Tree
A tree is a non-linear and hierarchical data structure where the elements are arranged in a tree-like structure. In a tree, the topmost node is called the root node. Each node contains some data, and data can be of any type. It consists of a central node, structural nodes, and sub-nodes which are connected via edges. Different tree data structures allow quicker and easier access to the data as it is a non-linear data structure. A tree has various terminologies like Node, Root, Edge, Height of a tree, Degree of a tree, etc.
There are different types of Tree-like
- Binary Tree,
- Binary Search Tree,
- AVL Tree,
- B-Tree, etc.
Tree
Characteristics of a Tree:
The tree has various different characteristics which are as follows:
- A tree is also known as a Recursive data structure.
- In a tree, the Height of the root can be defined as the longest path from the root node to the leaf node.
- In a tree, one can also calculate the depth from the top to any node. The root node has a depth of 0.
Applications of Tree:
Different applications of Tree are as follows:
- Heap is a tree data structure that is implemented using arrays and used to implement priority queues.
- B-Tree and B+ Tree are used to implement indexing in databases.
- Syntax Tree helps in scanning, parsing, generation of code, and evaluation of arithmetic expressions in Compiler design.
- K-D Tree is a space partitioning tree used to organize points in K-dimensional space.
- Spanning trees are used in routers in computer networks.
Operation performed on tree:
A tree is a non-linear data structure that consists of nodes connected by edges. Here are some common operations performed on trees:
- Insertion: New nodes can be added to the tree to create a new branch or to increase the height of the tree.
- Deletion: Nodes can be removed from the tree by updating the references of the parent node to remove the reference to the current node.
- Search: Elements can be searched for in a tree by starting from the root node and traversing the tree based on the value of the current node until the desired node is found.
- Traversal: The elements in a tree can be traversed in several different ways, including in-order, pre-order, and post-order traversal.
- Height: The height of the tree can be determined by counting the number of edges from the root node to the furthest leaf node.
- Depth: The depth of a node can be determined by counting the number of edges from the root node to the current node.
- Balancing: The tree can be balanced to ensure that the height of the tree is minimized and the distribution of nodes is as even as possible.
These are some of the most common operations performed on trees. The specific operations and algorithms used may vary based on the requirements of the problem and the programming language used. Trees are commonly used in applications such as searching, sorting, and storing hierarchical data.
Real-Life Applications of Tree:
- In real life, tree data structure helps in Game Development.
- It also helps in indexing in databases.
- A Decision Tree is an efficient machine-learning tool, commonly used in decision analysis. It has a flowchart-like structure that helps to understand data.
- Domain Name Server also uses a tree data structure.
- The most common use case of a tree is any social networking site.
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