|Big O (O)
|Worst-case growth rate
|O(n2) – Quadratic time
|Best-case growth rate
|Ω(n) – Linear time
|Asymptotically tight growth rate
|Θ(n2) – Quadratic time
Key points to note:
- Big O notation represents the maximum or worst-case growth rate of an algorithm.
- Omega notation represents the minimum or best-case growth rate of an algorithm.
- Theta notation represents the tight or asymptotically tight growth rate of an algorithm.
- Big O provides an upper bound, Omega provides a lower bound, and Theta provides both upper and lower bounds.
- Big O notation is commonly used to analyze and compare algorithms.
- Omega notation is less commonly used but can be helpful in understanding best-case scenarios.
- Theta notation is used when the upper and lower bounds of an algorithm match, providing a precise estimate of its complexity.