It can be used to enumerate all subsets of size N from a set of size M. Start with 1 << N - 1, and then repeatedly call this function until the value is larger than 1 << M. Every subset of size N will be visited, in order.
Years ago, I had a similar need and I consulted TAOCP to find the “standard” algorithm to do so, which is done by a binomial tree. The tree T is defined recursively as T(0) = nil and T(n) = [Cons(0, T(0)), Cons(1, T(1)), ..., Cons(n-1, T(n-1))]. There's no need to construct the tree explicitly; it's just a conceptual formalism that helps formulate an algorithm to traverse the tree.
The text did mention using bitwise operations to do so; in fact it says it presents a “remarkable sequence of seven bitwise operations that will convert any binary number to the lexicographically next t-combination” but I haven't been able to find those seven operations.
Take a 64 bit number and treat it like a bit field where each bit represents inclusion/exclusion of an element in a set S of size 64. Thus every number with M 1s represents a (distinct) M-sized subset of S
Every bit in a bitfield represents a "thing". The bitfield represents a collection of distinct things. If bit "i" is 1, then the corresponding thing "i" is in the collection.
This can be used generate all bit sequences over a particular range that have the same Hamming weight. I have needed that before when testing error-correction code decoders to make sure they properly correct all of the possible error patterns that they should be able to.
Chess engine stuff, at the very least. With an integer mask representing an 8x8 board and 1s representing a single type of piece, you can find all subsets of pawn positions etc.
I've used this to enumerate grids with a certain number of open and closed cells (0 and 1 bits). It is simply the next permutation of a bit string. C++ offers this in its standard lib, but that version is slower by factor 1000 or so.
I've also tested this with arbitrary bit-width numbers (LLVM can do that) and it worked fine. I've not checked if the code is the exact same tho.
I'm going out on a limb and say "bloom filters" so it has applications in fast filtering, seen-count, DB stuff like parallelism, discrete-different buckets, partially ordered sets being applied in a stream of events...
