Level order traversal of a binary tree is not a novel topic. You may have at least known it vaguely. Though, if you still believe you don't have enough knowledge of it, this blog post is for you
During a DFS traversal of a binary tree, there are three methods to reach nodes: before, after, and in between. Now, a distinct traversal method can be utilized to go through a hierarchical structure. This search method is also known as "level-order" or "breadth-first." BFS traversal refers to the reduction process.
A single root node is at the very top of a binary tree's hierarchy (0th level). The fundamental principle underlying reverse level order traversal is to first process all of the nodes at the root level, then all of the nodes at the next level, and so on. So, we look at each of the nodes at the current level before moving on to the ones above.
Backwards-Forwards-Successively Approached Traversal Recursion
Backwards-Forwards-Successively, Approached Traversal recursion is one method of performing recursion.
This approach to processing the nodes of each level is inefficient. It starts at the top and moves downward using a loop and recursion. Even though the idea is straightforward, execution of processing the nodes might be challenging.
Consider the following illustration of recursive BFS traversal:
The tree has the same number of tiers as its height. Therefore, we begin by utilizing the function height to calculate H's height (root).
In a loop, we can examine every node in the tree by traversing from l = 0 through l + h 1. We can process the nodes at the current level, l using a for loop and the function process Current Level (root, l).
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