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

Advanced problem solving


Backtracking calculates and finds the best overall solution to a particular problem. However, as described in Chapter 18, Algorithm Evaluation, there are problems that have a really large computational complexity, which leads to a really long running time. Since this is unlikely to be solved by simply making computers faster, smarter approaches are required.

With several strategies and techniques available, the choice is yours to find an approach that best solves your problem. The position of Rust in this space can be critical, thanks to its great speed and memory efficiency, so keeping an eye on solutions for complex problems might pay off in the future (in the author's opinion).

 

First up is a surprising programming technique that is aimed at improving the complexities of backtracking algorithms: dynamic programming.

Dynamic programming

The concept of dynamic programming is one of these techniques that you thought had a different name: caching. The fundamental idea...