Applications of tree data structure

A tree is a type of data structure that represents a hierarchical relationship between data elements, called nodes. The top node in the tree is called the root, and the elements below the root are called child nodes. Each child node may have one or more child nodes of its own, forming a branching structure. The nodes at the bottom of the tree, which do not have any child nodes, are called leaf nodes. In this article, we will learn about different applications of Tree Data Structure.

Uses of Tree Data Structure: 

Unlike Array and Linked List, which are linear data structures, tree is hierarchical (or non-linear) data structure.  

• Hierarchical Structure: One reason to use trees might be because you want to store information that naturally forms a hierarchy. For example, the file system on a computer: The DOM model of an HTML page is also tree where we have html tag as root, head and body its children and these tags, then have their own children. DNS System is also example where we have natural hierarchy.
• Searching Efficiency: Trees provide an efficient way to search for data. For example, in a binary search tree, searching for a value takes time proportional to the logarithm of the number of elements, which is much faster than searching in a linear data structure like an array or a linked list.
• Sorting: Trees can be used to sort data efficiently. For example, in a self-balancing binary search tree, the data is automatically sorted as it is inserted into the tree, making it easy to find the minimum, maximum, and other values in the tree.
• Dynamic Data: Trees are dynamic data structures, which means that they can grow and shrink as needed. This makes them well-suited for applications where the data changes frequently, such as in real-time systems.
• Efficient Insertion and Deletion: Trees provide efficient algorithms for inserting and deleting data, which is important in many applications where data needs to be added or removed frequently.
• Easy to Implement: Trees are relatively easy to implement, especially when compared to other data structures like graphs. This makes them a popular choice for many programming projects.

Other Applications of Tree Data Structure: 

1. Store hierarchical data, like folder structure, organization structure, XML/HTML data.
2. Binary Search Tree is a tree that allows fast search, insert, delete on a sorted data. It also allows finding closest item
3. Heap is a tree data structure which is implemented using arrays and used to implement priority queues.
4. B-Tree and B+ Tree : They are used to implement indexing in databases.
5. Syntax Tree:  Scanning, parsing , generation of code and evaluation of arithmetic expressions in Compiler design.
6. K-D Tree: A space partitioning tree used to organize points in K dimensional space.
7. Trie : Used to implement dictionaries with prefix lookup.
8. Suffix Tree : For quick pattern searching in a fixed text.
9. Spanning Trees and shortest path trees are used in routers and bridges respectively in computer networks
10. As a workflow for compositing digital images for visual effects.
11. Decision trees.
12. Organization chart of a large organization.
13. In XML parser.
14. Machine learning algorithm.
15. For indexing in database.
16. IN server like DNS (Domain Name Server)
17. In Computer Graphics.
18. To evaluate an expression.
19. In chess game to store defense moves of player.
20. In java virtual machine.
21. Tree data structures are used to organize and manage files and directories in a file system. Each file and directory is represented as a node in the tree, with parent-child relationships indicating the hierarchical structure of the file system.
22. Tree data structures are often used in parsing, such as in compilers and interpreters, to represent the structure of a program or a document.
23. Tree data structures, such as binary search trees, are commonly used to implement efficient searching and sorting algorithms.
24.  Graphics and UI design
25.  Tree data structures are commonly used in decision-making algorithms in artificial intelligence, such as game-playing algorithms, expert systems, and decision trees.
26. Tree data structures can be used to represent the topology of a network and to calculate routing tables for efficient data transmission.

Next Article :

• Advantages, and Disadvantages of Tree

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Article Tags :

• DSA
• Tree
• Self-Balancing-BST

Practice Tags :

• Tree