Depth First Search, or DFS, is an algorithm used to traverse a graph or tree. It is a powerful algorithm that can be used to solve a variety of problems, from finding a path between two nodes to solving complex problems such as the Hamiltonian Path Problem. In this post, we’ll take a look at what Depth First Search is, how it works, and how to use it to solve problems.
Depth First Search is an algorithm used to traverse a graph or tree. It starts at the root node and explores each branch of the tree as deeply as possible before backtracking. The algorithm works by first visiting a node, then exploring each of its adjacent nodes in a depth-first manner. This means that the algorithm will visit each node in the tree in a depth-first manner, meaning that it will explore each branch of the tree as deeply as possible before backtracking.
Depth First Search works by visiting a node, then exploring each of its adjacent nodes in a depth-first manner. This means that the algorithm will visit each node in the tree in a depth-first manner, meaning that it will explore each branch of the tree as deeply as possible before backtracking.
The algorithm works by first visiting a node, then exploring each of its adjacent nodes in a depth-first manner. This means that the algorithm will visit each node in the tree in a depth-first manner, meaning that it will explore each branch of the tree as deeply as possible before backtracking.
The algorithm works by first visiting a node, then exploring each of its adjacent nodes in a depth-first manner. This means that the algorithm will visit each node in the tree in a depth-first manner, meaning that it will explore each branch of the tree as deeply as possible before backtracking.
The pseudocode for Depth First Search is as follows:
DFS(G, v):
Mark v as visited.
for each edge (v, w) in G.adjacentEdges(v):
if w is not visited:
DFS(G, w)
The algorithm starts at the root node and visits each node in the tree in a depth-first manner, meaning that it will explore each branch of the tree as deeply as possible before backtracking. It then marks each node as visited and continues to explore each adjacent node. If a node has not been visited yet, the algorithm will visit it and continue to explore each adjacent node.
Depth First Search can be used to solve a variety of problems, from finding a path between two nodes to solving complex problems such as the Hamiltonian Path Problem.
For example, if you wanted to find a path between two nodes in a graph, you could use Depth First Search to traverse the graph and find the shortest path between the two nodes.
Depth First Search can also be used to solve complex problems such as the Hamiltonian Path Problem. This problem involves finding a path between two nodes in a graph such that all nodes are visited exactly once. Depth First Search can be used to traverse the graph and find the shortest path between the two nodes.
Depth First Search is a powerful algorithm that can be used to traverse a graph or tree and solve a variety of problems. It starts at the root node and visits each node in the tree in a depth-first manner, meaning that it will explore each branch of the tree as deeply as possible before backtracking. It can be used to solve problems such as finding a path between two nodes or solving complex problems such as the Hamiltonian Path Problem.