Book Image

The Complete Rust Programming Reference Guide

By : Rahul Sharma, Vesa Kaihlavirta, Claus Matzinger
Book Image

The Complete Rust Programming Reference Guide

By: Rahul Sharma, Vesa Kaihlavirta, Claus Matzinger

Overview of this book

Rust is a powerful language with a rare combination of safety, speed, and zero-cost abstractions. This Learning Path is filled with clear and simple explanations of its features along with real-world examples, demonstrating how you can build robust, scalable, and reliable programs. You’ll get started with an introduction to Rust data structures, algorithms, and essential language constructs. Next, you will understand how to store data using linked lists, arrays, stacks, and queues. You’ll also learn to implement sorting and searching algorithms, such as Brute Force algorithms, Greedy algorithms, Dynamic Programming, and Backtracking. As you progress, you’ll pick up on using Rust for systems programming, network programming, and the web. You’ll then move on to discover a variety of techniques, right from writing memory-safe code, to building idiomatic Rust libraries, and even advanced macros. By the end of this Learning Path, you’ll be able to implement Rust for enterprise projects, writing better tests and documentation, designing for performance, and creating idiomatic Rust code. This Learning Path includes content from the following Packt products: • Mastering Rust - Second Edition by Rahul Sharma and Vesa Kaihlavirta • Hands-On Data Structures and Algorithms with Rust by Claus Matzinger
Table of Contents (29 chapters)
Title Page
Copyright
About Packt
Contributors
Preface
Index

Summary


Putting things in order is a very fundamental problem that has been solved in many different ways, varying in aspects such as worst-case runtime complexity, memory required, the relative order of equal elements (stability), as well as overall strategies. A few fundamental approaches were presented in this chapter.

Bubble sort is one of the simplest algorithms to implement, but it comes at a high runtime cost, with a worst-case behavior of O(n²). This is due to the fact that it simply swaps elements based on a nested loop, which makes elements "bubble up" to either end of the collection.

Shell sort can be seen as an improved version of bubble sort, with a major upside: it does not start off by swapping neighbors. Instead, there is a gap that elements are compared and swapped across, covering a greater distance. This gap size changes with every round that shows worst-case runtime complexities of O(n²) for the original scheme to O(n log n) in the fastest variant. In fact, the runtime...