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Kotlin Design Patterns and Best Practices - Second Edition

You're reading from  Kotlin Design Patterns and Best Practices - Second Edition

Product type Book
Published in Jan 2022
Publisher Packt
ISBN-13 9781801815727
Pages 356 pages
Edition 2nd Edition
Languages
Author (1):
Alexey Soshin Alexey Soshin
Profile icon Alexey Soshin

Table of Contents (17) Chapters

Preface 1. Section 1: Classical Patterns
2. Chapter 1: Getting Started with Kotlin 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

Implementing Algebraic Data Types

Algebraic Data Types, or ATDs for short, is a concept from functional programming and is very similar to the Composite design pattern we discussed in Chapter 3, Understanding Structural Patterns.

To understand how ADTs work and what their benefits are, let's discuss how we can implement a simple binary tree in Kotlin.

First, let's declare an interface for our tree. Since a tree data structure can contain any type of data, we can parameterize it with a type (T):

sealed interface Tree<out T>

The type is marked with an out keyword, which means that this type is covariant. If you aren't familiar with this term, we'll cover it later, while implementing the interface.

The opposite of a covariant is a contravariant. Contravariant types should be marked using the in keyword.

We can also mark this interface with a sealed keyword. We saw this keyword applied to regular classes in Chapter 4, Getting Familiar with Behavioral...

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