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)

Chapter 7

Which std::collections data structure is not discussed here?

BinaryHeap (

How does Vec<T> or VecDeque<T> grow, as of 2018?

They double (or more) their size when more space is required.

Is LinkedList<T> a good default data structure?

No. It doesn't provide index access and is generally slower than Vec<T>, thanks to the internal memory structure, but provides the same basic features.

What hashing implementation does the 2018 HashMap<T> use by default?

SipHashing. There are others that are on their way into the standard library, such as the hashbrown crate (

What are three benefits of BTreeMap<T> over HashMap<T>?

Use any three, but here are some suggestions:

  • Ordered keys
  • Lower computational intensity (no hashing required...