Standard ML does not have explicit support for object-oriented programming. Here are some papers that show how to express certain object-oriented concepts in SML.
The question of OO programming in SML comes up every now and then. The following discusses a simple object-oriented (OO) programming technique in Standard ML. The reader is assumed to be able to read Java and SML code.
Motivation
SML doesn’t provide subtyping, but it does provide parametric polymorphism, which can be used to encode some forms of subtyping. Most articles on OO programming in SML concentrate on such encoding techniques. While those techniques are interesting — and it is recommended to read such articles — and sometimes useful, it seems that basically all OO gurus agree that (deep) subtyping (or inheritance) hierarchies aren’t as practical as they were thought to be in the early OO days. "Good", flexible, "OO" designs tend to have a flat structure
Interface
^
|
- - -+-------+-------+- - -
| | |
ImplA ImplB ImplC
and deep inheritance hierarchies
ClassA ^ | ClassB ^ | ClassC ^ |
tend to be signs of design mistakes. There are good underlying reasons for this, but a thorough discussion is not in the scope of this article. However, the point is that perhaps the encoding of subtyping is not as important as one might believe. In the following we ignore subtyping and rather concentrate on a very simple and basic dynamic dispatch technique.
Dynamic Dispatch Using a Recursive Record of Functions
Quite simply, the basic idea is to implement a "virtual function table" using a record that is wrapped inside a (possibly recursive) datatype. Let’s first take a look at a simple concrete example.
Consider the following Java interface:
public interface Counter {
public void inc();
public int get();
}
We can translate the Counter interface to SML as follows:
datatype counter = Counter of {inc : unit -> unit, get : unit -> int}Each value of type counter can be thought of as an object that
responds to two messages inc and get. To actually send messages
to a counter, it is useful to define auxiliary functions
local
fun mk m (Counter t) = m t ()
in
val cGet = mk#get
val cInc = mk#inc
endthat basically extract the "function table" t from a counter object
and then select the specified method m from the table.
Let’s then implement a simple function that increments a counter until a given maximum is reached:
fun incUpto counter max = while cGet counter < max do cInc counterYou can easily verify that the above code compiles even without any concrete implementation of a counter, thus it is clear that it doesn’t depend on a particular counter implementation.
Let’s then implement a couple of counters. First consider the
following Java class implementing the Counter interface given earlier.
public class BasicCounter implements Counter {
private int cnt;
public BasicCounter(int initialCnt) { this.cnt = initialCnt; }
public void inc() { this.cnt += 1; }
public int get() { return this.cnt; }
}
We can translate the above to SML as follows:
fun newBasicCounter initialCnt = let
val cnt = ref initialCnt
in
Counter {inc = fn () => cnt := !cnt + 1,
get = fn () => !cnt}
endThe SML function newBasicCounter can be described as a constructor
function for counter objects of the BasicCounter "class". We can
also have other counter implementations. Here is the constructor for
a counter decorator that logs messages:
fun newLoggedCounter counter =
Counter {inc = fn () => (print "inc\n" ; cInc counter),
get = fn () => (print "get\n" ; cGet counter)}The incUpto function works just as well with objects of either
class:
val aCounter = newBasicCounter 0
val () = incUpto aCounter 5
val () = print (Int.toString (cGet aCounter) ^"\n")
val aCounter = newLoggedCounter (newBasicCounter 0)
val () = incUpto aCounter 5
val () = print (Int.toString (cGet aCounter) ^"\n")In general, a dynamic dispatch interface is represented as a record type wrapped inside a datatype. Each field of the record corresponds to a public method or field of the object:
datatype interface =
Interface of {method : t1 -> t2,
immutableField : t,
mutableField : t ref}The reason for wrapping the record inside a datatype is that records,
in SML, can not be recursive. However, SML datatypes can be
recursive. A record wrapped in a datatype can contain fields that
contain the datatype. For example, an interface such as Cloneable
datatype cloneable = Cloneable of {clone : unit -> cloneable}can be represented using recursive datatypes.
Like in OO languages, interfaces are abstract and can not be instantiated to produce objects. To be able to instantiate objects, the constructors of a concrete class are needed. In SML, we can implement constructors as simple functions from arbitrary arguments to values of the interface type. Such a constructor function can encapsulate arbitrary private state and functions using lexical closure. It is also easy to share implementations of methods between two or more constructors.
While the Counter example is rather trivial, it should not be
difficult to see that this technique quite simply doesn’t require a huge
amount of extra verbiage and is more than usable in practice.
SML Modules and Dynamic Dispatch
One might wonder about how SML modules and the dynamic dispatch technique work together. Let’s investigate! Let’s use a simple dispenser framework as a concrete example. (Note that this isn’t intended to be an introduction to the SML module system.)
Programming with SML Modules
Using SML signatures we can specify abstract data types (ADTs) such as dispensers. Here is a signature for an "abstract" functional (as opposed to imperative) dispenser:
signature ABSTRACT_DISPENSER = sig
type 'a t
val isEmpty : 'a t -> bool
val push : 'a * 'a t -> 'a t
val pop : 'a t -> ('a * 'a t) option
endThe term "abstract" in the name of the signature refers to the fact that the signature gives no way to instantiate a dispenser. It has nothing to do with the concept of abstract data types.
Using SML functors we can write "generic" algorithms that manipulate dispensers of an unknown type. Here are a couple of very simple algorithms:
functor DispenserAlgs (D : ABSTRACT_DISPENSER) = struct
open D
fun pushAll (xs, d) = foldl push d xs
fun popAll d = let
fun lp (xs, NONE) = rev xs
| lp (xs, SOME (x, d)) = lp (x::xs, pop d)
in
lp ([], pop d)
end
fun cp (from, to) = pushAll (popAll from, to)
endAs one can easily verify, the above compiles even without any concrete dispenser structure. Functors essentially provide a form a static dispatch that one can use to break compile-time dependencies.
We can also give a signature for a concrete dispenser
signature DISPENSER = sig
include ABSTRACT_DISPENSER
val empty : 'a t
endand write any number of concrete structures implementing the signature. For example, we could implement stacks
structure Stack :> DISPENSER = struct
type 'a t = 'a list
val empty = []
val isEmpty = null
val push = op ::
val pop = List.getItem
endand queues
structure Queue :> DISPENSER = struct
datatype 'a t = T of 'a list * 'a list
val empty = T ([], [])
val isEmpty = fn T ([], _) => true | _ => false
val normalize = fn ([], ys) => (rev ys, []) | q => q
fun push (y, T (xs, ys)) = T (normalize (xs, y::ys))
val pop = fn (T (x::xs, ys)) => SOME (x, T (normalize (xs, ys))) | _ => NONE
endOne can now write code that uses either the Stack or the Queue
dispenser. One can also instantiate the previously defined functor to
create functions for manipulating dispensers of a type:
structure S = DispenserAlgs (Stack)
val [4,3,2,1] = S.popAll (S.pushAll ([1,2,3,4], Stack.empty))
structure Q = DispenserAlgs (Queue)
val [1,2,3,4] = Q.popAll (Q.pushAll ([1,2,3,4], Queue.empty))There is no dynamic dispatch involved at the module level in SML. An attempt to do dynamic dispatch
val q = Q.push (1, Stack.empty)will give a type error.
Combining SML Modules and Dynamic Dispatch
Let’s then combine SML modules and the dynamic dispatch technique introduced in this article. First we define an interface for dispensers:
structure Dispenser = struct
datatype 'a t =
I of {isEmpty : unit -> bool,
push : 'a -> 'a t,
pop : unit -> ('a * 'a t) option}
fun O m (I t) = m t
fun isEmpty t = O#isEmpty t ()
fun push (v, t) = O#push t v
fun pop t = O#pop t ()
endThe Dispenser module, which we can think of as an interface for
dispensers, implements the ABSTRACT_DISPENSER signature using
the dynamic dispatch technique, but we leave the signature ascription
until later.
Then we define a DispenserClass functor that makes a "class" out of
a given dispenser module:
functor DispenserClass (D : DISPENSER) : DISPENSER = struct
open Dispenser
fun make d =
I {isEmpty = fn () => D.isEmpty d,
push = fn x => make (D.push (x, d)),
pop = fn () =>
case D.pop d of
NONE => NONE
| SOME (x, d) => SOME (x, make d)}
val empty =
I {isEmpty = fn () => true,
push = fn x => make (D.push (x, D.empty)),
pop = fn () => NONE}
endFinally we seal the Dispenser module:
structure Dispenser : ABSTRACT_DISPENSER = DispenserThis isn’t necessary for type safety, because the unsealed Dispenser
module does not allow one to break encapsulation, but makes sure that
only the DispenserClass functor can create dispenser classes
(because the constructor Dispenser.I is no longer accessible).
Using the DispenserClass functor we can turn any concrete dispenser
module into a dispenser class:
structure StackClass = DispenserClass (Stack)
structure QueueClass = DispenserClass (Queue)Each dispenser class implements the same dynamic dispatch interface
and the ABSTRACT_DISPENSER -signature.
Because the dynamic dispatch Dispenser module implements the
ABSTRACT_DISPENSER-signature, we can use it to instantiate the
DispenserAlgs-functor:
structure D = DispenserAlgs (Dispenser)The resulting D module, like the Dispenser module, works with
any dispenser class and uses dynamic dispatch:
val [4, 3, 2, 1] = D.popAll (D.pushAll ([1, 2, 3, 4], StackClass.empty))
val [1, 2, 3, 4] = D.popAll (D.pushAll ([1, 2, 3, 4], QueueClass.empty))