computer science algorithms

Most Popular Computer Science Algorithms That You Should Know

Many of you might be heard about the word algorithm, whether in any conversation related to technology or online. This is the word that makes it delivered worldwide, but exactly what does the algorithm mean? The computer science algorithms are a particular procedure utilized for working definite computational issues. The evolution and examination of these algorithms are key aspects of the computer science discipline, such as databases, networking, security, artificial intelligence, graphics,  operating systems,  and much more.

The development of these algorithms is not just about the codings. It needs a knowledge of accessible alternatives that help solve any computational issue, involving the networking, hardware, coding language, and production compulsions that follow any appropriate resolution. It needs to know what this can be meant for an algorithm to get “correct” in the function that it resolves the query efficiently.

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What are computer science algorithms and its example?

An algorithm is just a collection of actions utilized to perform a particular job. These are the fundamental segments for coding, and it supports devices, such as smartphones, computers, and websites, that can function and take decisions.

Moreover, all technology is practiced by algorithms; several things one does daily are related to computer science algorithms. Let’s take an example of these: suppose one likes to make some spaghetti to eat. There is a certain collection of actions that require a distinct order to achieve the task successfully.


Initially, one requires to heat a bowl of water. Once the water gets boiled, one can now combine the spaghetti and heat this for a fixed value of time, mixing it irregularly. When it is finished, transfer the water, now it is available to serve by a flavoring of one’s preference.

The entire method is known as computer science algorithms. As it obeyed the number of actions in a precise manner, one stood their desired result: a tasty pasta meal. But if one were to perform an error like undercooking or overcooking their noodles, it reasonably might not be as best.

Algorithm programs operate similarly. Its code is created of algorithms directing individuals what to perform. Let’s take another example of this: we require to utilize a navigation app to get desired directions.

When a person types an address, the app practices a computer algorithm to view the numerous possible directions. Next, this practices a mixed algorithm to review contemporary traffic; then, three will take the desired data and determine the most suitable route.

These algorithms are made immediately into the app’s program. If any errors are generated in a code, the app can not accurately understand certain algorithms, suggesting one can not get desired directions.

These algorithm examples explain how computers and humans can practice algorithms to accomplish daily work. The only exception is that computers utilize computer science algorithms and measure information faster, better, and more effectively than humans can. 

Technology continues to develop and grow even beneficial at whatever it prepares. As long as programming and coding proceed to be utilized, algorithms would be the core of these modern technologies, managing what they can do and how they will do it.

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Top 5 computer science algorithms

#1: sorting algorithms:

Sorting is one of the most gradually considered theories in computer discipline. The purpose is to manage the things of a file in a particular arrangement. However, each significant coding language has its in-built sorting libraries, which is helpful if a program knows how it works. Based on the condition, one can practice any of these sorting algorithms.

  • Quick Sort
  • Heap Sort
  • Merge Sort
  • Bucket Sort
  • Counting Sort

#2: Searching algorithms

Breadth/Depth-First Search (in Chart data structures)

BFS and DFS are graph/tree searching and traversing for data structures. 

Binary Search (utilize linear data structures)

This searching algorithm is utilized to make an efficient search for the sorted dataset where the complexity time is O(log2N). The purpose is to frequently split in half the program that might include the thing until one narrows it into the possible detail.

#3: Hashing:

Nowadays, a Hash lookup is a widely utilized method to determine relevant information by ID or key. One can locate data with the help of its index. Before, One can rely on Sorting and Binary Search to view the index, now one can practice hashing.

The format of data structure is related to Hash-Table or Hash-Map or Dictionary that effectively outlines answers to conditions. One can make use of lookups utilizing keys. The purpose is to practice the suitable hash functions that do the code -> value mapping—adopting a conventional hash function based on the situation.

# 4: Dynamic coding:

DP (Dynamic programming) is one technique that can help the programmer solve a complicated query by splitting it into more manageable subproblems. One resolves the subproblems, identifies their outcomes, and practices these; you can make your method to resolve the complicated coding issues, immediately.

# 5: String matching /searching:

String matching/parsing is an essential query within computer science algorithms. There has been researched on the subject, but one can only enlist two requirements for any coder.

# 6: Rational Expression (String Parsing)

Several times a programmer needs to approve a string by searching over a predefined constraint. It is gradually applied in web development for the matching and parsing the URL.

# 7: KMP Algorithm (String Matching)

Knuth-Morris-Pratt computer science algorithms are utilized in states where one needs to balance a short guide within a large string. For example, when one presses the Ctrl+F key within a document, it will make string matching in the entire report.


In this blog, we have included the top 5 computer science algorithms. We have also mentioned details regarding the computer algorithms along with the two examples. Learners require to put a lot of effort in the right direction so that they can recognize which algorithm can benefit them in the future. Besides this, they need some basic guidance about these computational algorithms, which we already included in this article at various points.

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