Suppose we have a state machine Q, that implements a common first in first out queue. The input alphabet of Q consists of “Deq” and “Enq x” where “x” ranges over a set of values, say, V. Let’s fix the max length of Q at some constant k. As usual, given a sequence of events “w”, write Q(w) for the output of Q in the state reached by following “w” from the initial state. For the empty string NULL, define Q(NULL)=(). If a=Deq then define Q(wa) depending on Q(w) – if Q(w)=() or Q(w)=(x) then Q(wa)=(). If Q(w)=(x1 .. xn) then define Q(wa)=( x1 …). If a=Enq x then if Q(w)=() define Q(wa)=(x), if Q(w)=(x1 .. xn) where n<k define Q(wa)=(x,x1 … xn) and otherwise leave Q(wa)=Q(w). The number of states of Q is a function of the number of elements of V and the constant k and grows rapidly as they grow – sum[i=1, k](|V|^i ).
If you visualize the graph of Q, you can see it contains non-trivial loops – which means that the monoid associated with Q contains groups. The advantage of decomposing Q into a product of smaller machines is that this might guide a smarter implementation. Well, I’m kind of cheating here, because programmers have found a variety of smart implementations that do strip out the group structure.
The easy decomposition produces two counters, and a collection of k storage elements that are loop free state machines: an input “store x” moves the machine to a “x” state. They do contain loops but only trivial ones. The counters are group machines. We number the storage cells 0 to k-1. We can have one mod k counter that “points” to the tail of the queue and one that counts the size of the queue. On an enq operation the enqueued value is stored in the storage element identified by subtracting the size from the tail mod k, and the size is increment mod k+1. An enq operation when the size=k is ignored and has no effect. On a deq, the size is decremented and the tail is incremented by one mod k+1. What we’ve done is construct a system in which the state machine monoids are two cyclic groups and k-aperiodic monoids. If we then switch to more complicated data structures, like ordered lists, it’s not that hard to see how a permutation group might be used to manipulate pointers to a pile of storage locations. For example (n1,n2,n3,n4,blank, n5,n6) might be an ordered list with n5 and n6 being free. An enqueue would generate some shuffle to say, (n1,n2,n5,n3,n4,blank,n6) and then a dequeue would produce (n2,n5,n3,n4,blank, n6,n1).
A nice property of groups is that “undo” always works. So if the data in the storage elements can be marked in some way, a deq or enq can be undone by subtracting mod k or permuting backwards.