# lambda definition programming

B. Rosser in 1935 in the form of the Kleene–Rosser paradox. Since we are not formal on type annotations we can use Pair A B to express the type of a pair where the first component is of type A and the second component is of type B. In that case we want the expression a / b to return a in order to have a total function. Note that Group A has been replaced by R i.e. This representation doesn’t tell the output type of the function, but because + 1 would result in a natural number output as well, it’s easy to make the required assumption.

The iteration function f just used the iteration counter to compute the next result and ignores the result of the previous iteration. The availability of unbounded search makes lambda calculus as expressive as general recursive functions. In lambda calculus, when E is a lambda term and x is a variable, λx.E is a lambda term.
In the previous chapters represented the types Boolean and Natural in lambda calculus. the folding function has the type A -> List A -> R -> R. Internally the recursor uses pairs (tail list, previous result) starting with (nil, s) and throwing away the tail list at the end of the iteration.

Rather, type refers to the mathematical definition of the function’s domain (the set of outputs that the function will provide based on its defined argument values) and range (the codomain or image of the function), which is represented by A -> B.

Therefore evaluating a lambda term might be non deterministic.

From the viewpoint of the lambda calculus the terms are equivalent. The act of applying one thing to another seems simple enough.

But if you have a construction of such an object, you can use it as an upper bound and use least-below to find the smallest number satisfying the predicate. We get. However the programmer thinks in types. The hygiene condition guarantees that the name of the bound variable does not interfere with variable names in the world outside the abstraction. I would have never found such a cleverly constructed lambda term by myself.

We just know that this term has to do some kind of self replication to implement the loop.

A difficult situation when you want to define a calculus where all computable functions can be encoded and the calculus fails on such a simple task as to compute the predecessor of a natural number.

This is called the Church encoding of numbers and the encoded numbers are called Church numerals. Feel free to post any question, comment, remark or discusion as a github issue on https://github.com/hbr/Lambda-Calculus/issues.

With these helper functions based on predicates we can implement division functions and functions computing prime numbers. If we find a number below the bound which satisfies a certain predicate, we know that at least one number below the bound exists, which satisfies the predicate. A type definition of such a tree in a functional programming language looks like. And as you will see: We can express arbitrarily complex and interesting functions.

Having such a generic recursor, the encoding of the predecessor function is just a piece of cake. For example, a common proof is a property that holds for all natural numbers. Coding of comparison functions is now easy. Each list expression is a lambda term which iterates over the list given the folding function f and the start value s as arguments.

The following information describes how abstraction works for both untyped and typed lambda calculus. Lambda terms where all variables are bound are called combinators.

Next we want to implement an existential quantifier with an upper bound.
But anyhow.

The start value for isEven is true and the start value for isOdd is false to return the correct value for the number zero.

E.g.

When working with multiparameter inputs, you must curry the function as shown before.

With this preparation, it is easy to write the function least-below and convince ourself that the implementation is correct. Function application associates to the left, Nested function abstractions associate to the right.

The first argument is a function and the second a start value. We get the concatenation of the two lists a and b by folding cons over the list a with the start value b. We have just assigned an arbitrary result to the function for arguments, where it is mathematically undefined.

We interpret the type definition as the definition of an algebra and look at the expressions it generates and at corresponding expressions trees.