In computer science, a tree is a widely used abstract data structure that simulates a hierarchical tree structure with a set of connected nodes. Trees consist of nodes connected by edges, and each node can represent data or a value. Here’s a detailed look at their key concepts, types, and applications:
Key Concepts:
- Node: The fundamental part of a tree that contains data and links to other nodes.
- Root: The top node of the tree, where traversal begins. There is only one root in a tree.
- Child: A node that is a descendant of another node. Each node can have zero or more children.
- Parent: A node that has one or more children. Each child has exactly one parent.
- Siblings: Nodes that share the same parent.
- Leaf: A node that has no children. These nodes are often referred to as terminal nodes.
- Height: The height of a tree is the length of the longest path from the root to a leaf.
- Depth: The depth of a node is the length of the path from the root to the node.
- Subtree: Any node of a tree, along with its descendants, can be considered a subtree.
Types of Trees:
- Binary Tree: Each node has at most two children (commonly referred to as the left and right child).
- Binary Search Tree (BST): A binary tree where, for each node, the left child's value is less than the parent's value, and the right child's value is greater.
- Balanced Trees: Types of trees (like AVL Trees, Red-Black Trees) that maintain their height to ensure efficient operations.
- Trie: A specialized tree used for storing associative data structures, especially useful for prefix matching in strings.
- B-Trees: A self-balancing tree data structure that maintains sorted data and allows searches, sequential access, insertions, and deletions in logarithmic time. It is commonly used in databases and file systems.
- Heap: A special tree-based data structure that satisfies the heap property; either the parent node is greater than or equal to (in a max heap) or less than or equal to (in a min heap) the values of its children.
Applications of Trees:
- Data Storage: Trees are used to structure data hierarchically, enabling efficient data retrieval, insertion, and deletion.