What key property does computational complexity provide for an algorithm?

The computational complexity of an algorithm is determined by a key property — the number of elementary operations the algorithm performs depending on the size of the input data. This is usually expressed as a function of the input size (for example, O(n), O(n²)).

The main property is the asymptotic behavior of the algorithm, that is, how quickly the execution time or memory consumption grows as the data volume increases.

For example, if a sorting algorithm has a complexity of O(n log n), it means that when the number of elements doubles, the execution time increases by approximately 2 * log(2) times.

Thus, computational complexity reflects the scalability of the algorithm and helps evaluate its efficiency with large data volumes.