 # The Beginner’s Guide to Tree Transversal

Data mapping is as important as storing and organizing them. Whether your goal is to store or organize data, mapping and pairing make it is easier to reuse or retrieve data – anytime, anywhere. With the tree traversal method, data analysts can review, update, and work with a high level of accuracy. Best of all, the process of constructing a binary tree from preorder and postorder transversal is also useful in networking, clustering, and other data research.

## What is a tree transversal?

In graph theory, a tree traversal is a technique used to explore the tree in various combinations. Every one of these algorithms may be defined iteratively. In tree traversals, we inspect each vertex in a tree and do certain actions on it, namely displaying the nodes, etc.

## Types of tree transversal:

We may envision a tree as systematically collected; DFS traversals can be executed recursively. When users are at a node, three things may occur: execute some function on the current node (like display the value contained in it), explore the left substring, and traverse the right substring. Depending on this essence, we have the combination of DFS traversal of a tree:

Now, let’s check out the preorder, postorder, and inorder and transversal tree in brief:

### In-order Traversal

One of the most common variations of DFS tree traversal is inorder traversal. Here we process left subtree of the root node first, then the root node, and finally the right subtree of the root node. We mainly use the in-order traversal to print the values stored in the nodes of a binary search tree.

#### How it works?

In the In-order Traversal, we visit the left subtree first, then the root node, and finally the right sub-tree. We repeat this method until we are no longer left with a leaf node. Here, our expected output will always be in the form of sorted key values in low to high (ascending order).

The inorder transversal binary tree algorithm consists of three steps as mentioned:

Step-1: Traverse the left sub-tree.

Step-2: Take care of the root node.

Step-3: And, finally, moves to the right subtree.

Let us take a look at the syntax code:

# In-order Traversal

void inorder(struct node* root) {

if(root == NULL) {

return;

}

inorder(root -> left);

cout << root -> data << ” “;

inorder(root -> right);

}

### Preorder Traversal

Preorder traversal is a DFS variant in which the iterative function’s procedures are related to inorder traversal in a particular sequence. We process the root node first, then the left constituent of the root node, and finally the right subtree of the root node in the preorder traversal.

Unlike the binary tree inorder transversal, the preorder starts with the root node or the initiator node, then the left sub-tree, and finally the right-sub-tree. Using the recursive approach, we repeat the process until we are no longer left with any leaf node.

The preorder transversal tree algorithm consists of three steps as mentioned:

Step-1: Visit the root node first.

Step-2: Then visit the left sub-tree.

Step-3: And, finally, the right subtree.

Let us take a look at syntax code:

# Pre-Order Traversal

void preorder(struct node* root) {

if(root == NULL) {

return;

}

cout << root -> data << ” “;

preorder(root -> left);

preorder(root -> right);

}

### Post-order Traversal

Another DFS version is postorder traversal. In this case, recursive function operations are comparable to preorder and inorder traversal but are performed in a separate order.

How it works: In the Post-order traversal, we analyze the left subtree first, then right subtree, and finally the root node, as we did in preorder and inorder traversals.

The post order transversal binary tree algorithm consists of three steps as mentioned:

Step-1: Travel the left sub-tree.

Step-2: Travel the right subtree.

Step-3: Visit the root node.

Let us take a look at syntax code:

# Post-order Traversal

void postorder(struct node* root) {

if(root == NULL) {

return;

}

postorder(root -> left);

postorder(root -> right);

cout << root -> data << ” “;

}

## Final Words

It will be easy to pick the right one with a sound understanding of all the different types of transversal trees. Undeniably, the choice of the transversal tree will depend upon the nature of the program and your individual needs. Regardless of your choice, the primary goal is to speed up the program and make it more efficient.