Terminologies of Trees in data structure

Tree terminologies in computer science and graph theory help describe the structure and relationships within tree data structures. Understanding these terms is critical to working with trees and successfully solving various computer problems. These terminologies form the basis for understanding and working with trees in computer science, whether for data storage, retrieval, or solving various algorithmic problems. Different types of trees and their properties enable efficient organization and retrieval of data in various computer applications.

Trees Terminologies:

  • Node
  • Edge
  • Parent
  • Child
  • Root
  • Leaf
  • Height
  • Depth

Trees Terminologies in details:

  • Node: It stores a tree of data in the data structure.
  • Edge: It helps to connect two nodes in a tree. We can connect two nodes through the Edge.
  • Parent: Parent is called when there is one or more child nodes below the node.
  • Child: A child is a node that is connected to a parent node. Child nodes always have a parent node.
  • Root: The root is the main top node is a tree.
  • Leaf: A leaf node has no child node. It is the last node in a tree.
  • Height: The height of a tree is the maximum number of edges from the root node to any leaf node.
  • Depth: The number of edges from the root node to that node.

You can also write this method. Below names of the Tree Terminologies.

Trees Terminologies:

  • Root
  • Child node
  • Parent node
  • Sibling nodes
  • Leaf node
  • Level
  • Depth
  • Height
  • Degree
  • Forest

Types of Trees:

  1. Binary Tree
  2. Binary Search Tree
  3. Complete Binary tree
  4. Full Binary tree
  5. AVL Tree
  6. Red-black Tree
  7. B-tree
  8. B+ Tree
  9. Simple Tree

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