Can you explain what is meant by the time complexity assessment of an algorithm?

The assessment of an algorithm's time complexity shows how the execution time changes depending on the size of the input data. It is usually expressed as a function, for example, O(n), O(n²), where n is the size of the input.

This helps to understand how the algorithm scales and how efficient it is with large volumes of data. For example:

• O(1) — execution time does not depend on the size of the data.
• O(n) — time grows linearly with the size of the data.
• O(n²) — time grows quadratically, which can be impractical for large n.

Example in Python:

# Searching for an element in a list — O(n)
def find_element(lst, target):
    for item in lst:
        if item == target:
            return True
    return False

Here, the execution time depends on the length of the list.