The term "algorithm" is rather ambiguous; it typically refers to a series of operations designed to achieve a certain purpose. For example, there is one algorithm for boiling tea and another for constructing an IKEA furniture. However, in the context of programming, we refer to various algorithms.
Throughout computer science history, there has been an awareness of what algorithms and data structures (how to store them) are required to tackle real issues - the so-called gentleman's set, which every developer should be familiar with.
Sorting is an example: at a store, things are sorted by price or expiration date, and restaurants are sorted by distance or rating. Hash tables allow to validate passwords and avoid storing them in clear text on websites, while graphs help to discover the shortest path and store relationships between people in social networks.
All of these techniques and data structures have long been included in major programming language libraries. Nobody builds a number sorting algorithm by hand anymore, and you don't even need to understand how hash tables operate to utilise them. We understand why algorithms are required and when their expertise will be useful.
Knowledge of algorithms helps to find an effective solution to the problem
Assume you need to go to the grocery shop. There are three ways to get there: along the road along a well-lit sidewalk (long but safe), yards where many cars travel (quick but dangerous), and via tram (fast, safe, but you have to pay). This difficulty may also be solved by driving a car, ordering home delivery, or sending a dog to get food.
The same may be said about programming. The developer's job is to find the most efficient solution. To do so, consider the program's speed, memory consumption, economic efficiency (how much the cost of the solution is justified by the final result), ease of implementation, and scalability.
Example #1: We must arrange n numbers in ascending order. The assignment appears to be really straightforward. We loop through the array of integers n times. In the first phase, we choose the least number from among all of them and exchange it with the very first element. Second, beginning from the second place, choose the smallest integer in the array and swap it with the second element. Rep for the remaining parts. This is how selection sort functions. However, this technique results in O(n 2) operations. When n reaches absurdly huge, the machine will continue indefinitely. To understand which of the algorithms will be best for your initial data, you must first grasp how these algorithms function. You will almost certainly never have to directly apply them, but understanding how they function will come in useful.
Example #2: You've learned how to write code, but you've never heard of algorithms. A video service was made to order, and the development was warrantied for a year. The initiative was successful, but after the first ten thousand users, everything started to fail: the servers failed swiftly, and the movie, according to users, takes a million years to load. The consumer approaches you and requests that you remedy the situation. You suspect that a more efficient compression strategy is required. This is where knowing algorithms comes in handy: by understanding how each one works, you can pick the best solution for a problem or even build your own.
The availability of several ready-made libraries does not excuse you from learning how they function. Fundamental knowledge aids in determining what's inside, how it works, and why solution A is superior than solution B in a certain context. If you understand how traditional algorithms function, you may devise your own solutions and combine ways to address increasingly difficult issues.
You'll be prepared for interviews.
An algorithmic interview is a required stage in the selection of developers at big IT businesses such as Yandex or Google. It assesses the ability to quickly express a concept in code. However, understanding of algorithms is required not just by IT behemoths; for many businesses, this is the fundamental ability of a successful engineer.
You might be required to implement the complete algorithm or only a portion of it. Find a missing number or duplicates in an integer array ranging from 1 to 100, for example. In this example, you will be asked to compare multiple viable solutions, depending on their computational complexity. That example, don't just use counting sort; explain why it's better than bubble sort or insertion sort.
A programmer's primary responsibility is to evaluate and solve issues, with code serving as a tool to accomplish this. The algorithms are what make Google and Yandex search so clever and speedy. They are not only seeking for the most comparable search word, but they are also attempting to isolate the context and locate the best relevant answer in every way.
There are frequently difficulties that you have never experienced before. The programmer must then create a new algorithm or find out how to utilise an existing one. The more you understand about how algorithms function, the more probable it is that you will find a suitable answer. Even new problems can sometimes be simplified to old ones, but this requires fundamental understanding.
It's an excellent method to exercise your brain.
Algorithms are not limited to use in the workplace. This is one of the "simulator for programmers" variations. First, you complete tasks on Codeforces, and then you form a team to compete in sports programming tournaments.
Another advantage is that you will learn how to solve routine tasks fast and naturally. In his book Bad Choices: How Algorithms Can Help You Think Smarter and Live Happier, Apple Chief Engineer and MIT alum Ali Almossavi discusses how he employs computer science skills in everyday life.
It assigns essential algorithms to daily tasks. For example, you may need to increase your following. The simplest method is to discover people who can both interest and be interested in you. However, you must identify a connection between them. What does the social network have to offer in this regard? Hashtags. So, the simplest solution will be to tag your images with the appropriate hashtags, look for other accounts using them, and interact with people in the comments.
Algorithms, like mathematics, organise the mind, teach you how to express yourself, and solve even the most complex problems. If you want to learn how to tackle programming issues, go visit Codeforces, TopCoder, or LeetCode, all of which include exercises for all ability levels. In the free portion of the Algorithms for Developers courses, you may try to solve challenges characteristic of algorithmic interviews.
What should you read about algorithms?
Authors: S. Dasgupta, H. Papadimitriou, U. Vazirani
The book is better suited for novices because it explains the fundamental ways of designing and analysing algorithms. It is based on lectures delivered by lecturers from the Universities of San Diego and Berkeley. This book is a fantastic place to start if you've never read anything about algorithms before.
Algorithms: construction and analysis
Authors: T. Kormen, C. E. Leizerson, R. L. Rivest, K. Stein
This is an algorithm guide and handbook that will be valuable for new developers, seniors, and team leaders. The descriptions are written in easy language, and the chapters are self-contained and may be studied in any order or volume.
We rock algorithms. Illustrated guide for programmers and the curious
Author: A. Bhargava
Think algorithms are difficult? Otherwise, the book will persuade you. Each method is thoroughly examined in it, so that even a kid may understand it. It will be simple to replicate them in any programming language.
Programming. Theorems and problems
Author: A. Shen
The book teaches readers how to create correct and quick algorithms. It contains problems of varying complexity, and for the majority of them, a solution is provided for self-examination. Learn to work with data carefully and develop coding abilities.
The Art of Programming
Author: D. Knut
"If you can read all of this material, you should absolutely give me a résumé," Bill Gates stated of this book. Begin with it if you consider yourself a programming genius. According to American Scientist magazine, "The Art of Programming" is one of the 12 top books of scientific and mathematical monographs of the twentieth century.