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Level Order Traversal of N-ary Tree

Overview of N-ary Trees

Let's get a firm grasp on N-ary trees before we explore Level Order Traversal. N-ary trees allow nodes to have multiple children, in contrast to binary trees, which only permit each node to have a maximum of two children. This allows for more complex data relationships. Application areas for these trees include file systems, organisational hierarchies, and linguistics.

Level Order Traversal is a key technique for efficiently navigating and processing hierarchical data structures like N-ary trees. By methodically investigating a tree's levels, we can gain important insights into the configuration and connections between nodes. The Level Order Traversal of a N-ary Tree using a working Python program will be covered in detail in this article, along with explanations and sample outputs.

Knowledge of Level Order Traversal

A technique for methodically perusing and processing a tree structure is called level order traversal, also referred to as breadth-first traversal. Level Order Traversal visits every node on a level before moving to the following level, in contrast to Depth-First methods, which travel as far along a branch as possible before turning around. This strategy guarantees that nodes are processed layer by layer, starting at the root.

Explaining the Algorithm

It makes sense to use the Level Order Traversal algorithm. Beginning with the root node, it processes it before enqueuing its children. The processed node is then released from the queue, and the procedure is repeated for its unprocessed children. This keeps going until each node has been visited. The outcome is a list of nodes visited in order of their corresponding levels.

Level Order Traversal's advantages

Level Order Traversal has a number of benefits. It is perfect for tasks like creating a level-by-level view of a tree because it makes sure that nodes at the same level are processed together. This traversal technique is essential when attempting to find the shortest path or investigate nearby nodes in graph-like structures.

N-ary Tree Level Order Traversal: Basic Concepts

Level Order Traversal is a tree traversal algorithm that methodically investigates a tree's nodes level by level, also known as breadth-first search (BFS). This method visits the nodes at each level before moving on to the next in the context of N-ary trees. By using this method, it is made sure that nodes at the same level are processed before moving on to the next level. The Level Order Traversal comes in handy when processing a tree while maintaining its level-wise structure.

BFS: Breadth-First Search.

BFS is a quick and easy method for Level Order Traversal because it operates with a queue data structure. The root node is first enqueued by the algorithm, which then iteratively performs the following steps:

  • Dequeue a node from the front of the queue.
  • Process the node's data or perform any desired operations.
  • Enqueue the node's children, if any, to the back of the queue.

Following this strategy allows BFS to process nodes at the same level before going to the next level. Level Order Traversal differs from other traversal techniques due to this behavior.

Level Order Traversal's Benefits

Level Order Traversal is frequently chosen because it has the following benefits:

  • Breadth-First Exploration: As its name implies, BFS investigates nodes one level at a time, which is very useful when attempting to analyze a tree's structure breadth-first.
  • Finding the Shortest Path: In an unweighted graph or tree, BFS can be used to determine the shortest path between any two nodes. This is especially helpful in situations like network routing where finding the shortest path is essential.
  • Level-wise Operations: Level Order Traversal makes it easier to carry out operations on nodes that depend on their level, such as printing the data for each level or calculating level-specific metrics.
  • Avoiding Recursion: BFS doesn't use recursion, unlike depth-first traversal methods, which can help prevent stack overflow errors and make it suitable for trees with deep root systems.

Exploring Use Cases

The Level Order Traversal of N-ary Trees has numerous applications:

1. Search engines and web crawlers

BFS is used by web crawlers and search engines to level-wise index web pages. This makes sure that before indexing deeper pages, pages that are closely linked to the root are first indexed.

2. Analysis of social networks

BFS can be used in social networks to investigate relationships and friendships within a network. This aids in locating acquaintances or potential influencers who may be mutual.

3. Puzzle Solving

BFS helps with puzzles like the famous Rubik's Cube and the sliding puzzle. It methodically investigates potential states until a solution is discovered.

Implementation: Level Order Traversal

To illustrate Level Order Traversal, we'll first define a simple N-ary tree structure and then implement the traversal algorithm. Let's start with the tree structure:

Now, let's implement the Level Order Traversal algorithm:


When you run the above code, you should see the following output:

Level Order Traversal:
[1, 2, 3, 4, 5, 6, 7, 8]


To represent the nodes of the N-ary tree in the implementation given, we first define the Node class. Then, we build a straightforward N-ary tree structure with nodes and their offspring. The root node is the input for the level_order_traversal function, which uses a queue to carry out level order traversal. One by one, nodes are dequeued, their values are added to the result list, and then their children are re-queued.

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