Book Image

Learning Concurrency in Kotlin

By : Miguel Angel Castiblanco Torres
Book Image

Learning Concurrency in Kotlin

By: Miguel Angel Castiblanco Torres

Overview of this book

Kotlin is a modern and statically typed programming language with support for concurrency. Complete with detailed explanations of essential concepts, practical examples and self-assessment questions, Learning Concurrency in Kotlin addresses the unique challenges in design and implementation of concurrent code. This practical guide will help you to build distributed and scalable applications using Kotlin. Beginning with an introduction to Kotlin's coroutines, you’ll learn how to write concurrent code and understand the fundamental concepts needed to write multithreaded software in Kotlin. You'll explore how to communicate between and synchronize your threads and coroutines to write collaborative asynchronous applications. You'll also learn how to handle errors and exceptions, as well as how to work with a multicore processor to run several programs in parallel. In addition to this, you’ll delve into how coroutines work with each other. Finally, you’ll be able to build an Android application such as an RSS reader by putting your knowledge into practice. By the end of this book, you’ll have learned techniques and skills to write optimized code and multithread applications.
Table of Contents (11 chapters)


This chapter has covered some really important topics on how to use Kotlin to prevent common pitfalls of concurrent programming. All the different tools covered in this chapter will come in handy in different circumstances when you are writing concurrent applications. In the same way an actor is a mix of a coroutine with a channel, you can mix many of the solutions covered here to create an implementation that meets your requirements.

As mentioned at the beginning of this chapter, you shouldn't limit these tools to atomicity violation. They will help you to tackle other concurrency challenges as well.

Let's recap this chapter and the more important topics:

  • Having a shared state can be a problem in concurrent code. A thread's cache and the atomicity of memory access can cause modifications coming from different threads to be lost. It can also cause the state...