Classification of Data Structure

Data structure has many different uses in our daily life. There are many different data structures that are used to solve different mathematical and logical problems. By using data structure, one can organize and process a very large amount of data in a relatively short period. Let’s look at different data structures that are used in different situations. 
 

Classification of Data Structure

  • Linear data structure: Data structure in which data elements are arranged sequentially or linearly, where each element is attached to its previous and next adjacent elements, is called a linear data structure. 
    Examples of linear data structures are array, stack, queue, linked list, etc.
    • Static data structure: Static data structure has a fixed memory size. It is easier to access the elements in a static data structure. 
      An example of this data structure is an array.
    • Dynamic data structure: In the dynamic data structure, the size is not fixed. It can be randomly updated during the runtime which may be considered efficient concerning the memory (space) complexity of the code. 
      Examples of this data structure are queue, stack, etc.
  • Non-linear data structure: Data structures where data elements are not placed sequentially or linearly are called non-linear data structures. In a non-linear data structure, we can’t traverse all the elements in a single run only. 
    Examples of non-linear data structures are trees and graphs.

Data Structure Types, Classifications and Applications

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How Data Structure varies from Data Type:

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Classification of Data Structure:

Data structure has many different uses in our daily life. There are many different data structures that are used to solve different mathematical and logical problems. By using data structure, one can organize and process a very large amount of data in a relatively short period. Let’s look at different data structures that are used in different situations....

Need Of Data structure :

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Arrays:

An array is a linear data structure and it is a collection of items stored at contiguous memory locations. The idea is to store multiple items of the same type together in one place. It allows the processing of a large amount of data in a relatively short period. The first element of the array is indexed by a subscript of 0. There are different operations possible in an array, like Searching, Sorting, Inserting, Traversing, Reversing, and Deleting....

Linked list:

A linked list is a linear data structure in which elements are not stored at contiguous memory locations. The elements in a linked list are linked using pointers as shown in the below image:...

Stack:

Stack is a linear data structure that follows a particular order in which the operations are performed. The order is LIFO(Last in first out). Entering and retrieving data is possible from only one end. The entering and retrieving of data is also called push and pop operation in a stack. There are different operations possible in a stack like reversing a stack using recursion, Sorting, Deleting the middle element of a stack, etc....

Queue:

Queue is a linear data structure that follows a particular order in which the operations are performed. The order is First In First Out(FIFO) i.e. the data item stored first will be accessed first. In this, entering and retrieving data is not done from only one end. An example of a queue is any queue of consumers for a resource where the consumer that came first is served first. Different operations are performed on a Queue like Reversing a Queue (with or without using recursion), Reversing the first K elements of a Queue, etc. A few basic operations performed In Queue are enqueue, dequeue, front, rear, etc....

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....

Graph:

A graph is a non-linear data structure that consists of vertices (or nodes) and edges. It consists of a finite set of vertices and set of edges that connect a pair of nodes. The graph is used to solve the most challenging and complex programming problems. It has different terminologies which are Path, Degree, Adjacent vertices, Connected components, etc....

Conclusion

Although these are the most widely known and used data structures, there are some other forms of data structures as well which are used in Computer Science, such as policy-based data structures, etc. But no matter which data structure you choose, each one has its perks and disadvantages, without the knowledge of which, it can be very costly to choose the wrong type of data structure. So it is very important to understand the need of the situation, and then decide which kind of data structure suits best for the job....