When trying to understand inorder traversal, you might try to tiptoe around the subject. However, tree traversal algorithms aren’t as difficult as they seem. All they do is visit file systems and help us perform operations on them.
There are a few ways to approach a tree data structure, and inorder traversal is the most straightforward. In this article, we talk about how it visits nodes and when you might use its formula. We’ll even provide you with the syntax to get you started. Let’s not waste another minute learning about this simple algorithm.
Inorder Traversal: An Overview
In computer science, we use tree traversal algorithms to visit the nodes of a tree, which is a hierarchical data structure that consists of nodes connected by edges. There are different algorithms for visiting the nodes of a tree, each with a different order of operation. These include:
- Level Order
These traversal algorithms have a range of uses, including copying, deleting, analyzing, and balancing a tree. In particular, we use inorder traversal to search all the nodes in ascending order.
Here’s how you would write a basic syntax for this type of algorithm:
inorder(node): if node is not null: inorder(node.left) visit(node) inorder(node.right)
In this code, you can visit a particular node and perform an operation. The algorithm uses recursion to call itself on each subtree until it reaches a null node.
How Does Inorder Traversal Work?
In binary trees, smaller nodes are structured on the left subtree and larger ones on the right. This makes the inorder traversal algorithm ideal for searching in ascending order because it starts at the left, works down to the root, and finishes at the right. This is how it works:
- Starting at the root, the algorithm analyzes the left subtree by recursively performing an inorder traversal. It does this until there are no more child nodes to visit.
- Return to the root node.
- Traverse the right subtree using the same recursive nature.
The inorder traversal algorithm relies on a stack to keep track of the nodes it needs to visit. The stack allows the traversal to start at the smallest child node and work its way up, ensuring it doesn’t miss one while visiting them in ascending order.
What Are the Applications?
The most common function of an inorder traversal is to perform operations on binary trees. This can include searching for a particular file, inserting a new one, or deleting one altogether. And because inorder traversal scans nodes in a specific order, this is one of the easiest ways to find a unique value.
Additionally, this type of algorithm is great for indexing data in a database. Because of its ability to visit files in ascending system, inorder traversal becomes useful when you need to view data in alphabetical, chronological, or numerical order.
Going one step further, inorder traversal can take an indexed database and retrieve all the words, determining if each one is spelled correctly. We use this type of algorithm to edit files quickly without having to review each word manually.