I wrote a recursive version:
def quickSort[T](xs: List[T])(p: (T, T) => Boolean): List[T] = xs match{
case Nil => Nil
case _ =>
val x = xs.head
val (left, right) = xs.tail.partition(p(_, x))
val left_sorted = quickSort(left)(p)
val right_sorted = quickSort(right)(p)
left_sorted ::: (x :: right_sorted)
}
But I don't know how to change it into tail-recurisive. Can anyone give me a suggestion ?
Any recursive function can be be converted to use the heap, rather than the stack, to track the context. The process is called trampolining
.
Here's how it could be implemented with Scalaz.
object TrampolineUsage extends App {
import scalaz._, Scalaz._, Free._
def quickSort[T: Order](xs: List[T]): Trampoline[List[T]] = {
assert(Thread.currentThread().getStackTrace.count(_.getMethodName == "quickSort") == 1)
xs match {
case Nil =>
return_ {
Nil
}
case x :: tail =>
val (left, right) = tail.partition(_ < x)
suspend {
for {
ls <- quickSort(left)
rs <- quickSort(right)
} yield ls ::: (x :: rs)
}
}
}
val xs = List.fill(32)(util.Random.nextInt())
val sorted = quickSort(xs).run
println(sorted)
val (steps, sorted1) = quickSort(xs).foldRun(0)((i, f) => (i + 1, f()))
println("sort took %d steps".format(steps))
}
Of course, you need either a really big structure or a really small stack to have a practical problem with a non-tail-recursive divide and conquer algorithm, as you can handle 2^N elements with a stack depth of N.
http://blog.richdougherty.com/2009/04/tail-calls-tailrec-and-trampolines.html
UPDATE
scalaz.Trampoline
is a special case of a (much) more general structure, Free
. It's defined as type Trampoline[+A] = Free[Function0, A]
. It's actually possible to write quickSort
more generically, so it is parameterized by the type constructor used in Free
. This example shows how this is done, and how you can then use the same code to bind using the stack, the heap, or in concurrently.
https://github.com/scalaz/scalaz/blob/scalaz-seven/example/src/main/scala/scalaz/example/TrampolineUsage.scala
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