Apr 5 · 34 min read · TLDR: Big O notation describes how an algorithm's resource usage grows as input size grows — not how fast it runs on your laptop. Learn to identify the 7 complexity classes (O(1) through O(n!)), deriv
Join discussionSep 11, 2025 · 3 min read · When you write code, there are a multitude of ways to solve problems and make your ideas come to life. But there’s one thing to note: We are programmers! We are LAZY! This is why whenever we write code, we should always double-check that it’s the sim...
Join discussionAug 26, 2025 · 5 min read · Entender la base de Logaritmo Antes de explicar el Big O notation es necesario explicar qué es un logaritmo. Un logaritmo es preguntar cuántas multiplicaciones del mismo número X son necesarias para llegar a un número Y. EJ: \(2^x= 8\)¿Cuántos 2 ten...
Join discussion
Aug 26, 2025 · 5 min read · Understanding the Base of a Logarithm Before explaining Big O notation, it's necessary to explain what a logarithm is. A logarithm asks how many multiplications of the same number X are needed to reach a number Y. Ex: \(2^x = 8\) How many 2s do I ne...
Join discussion
Aug 5, 2025 · 2 min read · 알고리즘의 성능을 나타내는 척도로는 일반적으로 **복잡도(Complexity)**를 사용합니다. 복잡도는 크게 시간 복잡도와 공간 복잡도로 나뉘며, 각각 알고리즘이 실행되는 데 걸리는 시간과 필요한 메모리 공간의 양을 의미합니다. 동일한 기능을 수행하는 알고리즘이라면, 복잡도가 낮은 쪽이 더 효율적인 것으로 간주됩니다. 다만 시간과 공간은 종종 트레이드오프 관계에 있기 때문에, 코딩 테스트와 같은 환경에서는 메모리를 좀 더 사용하는 대신 실행 ...
Join discussionJul 22, 2025 · 7 min read · There are often many ways to solve a problem. These different approaches are called algorithms. An algorithm is just a clear, well-defined set of step-by-step instructions that a computer follows to perform a computation. For example, if you want to ...
Join discussion
Mar 30, 2025 · 3 min read · If you're a software engineer, you've probably heard about Big O notation—at least while learning about algorithms or preparing for job interviews at top tech companies (FAANG and similar). But without a formal Computer Science degree or a math backg...
Join discussion
Jul 14, 2024 · 3 min read · Big O notation is a mathematical concept used to describe an algorithm's performance or complexity. It shows how the runtime or space needs of an algorithm increase as the input size grow. If the pace of an algorithm is not known, it will be difficul...
Join discussion
Jun 4, 2024 · 1 min read · To become a better engineer, you shouldn't underestimate the power of big(O) Big(O) is really helpful to write efficient and scalable code. It is a method to calculate how fast an algorithm will run when we increase input size. The speed of an algori...
Join discussion
