What Is DFS in Data Structure?


Angela Bailey

What Is DFS in Data Structure?

DFS, short for Depth-First Search, is a popular algorithm used in data structures to traverse or search through a graph or tree. It explores as far as possible along each branch before backtracking and exploring other branches.

The Concept of DFS

DFS follows a simple yet powerful concept – exploring each vertex as deeply as possible before backtracking. It starts with an initial vertex and explores its adjacent vertices. It then moves to the next adjacent vertex and repeats the process until all vertices have been visited.

Application of DFS

DFS finds its applications in various real-world scenarios:

  • Maze Solving: You can use DFS to solve mazes by exploring each possible path until the exit is found.
  • Graph Traversal: DFS helps in traversing graphs, especially when you want to visit every node.
  • Cycle Detection: By keeping track of visited nodes, you can detect cycles within a graph using DFS.
  • Connected Components: With DFS, you can find all connected components within an undirected graph.

The Algorithm

The algorithm for DFS is straightforward:

  1. Pick a starting vertex: Choose any vertex from which you want to start your traversal.
  2. Mark it as visited: Once you choose a starting vertex, mark it as visited to avoid revisiting it later.
  3. Visit adjacent unvisited vertices: Explore the adjacent vertices of the current vertex that are not yet visited.
  4. Recursive call: For each unvisited adjacent vertex, repeat steps 2 and 3.
  5. Backtrack: If there are no more unvisited adjacent vertices, backtrack to the previous vertex and repeat step 3.

DFS Example

Let’s consider a simple graph to understand DFS better:

    / \
   B   C
  / \   \
 D   E   F

If we start our DFS traversal from vertex A, the order of visited vertices will be: A – B – D – E – C – F. It follows the concept of exploring each branch as deeply as possible before backtracking.


DFS is an important algorithm in data structures that allows you to traverse graphs and trees efficiently. Its ability to explore as far as possible along each branch makes it useful in various applications like maze solving, graph traversal, cycle detection, and finding connected components. Understanding DFS can greatly enhance your problem-solving skills in computer science.

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