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Type Systems

Luca Cardelli

The fundamental purpose of a type system is to prevent the occurrence of execution errors during the running of a program.

issue 0: what constitutes an execution error?

issue 1: How to prove its absence?


  • Execution errors: occurrence of an unexpected software fault, such as illegal instruction, illegal memory reference, divide by zero, dereferencing nil et cetera.
    • Trapped: Cause program to exit instantly
    • Untrapped: Reading garbage value from some address
  • Typed languages: variable's value are ranged.
  • Untyped languages: no types or single type for all
  • Safe languages: one does not cause untrapped errors. Untyped can also be safe with runtime check; Typed language might be a mixture of runtime check and static check.

      | Typed  | Untyped

    ------|--------|-------- Safe |ML, Java|LISP Unsafe|C |Assembly


Typing can improve security & execution speed, reduce maintenance cost, but maybe reduce development flexibility, and cost extra time for compilation

Type Equivalence

Structural versus Nominal

Language of type systems

Type systems, or the rules, can be decoupled from specific type-checking algorithm.

Judgement: $\Gamma \vdash \mathfrak J$, $\mathfrak J$ is an assertion, in which the free variables are declared in $\Gamma$.

Typing judgement: $\Gamma \vdash M : A$, $M$ has type $A$ in $\Gamma$.

Well formed: $\Gamma \vdash \diamond$

Type rule:

Type derivations: A tree of judgements.

Type inference: Find the type derivation which leads to some typing judgement.

Type construction: Constructive rule about type itself, usually in form of $\Gamma \Vdash T$

First-order Type Systems

No type param and type abstraction, but with higher order functions.

The most interesting construct introduced in the paper is Recursive Type.

First, environments are extended to include type variables $X$. So we can write type in form of $\mu X.A$.

Second, the operations fold and unfold are explicit coercions that map between a recursive type $\mu X.A$ and its unfolding $[\mu X.A/X]A$, and vice versa. They obey laws of $unfold(fold(M)) = M$ and $fold(unfold(M)) = M$.

Here gives the construction of recursive types:

Note: I found that the subscript $\mu X.A$ is just a indicator -- we shouldn't need to write it in code or infer anything about it

Let's apply it to construct a $List$ type.

Encoding of divergence and y combinator via recursive types:

Remember that "divergence" is something can't be evaluated to the normal form but instead reduced back to the original form.

Some induction:

Encoding the Untyped λ-calculus via recursive types

Second-Order Type Systems

Just the old-style parametric polymorphism.

Let's see how existential types are introduced.


We use it to implement a boolean interface:

BoolInterface = exists Bool . {
    true: Bool,
    false: Bool,
    cond: forall Y. Bool -> Y -> Y -> Y

This interface declares that there exists a type Bool (without revealing its identity) that supports the operations true, false and cond of appropriate types.

Now we define an implementation: Use $Unit + Unit$ to represent $Bool$.

boolModule : BoolInterface =
    pack BoolInterface Bool = Unit + Unit
    with {
        true  = inLeft(unit),
        false = inRight(unit)
        cond  = \\Y -> \x:Bool -> \y1:Y -> \y2:Y ->
                    case Y x of
                        x1:Unit -> y_1
                        x2:Unit -> y_2

Finally, a client could make use of this module by opening it, and thus getting access to an abstract name $Bool$ for the boolean type, and a name $boolOp$ for the record of boolean operations.

open Nat boolModule as Bool, boolOp {
    true:  Bool,
    false: Bool,
    cond:  forall Y. Bool -> Y -> Y -> Y
} in
    boolOp.cond Nat boolOp.true 1 0