In data structure, a tree is a widely used abstract data type that represents hierarchical relationships between elements. It is composed of nodes connected by edges, where each node can have zero or more child nodes. The topmost node of the tree is called the root, and each node can have a parent except for the root node.
What is the Purpose of Trees?
Trees are commonly used to represent hierarchical structures such as file systems, organization charts, and family trees. They provide an efficient way to organize and retrieve data in a hierarchical manner. Moreover, trees are used in various algorithms and data structures like binary search trees, AVL trees, B-trees, and heaps.
Basic Tree Terminology
Before diving deeper into the representation of trees in data structures, let’s understand some key terminologies:
- Node: Each element within a tree is called a node. It contains data and references to its child nodes.
- Root: The topmost node of the tree that has no parent.
- Parent Node: A node that has one or more child nodes.
- Child Node: Nodes directly connected to another node when moving away from the root.
- Sibling Node: Nodes that share the same parent.
- Leaf Node: Nodes that have no children.
- Edge: A connection between two nodes.
The Representation of Trees
Trees can be represented in various ways depending on the requirements and use cases. Let’s explore some common representations:
1. Array Representation
In this representation, each node is stored in an array, and the indices of the array represent the relationships between nodes. For example, if a node is stored at index i, its left child can be found at index 2i+1, and its right child can be found at index 2i+2. This representation works well for complete binary trees but may result in wasted space for sparse trees.
2. Linked List Representation
In this representation, each node is represented by an object that contains data and references to its child nodes. Each node has a pointer to its first child and a pointer to its next sibling. This representation is useful when the number of child nodes is not fixed or known in advance.
3. Parent-Child Relationship Representation
In this representation, each node has a reference to its parent and a list of references to its child nodes. This allows efficient traversal both upwards (from child to parent) and downwards (from parent to children). However, it requires additional memory for storing the parent references.
To process or search for data within a tree structure, different traversal algorithms can be used:
- Pre-order Traversal: Visit the current node before its children.
- In-order Traversal: Visit the left subtree, then the current node, and finally the right subtree.
- Post-order Traversal: Visit the children before visiting the current node.
- Level-order Traversal: Visit all nodes of a level before moving onto the next level.
Trees provide an efficient way to organize and represent hierarchical relationships in various applications. Understanding the representation of trees and the associated terminologies is essential for effective utilization of tree-based data structures.
Now that you have a solid understanding of the representation of trees in data structures, you can explore further and apply this knowledge to solve complex problems efficiently.