What Is Level of a Tree in Data Structure?

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Scott Campbell

In data structure, the level of a tree refers to the distance between a node and the root of the tree. The root node is considered to be at level 0, and every subsequent level increases by 1.

The Level of a Node

Each node in a tree has a unique level assigned to it. The level provides important information about the position of a node within the tree hierarchy.

Example:

Let’s consider a binary tree:

        A
       / \
      B   C
     / \
    D   E

In this example, node A is at level 0 since it is the root of the tree. Nodes B and C are at level 1 since they are directly connected to the root. Nodes D and E are at level 2 as they are connected to nodes B and C respectively.

Level-Based Operations

The level of a node can be used for various operations in data structure algorithms. Some common operations include:

  • Level Order Traversal: This traversal technique visits all nodes of a tree by their levels, starting from the root. It starts from level 0 and moves down towards the leaves.
  • Finding Depth: The depth of a tree is determined by finding the maximum level among all nodes.

    It helps in understanding how deep or shallow a particular tree is.

  • Finding Parent-Child Relationship: By comparing levels, we can determine if two nodes are parent-child or not. If one node is at level ‘x’ and another is at ‘x+1’, then they form a parent-child relationship.

Conclusion

The level of a tree in data structure plays a crucial role in understanding the position and relationship between nodes. It helps in implementing various algorithms and operations efficiently. By utilizing the level information, we can perform level-based traversals, find the depth of a tree, and determine parent-child relationships.

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