In computer science, a tree is a widely used abstract data type that represents a hierarchical structure. A tree data structure comprises nodes (which store data) linked by edges (which represent relationships between them). Trees provide an efficient way to organize and search data for a variety of computing tasks.


  • Root: The topmost node in the tree; the only node without a parent.
  • Node: The fundamental unit of a tree, storing data.
  • Child: A node directly connected to and descending from another node (its parent).
  • Parent: A node with one or more child nodes connected to it.
  • Siblings: Nodes that share the same parent.
  • Leaf: A node without any children.
  • Edge: The link or connection between a parent node and a child node.
  • Path: The sequence of nodes and edges traversed to move from one node to another.
  • Height of a Node: The length (number of edges) of the longest path from a given node to a leaf node.
  • Depth of a Node: The length (number of edges) of the path from a given node to the root.
  • Height of a Tree: The height of the root node.
  • Level of a Node: The depth of a node plus one.

Types of Trees

  • General Tree (N-ary Tree): A tree where a node can have an arbitrary number of children.
  • Binary Tree: A tree where each node can have a maximum of two children, often designated as "left" and "right."
  • Binary Search Tree (BST): A type of binary tree with the property that for each node:
    • Values in the left subtree are less than the node's value.
    • Values in the right subtree are greater than or equal to the node's value.
  • Balanced Trees: Trees structured to maintain efficiency of operations like searching, insertion, and deletion. Common types include:
    • AVL Trees: Height-balanced binary search trees, where for each node the height difference of its child subtrees can be at most one.
    • Red-Black Trees: Self-balancing binary search trees that use "color" properties to ensure balance.
  • Heap: A specialized tree, typically a complete binary tree. Types include:
    • Min-Heap: The value of each parent node is less than or equal to the values of its children.
    • Max-Heap: The value of each parent node is greater than or equal to the values of its children.
  • Trie (Prefix Tree): A specialized tree for efficient storage and retrieval of strings. Used in applications like autocomplete and spellchecking.

Operations on Trees

  • Traversal: Visiting each node in a tree in a systematic order. Common traversal methods include:
    • In-order Traversal: (Left, Root, Right)
    • Pre-order Traversal: (Root, Left, Right)
    • Post-order Traversal: (Left, Right, Root)
  • Insertion: Adding a new node to the tree in a suitable position.
  • Deletion: Removing a node from the tree while maintaining the tree structure.
  • Searching: Finding a node with a specific value in the tree.


  • Hierarchical Data: File systems, organizational charts, family trees.
  • Decision Making: Decision trees.
  • Efficient Searching: Binary search trees.
  • Priority Queues: Heaps.
  • Network Routing: Spanning trees.
  • Syntax Analysis: Abstract syntax trees in compilers.
  • Artificial Intelligence: Game trees