I was given the following problem in an interview:
Given a staircase with N steps, you can go up with 1 or 2 steps each time. Output all possible way
Here is a simple solution to this question in very simple CSharp (I believe you can port this with almost no change to Java/C++). I have added a little bit more of complexity to it (adding the possibility that you can also walk 3 steps). You can even generalize this code to "from 1 to k-steps" if desired with a while loop in the addition of steps (last if statement).
I have used a combination of both dynamic programming and recursion. The use of dynamic programming avoid the recalculation of each previous step; reducing the space and time complexity related to the call stack. It however adds some space complexity (O(maxSteps)) which I think is negligible compare to the gain.
///
/// Given a staircase with N steps, you can go up with 1 or 2 or 3 steps each time.
/// Output all possible way you go from bottom to top
///
public class NStepsHop
{
const int maxSteps = 500; // this is arbitrary
static long[] HistorySumSteps = new long[maxSteps];
public static long CountWays(int n)
{
if (n >= 0 && HistorySumSteps[n] != 0)
{
return HistorySumSteps[n];
}
long currentSteps = 0;
if (n < 0)
{
return 0;
}
else if (n == 0)
{
currentSteps = 1;
}
else
{
currentSteps = CountWays(n - 1) +
CountWays(n - 2) +
CountWays(n - 3);
}
HistorySumSteps[n] = currentSteps;
return currentSteps;
}
}
You can call it in the following manner
long result;
result = NStepsHop.CountWays(0); // result = 1
result = NStepsHop.CountWays(1); // result = 1
result = NStepsHop.CountWays(5); // result = 13
result = NStepsHop.CountWays(10); // result = 274
result = NStepsHop.CountWays(25); // result = 2555757
You can argue that the initial case when n = 0, it could 0, instead of 1. I decided to go for 1, however modifying this assumption is trivial.