Question: In which scenario would DFS be preferred over BFS?
Options:
Finding the shortest path
Exploring all nodes
When memory is limited
When the graph is dense
Correct Answer: When memory is limited
Solution:
DFS is preferred when memory is limited, as it can use less space than BFS in certain cases.
In which scenario would DFS be preferred over BFS?
Practice Questions
Q1
In which scenario would DFS be preferred over BFS?
Finding the shortest path
Exploring all nodes
When memory is limited
When the graph is dense
Questions & Step-by-Step Solutions
In which scenario would DFS be preferred over BFS?
Step 1: Understand what DFS (Depth-First Search) and BFS (Breadth-First Search) are. DFS explores as far down a branch as possible before backtracking, while BFS explores all neighbors at the present depth before moving on to nodes at the next depth level.
Step 2: Recognize that both algorithms are used for searching through data structures like trees and graphs.
Step 3: Identify the memory usage of both algorithms. BFS stores all nodes at the current level in memory, which can require a lot of space, especially in wide trees or graphs.
Step 4: Note that DFS, on the other hand, only needs to store the nodes along the current path from the root to the leaf, which can be less than the number of nodes stored by BFS.
Step 5: Conclude that if memory is limited, DFS is preferred because it can use less space than BFS in certain cases, especially when the search space is large and deep.
Depth-First Search (DFS) – A graph traversal algorithm that explores as far as possible along each branch before backtracking.
Breadth-First Search (BFS) – A graph traversal algorithm that explores all neighbors at the present depth prior to moving on to nodes at the next depth level.
Memory Usage – DFS can be more memory efficient than BFS in scenarios with deep but narrow trees, as it uses a stack structure.
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