<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Big-O on Maceage's Blog</title><link>https://blog.maceage.com/tags/big-o/</link><description>Recent content in Big-O on Maceage's Blog</description><generator>Hugo</generator><language>en-au</language><copyright>© Graham Mace</copyright><lastBuildDate>Thu, 24 Oct 2024 00:00:00 +0000</lastBuildDate><atom:link href="https://blog.maceage.com/tags/big-o/index.xml" rel="self" type="application/rss+xml"/><item><title>Big-O Notation: A Refresher</title><link>https://blog.maceage.com/posts/2024/big-o-notation-a-refresher/</link><pubDate>Thu, 24 Oct 2024 00:00:00 +0000</pubDate><guid>https://blog.maceage.com/posts/2024/big-o-notation-a-refresher/</guid><description>&lt;p&gt;Big-O notation is a fundamental concept in computer science that helps us understand the efficiency of algorithms and data structures. It gives us a language to analyse and compare the performance of different algorithms based on input size – without getting bogged down in hardware details or constant factors.&lt;/p&gt;&#10;&lt;p&gt;Despite reading books, watching videos, and implementing algorithms, Big-O notation is one of those topics that never properly stuck in my head.&lt;/p&gt;</description></item></channel></rss>