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

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

Options:

Correct Answer: DFS

Solution:

DFS can be more memory efficient in sparse graphs because it does not need to store all the nodes at the current level, unlike BFS.

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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