### Recursive Evaluation

The evaluator is the core of the interpreter--it's what does all of the interesting work to evaluate complicated expressions. The reader translates textual expressions into a convenient data structure, and the evaluator actually interprets it, i.e., figures out the "meaning" of the expression.

Evaluation is done recursively. We write code to evaluate simple expressions, and use recursion to break down complicated expressions into simple parts.

I'll show a simple evaluator for simple arithmetic expressions, like a four-function calculator, which you can use like this, given the read-eval-print-loop above:

```Scheme>(repl math-eval)  ; start up read-eval-print loop w/arithmetic eval
repl>1
1
repl>(plus 1 2)
3
repl>(times (plus 1 3) (minus 4 2))
8
```

As before, the read-eval-print-loop reads what you type at the `repl>` prompt as an s-expression, and calls `math-eval`.

Here's the main dispatch routine of the interpreter, which figures out what kind of expression it's given, and either evaluates it trivially or calls `math-eval-combo` to help:

```(define (math-eval expr)
(cond ;; self-evaluating object?  (we only handle numbers)
((number? expr)
expr)
;; compound expression? (we only handle two-arg combinations)
(else
(math-eval-combo expr))))
```

First `math-eval` checks the expression to see if it's something simple that it can evaluate straightforwardly, without recursion.

The only simple expressions in our language are numeric literals, so `math-eval` just uses the predicate `number?` to test whether the expression is a number. If so, it just returns that value. (Voila! We've implemented self-evaluating literals.)

If the expression is not simple, it's supposed to be an arithmetic expression with an operator and two operands, represented as a three element list. (This is the subset of Scheme's combinations that this interpreter can handle.) In this case, `math-eval` calls `math-eval-combo`.

```(define (math-eval-combo expr)
(let ((operator-name (car expr))
(cond ((eq? operator-name 'plus)
(+ arg1 arg2))
((eq? operator-name 'minus)
(- arg1 arg2))
((eq? operator-name 'times)
(* arg1 arg2))
((eq? operator-name 'quotient)
(/ arg1 arg2))
(else
(error "Invalid operation in expr:" expr)))))
```

`math-eval-combo` handles a combination (math operation) by calling `math-eval` recursively to evaluate the arguments, checking which operator is used in the expression, and calling the appropriate Scheme procedure to perform the actual operation.

#### Comments on the Arithmetic Evaluator

The 4-function arithmetic evaluator is very simple, but it demonstrates several important principles of Scheme programming and programming language implementation.

• Recursive style and Nested Lists. Notice that an arithemetic expression is represented as an s-expression that may be a 3-element list. If it's a three-element list, that list is made up of three objects (pairs), but we essentially treat it as a single conceptual object--a node in a parse tree of arithemetic expressions. The overall recursive structure of the evaluator is based on this conceptual tree, not on the details of the lists' internal structure. We don't need recursion to traverse the lists, because the lists are of fixed length and we can extract the relevant fields using `car`, `cadr`, and `caddr`. We are essentially treating the lists as three-element structures. This kind of recursion is extremely common in Scheme--nested lists are far more common than "pair trees." As in the earlier examples of recursion over lists and pair trees, the main recursive procedure can accept pointers to either interior nodes (lists representing compound expressions), or leaves of the tree. Either counts as an expression. Dynamic typing lets us implement this straightforwardly, so that our recursion doesn't have to "bottom out" until we actually hit a leaf. Things would be more complicated in C or Pascal, which don't allow a procedure to accept an argument that may be either a list or a number.\footnote{In C or Pascal, we could represent all of the nodes in the expression tree as variant records (in C, "unions") containing an integer or a list. We don't need to do that in Scheme, because in Scheme every variable's type is really a kind of variant record--it can hold a (pointer to a) number or a (pointer to a) pair or a (pointer to) anything else. C is particularly problematic for this style of programming, because even if we bite the bullet and always define a variant record type, the variant records are untagged. C doesn't automatically keep track of which variant a particular record represents--e.g., a leaf or nonleaf--and you must code this yourself by adding a tag field, and setting and checking it appropriately. In effect, you must implement dynamic typing yourself, every time.} It is possible to do Scheme-style recursion straightforwardly in some statically-typed languages, notably ML and Haskell. These polymorphic languages allow you to declare disjoint union types. A disjoint union is an "any of these" type--you can say that an argument will be of some type or some other type. In Scheme, the language only supports one very general kind of disjoint union type: pointer to anything. However, we usually think of data structure definitions as disjoint unions. As usual, we can characterize what an arithmetic expression recursively. It is either a numeric literal (the base case) or a three-element "node" whose first "field" is an operator symbol and whose second and third "fields" are arithmetic expressions. Also as usual, this recursive characterization is what dictates the recursive structure of the solution---not the details of how nodes are implemented. (The overall structure of recursion over trees would be the same if the interior nodes were arrays or records, rather than linear lists.) The conceptual "disjoint union" of leaves and interior nodes is what tells us we need a two-branch conditional in `math-eval`. It is important to realize that in Scheme, we usually discriminate between cases at edges in the graph, i.e., the pointers, rather than focusing on the nodes. Conceptually, the type of the `expr` argument is an edge in the expression graph, which may point to either a leaf node or an interior node. We apply `math-eval` to each edge, uniformly, and it discriminates between the cases. We don't examine the object it points to and decide whether to make the recursive call--we always do the recursive call, and sort out the cases in the callee.
• Primitive expressions and operations. In looking at any interpreter, it's important to notice which operations are primitive, and which are compound. Primitive operations are "built into" the interpreter, but the interpreter allows you to construct more complicated operations in terms of those. In `math-eval`, the primitive operations are addition, subtraction, multiplication, and division. We "snarf" these operations from the underlying Scheme system, in which we're implementing our little four-function calculator. We don't implement addition, but we do dispatch to this built-in addition operation. On the other hand, compound expressions are not built-in. The interpreter doesn't have a special case for each particular kind of expression--e.g., there's no code to add 4 to 5. We allow users to combine expressions by arbitrarily nesting them, and support an effectively infinite number of possible expressions. Later, I'll show more advanced interpreters that support more kinds of primitive expressions--not just numeric literals and more kinds of primitive operations--not just four arithmetic functions. I'll also show how a more advanced interpreter can support more different ways of combining the primitive expressions.
• Flexibility You may be wondering why we'd bother to write `math-eval`, since it essentially implements a small subset of Scheme, and we've already got Scheme. One reason for implementing your own interpreter is flexibility. You can change the features of the language by making minor changes to the interpreter. For example, it is trivial to modify `math-eval` to evaluate infix expressions rather than postfix expressions. (That is, with the operator in the middle, e.g., `(10 plus (3 times 2))`. All we have to do is change the two lines where the operator and the first operand are extracted from a compound expression. We just swap the `car` and `cadr`, so that we treat the second element of the list as the operand and the first element as the operator.

### A Note on Snarfing and Bootstrapping

Two concepts worth knowing about language implementation are snarfing and bootstrapping. Snarfing is "stealing" features from an underlying language when implementing a new language. Bootstrapping is the process of building a language implementation (or other system) by using the system to extend itself.

#### Snarfing

Our example interpreter implements Scheme in Scheme, but we could have written it in C or assembly language. If we had done that, we'd have to have written our own read-eval-print loop, and a bunch of not-very interesting code to read from the keyboard input and create data structures, display data structures on the screen, and so on. Instead, we "cheated" by snarfing those features from the underlying Scheme system--we simply took features from the underlying Scheme system and used them in the language we interpret. Our tiny language requires you to type in Scheme lists, because it uses the Scheme read-eval-print to get its input and call the interpreter. If we wanted to, we could provide our own reading routine that reads things in a different syntax. For example, we might read input that uses square brackets instead of parentheses for nesting, or which uses infix operators instead of prefix operators.

There are some features we didn't just snarf, though--we wrote our own evaluation procedure which controls recursive evaluation. For example, we use basic Scheme arithemetic procedures to implement individual arithmetic operations, but we don't simply snarf them: the interpreter recognizes arithmetic operations in its input language, and maps them onto procedure calls in the underlying language. We can change our language by changing those mappings: for example, we could use the symbols `+`, `-`, `*`, and `/` to represent those operations, as Scheme does, or whatever we choose for the language we're interpreting. Or we could use the same names, but implement the operations differently. (For example, we might have our own arithmetic routines that allow a representation of infinity, and do something reasonable for division by zero.)

We also use recursion to implement recursion, when we recursively call `eval`). But since we coded that recursion explicitly, we can easily change it, and do something different. Our arithmetic expressions don't have to have the same recursive structure as Scheme expressions.

We could also implement recursion ourselves. As written, our tiny interpreter uses Scheme's activation "stack" to implement it's own stack--each recursive call to `eval` implements a recursive call in our input language. We didn't have to do this. We could have implemented our own stack as a data structure, and written our interpreter as a simple non-recursive loop. That would be a little tedious, however, so we don't bother.

What counts as "snarfing"? The term is a good one, but not clearly defined. If we call Scheme's `read` rather than using our own reader, we clearly just snarf the Scheme reader, but we've done something a little different with recursion. We've done something very different with the interpretation of operator names.

#### Bootstrapping and Cross-compiling

Implementing a programming language well requires attention to the fine art of bootstrapping--how much of the system do you have to build "by hand" in some lower-level system, and how much can you build within the system itself, once you've got a little bit of it working.

Most Scheme systems are written mostly in Scheme, and in fact it's possible (but not particularly fun) to implement a whole Scheme system in Scheme, even on a machine that doesn't have a Scheme system yet.

How are these things possible?

First, let's take the simple case, where you're willing to write a little code in another language. You can write an interpreter for a small subset of Scheme in, say, C or assembler. Then you can extend that little language by writing the rest of Scheme in Scheme--you just need a simple little subset to get started, and then things you need can be defined in terms of things you already have. Writing an interpreter for a subset of Scheme in C is not hard--just a little tedious. Then you can use `lambda` to create most of the rest of the procedures in terms of simpler procedures. Interestingly, you can also implement most of the defining constructs and control constructs of Scheme in Scheme, by writing macros, which we'll discuss later.

You can start out this way even if you want your Scheme system to use a compiler. You can write the compiler in Scheme, and use the interpreter to run the compiler and generate machine code. Now you have a compiler for Scheme code, and can compile procedures so that they run faster than if you interpreted them. You can take most of the Scheme code that you'd been interpreting, and use the compiler to create faster versions of them. You then replace the old (interpreted) versions with the new (compiled) versions, and the system is suddenly faster.

Once the compiler works, you can compile the compiler, so that it runs faster. After all, a compiler is just a program that takes source code as input and generates executable code--it's just a program that happens to operate on programs. Now you're set--you have a compiler that can compile Scheme code that you need to run, including itself, and you don't need the interpreter anymore.

To get Scheme to work on a new system, without even needing an interpreter, you can cross-compile. If you have Scheme working on one kind of machine, but want to run it on another, you can write your Scheme compiler in Scheme, and have it run on one machine but generate code for the new machine. Then you can take the executable code it generates, copy it onto the new machine, and run it.

Most Scheme systems are built using tricks like this. For example, the RScheme system never had an interpreter at all. Its compiler was initially run in a different Scheme system (Scheme-48) and used to compile most of RScheme itself. This code was then used to run RScheme with no further assistance from another implementation.

The first Scheme system was built by writing a Scheme interpreter in Lisp, [ or was it a compiler first? ... blah blah ... ]