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Introduction to the Lambda calculus

In this article we introduce the basic formalism underlying functional programming, the lambda calculus
Excerpt from
© University of Glasgow

Introduction to the Lambda Calculus

  • The lambda calculus was developed in the 1930s by Alonzo Church (1903–1995), one of the leading developers of mathematical logic.

  • The lambda calculus was an attempt to formalise functions as a means of computing.

Significance to computability theory

  • A major (really the major) breakthrough in computability theory was the proof that the lambda calculus and the Turing machine have exactly the same computational power.

  • This led to Church’s thesis — that the set of functions that are effectively computable are exactly the set computable by the Turing machine or the lambda calculus.

  • The thesis was strengthened when several other mathematical computing systems (Post Correspondence Problem, and others) were also proved equivalent to lambda calculus.

  • The point is that the set of effectively computable functions seems to be a fundamental reality, not just a quirk of how the {Turing machine, lambda calculus} was defined.

Significance to programming languages

  • The lambda calculus has turned out to capture two aspects of a function:

    • A mathematical object (set of ordered pairs from domain and range), and

    • An abstract black box machine that takes an input and produces an output.

  • The lambda calculus is fundamental to denotational semantics, the mathematical theory of what computer programs mean.

  • Functional programming languages were developed with the explicit goal of turning lambda calculus into a practical programming language.

  • The ghc Haskell compiler operates by (1) desugaring the source program, (2) transforming the program into a version of lambda calculus called System F, and (3) translating the System F to machine language using graph reduction.

Abstract syntax of lambda calculus

  • We will work with the basic lambda calculus “enriched” with some constants and primitive functions (strictly speaking, that is not necessary).

  • The language has constants, variables, applications, and functions.

= const
| var
| exp exp
| var -> exp


  • Each occurrence of a variable in an expression is either bound or

    • In (backslash x rightarrow x+1), the occurrence of (x) in
      (x+1) is bound by the (backslash x).

    • In (y*3), the occurrence or (y) is free. It must be defined
      somewhere else, perhaps as a global definition.

  • In general, an occurrence of a variable is bound if there is some
    enclosing lambda expression that binds it; if there is no lambda
    binding, then the occurrence if free.

We need to be careful: the first occurrence of (a) is free but the
second occurrence is bound.

 a + ( a -> 2^a) 3 -- > a + 2^3

Being free or bound is a property of an occurrence of a variable, not
of the variable itself!

Conversion rules

  • Computing in the lambda calculus is performed using three
    conversion rules.

  • The conversion rules allow you to replace an expression by another
    (“equal”) one.

  • Some conversions simplify an expression; these are called

Alpha conversion

  • Alpha conversion lets you change the name of a function parameter

  • But you can’t change free variables with alpha conversion!

  • The detailed definition of alpha conversion is a bit tricky, because
    you have to be careful to be consistent and avoid “name capture”. We
    won’t worry about the details right now.

(x -> x+1) 3
(y -> y+1) 3

Beta conversion

  • Beta conversion is the “workhorse” of lambda calculus: it defines
    how functions work.

  • To apply a lambda expression an argument, you take the body of the
    function, and replace each bound occurrence of the variable with the

 (x -> exp1) exp2

is evaluated as (exp1[exp2/x])


 (x -> 2*x + g x) 42

is evaluated as (2*42 + g ;42)

Eta conversion

  • Eta conversion says that a function is equivalent to a lambda
    expression that takes an argument and applies the function to the
(x -> f x) 

is equivalent to (f)

Example (recall that ((*3)) is a function that multiplies its argument
by 3)

(x -> (*3) x) 

is equivalent to ((*3))

Try applying both of these to 50:

(x -> (*3) x) 50 

is the same as ((*3) ;50)

Removing a common trailing argument

There is a common usage of Eta conversion. Suppose we have a definition
like this:

f x y = g y

This can be rewritten as follows:

f = x -> (y -> g y)
f = x -> g = f x = g

Thus the following two definitions are equivalent:

 f x y = g y
f x = g

In effect, since the last argument on both sides of the equation is the same ((y)), it can be “factored out”.

© University of Glasgow
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