The data structure used in breadth first search of a graph to hold nodes is a Queue.

Here's why:

1. In a breadth-first search (BFS), you start at the root node and try to visit nodes as close to the root as possible. You move towards children nodes before moving onto sibling nodes.

2. To achieve this, you use a Queue data structure. A queue follows the First-In-First-Out (FIFO) principle. This means that the nodes you visit first (i.e., the nodes closest to the root) are the ones you explore first.

3. When you visit a node, you add all of its unvisited neighbors to the back of the queue. This ensures that nodes are visited in the order they were added to the queue (i.e., level by level).

4. Therefore, a Queue is the correct data structure to use for a breadth-first search of a graph.

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The data structure used in breadth first search of a graph to hold nodes is a Queue.

Here's why:

1. In a breadth-first search (BFS), you start at the root node and try to visit nodes as close to the root as possible. You move towards children nodes before moving onto sibling nodes.

2. To achieve this, you use a Queue data structure. A queue follows the First-In-First-Out (FIFO) principle. This means that the nodes you visit first (i.e., the nodes closest to the root) are the ones you explore first.

3. When you visit a node, you add all of its unvisited neighbors to the back of the queue. This ensures that nodes are visited in the order they were added to the queue (i.e., level by level).

4. Therefore, a Queue is the correct data structure to use for a breadth-first search of a graph.

Knowee AI · Accepted Answer

The data structure used in breadth first search of a graph to hold nodes is a Queue.

Here's why:

1. In a breadth-first search (BFS), you start at the root node and try to visit nodes as close to the root as possible. You move towards children nodes before moving onto sibling nodes.

2. To achieve this, you use a Queue data structure. A queue follows the First-In-First-Out (FIFO) principle. This means that the nodes you visit first (i.e., the nodes closest to the root) are the ones you explore first.

3. When you visit a node, you add all of its unvisited neighbors to the back of the queue. This ensures that nodes are visited in the order they were added to the queue (i.e., level by level).

4. Therefore, a Queue is the correct data structure to use for a breadth-first search of a graph.

Which data structure is used in breadth first search of a graph to hold nodes?a.Arrayb.Queuec.Treed.Stack

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