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Kotlin Design Patterns and Best Practices

You're reading from   Kotlin Design Patterns and Best Practices Build scalable applications using traditional, reactive, and concurrent design patterns in Kotlin

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801815727
Length 356 pages
Edition 2nd Edition
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Author (1):
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Alexey Soshin Alexey Soshin
Author Profile Icon Alexey Soshin
Alexey Soshin
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Classical Patterns
2. Chapter 1: Getting Started with Kotlin FREE CHAPTER 3. Chapter 2: Working with Creational Patterns 4. Chapter 3: Understanding Structural Patterns 5. Chapter 4: Getting Familiar with Behavioral Patterns 6. Section 2: Reactive and Concurrent Patterns
7. Chapter 5: Introducing Functional Programming 8. Chapter 6: Threads and Coroutines 9. Chapter 7: Controlling the Data Flow 10. Chapter 8: Designing for Concurrency 11. Section 3: Practical Application of Design Patterns
12. Chapter 9: Idioms and Anti-Patterns 13. Chapter 10: Concurrent Microservices with Ktor 14. Chapter 11: Reactive Microservices with Vert.x 15. Assessments 16. Other Books You May Enjoy

Recursion

Recursion is a function invoking itself with new arguments. Many well-known algorithms, such as Depth First Search, rely on recursion.

Here is an example of a very inefficient function that uses recursion to calculate the sum of all the numbers in a given list:

fun sumRec(i: Int, sum: Long, numbers: List<Int>): Long {
    return if (i == numbers.size) {
        return sum
    } else {
        sumRec(i+1, numbers[i] + sum, numbers)
    }
}

We often try to avoid recursion due to the stack overflow errors that we may receive if our call stack is too deep. You can call this function with a list that contains a million numbers to demonstrate this:

val numbers = List(1_000_000) {it}
println(sumRec(0,  numbers)) 
// Crashed pretty soon, around 7K

However, Kotlin supports an optimization called tail recursion. One...

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