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

Chapter 21. Random and Combinatorial

While sorting and searching are two very fundamental problems in computer science, they are far from the only ones. In fact, those problems have been thoroughly solved by people who deeply specialize in such things. In today's world, it is more likely that a solution to a real-world problem involves generating random numbers, the best possible combination of several items (combinatorics) , "rolling up" several time periods into single numbers, and visualizing the results. Random number generation algorithms and solving combinatorial problems efficiently have become very important. Especially for the latter, the implementation will be specific to the solution, but there are fundamental approaches that remain. In this chapter, we will discuss a few of these fundamental approaches and learn about the following:

  • Implementing backtracking algorithms
  • Utilizing dynamic programming techniques
  • How a pseudo-random number generator works