This is work in progress!
Greenspun's tenth rule of programming states that "any sufficiently complicated C or Fortran program contains an ad hoc, informally-specified, bug-ridden, slow implementation of half of Common Lisp."
Kotlin has some interesting features that suggest that it might be possible to add such an "inner" language directly in Kotlin -- without the need for an additional parser:
-
Trailing closures allow the addition of "custom" control structures, similar to Hugo Tunius' custom control structures for Swift
-
Operator overloading allows us to build a custom expression tree
-
Finally, Kotlin's DSL feature allows us to do this all this in a special implicit context
Of course, one "typical" motivation for adding a scripting language such as Lua is the ability to dynamically add code, e.g. as part of system configuration, which won't work if we use the Kotlin compiler in our language.
However, this shouldn't stop us from figuring out if it is possible to build a full "inner" programming language with "reasonable" syntax as a Kotlin DSL.
If you are just interested in what the end result looks like, don't hesitate to skip the process and jump ahead to the "FizzBuzz" example.
Before we start our DSL, let's quickly build up expressions as a building block.
Let's assume our language uses an interface Expr to represent expressions
that we can evaluate in some context that we'll come back to later:
class Context {
// We'll get to this later...
}
interface Expr {
fun eval(context: Context): Any
// Convenience
fun evalDouble(context: Context) = (eval(context) as Number).toDouble()
fun evalBoolean(context: Context) {
val v = eval(context)
return v == true || (v is Number && v.toDouble() != 0.0)
}
}For literals, we can define a class Literal as follows:
class Literal(val value: Any) : Expr {
override fun eval(context: Context) = value
override fun toString() = "Literal($value)"
}Operator overloading allows us to recursively build an expression tree with regular operators and operator precedence.
First, we define a binary expression node that is able to do some math:
class BinaryOperator(
val op: String,
val left: Expr,
val right: Expr
): Expr {
fun eval(context: Context) {
val l = left.evalDouble(context)
val r = right.evalDouble(context)
return when (op) {
"+" -> l + r
"*" -> l * r
// ...
else -> throw UnsupportedOperationException(op)
}
}
fun toString() = "($left $op $right)"
}Then we use operator overloading to enable building expression trees with the corresponding operators.
interface Expr {
operator fun Expr.add(other: Expr) =
BinaryOperator("+", this, other)
operator fun Expr.mul(other: Expr) =
BinaryOperator("-", this, other)
// ...
}Now we can build an expression that adds two numbers with the following code snippet:
val addExpr = Literal(40) + Literal(2)As we have implemented toString()-functions for all our expression classes, we can verify that the expression is constructed correctly via
println(addExpr)The output should be
(Literal(40) + Literal(2))Now we test if this works as expected by evaluating the expression:
print(addExpr.eval(Context()))Which should just print 42.0.
Of course there is a simpler way to calculate the sum of 40 and 2. The important difference here is that we have generated an expression tree that we can inspect and manipulate and where we can repeat the included operations if we want to.
For instance, after adding variables to our expressions, we could use this representation to implement symbolic derivation or integration.
With basic expressions in place, we can start working on our "actual" DSL.
First, we define a class Block that bundles multiple expressions and exectutes
them sequentially:
class Block(val statements: List<Expr>) : Expr {
override fun eval(context: Context) {
for (statement in statemnts) {
statement.eval(context)
}
}
}Now, we add a builder for these blocks,
adding a PrintLn function on the way.
To be able to easily distinguish our "inner" language from Kotlin, we'll start our identifiers with a capitalized letter.
class BlockBuilder {
var statements: mutableListOf<Expr>()
fun Print(expr: Expr) {
statements.add(
object : Expr {
override fun eval(context: Context) {
println(expr.eval(context))
}
}
)
}
fun build() = Block(statements.toList())
}Finally, we create the DSL to build these blocks:
fun block(init: BlockBuilder.() -> Unit): Block {
val builder = BlockBuilder()
init(builder)
return builder.build()
}Now we can use what we have defined so far and create our first block of code, which should just print "42" again, with the "print" command moved to our inner language now.
val b = block {
PrintLn(Const(40) + Const(2))
}
b.eval(Context())We'll implement variables by storing them in an array in our Context object:
class Context(size: Int = 0) {
val variables = Array<Any>(size) { Unit }
}To access variables in expressions, we'll just read the value at the corresponding index from the context:
class VarRef(val index: Int) : Expr {
override fun eval(context: Context) = context.variables[index]
override fun toString() = "var$index"
}With this in place, we still need something to assign values to variables:
class VarAssignment(
val declaration: Boolean,
val index: Int,
val value: Expr
) : Expr {
override fun eval(context: Context) {
context.variables[index] = value.eval(context)
}
override fun toString() =
if (declaration) "val var$index = $value" else "Set(var$index, $value)"
}
Finally, we need some support in the BlockBuilder
class BlockBuilder(val variables: MutableList<VarRef>) {
var statements = mutableListOf<Expr>()
fun Var(initialValue: Expr): VarRef {
val varRef = VarRef(variables.size)
variables.add(varRef)
statements.add(VarAssignment(true, index, initialValue))
return varRef
}
fun Set(target: VarRef, value: Expr) {
statements.add(VarAssignment(false, target.index, value))
}
// PrintLn definition from above etc.
}Now we can use variables like this:
val myVar = Var(Literal(40))
Set(myVar, myVar + Literal(2))
PrintLn(myVar)We can avoid some of the explicit Literal() calls
by automatically turning values into literals where we
know an expression is expected. For this,
we expand our expression class as follows:
interface Expr {
fun eval(context: Context): Any
operator fun plus(other: Any) =
BinaryOperator('+', this, Expr.of(other))
// other operator definitions omitted here...
companion object {
fun of(value: Any): Expr =
if (value is Expr) value else Literal(value)
}
}Converting expression references in our BlockBuilder
accordingly, we can write the previous example as follows:
val myVar = Var(40)
Set(myVar, myVar + 2)
PrintLn(myVar)Of course a programming language can't be complete without some sort of control structures.
So let's build a conditional expression:
class IfExpr(
val condition: String,
val then: Block,
val otherwise: Block = Block(emptyList())
) : Expr{
override fun eval(context: Context) {
if (condition.evalBoolean(context)) {
then.eval(context)
} else {
otherwise.eval(context)
}
}
fun Else(expr: Block) = If(condition, then, expr)
}And a while expression:
class WhileExpr(
val condition: String,
val body: Block
) : Expr {
override fun eval(context: Context) {
while (condition.evalBoolean(context)) {
body.eval(context)
}
}
}And wire them up in our DSL:
class BlockBuilder {
fun If(condition: Any, init: BlockBuilder.() -> Unit): IfExpr {
val blockBuilder = BlockBuilder()
init(blockBuilder)
val ifExpr = IfExpr(Expr.of(condition), blockBuilder.build())
statements.add(ifExpr)
return ifExpr
}
fun While(condition: Any, init: BlockBuilder.() -> Unit) {
val blockBuilder = BlockBuilder()
init(blockBuilder)
statements.add(WhileExpr(Expr.of(condition), blockBuilder.build()))
}
}Now we finally have enough functionality at our disposal to implement a "proper" simple program: FizzBuzz
val fizzBuzz = block {
val count = Var(20)
While (count) {
If (count % 5) {
If (count % 3) {
PrintLn(count)
}.Else {
PrintLn("Fizz")
}
}.Else {
If (count % 3) {
PrintLn("FizzBuzz")
}.Else {
PrintLn("Buzz")
}
}
Set(count, count - 1)
}
}
fizzBuzz.eval(Context(1))For functions, we can represent the body as a block. For paramters, we'll just keep track of their count and use the first local variables as parameters.
class FunRef(
val paramCount: Int,
val varCount: Int,
val body: Block) {
operator fun invoke(vararg args: Any) = Invocation(this, args.map { Expr.of(it) })
}We represent an invocation by an expression that calls the function:
class Invocation(val funRef: FunRef, val args: List<Expr>) : Expr {
init {
require(funRef.paramCount == args.size) {
"Parameter count mismatch; expected: ${funRef.paramCount}; actual: ${args.size}"
}
}
override fun eval(context: Context): Any {
val funContext = Context(funRef.varCount)
for (i in 0 until args.size) {
funContext.variables[i] = args[i].eval(context)
}
return funRef.body.eval(funContext)
}
}Now we still need a way to build the function body -- including parameter support. For this, we'll just us a slightly expanded subclass of our block builder:
class FunBuilder : BlockBuilder(mutableListOf()) {
var paramCount = 0
fun Param(): VarRef {
require(statements.isEmpty()) {
"Parameters must be declared before all other statements"
}
val varRef = VarRef(paramCount++)
variables.add(varRef)
return varRef
}
}Finally, we need a way to create a program -- consisting of multiple function declarations. We'll just use the function declared last as the "main" function that will be called implicitly when running the program:
fun program(init: ProgramBuilder.() -> Unit): () -> Any {
val builder = ProgramBuilder()
init(builder)
val funRef = builder.lastFunRef
require(funRef != null) {
"Program must declare at least one function"
}
val invocation = funRef.invoke()
return { invocation.eval(Context()) }
}
class ProgramBuilder() {
var lastFunRef: FunRef? = null
fun Fun(init: FunBuilder.() -> Unit): FunRef {
val builder = FunBuilder()
init(builder)
val funRef = FunRef(builder.paramCount, builder.variables.size, Block(builder.statements))
lastFunRef = funRef
return funRef
}
}Now we can run a small example progam containing function declarations as follows:
fun main() {
val program = program {
val sqr = Fun() {
val x = Param()
+(x * x)
}
Fun() {
PrintLn(sqr(5))
}
}
program()
}While there is a lot of stuff that could still be added, I think we have sufficiently demonstrated that it's possible to implement a full "independent" programming language inside a Kotlin DSL.
The full source code and all examples are available here: https://github.com/stefanhaustein/greenspun
When extending the language, there are some problems we have skipped over so far:
-
While mathematical operators can be overloaded in a way that works for our purposes, this is not possible for assignments, relational operators and equality checks; these have to be supported in a different way.
-
Functions can't be referenced inside their own declaration and forward references are also not possible. This could be fixed using explicit forward declarations.
While this just started as a quick idea / general proof of concept, our Kotlin Webassembler is roughly based on the approach demonstrated here. For more information, please refer to https://github.com/kobjects/kowa.