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In theoretical analysis of algorithms it is common to estimate their complexity in the asymptotic sense, i. e., to estimate the complexity function for arbitrarily large input.
Big O notation, omega notation and theta notation are used to this end.
For instance, binary search is said to run in a number of steps proportional to the logarithm of the length of the list being searched, or in O ( log ( n )), colloquially " in logarithmic time ".
Usually asymptotic estimates are used because different implementations of the same algorithm may differ in efficiency.
However the efficiencies of any two " reasonable " implementations of a given algorithm are related by a constant multiplicative factor called a hidden constant.

2.128 seconds.