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  • Book Overview & Buying Hands-On Data Structures and Algorithms with Rust
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Hands-On Data Structures and Algorithms with Rust

Hands-On Data Structures and Algorithms with Rust

By : Claus Matzinger
2.7 (3)
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Hands-On Data Structures and Algorithms with Rust

Hands-On Data Structures and Algorithms with Rust

2.7 (3)
By: Claus Matzinger

Overview of this book

Rust has come a long way and is now utilized in several contexts. Its key strengths are its software infrastructure and resource-constrained applications, including desktop applications, servers, and performance-critical applications, not forgetting its importance in systems' programming. This book will be your guide as it takes you through implementing classic data structures and algorithms in Rust, helping you to get up and running as a confident Rust programmer. The book begins with an introduction to Rust data structures and algorithms, while also covering essential language constructs. You will learn how to store data using linked lists, arrays, stacks, and queues. You will also learn how to implement sorting and searching algorithms. You will learn how to attain high performance by implementing algorithms to string data types and implement hash structures in algorithm design. The book will examine algorithm analysis, including Brute Force algorithms, Greedy algorithms, Divide and Conquer algorithms, Dynamic Programming, and Backtracking. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications.
Table of Contents (15 chapters)
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Pseudo-random numbers

In the last few years, random number generation has seen an interesting rise in popularity, yet many developers simply accept the generator provided by whatever technology they use. However, good random numbers are critical for many applications, such as encryption and security (or the lack thereof; see 2010's Sony PlayStation 3 security incident that prompted a famous XKCD—https://xkcd.com/221/), simulation, games, statistics, and biology.

As a basic principle: the more random a sequence is, the better. The reason for this is obvious. If any number in a sequence of random numbers is statistically dependent on one of the others, it becomes a pattern that can be predicted, and there is no such thing as predictable randomness. Thus, the numbers in a random sequence have to be statistically independent to qualify as good random numbers.

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Hands-On Data Structures and Algorithms with Rust
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