- If we know the solution lies somewhere deep in a tree or
**far from the source vertex in the graph, use DFS**. If we know the solution is not that far from the source vertex, use BFS. If our tree is broad, use DFS as BFS will take too much memory. Similarly, if our tree is very deep, choose BFS over DFS.

## When should we use DFS and BFS?

BFS is more suitable for searching vertices which are closer to the given source. DFS is more suitable when there are solutions away from source. 4. BFS considers all neighbors first and therefore not suitable for decision making trees used in games or puzzles.

## Which is better BFS or DFS?

BFS uses Queue to find the shortest path. DFS uses Stack to find the shortest path. BFS is better when target is closer to Source. DFS is better when target is far from source.

## Why is DFS used?

Using DFS we can find path between two given vertices u and v. We can perform topological sorting is used to scheduling jobs from given dependencies among jobs. Topological sorting can be done using DFS algorithm. Using DFS, we can find strongly connected components of a graph.

## What are the advantages of breadth-first search BFS over depth-first search DFS )?

For a complete/perfect tree, DFS takes a linear amount of space with respect to the depth of the tree whereas BFS takes an exponential amount of space with respect to the depth of the tree. This is because for BFS the maximum number of nodes in the queue is proportional to the number of nodes in one level of the tree.

## Is Dijkstra BFS or DFS?

You can implement Dijkstra’s algorithm as BFS with a priority queue (though it’s not the only implementation). Dijkstra’s algorithm relies on the property that the shortest path from s to t is also the shortest path to any of the vertices along the path. This is exactly what BFS does. Exactly like BFS.

## Why BFS takes more memory than DFS?

The DFS needs less memory as it only has to keep track of the nodes in a chain from the top to the bottom, while the BFS has to keep track of all the nodes on the same level. For example, in a (balanced) tree with 1023 nodes the DFS has to keep track of 10 nodes, while the BFS has to keep track of 512 nodes.

## Why is DFS not optimal?

DFS is non – optimal in nature. In DFS, we need to store only the nodes which are present in the path from the root to the current node and their unexplored successors. For state space with branching factor b and maximum depth m, DFS has space complexity of O(bm), a much better improvement over that of BFS.

## Does DFS find shortest path?

Both BFS and DFS will give the shortest path from A to B if you implemented right.

## Can DFS be used to find shortest path?

Depth-First Search ( DFS ) Your graph needs to be a tree or polytree. If this condition is met, you can use a slightly modified DFS to find your shortest path: If there does not exist a path between startNode and stopNode, the shortest path will have a length of -1.

## Where is DFS useful?

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.

## What is DFS stand for?

Stands for ” Distributed File System.” A DFS manages files and folders across multiple computers. It serves the same purpose as a traditional file system, but is designed to provide file storage and controlled access to files over local and wide area networks.

## Why does BFS find the shortest path?

We say that BFS is the algorithm to use if we want to find the shortest path in an undirected, unweighted graph. The claim for BFS is that the first time a node is discovered during the traversal, that distance from the source would give us the shortest path. The same cannot be said for a weighted graph.

## Why we use queue in BFS and stack in DFS?

Because using queue is the essential element to simulate breadth-first search. If you use stack, it would rather become depth-first search. Start from one node. By enqueuing its neighbors, you are forcing the traversal process to visit all these neighbors before moving to the next level (neighbors or neighbors).

## What is true wrt BFS?

BFS is a traversing algorithm where we start traversing from a selected source node layerwise by exploring the neighboring nodes. The data structure used in BFS is a queue and a graph. The algorithm makes sure that every node is visited not more than once.

## What are the advantages of depth first search?

DFSconsumes very less memory space. It will reach at the goal node in a less time period than BFS if it traverses in a right path. It may find a solution without examining much of search because we may get the desired solution in the very first go.