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  • Book Overview & Buying Swift Data Structure and Algorithms
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Swift Data Structure and Algorithms

Swift Data Structure and Algorithms

By : Erik Azar, Mario Eguiluz Alebicto
3.7 (3)
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Swift Data Structure and Algorithms

Swift Data Structure and Algorithms

3.7 (3)
By: Erik Azar, Mario Eguiluz Alebicto

Overview of this book

Apple’s Swift language has expressive features that are familiar to those working with modern functional languages, but also provides backward support for Objective-C and Apple’s legacy frameworks. These features are attracting many new developers to start creating applications for OS X and iOS using Swift. Designing an application to scale while processing large amounts of data or provide fast and efficient searching can be complex, especially running on mobile devices with limited memory and bandwidth. Learning about best practices and knowing how to select the best data structure and algorithm in Swift is crucial to the success of your application and will help ensure your application is a success. That’s what this book will teach you. Starting at the beginning, this book will cover the basic data structures and Swift types, and introduce asymptotic analysis. You’ll learn about the standard library collections and bridging between Swift and Objective-C collections. You will see how to implement advanced data structures, sort algorithms, work with trees, advanced searching methods, use graphs, and performance and algorithm efficiency. You’ll also see how to choose the perfect algorithm for your problem.
Table of Contents (10 chapters)
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Binary search trees


Binary search tree basic operations such as access, search, insertion, and deletion take between O(n) and O(log(n)) time. Being both values the worst and the average scenarios. At the end, these times are going to depend on the height of the tree itself.

For example, for a complete binary search tree with n nodes, these operations could take O(log(n)) time. But if a tree with the same number of nodes n is built like a linked list (just 1 child per node), having more levels/depth for the same n nodes, then the operations are going to take O(n) time.

In order to make basic operations such as insertion or search, we need to scan nodes from the root to the leaves. Because of this, we can infer that the height of the tree (the distance or nodes between the root and a leaf) will affect the time we spend performing basic operations.

Now, before jumping into the code of some operations, such as inserting and searching nodes in a binary search tree, lets recall the basic property...

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Swift Data Structure and Algorithms
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