Alorithms: Types, Importance, Characterstics, And Applications Of Algorithms

The Algorithm: What is it?

For completing a task or solving a problem, an algorithm is a set of step-by-step procedures or rules to follow. We use algorithms every day. We use algorithms to solve problems such as baking a cake, solving a long division problem, and doing laundry. A list of instructions for baking a cake, just like an algorithm, might look like this:

In fact, an algorithm is simply a set of instructions for the computer on how to accomplish a task. In essence, a computer program is an algorithm that instructs the computer which steps to perform in what order, so that a particular task can be carried out. Depending on the programming language used, algorithms are written with a specific syntax.

What are the different types of algorithms?

The most common types of algorithms in computer science include:

1. Divide-And-Conquer Algorithms

Specially, there are three parts to this technique:

Divide: This involves breaking down the problem into smaller sub-problems.
Conquer: Solve sub-problems recursively until they are resolved.
Combine: And, the last part is to combine the subproblems and get the solution.

2. Brute Force Algorithms

An algorithm of this type is the most basic and simplest. Brute Force Algorithms are the first approach we think of when we see a problem, i.e., the first step we take when we see it. On a technical level, it is like reiterating all the possible solutions to the problem.

3. Randomized Algorithms

Randomized algorithms use random numbers to determine what to do next in their logic. A random number is used to select the next pivot in Randomized Quick Sort (or the array is shuffled randomly). These randomizations are typically used to reduce the complexity of other standard algorithms, usually in terms of time or space.

4. Greedy Algorithms

In greedy paradigm logic, one piece of a solution is always chosen to offer the most immediate and obvious benefit, rather than to build up a solution from the bottom up. Greedy is better suited to solving problems where local optimization also leads to the global solution.

For example, choosing the item with the highest value to weight ratio is the local optimal strategy. Furthermore, this strategy allows us to take fractions of an item, so we get a globally optimal solution.

5. Recursive Algorithms

Recursion is the process by which a function calls itself directly or indirectly, and the resulting function is called a recursive function. You can solve certain problems quite easily using recursive algorithms. There are many examples of such problems, including Towers of Hanoi (TOH), Inorder/Preorder/Postorder Tree Traversals, DFS of Graphs, etc.

6. Dynamic Programming Algorithms

As a programming paradigm, Dynamic Programming is a process that breaks down a complex problem into smaller problems and stores the results of those smaller problems so that similar problems do not have to be recalculated subsiquently.

Decide the best algorithm for your task

1. Depending on how efficient the algorithm is when dealing with higher orders of inputs.
2. Any limitations/constraints associated with values.
3. What kind of computer architecture is used and how much storage is required.

4. Go and check the used computer architecure and the storage required.
4. An algorithm is also correct if, for every instance, it produces the appropriate output, which is another key aspect. Depending on the input instances, some incorrect algorithms may not halt at all or may give incorrect output.

Why are Algorithms Important to Understand?

In fact, algorithmic thinking, or the ability to divide a problem into clear steps, is valuable in a variety of fields. Algorithms and algorithmic thinking are part of our everyday lives, even if we aren’t aware of it. Students who use algorithmic thinking can break down problems into discrete steps and visualize solutions. A student must practice structured
thinking and reasoning abilities to be able to understand and implement an algorithm.

Characteristics of an Algorithm

Every algorithm should follow certain characteristics and here is a list of some of them that we will go over one by one.

Specified inputs

The inputs are the values to change during the calculation to generate outputs. It is necessary for algorithms to have at least 0 characterized inputs all around. The exactness of input requires an understanding of what kind of information, how much information, and in what format the information should be provided.

A calculation’s output is the information that comes about as a result of it. An algorithm should have a minimum of one characterized output, and it should coordinate the desired output. In order to achieve output accuracy, you should also understand what kind of information, how much, and what type of structure the output should have.

Clear and Unambiguous

It is essential that an algorithm determines each step, and that each step is clear in all behaviors and must only have one meaning. Thus, a clear and unambiguous algorithm is essential. Every step must also be explained in detail (including how errors should be handled). There must be no subjective information.


All the means necessary to get to output must be feasible with the available resources so that the algorithm is effective. A good algorithm should not contain any pointless or excessive advances that could render it ineffective.


It is important that an algorithm follows step-by-step directions that are independent of coding. Hence, it is very likely there will be a spike in demand for any of the programming dialects.


At some point, the algorithm must stop working. At some point, you will get the normal result. Each algorithm has a set number of steps. It is not acceptable for an algorithm to be limitless and to always end after a specific number of steps.

Applications of the Algorithm

Below given are the applications of algorithms. Here we go!

• Firstly, we will discuss the importance of the internet in our daily lives, and how this is the result of clever and creative algorithms. These algorithms are the only ones that enable a large number of websites on the web to operate and falsify this huge amount of data.

• Almost all of our everyday activities involving electronic commerce are subject to data collection, such as credit or debit card numbers, passwords, OTPs, and so on. The center technology used for this project incorporates public-key crypto-currency and digital signatures that rely heavily on mathematical algorithms.

• Application content that does not use algorithms at the application level is nevertheless heavily reliant on algorithms since the application makes use of hardware, GUI, networking, or object-based controls, all of which produce a substantial use of algorithms.


We can conclude that an algorithm is a process for solving problems step by step. There are numerous advantages and disadvantages of algorithms, but we have only seen a few applications and characteristics of them.

By breaking down the problem into smaller parts or steps, the algorithm makes it easier to understand. By doing so, the programmer has an easier time changing it into an actual program.

Moreover, there are some disadvantages, such as the time it takes to write an algorithm and how hard it is for algorithms to indicate branching and looping. This problem-solving term algorithm provides a lot of information to learn.


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