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Functional Kotlin

You're reading from   Functional Kotlin Extend your OOP skills and implement Functional techniques in Kotlin and Arrow

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788476485
Length 350 pages
Edition 1st Edition
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Authors (2):
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Mario Arias Mario Arias
Author Profile Icon Mario Arias
Mario Arias
Rivu Chakraborty Rivu Chakraborty
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Rivu Chakraborty
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Toc

Table of Contents (16) Chapters Close

Preface 1. Kotlin – Data Types, Objects, and Classes FREE CHAPTER 2. Getting Started with Functional Programming 3. Immutability - It's Important 4. Functions, Function Types, and Side Effects 5. More on Functions 6. Delegates in Kotlin 7. Asynchronous Programming with Coroutines 8. Collections and Data Operations in Kotlin 9. Functional Programming and Reactive Programming 10. Functors, Applicatives, and Monads 11. Working with Streams in Kotlin 12. Getting Started with Arrow 13. Arrow Types 14. Kotlin's Quick Start 15. Other Books You May Enjoy

Memoization


Memoization is a technique to cache results of pure functions. A memoized function behaves as a normal function, but stores the result of previous computations associated with the parameters supplied to produce that result.

The classic example of memoization is Fibonacci:

import arrow.syntax.function.memoize
import kotlin.system.measureNanoTime

fun recursiveFib(n: Long): Long = if (n < 2) {
   n
} else {
   recursiveFib(n - 1) + recursiveFib(n - 2)
}

fun imperativeFib(n: Long): Long {
   return when (n) {
      0L -> 0
      1L -> 1
      else -> {
         var a = 0L
         var b = 1L
         var c = 0L
         for (i in 2..n) {
            c = a + b
            a = b
            b = c
         }
         c
      }
   }
}

fun main(args: Array<String>) {

   var lambdaFib: (Long) -> Long = { it } //Declared ahead to be used inside recursively

   lambdaFib = { n: Long ->
      if (n < 2) n else lambdaFib(n - 1) + lambdaFib(n - 2)
   }

   var memoizedFib...
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