The "count how many times you subtract 3" algorithm takes theta(|input|) steps. You could argue that theta(|input|) is fine for 32-bit integers, in which case why do any programming? Just use a lookup table. However, there are much faster methods which can be used for larger inputs.
You can perform a binary search for the quotient, testing whether a candidate quotient q is too large or too small by comparing q+q+q with the input. Binary search takes theta(log |input|) time.
Binary search uses division by 2, which can be done by the shift operator instead of /, or you can implement this yourself on arrays of bits if the shift operator is too close to division.
It is tempting to use the fact that 1/3 is the sum of the geometric series 1/4 + 1/16 + 1/64 + 1/256 + ... by trying (n>>2) + (n>>4) + (n>>6) + ... however this produces the wrong answer for n=3,6,7,9, 11, 12, 13, 14, 15, 18, ... It is off by two for n=15,30,31, 39, .... In general, this is off by O(log n). For n nonnegative,
(n>>2) + (n>>4) + (n>>6) + ... = (n-wt4(n))/3
where wt4(n) is the sum of the base 4 digits of n, and the / on the right hand side is exact, not integer division. We can compute n/3 by adding wt4(n)/3 to (n>>2)+(n>>4)+(n>>6)+... We can compute the base 4 digits of n and therefore wt4(n) using only addition and the right shift.
int oneThirdOf(int n){
if (0<=n && n<3)
return 0;
if (n==3)
return 1;
return sum(n) + oneThirdOf(wt4(n));
}
// Compute (n>>2) + (n>>4) + (n>>6) + ... recursively.
int sum(int n){
if (n<4)
return 0;
return (n>>2) + sum(n>>2);
}
// Compute the sum of the digits of n base 4 recursively.
int wt4(int n){
if (n<4)
return n;
int fourth = n>>2;
int lastDigit = n-fourth-fourth-fourth-fourth;
return wt4(fourth) + lastDigit;
}
This also takes theta(log input) steps.