step 1: Understand what sparse graphs are. Sparse graphs have fewer edges compared to the number of nodes.
Step 2: Learn about traversal methods. The two common methods are Depth-First Search (DFS) and Breadth-First Search (BFS).
Step 3: Know how BFS works. BFS explores all neighbors at the present depth before moving on to nodes at the next depth level.
Step 4: Realize that BFS needs to keep track of all nodes at the current level in a queue, which can use a lot of memory, especially in wide graphs.
Step 5: Understand how DFS works. DFS explores as far as possible along one branch before backtracking.
Step 6: Note that DFS only needs to keep track of the current path in memory, which is usually less than the number of nodes at the current level.
Step 7: Conclude that in sparse graphs, DFS can be more memory efficient because it doesn't store all nodes at the current level like BFS does.

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