An introduction to Algorithm Complexity and Big O/Theta/Omega notation [ECLIPSE]

SIM-2015410 · 2015-09-03T08:35:57+00:00

https://i.imgur.com/CjHLP65.png [color=#00BFFF]Introduction to Algorithm Complexity and Big-O notation Introduction: It is common for coders to jump straight into writing code, without thinking about the best way to do things. There have been many alternative algorithms written for common things, such as sorting lists, and some are much better than others. This tutorial is designed to introduce you to algorithm complexity analysis, and the big O (pronounced "big oh") notation. This will help you understand more about the best way to write algorithms to minimize time and memory usage. https://imgur.com/LBOnHI1.png What is algorithm complexity, and why should I care about it: Algorithm complexity is just a way to formally measure how fast a program or algorithm runs. We cannot just write the code and time how fast it runs in practise, because many things affect the runtime in practise (such as the processor you are using, RAM, bus speeds, etc). So algorithm complexity analysis is designe

Fʀᴀɴᴋɪᴇ
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Sep 3, 2015 04:32 AM

Astonishing change in what's normally posted. Although it is all greek to me, I have no doubt others can take from it.

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