www.mikescher.com/www/statics/euler/Euler_Problem-076_explanation.md

The big trick is - similar to many other problems - caching.

This problem remembered me a little bit of problem-15. We use a 100x100 grid to remember pre-calculated sums.

So in cell [3, 6] is the amount of sums which result in 6, start with 3 and have all summands in descending order:

3 + 3
3 + 2 + 1
3 + 1 + 1

You see cache[3,6] = 3.

Now to find a new value (for example [4, 7]) we just have to look at the our cache:

7 = 4 + x
sum(x) = 7-4 = 3

// first_digit_of_x <= first_digit, because of the descending order
sum(x) = sum([n, 3]); n = [1..3]
sum(x) = [3, 3] + [2, 3] + [1, 3] 

You see it's important not only to remember the amount but also the first (= highest) summand, so we can guarantee the oder of the sums (an this way that we don't count any sums multiple times).

Note: cache[a, a] is always 1. But the problem rules dictate that when we calculate the final result we must ignore this (100 = 100 is not a valid solution)

Oh and this algorithm improves the native approach (enumerating all solutions) from O(wtf) to O(n^2). I'm not sure if I would be still alive when my first algorithm finishes :)

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Edit:

I did a little optimization:

The value of cell [d, s] is now the sum of all previous cells from [0, s] to [d, s].

This way we don't have to iterate through all the cells from 0 to d every time. We can just look at the biggest cell which contains the sum of all previous.