Data Structures: An Integral Concept For Programmers

BySkillslash

The fundamentals of data structures should be mastered by a candidate who wants to become a programmer. This in-demand ability can help you stand out from the competition and shine on your resume. Understanding algorithms is equally important because they are utilized to solve issues about the structured data that is created.

 

The Definition of Data Structure

We’ll now look into the definition of Data Structure.

A data structure is a way to arrange and store data in a computer so that actions may be carried out quickly and effectively. Most businesses gather data and store it in an unorganized manner that makes it difficult to use. Data structures come in various types (forms), and each type may work well for some operations but not others. Most software systems use data structures, which are the fundamentals of both software engineering and computer science.

 

The Types of Data Structures that Every Programmer Must Know

Now, we’ll dive into the types of data structures that every programmer must get a hold of.

 

  1. Arrays

An array is a fixed-size data structure that sequentially holds several instances of similar kinds of data. The identical, fixed-size data type elements are contained in an array (also known as variables). Hence, the size of an Array cannot be altered. An Array index always starts with Zero.

  1. Linked List

A linear data structure, called a linked list contains items that are arranged in a linear order. These items are linked (connected) to one another. As a result, one can only access data in an orderly fashion.

In the linked list, each item is referred to as a “node“, and each node includes a pointer and a key. The Pointer directs you to the “next” Node, which is the next Node.

By building a single linked list, data can be traversed.

A double-linked list can be traversed in both directions.

  1. Stacks

Stack is the next fundamental data structure. Stack is also a linear data structure, and it operates in the Last in First Out (LIFO) order. Due to this, it is sometimes referred to as a LIFO structure. It implies that the last entry in a list can be retrieved first.

The two operations of the Stack are Push and Pop.

Push is used to add elements to the stack.

Pop is used to delete the elements from the stack.

  1. Queues

Although queues are similar to stack structures, they do not adhere to the LIFO concept. The FIFO (First in First out) concept is used in queues. As a result, it is possible to access the first element first.

Enqueue and Dequeue are the two terminologies involved in this concept.

Enqueue – Adding elements at the end.

Dequeue – Deleting elements from the beginning.

  1. Hash Tables

Each value is linked to a key and stored in the hash table data structure. The hash table employs the hash function to reduce any size data set to one fixed size. Hash values are the outcomes of a hashing operation.

  1. Tree

A Tree is another fundamental data structure. Data is connected in a tree structure, just like in a linked list, but it is ordered hierarchically, like the picture of a family tree.

The various types of Trees are listed below.

  1. i) Binary Search Tree (BST)
  2. ii) Red Black Tree

iii) B Tree

  1. iv) Splay Tree
  2. v) N-Ary Tree
  3. vi) AVL Tree
  1. Heap

A heap is a particular kind of binary tree where values are arranged in the nodes by how the parent and child nodes compare to one another.

There are two types of Heaps: Max Heap and Min Heap

When the parent’s key is equal to or less than the keys of its offspring, it is called a min-heap.

Max heap, where the parent’s key is bigger than its children’s keys.

  1. Graphs

An abstract, non-linear data structure called a graph is made up of a fixed (finite) set of nodes, also known as vertices, that are connected by a set of edges. The arcs or lines that merely link the nodes of a graph are known as edges.

  1. Tries

Using Tries, string-related issues can be resolved. They are also referred to as “prefix trees” since they are prefixes of longer paths.

 

Conclusion

This article is about the types of data structures every programmer must get hold of. We have discussed the definition of Data Structures, and its different types which form an integral part of cracking interviews in almost all the top product-based organizations. One must be technically astute in these concepts. There are many training institutes in our country that train candidates in Data Structures such as Skillslash. However, at Skillslash also has in store, exclusive courses like  Full Stack Web Development Course, Full Stack Developer Course in Hyderabad and Data Structure and Algorithm and System Design Course to ensure aspirants of each domain have a great learning journey and a secure future in these fields. To find out how you can make a career in the IT and tech field with Skillslash, contact the student support team.

 

 

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