Measuring complexity: Many algorithms have an integer n, or two integers m and n, as input - e.g., addition, multiplication, exponentiation, factorisation and primality testing. When we want to describe or analyse the `easiness' or `hardness' of the algorithm, we want to measure its `running time' as a function of the `size' of the input value(s).
If the input value is n, then it is usual to use the number of (decimal) digits, or bits (binary digits), required to store n as a measure of the size of n.
Given input n, the number of decimal digits in n is given by
[log_{10} n] +1;
where [x], pronounced `floor of x', denotes the greatest integer less than or equal to x. The number of binary digits or bits is similarly given by
[lg n] +1;
where we use the abbreviation lg x for log2 x (this notation is common, but not completely standard).