Aryan Chauhan

Asymptotic Notations in Data Structures | Big-O, Omega, Theta Explained Asymptotic Notations in Data Structures and Algorithms Asymptotic notations help us analyze the efficiency of algorithms by describing how the runtime grows as input size increases. These notations are fundamental in data structures and algorithm analysis , and include Big-O, Omega, Theta, little-o, and little-omega . 📊 What is Asymptotic Analysis? Asymptotic analysis refers to evaluating the growth rate of an algorithm in terms of input size n . It removes constant factors and focuses on how functions behave for very large inputs. We often write this using notations like: O(f(n)) — Worst-case scenario Ω(f(n)) — Best-case scenario Θ(f(n)) — Average (tight bound) Instead of focusing on actual execution time (which can vary with hardware, compiler, OS, etc.), asymptotic analysis lets us focus on algorithm performance regardless of system-de...