DFS: The order of visitation is dependent on the order in which neighbors are explored, leading to different traversal paths.

BFS: Guarantees that nodes are visited in increasing order of their distance from the source node.

DFS: Generally has a lower space complexity as it only needs to store the vertices on the current path, making it more suitable for memory-constrained environments.

BFS: Requires additional memory to store the queue, making it less memory-efficient for large graphs.

DFS: Well-suited for problems involving cycle detection, topological sorting, and solutions with multiple paths, like mazes and game simulations.

BFS: Often used in scenarios where the shortest path is crucial, such as network routing protocols, social network analysis, and puzzle-solving algorithms like the 15-puzzle.

DFS: Typically has a lower time complexity, O(V + E), making it more efficient for large and sparse graphs.

It is O(V + E), where V is the number of vertices and E is the number of edges.

BFS: Generally has a higher time complexity compared to DFS.

DFS: Not necessarily complete it might get stuck in an infinite loop if not implemented carefully. We say that a visitation algorithm is a depth first search or DFS, algorithm, if vertices are visited in depth first order.

DFS: May not find the shortest path it depends on the order in which nodes are explored. The dfs() function uses a stack to keep track of the nodes that need to be explored, while the bfs() function uses a queue to keep track of the nodes that need to be explored.

BFS: Guarantees the shortest path in an unweighted graph due to its level-by-level exploration. Breadth First Nodes entered X earlier, have to be generated on the tree first: X is a queue.

DFS: Utilizes a stack (or recursion in the case of function call stack), generally requiring less memory.

BFS: Uses a queue to keep track of vertices at the current level.

and BFS( Breadth Search Algorithm) use more than DFS.because DFS don’t store the information of all the child.But in BFS we need to store.But still both algorithm depends more on problem types.

BFS is considered more efficient as it searches for the optimal goal first, making it suitable for specific scenarios.The Big advantage of DFS( Depth First Search) is lower memory consuption.

DFS yields deeper solutions and is generally not considered optimal, although it can be optimal in dense graphs.

the order in which the algorithm discovers the new vertices of the graph, then yes: you can take the classic BFS algorithm, replace the FIFO queue with LIFO stack, and you will get pseudo-DFS algorithm. If all you care about is the forward traversal order, i.e.

DFS typically requires less space as it remembers only a single path with unexplored nodes, whereas BFS stores every node in memory, consuming more space. DFS: yes and no, but more 'no' than 'yes'.DFS and BFS are graph traversal techniques with the same time complexity but differing space consumption.Time Complexity of DFS = O(V+E) where V is the number of vertices and E is the number of edges in the given graph.īFS constructs the tree in a level-wise manner.ĭFS constructs the tree one sub-tree at a time.īFS finds utility in applications like identifying bipartite graphs and calculating shortest paths.ĭFS is commonly used for tasks such as exploring acyclic graphs and determining topological orders.īFS doesn't encounter problems with infinite loops.ĭFS may lead to situations where the algorithm gets stuck in an infinite loop.īFS is unsuitable for game decision-making treesĮxplore Scaler Topics Data Structures Tutorial and enhance your DSA skills with Reading Tracks and Challenges. Time Complexity of BFS = O(V+E) where V is the number of vertices and E is the number of edges in the given graph.

The amount of memory required for DFS is less than that of BFS. The amount of memory required for BFS is more than that of DFS. In DFS, it might need to traverse through more edges than BFS to find and reach the destination vertex from your source vertex.

It is because, in BFS, one can easily reach the vertex with a minimum number of edges from the source vertex. In fact DFS recursion approach print the output just in same fashion as BFS. It uses the Stack Data Structure for finding. You can use BFS to find a single source of the shortest path in the case of an unweighted graph. Difference Between BFS and DFS Structure of Data, It uses the Queue Data Structure for finding the shortest path. In Depth First Search, each node is traversed twice due to backtracking. In Breadth First Search, each node is traversed only once. BFS is better when the destination vertex is closer to the source index.ĭFS is better when the destination is far away from the source.

Dfs vs bfs stack vs queue