Book Image

Hands-On Data Structures and Algorithms with Rust

By : Claus Matzinger
Book Image

Hands-On Data Structures and Algorithms with Rust

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)

Algorithm Evaluation

When looking at algorithms as defined entities, what makes one algorithm better than the other? Is it the number of steps required to finish? The amount of memory that is committed? CPU cycles? How do they compare across machines and operating systems with different memory allocators?

There are a lot of questions here that need answers, since comparing work with others is important in order to find the best approach possible to solve a given problem. In this chapter, you can look forward to learning about the following:

  • Evaluating algorithms in practice
  • Classifying algorithm and data structure behaviors
  • Estimating the plausibility of a better algorithm