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118 lines
3.3 KiB
Markdown
118 lines
3.3 KiB
Markdown
---
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title: "Deep Recursion"
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date: 2022-11-11T14:45:17-05:00
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draft: false
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tags: ["Scala", "Functional Programming"]
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math: false
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---
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In functional programming, we often look at a list in terms of its head (first-element) and tail (rest-of-list). This allows us to define operations on a list recursively. For example, how do we sum a list of integers such as `[1, 2, 3, 4]`?
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```scala
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def sum(l : List[Int]): Int =
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if l.size == 0 then
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0
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else if l.size == 1 then
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l.head
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else
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l.head + sum(l.tail)
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```
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We later learn that the `fold` version is more compact.
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```scala
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l.foldLeft(0)(_ + _)
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```
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The big question though, is how do we write this function if we allow lists to be arbitrarily nested? One example of this is the list `[[1, 2, [3, 4]], 5, [[6, 7], 8]]`
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## Deep Recursion
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To accomplish this, we need to make use of *deep recursion*. At its essence, we change the previous program so that it also recurses on the head of the list as well since that may be a list.
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```scala
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def deep_sum(l: Int | Matchable): Int =
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if l.isInstanceOf[Int] then
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l.asInstanceOf[Int]
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else
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val ll = l.asInstanceOf[List[Int | Matchable]]
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if ll.size == 0 then
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0
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else if ll.size == 1 then
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deep_sum(ll.head)
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else
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deep_sum(ll.head) + deep_sum(ll.tail)
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```
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Lets trace through an example `[[1], 2]`
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```
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deep_sum([[1], 2])
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deep_sum([1]) + deep_sum([2])
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deep_sum(1) + deep_sum([2])
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1 + deep_sum([2])
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1 + deep_sum(2)
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1 + 2
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3
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```
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## Deep Recursion via Fold
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Similar to shallow recursion, we can use the `foldLeft` function to help clean up the code a little:
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```scala
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def deep_sum(l : Int | Matchable): Int =
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if l.isInstanceOf[Int] then
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l.asInstanceOf[Int]
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else
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val ll = l.asInstanceOf[List[Int | Matchable]]
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ll.foldLeft(0)((c, n) => c + deep_sum(n))
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```
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In the above fold, `c` contains the current partial result (of type `Int`) which we can then add the recursive result of the next element of the list.
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Let's trace through an example `[[1], 2]`
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```
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deep_sum([[1], 2])
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[[1], 2].foldLeft(0)((c, n) => c + deep_sum(n))
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(0 + deep_sum([1])) + deep_sum(2)
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(0 + [1].foldLeft(0)((c1, n1) => c1 + deep_sum(n1))) + deep_sum(2)
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(0 + (0 + deep_sum(1))) + deep_sum(2)
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(0 + (0 + 1)) + deep_sum(2)
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(0 + 1) + deep_sum(2)
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1 + deep_sum(2)
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1 + 2
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3
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```
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## Deep Recursion via Fold/Map
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In the prior example, the deep recursion and the reduction logic were combined within the same anonymous function. We can separate this out by making use of `map`.
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```scala
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def deep_sum(l: Int | Matchable): Int =
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if l.isInstanceOf[Int] then
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l.asInstanceOf[Int]
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else
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val ll = l.asInstanceOf[List[Int | Matchable]]
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l.map(deep_sum).foldLeft(_ + _)
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```
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Intuitively, the map will apply `deep_sum` to each element of the list and returns an `Int` for each element as that's the return type of `deep_sum`. Once we have our list of integers, we can perform the fold to reduce it to a single sum.
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Lets trace through an example `[[1], 2]`
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```
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deep_sum([[1], 2])
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[deep_sum([1]), deep_sum(2)].foldLeft(0)(_ + _)
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[[deep_sum(1)].foldLeft(0)(_ + _), deep_sum(2)].foldLeft(0)(_ + _)
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[[1].foldLeft(0)(_ + _), deep_sum(2)].foldLeft(0)(_ + _)
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[(0 + 1), deep_sum(2)].foldLeft(0)(_ + _)
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[1, deep_sum(2)].foldLeft(0)(_ + _)
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[1, 2].foldLeft(0)(_ + _)
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(0 + 1) + 2
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1 + 2
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3
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```
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