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Swift Functional Programming

You're reading from   Swift Functional Programming Ease the creation, testing, and maintenance of Swift codes

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781787284500
Length 316 pages
Edition 2nd Edition
Languages
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Author (1):
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Dr. Fatih Nayebi Dr. Fatih Nayebi
Author Profile Icon Dr. Fatih Nayebi
Dr. Fatih Nayebi
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Table of Contents (19) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface
1. Getting Started with Functional Programming in Swift FREE CHAPTER 2. Functions and Closures 3. Types and Type Casting 4. Enumerations and Pattern Matching 5. Generics and Associated Type Protocols 6. Map, Filter, and Reduce 7. Dealing with Optionals 8. Functional Data Structures 9. Importance of Immutability 10. Best of Both Worlds and Combining FP Paradigms with OOP 11. Case Study - Developing an iOS Application with FP and OOP Paradigms

Memoization


In previous sections, we talked about functions as building blocks and explained that we can compose our applications with functions. If functions can be building blocks in our programs, then they should be cacheable! But how do we cache them? The answer is memoization.

Memoization is the process of storing the result of functions, given their input, in order to improve the performance of our programs. We can memoize pure functions as pure functions do not rely on external data and do not change anything outside themselves. Pure functions provide the same result for a given input every time. Therefore, we can save or cache the results (in other words, memoize the results) given their inputs and use them in the future without going through the calculation process.

To be able to understand the concept, let's look at the following example in which we will manually memoize the power2 function:

var memo = Dictionary<Int, Int>() 

func memoizedPower2(n: Int) -> Int { 
    if...
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