Big-O on Karpoke - Just Another Blog

Binary Search – Algorithm and Time Complexity Explained

Thu, 13 Jul 2023 20:54:08 +0100

When working with arrays, you’ll often have to search through them to check if they contain a target element. You can always run a sequential search—scanning the array from the beginning to the end—on the array. But if the array is sorted, running th…

» freeCodeCamp.org | freecodecamp.org

Big O Cheat Sheet – Time Complexity Chart

Fri, 07 Oct 2022 11:00:30 +0100

An algorithm is a set of well-defined instructions for solving a specific problem. You can solve these problems in various ways. This means that the method you use to arrive at the same solution may differ from mine, but we should both get the same r…

» olawanletjoel | freecodecamp.org

The Big O

Wed, 03 Aug 2022 16:58:53 +0100

The Big O is a way to measure how well your code solves a problem

» hackernoon.com | hackernoon.com

Big O, code efficiency analysis

Fri, 13 Aug 2021 14:13:01 +0100

In this article I would do my best to introduce you to algorithmic complexity and a way to roughly…

» DEV Community | dev.to

Four Rules for Big O

Mon, 26 Jul 2021 07:56:57 +0100

Worst case When calculating for the Big O of algorithms we’re supposed to assume the…

» DEV Community | dev.to

Big(O) Notation summarized!

Fri, 09 Jul 2021 14:32:09 +0100

Big(O) is the way in which we compare algorithmic complexities of two programs in a standard…

» DEV Community | dev.to

Big O Notation

Wed, 13 Jan 2021 09:01:13 +0100

-Intro to Big O -Timing Our Code -Counting…

» DEV Community | dev.to

A Gentle Introduction to the Big O Notation, Time & Space Complexity

Thu, 15 Oct 2020 14:50:52 +0100

Introduction I have been in Software Engineering for a decade and a half and I am not a Co…

» DEV Community | dev.to

Big O Notation for beginners!!

Sat, 15 Aug 2020 17:23:56 +0100

Why beginners should not be afraid of AL As a code newbie, I have read a few posts that sa…

» DEV Community | dev.to

Big-O For the Non-CS Degree - Part 2

Sat, 04 Jul 2020 20:27:14 +0100

If you’re reading this, and haven’t read part one in the series I recommend reading that first. There…

» DEV Community | dev.to

Notes on algorithms

Fri, 10 Jan 2020 23:25:21 +0100

notes on algorithms after CS50 week 3

» DEV Community | dev.to

A Gentle Introduction to Algorithm Complexity Analysis

Thu, 05 Jul 2012 18:17:00 +0100

A lot of programmers that make some of the coolest and most useful software today, such as many of the stuff we see on the Internet or use daily, don’t have a theoretical computer science background. They’re still pretty awesome and creative programmers and we thank them for what they build.

However, theoretical computer science has its uses and applications and can turn out to be quite practical. In this article, targeted at programmers who know their art but who don’t have any theoretical computer science background, I will present one of the most pragmatic tools of computer science: Big O notation and algorithm complexity analysis. As someone who has worked both in a computer science academic setting and in building production-level software in the industry, this is the tool I have found to be one of the truly useful ones in practice, so I hope after reading this article you can apply it in your own code to make it better. After reading this post, you should be able to understand all the common terms computer scientists use such as ”big O”, ”asymptotic behavior” and ”worst-case analysis”.