| Notation | Meaning | Represents | Example |
|---|---|---|---|
| Big O (O) | Upper bound | Worst-case growth rate | O(n2) – Quadratic time |
| Omega (Ω) | Lower bound | Best-case growth rate | Ω(n) – Linear time |
| Theta (Θ) | Tight bound | 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.