# Scala algorithm: QuickSelect Selection Algorithm (kth smallest item/order statistic)

Published

## Algorithm goal

The QuickSelect Selection algorithm finds the kth smallest item in a collection. It it related to QuickSort.

## Test cases in Scala

``````assert(quickSelect(List(1, 2, 3, 4, 5), 3) == Some(3))
assert(quickSelect(List(5, 4, 3, 2, 1), 3) == Some(3))
assert(quickSelect(List(5, 4, 3, 2, 1), 1) == Some(1))
assert(quickSelect(List.empty[Int], 1) == None)
assert(quickSelect(List(1), 1) == Some(1))
assert(quickSelect(List(1), 2) == None)
``````

## Algorithm in Scala

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

## Explanation

The implementation is similar in principle to QuickSort, however we get a simplification because we do not need to care about certain values once we know where our minimum/maximum are after partitioning.

In this algorithm, we pick a pivot (the most straightforward is the first element), and then partition the remaining list by elements lower and higher than the pivot. (this is Â© from www.scala-algorithms.com)

After partitioning by the pivot, if the number of elements we need is higher than the number provided in the smaller partition, then we immediately look at the higher partition, eliminating a large number of elements.

## Scala concepts & Hints

1. ### Option Type

The 'Option' type is used to describe a computation that either has a result or does not. In Scala, you can 'chain' Option processing, combine with lists and other data structures. For example, you can also turn a pattern-match into a function that return an Option, and vice-versa!

``````assert(Option(1).flatMap(x => Option(x + 2)) == Option(3))

assert(Option(1).flatMap(x => None) == None)
``````
2. ### 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))
``````
3. ### 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")
``````
4. ### 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)
``````
5. ### 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)
``````
6. ### Type Class

Type classes are one of Scala's most important super-powers: they enable you to add new behaviour to existing classes, without modifying those classes. In many languages, to add a behaviour to a class, you would typically extend it with an interface, and then implement methods against this interface.This, however, does not scale: especially when you have older libraries, you would be forced to make them depend on a new interface, and have to re-build everything.

Type classes are used heavily in Apple's SwiftUI as "extensions" to enable powerful abstraction capabilities.

Type classes enable you to do things like this:

``````import Ordering.Implicits._

type CommonType = (Int, String, Option[String])

val a: CommonType = (1, "X", None)

val b: CommonType = (2, "A", Some("B"))

assert(a < b, "We can order tuples using Scala-provided type classes")
``````

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

### Study our 92 Scala Algorithms: 6 fully free, 87 published & 5 upcoming

Fully unit-tested, with explanations and relevant concepts; new algorithms published about once a week.

### 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.

## Register now (free)

Register with GitHub

## How the algorithms look

1. A description/goal of the algorithm.
2. An explanation with both Scala and logical parts.
3. A proof or a derivation, where appropriate.
4. Links to Scala concepts used in this specific algorithm, also unit-tested.
5. An implementation in pure-functional immutable Scala, with efficiency in mind (for most algorithms, this is for paid subscribers only).
6. Unit tests, with a button to run them immediately in our in-browser IDE.