# Kalami: Introduction

A few years ago I was the teaching assistant in a course on computability and as such was involved in explaining the concept of non-deterministic “guessing”. I always found this topic fascinating myself, so since I also had to come up with a few project suggestions I thought some of them might be interested in making a programming language with a guessing construct. And to give them a place to start I quickly put together a prototype interpreter in Caml that I’ll explain over the course of a few posts. But let’s first get an idea of what the little toy language can do.

Say you want to find two factors in a given number. There are many ways to do this, but using non-determinism we may simple ask the computer to “guess” them. Expressed in the toy language we can write:

```let n = 681 in

guess p from 2 in
guess q from 2 in

if n == p*q then accept
otherwise reject```

where p and q are the factors to be guessed, and assumed to be larger than 2 to avoid the trivial solutions with p=1 or q=1. This could of course be expressed similarly in e.g. Prolog, but the aim was also for the project to have a touch of finding suitable evaluation strategies and using static analysis, as well as to illustrate the power of working with languages in Caml.

To illustrate some of the issues consider programme

```guess x in
guess y in
if x == y+1 then accept
otherwise reject```

which have solution x=1 and y=0. Yet if the evaluation strategy simply starts with x=0 and tries all values for y then it will never find it; in other words, the evaluation strategy must eventually enumerate all tuples of values.

For some programmes we may also benefit from first employing static analysis. Consider for instance programme

```guess x in
if x == x+1 then accept
otherwise reject```

that is easily seen to not have any solutions — yet the interpreter might not realise this without some kind of static analyse. Likewise, for programmes such as

```guess n in
if n == 1*2*3 then accept
otherwise reject```

static analysis may speed up execution time by letting the interpreter discover that it only needs to consider a subset of values — in this case only n=6 — instead of it simply brute forcing for all possibly values.

So there you have it. In the next post I’ll provide the source code for the interpreter and begin dinning into it by looking at its parser. Oh, and by the way, the name Kalami came from The Meaning of Liff by Douglas Adams and John Lloyd, which I was reading at the time.