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Introduction to data structure and algorithms

Introduction to data structure and algorithms

By Nicodemus Ngufuli
Published in DSA
January 02, 2021
3 min read

The organization of a collected data in a unique way so that the function to be performed on it will be done effectively is called data structures.

Data structures

Bad programmers worry about the code. Good programmers worry about data structures and their relationships. - Lunus Torvads

Data elements are provided to build successful relationships with the other data elements to bring out the successive results, good alignments, and improved capacity.

Are you familiar with OOP?

It is a simple and comprehensive concept of programming known as Object-oriented programming. If you know what it is, it will be effortless to understand the subject because it exhibits the same functions. The class works under one entity and gathers multiple data types in it. There is only one difference between the two, and that is, data structure renders for accessing techniques and systematically manipulating the data.

Not confusing you much, let us make things easier.

All data structures put their efforts into storing data in a well-organized manner to efficiently carry out the functions. It is recommended to make the entire procedure easy to understand and modified easily because the complex ones might cause complications in the next level programs.

Main types of Data Structures

Revising the description mentioned above, anything that can organize and store data for you is called a data structure.

According to this, we realized that Boolean, Float, Char, Integer, etc., are also in this category that is signed as primitive.

Other than Primitive Data structures, there are Abstract data structures as well, which are comparatively complex. It is used to accommodate the big data chucks, usually linked or connected data. They are Tree, Graph, Linked list, stack, queue, etc.

We are here to dig into what stacks, queues, and Deque are and their applications.

What is a Stack?

If you know about the term stacking, then you will get the point in no time. A stack is the row in which the insertion and deletion of data are done at only one end. Irrespective of the middle point, this linear data structure performs the function linearly at the endpoints. The linear form of arrays combines to make this linear stack.

Conversion and the expressions of evaluations are often carried out via stack like infix, prefix, and postfix. Arrays and linked lists allow programmers to insert and delete elements from any place within the list. Whether from the beginning or the end or even from the middle.

Stack Data structure
Stack Data structure

Nevertheless, in computer programming and development, some situations may arise where insertion and deletion require only at one end, either at the beginning or end of the list.

The stack is a linear set of data, and all of its attributes are added and discarded at the same end (top). Let us presume that a stack of sheets or a stack of papers, etc., is a strong example. Since the element will only be deleted or inserted from the upper end in this type of data structure, this implies that the very last item to be included to the stack will be the first item to be excluded. So you might assume the stack fits the pattern of Last In First Out (LIFO).

In the stack, the following process operations are typically conducted:


It introduces an object to the stack. If the stack is complete, then it is indeed a situation of overflow.


It deletes an object from the stack. In the opposite direction in which they are driven, the items pop up. When the stack is blank, so it may well be a state of the underflow.

Peek or Top

The top portion of the stack is returned


Returns true, otherwise false, if the stack is vacant

How do we actually comprehend a stack?

Many concrete examples of a stack are available. Understand the general case of dishes in a canteen piled over each other. The dish at the upper end is the primary to be eliminated, i.e., the dish put at the lowermost place stays for the most extended amount of time in the stack. So, it can clearly be shown that the LIFO/FILO rule must be followed

Stack applications

  1. Sign balancing
  2. Migration Infix to Postfix /Prefix Redo-undo functions such as templates, photo editing, in many areas. Forward and backward support in operating systems Seen in many methodologies, such as Hanoi Tower, tree traversals, stock span issue, histogram issue.
  3. Backsliding is one of the methods of attribute selection. A few other backpedaling instances are Knight-Tour issue, N-Queen issue, navigate your way via hall of mirrors and gaming like chess or checkers. In all these issues, we plunge into somehow the direction that is not efficient, then we go through each state effectively and check some other order.
  4. We have to archive the entire history for that reason in restoring from the present state. In graph algorithms such as topological sorting and firmly linked pieces, every modern device uses a stack as the critical control for an operating task in dynamic memory. Each system operating on a computer network has its own allocated memory
  5. String reversal is also another method of the stack. Here one by one, every character gets added to the stack. The initial element of the sequence is on the stack’s underside, and the final component of the string is on the top of the stack. We get a string in reverse order after conducting the pop operations on the stack

Next, read about what is a queue?.


#data structure#algorithms#stack#queue
Nicodemus Ngufuli

Nicodemus Ngufuli

Software Engineer and content editor at UltimaxDev

I am a Full-Stack Software engineer, currently learning advaced java as a hobby



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