Scala algorithm: Merge Sort: stack-safe, tail-recursive, in pure immutable Scala, N-way

Published

Algorithm goal

Merge Sort is a standard merging algorithm. It works by grouping items into pairs, and then merging those pairs by selecting the smallest items in ascending order. Then, it repeats this process until 1 whole array is computed.

Our goal is to achieve a sorting like this:

3214
1234

Merge sort algorithm illustration

The data transformation in Merge Sort looks like this:

Picking of items from two halves
Resulting ListLeft HalfRight Half
Original list (split in half)
3241
Applying a merge+sort function to each of the halves
2314
Then, in the merge function, we begin to extract the smallest elements (as the two halves are sorted)
2314
1234
1234
1234
1234
And now we have solved one level of merging.

In the non-stack-safe version, we achieve this via recursion, where we really say 'our sorted version is the merge of sorting of the two halves of our original input'.

This version is stack-safe (and thus a bit more complicated); to find the standard recursive version, see here: MergeSort.

Test cases in Scala

assert(mergeSort(Vector.empty) == Vector.empty)
assert(mergeSort(Vector(1)) == Vector(1))
assert(mergeSort(Vector(1, 2)) == Vector(1, 2))
assert(mergeSort(Vector(2, 1)) == Vector(1, 2))
assert(mergeSort(Vector(2, 1, 3)) == Vector(1, 2, 3))
assert(mergeSort(Vector(2, 1, 4, 3)) == Vector(1, 2, 3, 4))
assert(mergeSort(Vector(2, 4, 5, 1, 3)) == Vector(1, 2, 3, 4, 5))
assert(
  {
    val randomArray = scala.util.Random
      .nextBytes(10 + Math.abs(scala.util.Random.nextInt(1000)))
      .map(_.toInt)
      .toVector
    mergeSort(randomArray) == randomArray.sorted
  },
  "Random array of any length is sorted"
)

Algorithm in Scala

29 lines of Scala (compatible versions 2.13 & 3.0), showing how concise Scala can be!

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Explanation

This solution takes a bottom-up approach to avoid having to use non-tail recursion (which is not stack-safe).

We group all input items into pairs of 2, and then repeat as per the problem definition. (this is © from www.scala-algorithms.com)

The difference to many other solutions out there is that we do not split the input, but rather read from it sequentially, meaning that it is quite intuitive. Another beneficial aspect is that the complexity of the computation is very easy to establish, as the number of iterations required is defined, \(O(n * \log{n})\).

We use a utility method 'iterate' to iterate a function on an initial value n times. LazyList provides us with the 'last' method which allows us to get the iteration really quickly, although we could just as easily use tail recursion to implement it well -- which is a little more verbose.

The merge function

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Scala concepts & Hints

  1. Def Inside Def

    A great aspect of Scala is being able to declare functions inside functions, making it possible to reduce repetition.

    def exampleDef(input: String): String = {
      def surroundInputWith(char: Char): String = s"$char$input$char"
      surroundInputWith('-')
    }
    
    assert(exampleDef("test") == "-test-")
    

    It is also frequently used in combination with Tail Recursion.

  2. Drop, Take, dropRight, takeRight

    Scala's `drop` and `take` methods typically remove or select `n` items from a collection.

    assert(List(1, 2, 3).drop(2) == List(3))
    
    assert(List(1, 2, 3).take(2) == List(1, 2))
    
    assert(List(1, 2, 3).dropRight(2) == List(1))
    
    assert(List(1, 2, 3).takeRight(2) == List(2, 3))
    
    assert((1 to 5).take(2) == (1 to 2))
    
  3. Lazy List

    The 'LazyList' type (previously known as 'Stream' in Scala) is used to describe a potentially infinite list that evaluates only when necessary ('lazily').

  4. Ordering

    In Scala, the 'Ordering' type is a 'type class' that contains methods to determine an ordering of specific types.

    assert(List(3, 2, 1).sorted == List(1, 2, 3))
    
    assert(List(3, 2, 1).sorted(Ordering[Int].reverse) == List(3, 2, 1))
    
    assert(Ordering[Int].lt(1, 2))
    
    assert(!Ordering[Int].lt(2, 1))
    
  5. Pattern Matching

    Pattern matching in Scala lets you quickly identify what you are looking for in a data, and also extract it.

    assert("Hello World".collect {
      case character if Character.isUpperCase(character) => character.toLower
    } == "hw")
    
  6. Stack Safety

    Stack safety is present where a function cannot crash due to overflowing the limit of number of recursive calls.

    This function will work for n = 5, but will not work for n = 2000 (crash with java.lang.StackOverflowError) - however there is a way to fix it :-)

    In Scala Algorithms, we try to write the algorithms in a stack-safe way, where possible, so that when you use the algorithms, they will not crash on large inputs. However, stack-safe implementations are often more complex, and in some cases, overly complex, for the task at hand.

    def sum(from: Int, until: Int): Int =
      if (from == until) until else from + sum(from + 1, until)
    
    def thisWillSucceed: Int = sum(1, 5)
    
    def thisWillFail: Int = sum(1, 300)
    
  7. Tail Recursion

    In Scala, tail recursion enables you to rewrite a mutable structure such as a while-loop, into an immutable algorithm.

    def fibonacci(n: Int): Int = {
      @scala.annotation.tailrec
      def go(i: Int, previous: Int, beforePrevious: Int): Int =
        if (i >= n) previous else go(i + 1, previous + beforePrevious, previous)
    
      go(i = 1, previous = 1, beforePrevious = 0)
    }
    
    assert(fibonacci(8) == 21)
    

Scala Algorithms: The most comprehensive library of algorithms in standard pure-functional Scala

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  11. Compute a Roman numeral for an Integer, and vice-versa
  12. Compute keypad possibilities
  13. Matching parentheses algorithm with foldLeft and a state machine
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  15. Read a matrix as a spiral
  16. Remove duplicates from a sorted list (state machine)
  17. Token Bucket Rate Limiter
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  19. Merge Sort: stack-safe, tail-recursive, in pure immutable Scala, N-way
  20. Longest increasing sub-sequence length
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  27. Count number of contiguous countries by colors
  28. Add numbers without using addition (plus sign)
  29. Tic Tac Toe MinMax solve
  30. Run-length encoding (RLE) Encoder
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  32. Find kth largest element in a List
  33. Balanced parentheses algorithm with tail-call recursion optimisation
  34. Reverse a String's words efficiently
  35. Count number of changes (manipulations) needed to make an anagram with foldLeft and a MultiSet
  36. Count passing cars
  37. Establish execution order from dependencies
  38. Counting inversions of a sequence (array) using a Merge Sort
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  40. Check if an array is a palindrome
  41. Compute missing ranges
  42. Check a directed graph has a routing between two nodes (depth-first search)
  43. Compute nth row of Pascal's triangle
  44. Run-length encoding (RLE) Decoder
  45. Check if a number is a palindrome
  46. In a range of numbers, count the numbers divisible by a specific integer
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  49. Reshape a matrix
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  51. Compute modulo of an exponent without exponentiation
  52. Closest pair of coordinates in a 2D plane
  53. Find the contiguous slice with the minimum average
  54. Compute maximum sum of subarray (Kadane's algorithm)
  55. Pure-functional double linked list
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  57. Check if a directed graph has cycles
  58. Rotate Array right in pure-functional Scala - using an unusual immutable efficient approach
  59. Check a binary tree is a search tree
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  65. Count binary gap size of a number using tail recursion
  66. Remove duplicates from a sorted list (Sliding)
  67. Monitor success rate of a process that may fail
  68. Least-recently used cache (MRU)
  69. Find sub-array with the maximum sum
  70. Find the minimum absolute difference of two partitions
  71. Find maximum potential profit from an array of stock price
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  82. Count factors/divisors of an integer
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  87. Find k closest elements to a value in a sorted Array
  88. QuickSelect Selection Algorithm (kth smallest item/order statistic)
  89. Rotate a matrix by 90 degrees clockwise

Explore the 21 most useful Scala concepts

To save you going through various tutorials, we cherry-picked the most useful Scala concepts in a consistent form.

  1. Class Inside Class
  2. Class Inside Def
  3. Collect
  4. Def Inside Def
  5. Drop, Take, dropRight, takeRight
  6. foldLeft and foldRight
  7. For-comprehension
  8. Lazy List
  9. Option Type
  10. Ordering
  11. Partial Function
  12. Pattern Matching
  13. Range
  14. scanLeft and scanRight
  15. Sliding / Sliding Window
  16. Stack Safety
  17. State machine
  18. Tail Recursion
  19. Type Class
  20. View
  21. Zip

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