Introduction to Concurrency

This is the first article in our series on SwiftUI Concurrency. With SwiftUI, one of the most well-liked frameworks for creating user interfaces in the Apple ecosystem, we will be examining concurrent programming in this series.

In this article, we will define concurrency and discuss how it relates to SwiftUI development. We will also look at a few of the typical difficulties that come up when dealing with concurrent code.

Concurrency is a huge asset for SwiftUI as a framework for creating user interfaces. For instance, SwiftUI’s user interface is described using declarative syntax, which necessitates that the framework modify the view hierarchy in response to changes in the underlying data. When updating complex views or large data sets, this process can be computationally expensive.

SwiftUI can enhance view update performance through concurrency, resulting in a more streamlined user experience.

Working with concurrent code, however, can be difficult. Deadlocks, synchronization problems, and race conditions are all frequent problems in concurrent programming. Due to the necessity of updating the user interface on the main thread and the possibility of data races when multiple views access the same data at once, SwiftUI also faces additional difficulties.

This series will examine various concurrency patterns and methods that SwiftUI developers can employ to solve these problems and enhance performance. We will talk about the following concurrency design patterns:

  • Observer Pattern
  • Combinator Pattern
  • Producer-Consumer Pattern
  • Semaphore Pattern
  • Futures and Promises Pattern

What is Concurrency?


Concurrency is defined as a system’s capacity to carry out multiple tasks concurrently or to appear to do so. In other words, concurrency enables the simultaneous execution of multiple tasks without regard to their sequence or order. There are many ways to implement concurrency, including parallelism, asynchronous programming, and multi-threading.

Multiple threads of the same program are run concurrently on various processors or cores of the same machine when multi-threading. By utilizing callbacks, promises, or futures, asynchronous programming enables a single thread to manage numerous tasks concurrently. By using parallelism, a single task can be broken up into several smaller ones that can run concurrently on various processors or machines.

Because it enables developers to increase performance and responsiveness by allowing various components of the application to execute concurrently, concurrency is particularly important in contemporary software development. For instance, a web application can render the user interface, process user input, and execute database queries simultaneously, resulting in quicker response times and a better user experience.

### Contrast with Parallelism

Parallelism and concurrency are two distinct concepts that are frequently mixed up. Executing multiple tasks concurrently across various processors or machines is known as parallelism. For parallelism to work properly, there must be synchronization and coordination between various tasks.

Contrarily, concurrency enables the simultaneous execution of many tasks without necessitating that they be carried out on various processors or devices. Instead, several processes can be run simultaneously on a single processor or core while being scheduled and carried out in a precise order to achieve concurrency.

In high-performance computing applications like scientific simulations or video encoding, where the tasks need a lot of processing and can be readily broken down into smaller tasks that can be carried out in parallel, parallelism is frequently used.

Advantages and disadvantages of Concurrency

The advantages and disadvantages of concurrency include better performance, responsiveness, and scalability for software development. Concurrency reduces the amount of time needed to accomplish various operations, which enhances the performance of programs by enabling several tasks to be completed simultaneously.

By allowing users to interact with a program while it is working on other tasks in the background, concurrency also makes software more responsive. This can be crucial for real-time interaction-based applications like online gaming or video conferencing.

Scalability is a benefit of concurrency as well. Concurrency enables an application to handle more requests as the number of users or requests increases without slowing down or crashing.

Concurrency, however, also brings with it both difficulties and disadvantages. Coordination and synchronization between several tasks is one of the key difficulties of concurrency. Concurrency can lead to race situations, deadlocks, and other problems that can compromise the accuracy and dependability of the application without effective coordination and synchronization.

Concurrency can also add complexity and costs, especially in programs that call for synchronization between many tasks. Concurrent code can be harder to debug and test than single-threaded code, therefore developers must be aware of potential problems and design patterns to make sure the concurrent code is dependable and correct.