What did I cover? The aim was to hammer home the message about the data driving the programming, and I took the example of processing arithmetical expressions, writing an evaluator, a virtual machine and a compiler … I didn't cover parsing, but that can come in the second half of the course: Stefan?
So, we started with a data type for expressions, with literals, +, - and *.
data Exp = Lit Int
| Add Exp Exp
| Sub Exp Exp
| Mul Exp Exp
with the expression 2+((3-(-3))*3) represented by
(Lit 2) `Add` (((Lit 3) `Sub` (Lit (-3))) `Mul` (Lit 3))
The first thing to define is the evaluator, which has a straightforward data-directed definition:
eval :: Exp -> Int
eval (Lit n) = n
eval (Add ex1 ex2) = eval ex1 + eval ex2
eval (Sub ex1 ex2) = eval ex1 - eval ex2
eval (Mul ex1 ex2) = eval ex1 * eval ex2
What sort of machine should we use to evaluate the expressions? The simplest approach is to build a stack machine, which can either push literals, or apply an operation to the top elements on the stack (from my slides):
Here's the type of code.
data Code = PushLit Int
We can describe this machine by giving the function that runs a program, when we represent the stack by a list of integers, and the program by a list of code.
type Program = [Code]
type Stack = [Int]
run :: Program -> Stack -> Stack
run  stack
run (PushLit int : program) stack
= run program (int : stack)
run (DoAdd : program) (v1:v2:stack)
= run program (v1 + v2 : stack)
run (DoSub : program) (v1:v2:stack)
= run program (v1 - v2 : stack)
run (DoMul : program) (v1:v2:stack)
= run program (v1 * v2 : stack)
run _ _ = 
An alternative here would be to give the oneStep function, and then to define run in terms of that: that's an exercise for the reader.
The final piece of the puzzle is to define the compiler:
compile :: Exp -> Program
compile (Lit n)
= [PushLit n]
compile (Add ex1 ex2)
= compile ex2 ++ compile ex1 ++ [DoAdd]
compile (Sub ex1 ex2)
= compile ex2 ++ compile ex1 ++ [DoSub]
compile (Mul ex1 ex2)
= compile ex2 ++ compile ex1 ++ [DoMul]
Why do I like this example so much?
- It shows Haskell's strengths: I think my students get fed up of me comparing Haskell with Java, but this is a case where it really shines. The types make it very clear what's going on; the algebraic types guide the definitions, and we can even prove it correct …
- What is the statement of correctness? That evaluation is the same as compiling and running:
run (compile exp)  = [eval exp]
but there's a bit of work to do to get the right induction hypothesis (exercise).
- There are lots of nice generalisations: we can introduce local definitions with a let construct, or indeed allow (updatable) variables within expressions. All these can be added in a nice type-directed way.
- There are lots of related exercises too: e.g. generate truth tables for Boolean expressions, and using these write tautology checkers.
So, a very enjoyable last lecture on Haskell.