In graph theory, the Breadth First Search (BFS) algorithm is used to traverse or search a graph. It explores all the vertices of a graph in a breadthward motion, starting from a given source vertex. BFS uses a specific data structure called a **queue** to determine the order in which vertices are visited.

## Queue Data Structure

A queue is an abstract data type that follows the **FIFO (First-In-First-Out)** principle. It maintains two operations: __enqueue__, which adds an element to the end of the queue, and __dequeue__, which removes an element from the front of the queue.

In BFS, we enqueue each unvisited neighbor of a vertex before moving on to its next neighbor. This ensures that vertices closer to the source vertex are visited first.

## Pseudocode for BFS using Queue

To illustrate how BFS works with a queue, let’s consider the following pseudocode:

```
function BFS(graph, source):
create an empty queue
enqueue source into the queue
mark source as visited
while queue is not empty:
dequeue a vertex v from the queue
visit v
for each unvisited neighbor w of v:
enqueue w into the queue
mark w as visited
```

## Example Implementation

Let’s see how this works with an example graph:

```
graph = {
'A': ['B', 'C'],
'B': ['D', 'E'],
'C': ['F'],
'D': [],
'E': ['F'],
'F': []
}
```

If we start BFS from vertex ‘A’, the order of visiting the vertices will be:

## Visualization of BFS using a Queue

Let’s visualize the BFS algorithm using a queue:

```
Queue: A
Visited: A
Queue: B, C
Visited: A, B
Queue: C, D, E
Visited: A, B, C
Queue: D, E, F
Visited: A, B, C, D
Queue: E, F
Visited: A, B, C, D, E
Queue: F
Visited: A, B, C, D, E ,F
```

As you can see in the visualization above, BFS explores all vertices at the same level before moving to the next level. This makes it suitable for finding the shortest path between two vertices in an unweighted graph.

## Conclusion

In summary, a queue is used as the data structure for Breadth First Search (BFS) of a graph. It ensures that vertices are visited in a breadthward manner and helps in maintaining the order of exploration. Understanding this concept is crucial for implementing and comprehending BFS algorithms.

### 9 Related Question Answers Found

Breadth First Search (BFS) is a widely used algorithm for traversing or searching graph data structures. It explores all the vertices of a graph in breadth-first order, meaning that it visits all the vertices at the same level before moving on to the next level. But have you ever wondered which data structure is used in BFS to efficiently manage the vertices and edges?

Data structures play a vital role in computer science and programming. They help organize and manipulate data efficiently. When dealing with graphs, various data structures come into play.

What Data Structure Is Used for Breadth First Traversal of Graph? When it comes to traversing a graph, there are two commonly used methods: depth-first traversal and breadth-first traversal. In this tutorial, we will focus on the latter and explore the data structure that is used for breadth-first traversal of a graph.

Which Data Structure Is Required for Breadth First Traversal on a Graph? When it comes to traversing a graph using breadth-first search, choosing the right data structure is crucial. The data structure you use can greatly impact the performance and efficiency of the algorithm.

What Data Structure Is Used for Breadth First Transfer of a Graph? When it comes to traversing or searching a graph, there are various algorithms available. One of the popular algorithms is the Breadth First Search (BFS) algorithm.

Which Data Structure Required for Breadth First Traversal on a Graph Is? Breadth First Traversal (BFS) is a fundamental graph traversal algorithm used to explore all the vertices of a graph in breadth-first order, i.e., it visits all the vertices at the same level before moving to the next level. To efficiently implement BFS, we need a data structure that can maintain the order of visited vertices and allow us to enqueue and dequeue elements in constant time.

What Data Structure Is Used for the Breadth First Traversal of a Graph? When performing a breadth-first traversal of a graph, it is essential to choose the right data structure to efficiently explore and visit all the vertices or nodes. The breadth-first traversal algorithm visits each level of the graph before moving on to the next level.

Which Data Structure Is Used in Breadth First Search Algorithm? Breadth First Search (BFS) is a graph traversal algorithm that explores all the vertices of a graph in breadth-first order, i.e., it visits all the vertices at the same level before moving to the next level. BFS uses a specific data structure to efficiently traverse the graph and keep track of the visited vertices.

Breadth First Search (BFS) is a popular algorithm used in graph traversal. It explores all the vertices of a graph in breadth-first order, i.e., it visits all the vertices at the same level before moving to the next level. BFS is widely used in various applications, including graph algorithms, network analysis, and data mining.