Time ComplexityLesson 44Free preview

Introduction

This lesson is part of DSA · All levels

Summary

Time complexity analysis measures how fast the algorithm's execution time grows with n input sizes, without being dependent on a particular machine. The Big O notation states the upper limit, Omega states the lower limit, and Theta states the strict limit. The most commonly used are O(1), O(log n), O(n), O(n log n), and O(n^2).

Key points

Big O states the limit on the growth of execution time to input
Common notation: O(1), O(log n), O(n), O(n log n), O(n^2), O(2^n)
Space complexity is also analyzed.
The constants and lower triangle factors are ignored in the Big O

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