What Are the 3 Depth Traversal for a Tree Data Structure?

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Heather Bennett

When working with a tree data structure, traversing the elements in a specific order is often necessary. Depth traversal is one such method that allows us to visit each node of the tree in a specific order.

In this article, we will explore the three depth traversal techniques commonly used: pre-order, in-order, and post-order. Let’s dive in!

Pre-order Traversal

The pre-order traversal starts at the root of the tree and visits each node before its children. This means that we first process the value of the current node, then recursively traverse its left subtree, and finally traverse its right subtree.

To visualize this process, let’s consider a simple binary tree:

    1
   / \
  2   3
 / \
4   5

If we perform pre-order traversal on this tree, the node values will be visited in the following order: 1, 2, 4, 5, 3. This technique is useful when we want to create a copy of the tree or when we need to serialize it into a string representation.

In-order Traversal

The in-order traversal visits each node of the tree by first traversing its left subtree, then processing the value of the current node, and finally traversing its right subtree. This results in visiting nodes in ascending order if dealing with a binary search tree.

Let’s continue using our previous example:

If we perform in-order traversal on this tree, the nodes will be visited as follows: 4, 2, 5, 1, 3. In-order traversal is commonly used when we want to retrieve the values in a sorted order or when dealing with binary search trees.

Post-order Traversal

The post-order traversal visits each node’s children before processing the value of the current node. Starting from the left, it recursively traverses the left and right subtrees before visiting the current node.

Let’s use our example tree one more time:

If we perform post-order traversal on this tree, the nodes will be visited in the following order: 4, 5, 2, 3, 1. Post-order traversal is often used when we want to delete nodes from a tree or free up resources associated with each node.

Conclusion

In this article, we explored three depth traversal techniques for a tree data structure: pre-order, in-order, and post-order. Each technique offers a different way to visit nodes in a specific order. Pre-order is useful for creating copies or serializing trees.

In-order helps with retrieving values in sorted order or working with binary search trees. Post-order aids in deleting nodes or freeing up resources. Understanding these techniques will empower you to effectively traverse tree structures and process their elements accordingly.

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