Book Image

Learn Kotlin Programming - Second Edition

By : Stephen Samuel, Stefan Bocutiu
Book Image

Learn Kotlin Programming - Second Edition

By: Stephen Samuel, Stefan Bocutiu

Overview of this book

Kotlin is a general-purpose programming language used for developing cross-platform applications. Complete with a comprehensive introduction and projects covering the full set of Kotlin programming features, this book will take you through the fundamentals of Kotlin and get you up to speed in no time. Learn Kotlin Programming covers the installation, tools, and how to write basic programs in Kotlin. You'll learn how to implement object-oriented programming in Kotlin and easily reuse your program or parts of it. The book explains DSL construction, serialization, null safety aspects, and type parameterization to help you build robust apps. You'll learn how to destructure expressions and write your own. You'll then get to grips with building scalable apps by exploring advanced topics such as testing, concurrency, microservices, coroutines, and Kotlin DSL builders. Furthermore, you'll be introduced to the kotlinx.serialization framework, which is used to persist objects in JSON, Protobuf, and other formats. By the end of this book, you'll be well versed with all the new features in Kotlin and will be able to build robust applications skillfully.
Table of Contents (21 chapters)
Free Chapter
1
Section 1: Fundamental Concepts in Kotlin
5
Section 2: Practical Concepts in Kotlin
15
Section 3: Advanced Concepts in Kotlin

Concurrency

You've most likely heard of Moore's Law. In 1965, Gordon Moore noticed that the number of transistors that could be fit on a circuit board per square inch had doubled every year since their invention. Moore's Law was the name given to the belief that this would continue, albeit every 18 months. So far, this has been remarkably correct. The upshot is that computers are getting faster and smaller, and they use less power; one example is the ubiquity of mobile phones.

However, nothing lasts forever. The exponential growth in the context of processing power is already tailing off. If we are unable to continually make systems work faster by increasing raw speed, we must look for an alternative.

One such alternative is to split programs into parts that can run concurrently and then use multiple processors. Together, a collection of slower chips can perform...