One of the most-read posts on this blog is this one about typical iOS take-home coding exercises. The post has 3,797 views at time of writing, and several readers have privately thanked me for writing it. But, in my experience, the application process for many companies involves not a take-home coding exercise but rather a live-coding exercise. The candidate typically has forty-five minutes to implement an app from scratch that is similar to the app described in the post mentioned above but without unit tests or dependency injection.

The live-coding exercise is a different beast. Much of the knowledge required for a take-home coding exercise is applicable to a live-coding exercise, but the extreme time constraint of a live-coding exercise means that success is unlikely without extreme practice, preparation, and time-saving. Worse, the competitiveness of the job market means that, even if you complete 80% of the requirements of a live-coding exercise, you will be rejected in favor of another candidate who completes 100%.

In this post, I describe practice, preparation, and execution that make success in a live-coding exercise more likely. In an accompanying YouTube video, I apply this knowledge and complete a live-coding exercise within forty-five minutes.

This post is not about preparing for and succeeding in data-structure-and-algorithm interviews. Learning materials for those interviews are available elsewhere.

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Loyal readers of this blog may have noticed a decrease in post frequency since January 2023. The reason for this decrease is that I spent most of 2023 creating a video course, iOSExpert. This post describes iOSExpert and presents some learnings from the creation process.

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In a recent post, I presented an approach for succeeding on take-home iOS-developer coding challenges. (For brevity, I henceforth refer to these particular coding challenges as “coding challenges”.) The model solution in that post used UIKit because, at the time I wrote the post, I had already completed coding challenges using that framework. But SwiftUI may be a good, or indeed the best, option.

My goal in this post is to help readers who are are considering or have been assigned a SwiftUI-based coding challenge.

This post presents factors for the UIKit-or-SwiftUI decision. This post then addresses certain challenges posed by a SwiftUI solution, including architecture, dependency injection, testing, image caching, and Identifiable.

In the course of discussing these considerations and challenges, this post introduces a SwiftUI model solution, KatFancy, and uses that solution for illustrative purposes.

To derive maximum benefit from this post, readers should review the original post before reading this one. Most of the content of that post is relevant to all coding challenges.

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