BFS vs DFS for Binary Tree
Last Updated :
19 Feb, 2024
Breadth-First Search (BFS) and Depth-First Search (DFS) for Binary Trees are ways to traverse nodes of the Binary Tree. This article aims to provide the basic difference between BFS and DFS for Binary Tree.
A Tree is typically traversed in two ways:
- Breadth First Traversal (Or Level Order Traversal)
- Depth First Traversals
- Inorder Traversal (Left-Root-Right)
- Preorder Traversal (Root-Left-Right)
- Postorder Traversal (Left-Right-Root)
.png)
BFS vs DFS for Binary Tree
Breadth First Search (BFS) is a graph traversal algorithm that starts traversing the graph from the root node and explores all the neighboring nodes at the present depth prior to moving on to the nodes at the next depth level.
How does BFS Tree Traversal work?
Breadth First Search (BFS) traversal explores all the neighboring nodes at the present depth prior to moving on to the nodes at the next depth level. In the context of a tree, BFS traversal works similarly.
Here's how BFS tree traversal typically works:
- Start at the root node and add it to a queue.
- While the queue is not empty, dequeue a node and visit it.
- Enqueue all of its children (if any) into the queue.
- Repeat steps 2 and 3 until the queue is empty.
This approach ensures that nodes are visited level by level, moving horizontally across the tree before moving to the next level. This way, BFS explores the nodes in a breadth-first manner, making it useful for tasks like finding the shortest path in unweighted graphs or trees.
DFS (Depth-first search) is a technique used for traversing trees or graphs. Here backtracking is used for traversal. In this traversal first, the deepest node is visited and then backtracks to its parent node if no sibling of that node exists
1. Inorder Traversal (Practice):
Follow the below steps to solve the problem:
- Traverse the left subtree, i.e., call Inorder(left-subtree)
- Visit the root
- Traverse the right subtree, i.e., call Inorder(right-subtree)
2. Preorder Traversal (Practice):
Follow the below steps to solve the problem:
- Visit the root
- Traverse the left subtree, i.e., call Preorder(left-subtree)
- Traverse the right subtree, i.e., call Preorder(right-subtree)
3. Postorder Traversal (Practice):
Follow the below steps to solve the problem:
- Traverse the left subtree, i.e., call Postorder(left-subtree)
- Traverse the right subtree, i.e., call Postorder(right-subtree)
- Visit the root.
Difference Between BFS and DFS:
| Parameters | BFS | DFS |
|---|
| Stands for | BFS stands for Breadth First Search. | DFS stands for Depth First Search. |
|---|
| Data Structure | BFS(Breadth First Search) uses Queue data structure for finding the shortest path. | DFS(Depth First Search) uses Stack data structure. |
|---|
| Definition | BFS is a traversal approach in which we first walk through all nodes on the same level before moving on to the next level. Â | DFS is also a traversal approach in which the traverse begins at the root node and proceeds through the nodes as far as possible until we reach the node with no unvisited nearby nodes. |
|---|
| Conceptual Difference | BFS builds the tree level by level. | DFS builds the tree sub-tree by sub-tree. |
|---|
| Approach used | It works on the concept of FIFO (First In First Out). | It works on the concept of LIFO (Last In First Out). |
|---|
| Suitable for | BFS is more suitable for searching vertices closer to the given source. | DFS is more suitable when there are solutions away from source. |
|---|
| Applications | BFS is used in various applications such as bipartite graphs, shortest paths, etc. | DFS is used in various applications such as acyclic graphs and finding strongly connected components etc. |
|---|
Conclusion
BFS and DFS are both efficient algorithms for traversing binary trees. The choice of which algorithm to use depends on the specific application and the desired traversal order. BFS is preferred when the goal is to visit all nodes at the same level, while DFS is preferred when exploring a branch as far as possible is more important.
Similar Reads
Binary Tree Data Structure A Binary Tree Data Structure is a hierarchical data structure in which each node has at most two children, referred to as the left child and the right child. It is commonly used in computer science for efficient storage and retrieval of data, with various operations such as insertion, deletion, and
3 min read
Introduction to Binary Tree Binary Tree is a non-linear and hierarchical data structure where each node has at most two children referred to as the left child and the right child. The topmost node in a binary tree is called the root, and the bottom-most nodes are called leaves. Introduction to Binary TreeRepresentation of Bina
15+ min read
Properties of Binary Tree This post explores the fundamental properties of a binary tree, covering its structure, characteristics, and key relationships between nodes, edges, height, and levelsBinary tree representationNote: Height of root node is considered as 0. Properties of Binary Trees1. Maximum Nodes at Level 'l'A bina
4 min read
Applications, Advantages and Disadvantages of Binary Tree A binary tree is a tree that has at most two children for any of its nodes. There are several types of binary trees. To learn more about them please refer to the article on "Types of binary tree" Applications:General ApplicationsDOM in HTML: Binary trees help manage the hierarchical structure of web
2 min read
Binary Tree (Array implementation) Given an array that represents a tree in such a way that array indexes are values in tree nodes and array values give the parent node of that particular index (or node). The value of the root node index would always be -1 as there is no parent for root. Construct the standard linked representation o
6 min read
Maximum Depth of Binary Tree Given a binary tree, the task is to find the maximum depth of the tree. The maximum depth or height of the tree is the number of edges in the tree from the root to the deepest node.Examples:Input: Output: 2Explanation: The longest path from the root (node 12) goes through node 8 to node 5, which has
11 min read
Insertion in a Binary Tree in level order Given a binary tree and a key, the task is to insert the key into the binary tree at the first position available in level order manner.Examples:Input: key = 12 Output: Explanation: Node with value 12 is inserted into the binary tree at the first position available in level order manner.Approach:The
8 min read
Deletion in a Binary Tree Given a binary tree, the task is to delete a given node from it by making sure that the tree shrinks from the bottom (i.e. the deleted node is replaced by the bottom-most and rightmost node). This is different from BST deletion. Here we do not have any order among elements, so we replace them with t
12 min read
Enumeration of Binary Trees A Binary Tree is labeled if every node is assigned a label and a Binary Tree is unlabelled if nodes are not assigned any label. Below two are considered same unlabelled trees o o / \ / \ o o o o Below two are considered different labelled trees A C / \ / \ B C A B How many different Unlabelled Binar
3 min read
Types of Binary Tree