Trees are fundamental data structures that represent hierarchical relationships. They consist of nodes connected by edges, with each node storing data and references to other nodes. Understanding tree concepts is crucial for organizing and efficiently accessing information in computer science.
Trees come in various types, including binary trees and binary search trees, each with specific properties. Relationships between nodes, such as paths and common ancestors, play a vital role in tree operations. Traversal methods allow systematic exploration of tree structures, enabling efficient data manipulation and analysis.
Tree Fundamentals
Fundamental concepts of trees
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Tree represents a hierarchical data structure composed of nodes connected by edges
Acyclic property ensures no cycles or loops exist within the structure
Directed edges establish a specific direction from parent to child nodes
Node serves as the basic unit in a tree, storing data and references to other nodes
Root node sits at the topmost position in the tree hierarchy, lacking a parent
Parent node directly connects to and resides above another node
Child node directly connects to and resides below another node
Sibling nodes share a common parent node
Leaf (external node) represents a node without any children
Internal node signifies a node with at least one child
Edge denotes a connection between two nodes, signifying a parent-child relationship
Subtree constitutes a portion of a tree, including a node and all its descendants
Properties and characteristics of trees
Depth indicates the number of edges from the root to a particular node
Level refers to nodes positioned at the same depth within the tree
Root node resides at level 0, its children at level 1, and so on
Height represents the maximum depth of any node in the tree
Height of a node equals the number of edges on the longest path from the node to a leaf
Height of a tree corresponds to the height of the root node
Degree denotes the number of children associated with a node
Degree of a tree signifies the maximum degree of any node within the tree
Tree Types and Relationships
Types of trees
Binary tree restricts each node to have at most two children, designated as left and right child
Strict/proper binary tree mandates each node to have either 0 or 2 children
Complete binary tree requires all levels, except possibly the last, to be entirely filled, with nodes positioned as far left as possible
Binary search tree (BST) adheres to specific properties:
Left subtree of a node contains only nodes with keys less than the node's key
Right subtree of a node contains only nodes with keys greater than the node's key
Both left and right subtrees must also satisfy BST properties
Balanced tree maintains a height difference of at most one between the left and right subtrees of any node
Examples include AVL trees and Red-Black trees
Guarantees O ( log n ) O(\log n) O ( log n ) time complexity for search, insertion, and deletion operations
Relationships between tree nodes
Path represents a sequence of nodes and edges connecting a node with its descendant
Path length corresponds to the number of edges in a path
Distance between two nodes equals the number of edges on the path connecting them
Lowest common ancestor (LCA) identifies the deepest node that serves as an ancestor to both nodes
LCA helps determine the distance between two nodes
Traversal involves visiting each node in a tree exactly once
Preorder traversal: visit root, then left subtree, followed by right subtree
Inorder traversal: visit left subtree, then root, followed by right subtree
Postorder traversal : visit left subtree, then right subtree, followed by root