## What is an Algorithm?

Algorithms have been used for every computing system you've ever used, from your school computers to your calculator. The terms '**algorithm**' and '**algorism**' are derived from the name of a Persian mathematician known as **Moḥammad ben Musā Al-Khwrizm**, Latinized as ** Algoritmi**. The term algorithm comes from ninth-century Arabic and combines the Greek word for number (

**arithmos**).

**Thomas H. Cormen**is the co-author of Introduction to Algorithms

**,**along with

**Charles Leiserson.**

An algorithm is a collection of well-defined, computer-implementable instructions. An algorithm (pronounced AL-go-rith-um) is a process for solving a problem that is based on performing a sequence of specific actions. Algorithms are important in computer science because they assist programmers in creating effective and error-free programmes. The most important thing to remember about algorithms is that there can be a variety of them.

Computers are extremely fast at manipulating, moving, and searching for data. However, the amount of data that computers use is frequently so large that it takes far too long to examine every single piece of data (companies like Google, Facebook, and Twitter routinely process billions of things per day, and in some cases, per minute!). This is where algorithms come into play. If a computer is given a better algorithm to **process** data, it will do so in a reasonable amount of time regardless of how much information it has to look through. Data is the heart of data structure. Data Structure is concerned with effectively organizing and handling data so that we can perform specific operations, while Algorithm is a step-by-step process to be followed in order to achieve the desired performance.

An **algorithm** is simply a series of steps that are used to complete a specific task. They serve as the foundation for programming, allowing computers, smartphones, and websites to function and make decisions. Computers can use algorithms to perform everyday tasks. A recipe is an excellent example of an algorithm because it specifies what must be done, step by step. It takes inputs (ingredients) and outputs a result (the completed dish). When coding and programming continue to be used, algorithms will be at the core of these innovations, directing what they do and how they do it. Algorithms are written in **pseudocode**, flow charts, or **programming languages** for computing purposes. Algorithm development and analysis is fundamental to all aspects of **computer science**, including **artificial intelligence**, databases, graphics, networking, operating systems, and security.

## Characteristics of an Algorithm

The term "client" corresponds to someone who is looking for a solution to a problem, while "developer" corresponds to someone who comes up with a solution. The programmer must develop an algorithm to solve the client's problem.

When making a recipe, one does not obey any written instructions but the regular one. Similarly, not all written programming instructions are algorithms. Some instructions must consider the characteristics mentioned below to be considered an algorithm.

**Unambiguous and clear**: The algorithm should be unambiguous and clear. Each step should be simple to understand in any way and lead to a single meaning.**Well-Defined Inputs**: If an algorithm requires inputs, those inputs should be well-defined.**Well-Defined Outputs**: What performance will be generated by the algorithm must be clearly specified and well-defined.**Finiteness**: The algorithm has to be finite, which means it can't end up in infinite loops or anything like that.**Feasibility**: The algorithm must be straightforward, generic, and practical, and it must be able to be executed using the available resources. It must not include any future technology or anything else.**Language Independence**: The designed algorithm must be language-independent, i.e. it must be just plain instructions that can be implemented in any language and still produce the expected results.

## Designing of an Algorithm

To write an algorithm, the following prerequisites must be met:

**Design:** Identify and understand the problem. Create basic framework.

**Analyse:** Analyse the efficiency of the code while solving the problem.

**Implement:** Writing and coding the algorithm is the next step in the process.

**Experiment:** Fine-tune the algorithm by experimenting on different platforms.

**Example of Algorithm**

To add three numbers and print their sum

- START.
- Create three integer variables with the names num1, num2, and num3.
- Input the three numbers to be inserted into variables num1, num2, and num3.
- Declare the sum of the three numbers as an integer variable sum.
- Add the three numbers together and save the result in the variable sum.
- Print the value of the variable sum
- END

##### Advantages of Algorithm

- It is a step-by-step a response to a particular problem, making it easy to comprehend.
- An algorithm uses definite procedures.
- It isn't reliant on any particular programming language, making it simple to understand even for those who lack programming knowledge.
- Each algorithm step has its own logical sequence, making it simple to debug.
- The problem has been broken down into smaller chunks or measures by using an algorithm, making it easier for programmers to convert it into an actual program.

##### Disadvantages of Algorithm

- It takes a long time to write an algorithm, As a result, it is time-consuming.
- Algorithms make it challenging to demonstrate Branching and Looping statements.
- Algorithms are difficult to implement for large tasks.

## Types of Algorithm

There are numerous types of algorithms, but the most basic types of algorithms are

**Recursive****Algorithm -**The mechanism by which a function directly or indirectly calls itself is known as recursion, and the corresponding function is known as a recursive function.**Divide and Conquer****Algorithm -**In computer science, the divide and conquer algorithm design paradigm is used. A divide-and-conquer algorithm divides a problem into two or more sub-problems of the same or similar kind in a recursive manner until they are easy enough to be solved directly.**Dynamic Programming Algorithm**- Dynamic Programming is an algorithm design methodology that solves an optimization problem by finding sub-problem solutions and applying the "principle of optimality**."****Greedy****Algorithm-**A greedy algorithm is a straightforward, user-friendly algorithm that is used in optimization problems**.****Brute Force****Algorithm-**Brute-force search is a problem-solving technique and algorithmic framework in computer science that involves systematically addressing all possible solution candidates and deciding whether or not each candidate satisfies the problem's argument.**Backtracking****Algorithm-**By incrementally constructing candidates to the solutions, backtracking is a general algorithm for finding all (or some) solutions to some computational problems, most notably constraint satisfaction problems.**Heuristic algorithm-**A heuristic algorithm is designed for faster solving of problems in most efficient manner by sacrificing accuracy, optimality, or comprehensiveness for speed.**Core algorithm-**In broader way core algorithm update means revamping of the main algorithm in some way.

## Applications of Algorithm

- Algorithms are created and implemented by computer scientists and engineers to make specific tasks more manageable. An Introduction to Algorithm is one of the best seller books published by MIT press.
- Google, in particular, created an algorithm that assists ordinary people in quickly finding specific information.
- Google PageRank is a more complex algorithm example. Google updates are critical for webmasters and SEOs all over the world. When a website's ranking or SEO visibility drops, these algorithm updates, filters, data refreshes, or other alterations are often to blame. A heuristic is a technique for solving a problem faster than traditional methods or for estimating a solution when traditional methods fail. A heuristic (also known as a heuristic function) examines search algorithms.
- A simple, unsupervised learning algorithm frequently used with large data sets to pre-cluster or classify data into more significant categories that other algorithms can then refine is called big-data algorithm.

## Common Mistakes

- Lack of understanding of algorithms models.
- The error, also known as a logic error, occurs when a program runs but produces the incorrect result. This may be due to a bug in the underlying algorithm or a mistranslation of the algorithm by you. Choosing the appropriate metric.

## Context and Applications

- Bachelor of Computer Engineering courses.
- Master of computer engineering courses.
- Bachelor and Master of Computer Application.

## Related Concepts

- Data Structures.
- Computer Programming.
- Flow chart.
- Randomized Algorithms.

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