Calculating the modulo of two intervals - math

Question

I want to understand how the modulus operator works when applied to two intervals. Adding, subtracting and multiplying two intervals is trivial to implement in code, but how do you do it for modulus?
I'd be happy if someone can show me the formula, sample code or a link which explains how it works.
Background info: You have two integers x_lo < x < x_hi and y_lo < y < y_hi. What is the the lower and upper bound for mod(x, y)?
Edit: I'm unsure if it is possible to come up with the minimal bounds in an efficient manner (without calculating the mod for all x or for all y). If so, then I'll accept an accurate but non-optimal answer for the bounds. Obviously, [-inf,+inf] is a correct answer then :) but I want a bound that is more limited in size.

Answer 1

It turns out, this is an interesting problem. The assumption I make is that for integer intervals, modulo is defined with respect to truncated division (round towards 0).
As a consequence, mod(-a,m) == -mod(a,m) for all a, m. Moreover, sign(mod(a,m)) == sign(a).
Definitions, before we start
Closed interval from a to b: [a,b]
Empty interval: [] := [+Inf,-Inf]
Negation: -[a,b] := [-b,-a]
Union: [a,b] u [c,d] := [min(a,c),max(b,d)]
Absolute value: |m| := max(m,-m)
Simpler Case: Fixed modulus m
It is easier to start with a fixed m. We will later generalize this to the modulo of two intervals. The definition builds up recursively. It should be no problem to implement this in your favorite programming language. Pseudocode:
def mod1([a,b], m):
// (1): empty interval
if a > b || m == 0:
return []
// (2): compute modulo with positive interval and negate
else if b < 0:
return -mod1([-b,-a], m)
// (3): split into negative and non-negative interval, compute and join
else if a < 0:
return mod1([a,-1], m) u mod1([0,b], m)
// (4): there is no k > 0 such that a < k*m <= b
else if b-a < |m| && a % m <= b % m:
return [a % m, b % m]
// (5): we can't do better than that
else
return [0,|m|-1]
Up to this point, we can't do better than that. The resulting interval in (5) might be an over-approximation, but it is the best we can get. If we were allowed to return a set of intervals, we could be more precise.
General case
The same ideas apply to the case where our modulus is an interval itself. Here we go:
def mod2([a,b], [m,n]):
// (1): empty interval
if a > b || m > n:
return []
// (2): compute modulo with positive interval and negate
else if b < 0:
return -mod2([-b,-a], [m,n])
// (3): split into negative and non-negative interval, compute, and join
else if a < 0:
return mod2([a,-1], [m,n]) u mod2([0,b], [m,n])
// (4): use the simpler function from before
else if m == n:
return mod1([a,b], m)
// (5): use only non-negative m and n
else if n <= 0:
return mod2([a,b], [-n,-m])
// (6): similar to (5), make modulus non-negative
else if m <= 0:
return mod2([a,b], [1, max(-m,n)])
// (7): compare to (4) in mod1, check b-a < |modulus|
else if b-a >= n:
return [0,n-1]
// (8): similar to (7), split interval, compute, and join
else if b-a >= m:
return [0, b-a-1] u mod2([a,b], [b-a+1,n])
// (9): modulo has no effect
else if m > b:
return [a,b]
// (10): there is some overlapping of [a,b] and [n,m]
else if n > b:
return [0,b]
// (11): either compute all possibilities and join, or be imprecise
else:
return [0,n-1] // imprecise
Have fun! :)

Answer 2

Let see mod(x, y) = mod.
In general 0 <= mod <= y. So it's always true: y_lo < mod < y_hi
But we can see some specific cases below:
- if: x_hi < y_lo then div(x, y) = 0, then x_low < mod < x_hi
- if: x_low > y_hi then div(x, y) > 0, then y_low < mod < y_hi
- if: x_low < y_low < y_hi < x_hi, then y_low < mod < y_hi
- if: x_low < y_low < x_hi < y_hi, then y_low < mod < x_hi
- if: y_low < x_low < y_hi < x_hi, then y_low < mod < y_hi
....