[crazygringo]

I guess I just don't see why it's worse than FP. I mean, you said:

> Contrast this with just leaving it as a float instead of an interval, where you would've gotten the correct answer.

But if I type into my console:

  var a = 0.1; var b = a + 0.2; b -= 0.2; b == a;

I get false. That's not correct. Whereas if "==" checked for overlap between intervals, it would be true. Which would be correct.

Heck, to use your own division example:

  (0.1 + 0.2 - 0.2) / 0.1 ==> 1.0000000000000002

That's not 1.0. So the FP you claim is so correct... just isn't at all. Again, while interval arithmetic would correctly detect overlap of intervals between that and 1.0.

Anyways, thanks for trying to explain.

[dataflow]

Turns out Wikipedia has a decent article on this; you might want to check it out: https://en.wikipedia.org/wiki/Interval_arithmetic#Dependency...

[crazygringo]

Ah, thanks for that, I finally understand what you were getting at. I see now what you mean about intervals growing larger than they actually need to in formulas that use the same variable more than once, that is an unfortunate drawback.

Now you've got me learning about how affine arithmetic can help with the dependency problem but has its own drawbacks. Thanks for pointing me in that direction!

[Stupulous]

I think you run into the opposite issue, where equality is too likely and nonequal values return as equal. There might be a sweet spot with something like

(0.1 + 0.2 - 0.2) / 0.1 ==[+/- .001] 1.0 => True