Simulating Higher-Kinded Types, Part 1

April 16, 2017

Java is the de facto choice for my daily work. As a result, I often miss useful features from other languages. Introducing non-idiomatic code in a team-based context can do more harm than good, but it doesn’t stop me from wondering: what would higher-kinded types look like in a language that does not have built-in support for them? In these posts, I take on this quixotic task.

NOTE: This is an ongoing research topic, so I have no definite solutions. For brevity’s sake, most examples will be in Haskell.


Before we can tackle the problem of implementing higher-kinded types, let’s take a step back and talk about what a higher-kinded type is. Just as a type classifies a collection of values, a kind classifies a collection of types. It is the same concept, but “one level higher” in hierarchy of abstraction.

Since most languages have relatively simple type systems, the concept of kind may be new. In these languages, all types have the same kind, denoted ★ (or * in ASCII). Higher-kinded types extend this system by introducing a new way to form kinds: given any two kinds k and k', we can form the function kind k -> k'. We can form kinds such as ★, ★ →★, (★→★)→(★→★), et al.

This is an analogue of the function type, which allows us to form a new type a -> b from any two types a and b. The only difference is that instead of dealing with types of values, we are now dealing with kinds of types.

A common type in Haskell is Identity a, which is just a wrapper over the type a. Usually it is defined like so:

newtype Identity a = Identity { runIdentity :: a }

We can construct a value such as Identity 10, which has a type of Identity Int. Since this is a value, it has kind ★. However, the type constructor Identity can be seen as a function over types, taking in an input type a and producing an output type Identity a. Thus, the type constructor Identity has kind ★ →★.

Identity can be defined in many languages. For instance, it can be defined in Java:

public final class Identity<A> {

    private final A value;

    public Identity(A value) {
        this.value = value;

    public A value() {
        return this.value;

Given this, it may be confusing when someone says that a language does not support higher-kinded types. Haven’t we just defined one here? Usually, they mean that the language does not support abstraction over these types, i.e. we cannot be polymorphic over any higher-kinded type. A more correct description of the missing feature is higher-kinded polymorphism. If we had support for higher-kinded polymorphism, we would be able to define an interface for Functor in Java:

public interface Functor<F> {
    <A, B> F<B> fmap(Function<A, B> f, F<A> x);

The issue here is that F must be of kind ★ →★ in order for F<A> and F<B> to be well-typed. Without the ability to instantiate F to a particular parameter, we cannot implement this.

Approach 1: Type families

This topic is heavily inspired by Lightweight Higher-Kinded Polymorphism, which describes an implementation in OCaml. However, most languages do not have support for ML functors, which limits the applicability of these results.

The core idea of this paper is to convert a type F<A> into App<F, A> by giving F the kind of ★. Since all polymorphic types now have kind ★, we no longer run into limitations of the host language. In this approach, we also apply a type family to map App<F, A> back to the the underlying type.

What is a type family? The previous link describes it in much better detail than I could hope to, but for the sake of self-containment we will go over it briefly here.

Previously, we mentioned that a type constructor could be interpreted as a function over types. However, these functions are very restricted in what we allow them to map to, e.g. Identity can only produce Identity as. A type family allows us to relax this restriction and map input types to arbitrary types. For example, this type family will map Int to String, but Float is mapped to Maybe String:

type family F a where
    F Int   = String
    F Float = Maybe String

NOTE: The TypeFamilies extension must be enabled in GHC for this to work.

This is a closed type family, which means that we have exhaustively defined all of the input types F will map. In an open type family we leave the definition open for extension by others. To allow arbitrary implementations of functors we will use an open type family, initially defining a mapping for list types:

data List

type family Apply f a
type instance Apply List a = [a]

Ideally we would continue in our quest, defining Functor and providing an implementation:

class Functor f where
    fmap :: (a -> b) -> Apply f a -> Apply f b

instance Functor List where
    fmap = map

However, this fails because Apply does not represent an injective function over types. Without this knowledge, the type checker rejects our definition of Functor. To solve this, we can introduce a new type that wraps Apply f a:

newtype App f a = Inject { project :: Apply f a }

Since all type constructors are injective, the type checker is suitably convinced and we can complete our implementation:

class Functor f where
    fmap :: (a -> b) -> App f a -> App f b

instance Functor List where
    fmap f = Inject . map f . project

This approach is straightforward enough to warrant an automated solution. One implementation is the higher library in OCaml.

A solution in Java?

Let’s take the Haskell implementation and naïvely attempt to transform it to Java. In A Comparative Study of Language Support for Generic Programming an approach for associated types in Java is laid out. This allows us to recover behavior similar to type families:

public interface Apply<F, A> {

public class App<F, A, T extends Apply<F, A>> {

    private final T value;

    public App(T value) {
        this.value = value;

public interface Functor<F> {
    <A, T extends Apply<F, A>, B, U extends Apply<F, B>>
        App<F, B, U> fmap(Function<A, B> f, App<F, A, T> x);

Everything looks good so far; we have managed to define a Functor interface. Since Java does not have full support for associated types, we introduce the type T (resp. U) as a parameter, using F and A (resp. B) to constrain what is allowed.

However, the problem surfaces when you attempt to implement Functor. In its definition, we allow T and U to be any subtypes of Apply<F, A> and Apply<F, B>, respectively. But in our implementation, we wish for them to be a specific concrete subtype. Without this, we will not be able to extract a List<B> after performing fmap, since we do not have enough information to conclude that U = List<B>.

We’ve hit our first show stopper. In the next post, I will describe another approach based on GADTs which runs into its own set of challenges during implementation.