/categories/algorithms/Recent content in Algorithms on Pocket DevHugoen-usThu, 06 Feb 2025 15:11:00 +0000/posts/big-o-complexity-ecommerce-performance/Thu, 06 Feb 2025 15:11:00 +0000/posts/big-o-complexity-ecommerce-performance/<h1 id="understanding-big-o-complexity-in-an-e-commerce-application"><strong>Understanding Big O Complexity in an E-Commerce Application</strong></h1> <p>Big O notation helps us analyze how an algorithm&rsquo;s <strong>runtime grows</strong> as the input size increases. In an <strong>e-commerce application</strong>, different tasks—like searching for products, sorting items, and checking user sessions—have <strong>different time complexities</strong>. Writing efficient code ensures that your application scales well as the number of users and products grows.</p>/posts/big-o-notation-explained-algorithm-complexity/Wed, 05 Feb 2025 13:56:00 +0000/posts/big-o-notation-explained-algorithm-complexity/<h1 id="understanding-big-o-notation-a-simple-comparison"><strong>Understanding Big O Notation: A Simple Comparison</strong></h1> <p>This post is part of my <strong>data structures and algorithms refresher series</strong>, where I revisit essential concepts that every developer should understand. One of the most important is <strong>Big O notation</strong>—a way to measure how an algorithm&rsquo;s efficiency scales as input size increases.</p>