Transfer language reference

Author: Björn Bringert <bringert@cs.chalmers.se>
Last update: Wed Dec 7 12:50:46 2005



This document describes the features of the Transfer language. See the Transfer tutorial for an example of a Transfer program, and how to compile and use Transfer programs.

Transfer is a dependently typed functional programming language with eager evaluation.

Current implementation status

Not all features of the Transfer language have been implemented yet. The most important missing piece is the type checker. This means that there are almost no checks done on Transfer programs before they are run. It also means that the values of metavariables are not inferred. Thus metavariables cannot be used where their values matter. For example, dictionaries for overlaoded functions must be given explicitly, not as metavariables.

Layout syntax

Transfer uses layout syntax, where the indentation of a piece of code determines which syntactic block it belongs to.

To give the block structure of a piece of code without using layout syntax, you can enclose the block in curly braces ({ }) and separate the parts of the blocks with semicolons (;).

For example, this case expression:

  case x of
         p1 -> e1
         p2 -> e2

is equivalent to this one:

  case x of {
         p1 -> e1 ;
         p2 -> e2 
  }

Here the layout is insignificant, as the structure is given with braces and semicolons. Thus the above is equivalent to:

  case x of { p1 -> e1 ; p2 -> e2 }

Imports

A Transfer module start with some imports. Most modules will have to import the prelude, which contains definitons used by most programs:

  import prelude

Function declarations

Functions need to be given a type and a definition. The type is given by a typing judgement on the form:

  f : T

where f is the function's name, and T its type. See Function types for a how the types of functions are written.

The definition of the function is the given as a sequence of pattern equations. The first equation whose patterns match the function arguments is used when the function is called. Pattern equations are on the form:

  f p11 ... p1m = exp
  ...
  f pn1 ... pnm = exp

where p11 to pnm are patterns, see Patterns.

Data type declarations

Transfer supports Generalized Algebraic Datatypes. They are declared thusly:

  data D : T where 
       c1 : Tc1
       ...
       cn : Tcn

Here D is the name of the data type, T is the type of the type constructor, c1 to cn are the data constructor names, and Tc1 to Tcn are their types.

Lambda expressions

Lambda expressions are terms which express functions, without giving names to them. For example:

  \x -> x + 1

is the function which takes an argument, and returns the value of the argument + 1.

Local definitions

To give local definition to some names, use:

  let x1 : T1 = exp1
      ...
      xn : Tn = expn
   in exp

Types

Function types

Functions types are of the form:

  A -> B

This is the type of functions which take an argument of type A and returns a result of type B.

To write functions which take more than one argument, we use currying. A function which takes n arguments is a function which takes 1 argument and returns a function which takes n-1 arguments. Thus,

  A -> (B -> C)

or, equivalently, since -> associates to the right:

  A -> B -> C

is the type of functions which take 2 arguments, the first of type A and the second of type B. This arrangement lets us do partial application of function to fewer arguments than the function is declared to take, returning a new function which takes the rest of the arguments.

Dependent function types

In a function type, the value of an argument can be used later in the type. Such dependent function types are written:

  (x1 : T1) -> ... -> (xn : Tn) -> T

Here, x1 can be used in T2 to Tn, x1 can be used in T2 to Tn.

Basic types

Integers

The type of integers is called Integer. standard decmial integer literals are used to represent values of this type.

Floating-point numbers

The only currently supported floating-point type is Double, which supports IEEE-754 double-precision floating-point numbers. Double literals are written in decimal notation, e.g. 123.456.

Strings

There is a primitive String type. This might be replaced by a list of characters representation in the future. String literals are written with double quotes, e.g. "this is a string".

Booleans

Booleans are not a built-in type, though some features of the Transfer language depend on them.

  data Bool : Type where
          True : Bool
          False : Bool

In addition to normal pattern matching on booleans, you can use the built-in if-expression:

  if exp1 then exp2 else exp3

where exp1 must be an expression of type Bool.

Records

Record types

Record types are created by using a sig expression:

  sig { l1 : T1; ... ; ln : Tn }

Here, l1 to ln are the field labels and T1 to Tn are field types.

Record values

Record values are constructed using rec expressions:

  rec { l1 = exp1; ... ; ln = expn }

Record projection

Fields are selection from records using the . operator. This expression selects the field l from the record value r:

  r.l

Records and layout syntax

The curly braces and semicolons are simply explicit layout syntax, so the record type and record expression above can also be written as:

  sig l1 : T1
      ...
      ln : Tn

  rec l1 = exp1
      ...
      ln = expn

Record subtyping

A record of some type R1 can be used as a record of any type R2 such that for every field p1 : T1 in R2, p1 : T1 is also a field of T1.

Tuples

Tuples on the form:

  (exp1, ..., expn)

are syntactic sugar for records with fields p1 to pn. The expression above is equivalent to:

  rec { p1 = exp1; ... ; pn = expn }

Lists

The List type is not built-in, though there is some special syntax for it. The list type is declared as:

  data List : Type -> Type where 
  	Nil : (A:Type) -> List A
          Cons : (A:Type) -> A -> List A -> List A

The empty lists can be written as []. There is a operator :: which can be used instead of Cons. These are just syntactic sugar for expressions using Nil and Cons, with the type arguments hidden.

Case expressions

Pattern matching is done in pattern equations and by using the case construct:

  case exp of
       p1 | guard1 -> rhs1
       ...
       pn | guardn -> rhsn

where p1 to pn are patterns, see Patterns. guard1 to guardn are boolean expressions. Case arms can also be written without guards, such as:

       pk -> rhsk

This is the same as writing:

       pk | True -> rhsk

Patterns

Constructor patterns

Constructor patterns are written as:

  C p1 ... pn

where C is a data constructor which takes n arguments. If the value to be matched is the constructor C applied to arguments v1 to vn, then v1 to vn will be matched against p1 to pn.

Variable patterns

A variable pattern is a single identifier:

  x

A variable pattern matches any value, and binds the variable name to the value. A variable may not occur more than once in a pattern.

Wildcard patterns

Wildcard patterns are written as with a single underscore:

  _

Wildcard patterns match all values and bind no variables.

Record patterns

Record patterns match record values:

  rec { l1 = p1; ... ; ln = pn }

A record value matches a record pattern, if the record value has all the fields l1 to ln, and their values match p1 to pn.

Note that a record value may have more fields than the record pattern and they will still match.

Disjunctive patterns

It is possible to write a pattern on the form:

  p1 || ... || pn

A value will match this pattern if it matches any of the patterns p1 to pn. FIXME: talk about how this is expanded

List patterns

When pattern matching in lists, there are two special constructs. A whole list can be matched be a list of patterns:

  [p1, ... , pn]

This pattern will match lists of length n, such that each element in the list matches the corresponding pattern. The empty list pattern:

  []

is a special case of this. It matches the empty list, oddly enough.

Non-empty lists can also be matched with ::-patterns:

  p1::p2

This pattern matches a non-empty lists such that the first element of the list matches p1 and the rest of the list matches p2.

Tuple patterns

Tuples patterns on the form:

  (p1, ... , pn)

are syntactic sugar for record patterns, in the same way as tuple expressions.

String literal patterns

String literals can be used as patterns.

Integer literal patterns

Integer literals can be used as patterns.

Metavariables

Metavariable are written as questions marks:

  ?

A metavariable is a way to the the type checker that: "you should be able to figure out what this should be, I can't be bothered to tell you".

Metavariables can be used to avoid having to give type and dictionary arguments explicitly.

Overloaded functions

In Transfer, functions can be overloaded by having them take a record of functions as an argument. For example, the functions for equality and inequality in the Transfer prelude module are defined as:

  Eq : Type -> Type
  Eq A = sig eq : A -> A -> Bool
  
  eq : (A : Type) -> Eq A -> A -> A -> Bool
  eq _ d = d.eq
  
  neq : (A : Type) -> Eq A -> A -> A -> Bool
  neq A d x y = not (eq A d x y)

We call Eq a type class, though it's actually just a record type used to pass function implementations to overloaded functions. We call a value of type Eq A an Eq dictionary for the type A. The dictionary is used to look up the version of the function for the particular type we want to use the function on. Thus, in order to use the eq function on two integers, we need a dictionary of type Eq Integer:

  eq_Integer : Eq Integer
  eq_Integer = rec eq = prim_eq_Integer

where prim_eq_Integer is the built-in equality function for integers. To check whether two numbers x and y are equal, we can then call the overloaded eq function with the dictionary:

  eq Integer eq_Integer x y

Giving the type at which to use the overloaded function, and the appropriate dictionary is cumbersome. Metavariables come to the rescue:

  eq ? ? x y

The type checker can in most cases figure out the values of the type and dictionary arguments. NOTE: this is not implemented yet.

Type class extension

By using record subtyping, see Record subtyping, we can create type classes which extend other type classes. A dictionary for the new type class can also be used as a dictionary for old type class.

For example, we can extend the Eq type class above to Ord, a type class for orderings:

  Ord : Type -> Type
  Ord A = sig eq : A -> A -> Bool
              compare : A -> A -> Ordering

To extend an existing class, we keep the fields of the class we want to extend, and add any new fields that we want. Because of record subtyping, for any type A, a value of type Ord A is also a value of type Eq A.

Extending multiple classes

A type class can also extend several classes, by simply having all the fields from all the classes we want to extend. The Num class described below is an example of this.

Standard prelude

The standard prelude, see prelude.tra contains definitions of a number of standard types, functions and type classes.

Operators

Unary operators

Operator Precedence Translation
- 10 -x => negate ? ? x

Binary operators

Operator Precedence Associativity Translation of x op y
>>= 3 left bind ? ? x y
>> 3 left bind ? ? x (\_ -> y)
|| 4 right if x then True else y
&& 5 right if x then y else False
== 6 none eq ? ? x y
/= 6 none neq ? ? x y
< 6 none lt ? ? x y
<= 6 none le ? ? x y
> 6 none gt ? ? x y
>= 6 none ge ? ? x y
:: 7 right Cons ? ? x y
+ 8 left plus ? ? x y
- 8 left minus ? ? x y
* 9 left times ? ? x y
/ 9 left div ? ? x y
% 9 left mod ? ? x y

Compositional functions

do notation

Sequences of operations in the Monad type class can be written using do-notation, like in Haskell:

  do x <- f
     y <- g x
     h y

is equivalent to:

  f >>= \x -> g x >>= \y -> h y