What Is An Algorithm?

In the intricate world of computer science, algorithms serve as the backbone of problem-solving and computational tasks. Like artisans crafting a masterpiece, programmers utilize a palette of algorithmic structures to weave together solutions that power our digital landscape.

In order to perform an operation on the computer, a plan must be made and all the steps required for this plan must be determined. The terminological expression of this planning is algorithm. In other words, it is explained as the processing steps transmitted to the computer to perform some operations.

The answer to the question “What is an algorithm?” is a very curious topic. This subject, which seems quite complex, is also one of the indispensable systems on the computer.

Algorithm developed to solve a problem;

• Open,
• Executable,
• In-line,
• Simple,
• It consists of repeated steps.

How Algorithms Work?

Welcome to the enchanting world of algorithms! Picture this: you’ve got a problem, a puzzle that needs solving. Maybe it’s figuring out the best route for your weekend road trip or finding the perfect playlist to match your mood. Enter the algorithm, your trusty wizard companion, here to weave its spell and guide you to the solution.

1-) Problem Definition: Defining the Quest

Every great adventure starts with a clear quest. You’ve got to define the problem you’re facing. Is it a maze you’re trying to navigate? A treasure map you’re deciphering? Or perhaps you’re just trying to organize your chaotic collection of cat memes. Whatever it is, the first step is understanding what you’re up against.

2-) Input Data: Gathering Your Tools

Once you’ve got your quest in mind, it’s time to gather your tools. Algorithms can handle all sorts of input data – numbers, words, pictures, you name it. They’re like the Swiss Army knives of problem-solving, equipped for anything you throw their way.

3-) Processing: Let the Magic Happen

Now for the fun part – the magic! Your algorithm gets to work, following its set of rules and instructions like a seasoned spellcaster. It might crunch numbers, sift through data, or dance through a maze of if-else statements. Whatever the task, the algorithm is on it, conjuring up solutions faster than you can say “abracadabra!”

4-) Output: Voila! The Big Reveal

After all that wizardry, it’s time for the grand finale – the big reveal! Your algorithm has done its thing, and now it’s time to bask in the glory of your newfound knowledge or perfectly curated playlist. The problem is solved, the puzzle is complete, and you’re left feeling like the hero of your very own epic tale.

5-) Optimization and Analysis: Optimizing for Extra Sparkle

But wait, there’s more! Just like any good wizard, algorithms can always level up their game. Maybe there’s a faster route to your destination, a more efficient way to sort your memes, or a clever trick to squeeze even more magic out of your algorithm. Optimization is the name of the game, making sure your spells are as powerful and efficient as they can be.

6-) Testing and Validation: Testing Your Mettle

Last but not least, it’s time to put your skills to the test. Before you embark on your real-world quest, you’ll want to make sure your algorithm is up to snuff. Throw some curveballs its way, test its limits, and see if it can handle whatever you throw at it. Only then can you unleash your algorithmic magic on the world with confidence.

And there you have it – the secret behind the sorcery of algorithms! With a little bit of imagination and a whole lot of magic, these powerful tools can tackle any problem, solve any puzzle, and turn even the most mundane tasks into epic adventures. So next time you find yourself facing a daunting challenge, just remember – with the right algorithm by your side, anything is possible!

Why Is It Important To Know The Working Logic Of Algorithms?

Understanding the working logic of algorithms is important for several reasons:

1. Problem-solving: It enables efficient problem-solving by choosing the right algorithm for a specific task or problem domain.
2. Optimization: Knowing how algorithms work helps in optimizing their performance, making them faster or more resource-efficient.
3. Critical Thinking: It fosters critical thinking skills by analyzing and improving algorithms to better meet real-world needs.
4. Innovation: Understanding algorithms encourages innovation by enabling the development of new algorithms or improvements to existing ones.
5. Application: It facilitates practical application across various fields, from technology and business to science and engineering.
6. Decision-making: Knowing algorithmic logic aids in making informed decisions about technology adoption and development.
7. Education: It forms a fundamental aspect of computer science and software engineering education, providing foundational knowledge for future advancements.

Why is the Algorithm Necessary?

The prepared algorithms are shown both in text form, pseudocodes and geometric shapes. In order to have a good understanding of the answer to the question “What is an algorithm?”, it is necessary to have knowledge about what the algorithm does. Thanks to a successful algorithm prepared;

• Writing programs becomes easier.
• The rate of incorrect coding is reduced to a minimum.
• The process flow of the program is seen. This makes program control easier.
• Since program writing becomes practical, there is no time wasted.
• It becomes easier to add extra features to the program later.
• The program works quickly.
• The written program should not take up too much space in memory.

In order for the algorithm to be successful, all possibilities must be specified, and it is important that these possibilities are clear so that they are not left to chance. Additionally, it should be simple to write in order to be stated on paper.

How to Prepare an Algorithm?

Although the answers to questions such as what is an algorithm and how to prepare it seem complicated, they are actually quite simple and understandable. While the algorithms are being prepared;

• First of all, the problem to be solved is clarified.
• Then this problem is examined thoroughly and all possibilities are examined.
• In this process, the aim is to determine the solution to achieve the most accurate performance with minimum
• commands and minimum time.
• Being a part, it is given a processing number.
• All data required to solve the problem is entered.
• Stopping procedures are specified.
• Finally, the results found are displayed and stored in a suitable place.

In order for the prepared algorithm to give successful results;

• All the details should be explained in order.
• All process steps must be flexible. It should be suitable for updating whenever any changes are needed.
• It must be suitable for program writing.
• It should be able to work independently of any programming language.

Thus, the program runs smoothly and program control is ensured. Additionally, many operators are used while preparing the algorithm. These are as follows:

• Mathematical operators
• Comparison operators
• Logical operation operators
• Alphanumeric operators
• General operation operators
• They are set operation operators.

Another definition of algorithm is that it is considered as the computer equivalent of planning in human life. People always make a plan before starting a business and aim to be successful by dividing their plans into steps. Here’s coding etc. in the computer field. It ensures that the operations expected from the computer are carried out by using the algorithm while performing the operations.

This concept, also known as process steps, ensures success in terms of which method to choose in solving the problem, the tools to be used and the results to be obtained. Generally produced for problem solving purposes; A clear, simple, sequential and repeatable algorithm is the most important element of programming. Algorithms, which can be prepared and displayed in three different ways, can be presented in the form of text, verbal codes called pesudo-codes, or flowcharts, depending on the need.

What Is Not An Algorithm?

Algorithm:

1. It does not involve random or uncertain steps; The steps must be specific, accurate and clearly defined.
2. It is not a creative process; It is a procedure determined by logical steps and precise rules.
3. It does not offer an absolute solution to a single problem; Solutions may vary depending on context and problem conditions.
4. It can be difficult to explain or comprehend in natural language; It is usually expressed in formal and mathematical language.
5. It may not give accurate results; In some cases, it may not reach a certain result or may give incorrect results.

Algorithm Preparation Process

Various factors play a role in the success of this concept, which was produced with the basic goal of solving problems. The first of these factors is understanding and researching the problem in every aspect for a definitive result in solving the problem. Otherwise, the codes produced for the solution will be unsuccessful and insufficient. Another factor that directs success is achieving the most efficiency with the fewest commands in the shortest time.

Therefore, it is important to produce codes that are result-oriented and focus only on the solution. Afterwards, the algorithm creation phase begins. In the preparation process, where each step is given a number, data and methods are combined and the order of use of these data is determined. After this stage, where everything is done clearly, the result is obtained in detail. The algorithm produced during the algorithm creation process must be programmable and open to updates.

Algorithm Concepts

It is possible to list the terms used in the algorithm as follows;

Descriptor: It is the name given to the words used to describe all the data created by the programmer. Descriptive expressions are used especially to make the program more understandable. Since there are letters, numbers and some other limitations in the selection of identifiers, an identifier cannot be chosen randomly.

Variable: Information that changes values every time the program is started. A variable named at the programmer’s discretion cannot be named randomly like an identifier.

Constant: In contrast to a variable, it is certain and unchanging information in the program.
Counter: In some programs, certain operations are repeated. For this reason, add-ons called counters are used.

Algorithm Examples

Let’s explore some everyday examples of algorithms in action:

1. Sorting Algorithms: Imagine you have a jumbled stack of cards and you want to arrange them in ascending order. Sorting algorithms like Bubble Sort, Insertion Sort, Merge Sort, and Quick Sort come to your rescue. They follow specific rules to compare and rearrange the cards until they’re neatly sorted.
2. Search Algorithms: Ever searched for a particular item in a long list? That’s where search algorithms shine. Binary Search, for instance, efficiently finds an item in a sorted list by repeatedly dividing the search interval in half until the desired item is found.
3. Pathfinding Algorithms: Think of navigating through a maze or finding the shortest route on a map. Pathfinding algorithms like Dijkstra’s Algorithm and A* Search Algorithm determine the most efficient path from one point to another by considering factors like distance, obstacles, and cost.
4. Recommendation Algorithms: Ever noticed how streaming services suggest movies or songs based on your viewing/listening history? Recommendation algorithms analyze your past preferences, compare them with similar users’ preferences, and suggest content you’re likely to enjoy.
5. Image Recognition Algorithms: Have you ever uploaded a photo to social media and had it automatically tagged with names? Image recognition algorithms use complex mathematical models to analyze the features of an image and identify objects, faces, or patterns within it.
6. Natural Language Processing (NLP) Algorithms: When you use voice assistants like Siri or Alexa, or when you interact with chatbots, NLP algorithms work behind the scenes to understand and respond to human language. They analyze text or speech, identify patterns, and derive meaning from language input.
7. Machine Learning Algorithms: In a broader sense, machine learning algorithms learn from data and make predictions or decisions without being explicitly programmed. They power various applications such as spam detection, fraud detection, recommendation systems, and autonomous vehicles.

These examples just scratch the surface of the vast and varied world of algorithms. From solving puzzles to driving technological innovations, algorithms are the building blocks of modern computing, shaping our digital experiences in countless ways.

Algorithm Examples In Daily Life

Here are a few instances of algorithms in everyday life.

1. Google Search: The search algorithm sorts through billions of web pages to find the most relevant results for your query. ( How to search on Google? )
2. Social Media Feeds: Algorithms determine which posts appear at the top of your feed based on your interactions and preferences.
3. Online Shopping: Recommendation algorithms suggest products based on your browsing history and previous purchases.
4. Navigation Apps: GPS algorithms calculate the best route based on real-time traffic data.
5. Email Filtering: Spam filters use algorithms to detect and move unwanted emails to the spam folder.
6. Streaming Services: Algorithms recommend movies, shows, or songs based on your viewing and listening habits.
7. Financial Services: Credit scoring algorithms assess the risk of lending to a person based on their financial history.
8. Digital Assistants: Voice recognition algorithms enable devices like Siri and Alexa to understand and respond to your commands.
9. Health Apps: Fitness trackers use algorithms to monitor and analyze physical activity, sleep patterns, and heart rates.
10. Smart Home Devices: Algorithms control lighting, heating, and security systems to optimize energy use and enhance safety.

Loops

Loops allow a series of instructions to be executed repeatedly under certain conditions. While For Loop is used for a certain number of iterations, While Loop continues to run as long as a certain condition is met. These structures are the basic building blocks for tasks such as data processing, automatic calculations, and handling user input.

Decision Structures

Decision structures enable different sets of instructions to be executed depending on certain conditions. The If-Else Construct executes one set of commands if a given condition is true, and another set of commands if it is false. Switch-Case Structure allows different commands to be executed based on more than one value of a variable. These structures are fundamental in controlling the program flow and performing different actions according to conditions.

Functions and Procedures

Functions and procedures allow code to be organized into reusable pieces. Recursive Functions can call themselves and are often used in mathematical calculations, especially in cases such as factorial calculation or the Fibonacci sequence. Utility Functions implement smaller functions that are used to solve a larger problem. These structures make the code easier to read and maintain.

Working with Data Structures

Data structure algorithms are used to organize, store and access data. Stack works on the last-in, first-out (LIFO) principle and is used in situations such as parenthesis matching and undo operations. Queue works on the first-in, first-out (FIFO) principle and is preferred in applications such as transaction queues and printing queues. A Linked List stores data flexibly by connecting data elements together through a series of nodes. These structures are basic tools in solving algorithmic problems.

Algorithm Diagram

Flow Diagrams

Flow diagrams graphically show the step-by-step operation of an algorithm or program. It represents different programming structures such as loops, decision points, and operations with various symbols. These diagrams make it easier to understand and debug the logic of the program.

Pseudocode

Pseudocode describes the steps of an algorithm in a comprehensible form, independent of actual programming languages. This is used to develop the logic of the algorithm and express ideas during the design phase. Pseudocode helps programmers clarify their ideas and detect potential problems before writing the actual code of the algorithm.

Graphical Representations

Graphical representations are used to visually represent the operation of data structures and algorithms. While tree structures show data in a hierarchical way; Graph structures express the relationships between nodes with edges. These representations make data structures and algorithms easier to understand and analyze.

In this article “What is an Algorithm?” I answered the question. For my other articles, please click the link: Algorithm Man