What is O-notation (Big O notation)? Tell the main points.

O-notation (Big O notation) is a way of describing the asymptotic complexity of an algorithm, that is, how the execution time or memory consumption grows with increasing input size.

Main points:

• Describes the upper bound of the growth of a function in terms of time or memory.
• Ignores constants and less significant terms, focusing on the dominant term.
• Allows comparison of algorithm efficiency regardless of hardware.

Examples:

• O(1) — constant time, independent of input size.
• O(n) — linear time, grows proportionally to input size.
• O(n²) — quadratic time, for example, nested loops over input.

Thus, Big O helps evaluate the scalability of algorithms and choose the most suitable one for a task.