I dug into this problem a while ago and came to the conclusion that these are all rounding problems, which you still can't escape with arbitrary precision syste

I dug into this problem a while ago and came to the conclusion that these are all rounding problems, which you still can't escape with arbitrary precision systems, because memory is finite. You're always making a tradeoff between precision and space, and you have to rely on programmers to make that tradeoff themselves. Enter the typical floating point types that do some of that work already: float/double. These let you not think (as much) about the memory your math might take up, but they still need you to think about rounding, which almost no one does. This is a long winded way of saying that if you set up your arbitrary precision arithmetic library to use 4 bytes and the same rounding mode (the default is round to nearest) as was used here, you'd reproduce the bug. You'd also reproduce the 64-bit bug moving up sizes, and the 128/256/etc bug. You gotta round. The good news, though, is that actually solves it! You can even use floats for money!