**Which Data Structure Is Used in Depth First Search?**

In the field of computer science, various algorithms are used to solve different problems efficiently. One such algorithm is Depth First Search (DFS), which is commonly used to traverse or search through a graph. DFS explores vertices, or nodes, of a graph in depth before backtracking.

## Introduction to Depth First Search

Depth First Search is a graph traversal algorithm that starts at a given vertex and explores as far as possible along each branch before backtracking. It uses a stack data structure to keep track of the vertices to explore next. DFS is often used in finding connected components, detecting cycles, and solving maze-like puzzles.

## Data Structures Used in Depth First Search

DFS can be implemented using various data structures, depending on the specific needs and requirements of the problem at hand. The most commonly used data structure in DFS is the __stack__. A stack follows the Last-In-First-Out (LIFO) principle, meaning that the last element added will be the first one removed.

When implementing DFS with a stack, each vertex visited is pushed onto the stack. The algorithm then explores the adjacent vertices of the current vertex until there are no more unvisited vertices left. If there are no adjacent unvisited vertices, it backtracks by popping the topmost vertex from the stack and continues exploring from there.

### Example:

To illustrate how DFS works with a stack, let’s consider an example where we have a graph with five vertices: A, B, C, D, and E.

- We start by choosing a starting vertex (let’s say A) and push it onto the stack.
- We visit vertex A and mark it as visited.
- Next, we choose an unvisited adjacent vertex of A (let’s say B) and push it onto the stack.
- We visit vertex B and mark it as visited.
- From vertex B, we choose an unvisited adjacent vertex (let’s say C) and push it onto the stack.
- We visit vertex C and mark it as visited.
- If there are no more unvisited adjacent vertices of C, we backtrack by popping C from the stack.
- Now, the topmost vertex in the stack is B. We continue exploring from B by choosing an unvisited adjacent vertex (let’s say D) and pushing it onto the stack.
- We repeat this process until all vertices are visited or there are no more vertices left to explore.

## Conclusion

In Depth First Search, a stack data structure is used to keep track of the vertices to be explored. The algorithm explores as far as possible along each branch before backtracking.

By using a stack, DFS ensures that nodes at deeper levels are explored first. This algorithm has numerous applications in various fields such as network analysis, pathfinding, and solving puzzles. Understanding the data structures used in DFS is essential for implementing this algorithm effectively.