DFS (Depth First Search) and BFS (Breadth First Search) are two algorithms for traversing a graph.  DFS is an algorithm for traversing a graph that starts at the root node and explores as far as possible along each branch before backtracking. To implement DFS, we can use a stack data structure. The basic idea is to start at the root node and push all the nodes along the first path onto the stack. Then, we pop the top node from the stack and explore its children. If a node has no children, we pop it from the stack. Otherwise, we push the children onto the stack and repeat the process. This continues until the stack is empty.  BFS is an algorithm for traversing a graph that starts at the root node and explores the neighbor nodes first, before moving to the next level neighbors. To implement BFS, we can use a queue data structure. The basic idea is to start at the root node and add all its neighbors to the queue. Then, we remove the front node from the queue and explore its neighbors. This continues until the queue is empty.  Both DFS and BFS can be used to solve a variety of problems, such as finding a path between two nodes, determining whether a graph is connected, and finding the shortest path between two nodes. However, DFS is generally better suited for searching deep into the graph, while BFS is better suited for searching wide into the graph.