## What is Breadth-First Search with example?

Breadth First Search (BFS) algorithm traverses a graph in a breadthward motion and uses a queue to remember to get the next vertex to start a search, when a dead end occurs in any iteration. As in the example given above, BFS algorithm traverses from A to B to E to F first then to C and G lastly to D.

### How do you do a Breadth-First Search?

Algorithm for BFS: Step 1: Choose any one node randomly, to start traversing. Step 2: Visit its adjacent unvisited node. Step 3: Mark it as visited in the boolean array and display it. Step 4: Insert the visited node into the queue.

#### How do I code BFS and DFS?

Example Implementation Of Bfs And Dfs

- Step 1: Push the root node in the Stack.
- Step 2: Loop until stack is empty.
- Step 3: Peek the node of the stack.
- Step 4: If the node has unvisited child nodes, get the unvisited child node, mark it as traversed and push it on stack.

**How do I use BFS in Java?**

BFS Algorithm

- Take the input for the adjacency matrix or adjacency list for the graph.
- Initialize a queue.
- Enqueue the root node (in other words, put the root node into the beginning of the queue).
- Dequeue the head (or first element) of the queue, then enqueue all of its neighboring nodes, starting from left to right.

**Should I use BFS or DFS?**

BFS is better when target is closer to Source. DFS is better when target is far from source. As BFS considers all neighbour so it is not suitable for decision tree used in puzzle games. DFS is more suitable for decision tree.

## Where can I use BFS and DFS?

BFS can be used to find the shortest path, with unit weight edges, from a node (origional source) to another. Whereas, DFS can be used to exhaust all the choices because of its nature of going in depth, like discovering the longest path between two nodes in an acyclic graph.

### Why is BFS so fast?

If the search can be aborted when a matching element is found, BFS should typically be faster if the searched element is typically higher up in the search tree because it goes level by level. DFS might be faster if the searched element is typically relatively deep and finding one of many is sufficient.

#### What are some real life examples of depth first search?

Applications. Depth-first search is used in topological sorting, scheduling problems, cycle detection in graphs, and solving puzzles with only one solution, such as a maze or a sudoku puzzle. Other applications involve analyzing networks, for example, testing if a graph is bipartite.

**Is BFS complete in infinite space?**

The algorithm is not complete since it does not find a solution in an infinite space, even though the solution is in depth d which is much lower than infinity. Imagine a strangely defined state space where each node has same number of successors as following number in Fibonacci sequence.