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)

Red-black tree

With the previous tree structure, there was a major downside: a previously unknown sequence of keys that is inserted into the tree cannot be sorted. Think of how most identifiers are generated; they are typically ascending numbers. Shuffling these numbers won't always work, especially when they are gradually added. Since this leads to an unbalanced tree (the extreme case behaves just like a list), Rudolf Bayer came up with the idea of a special, self-balancing tree: the red-black tree.

This tree is a binary search tree that adds logic to rebalance after inserts. Within this operation, it is crucial to know when to stop "balancing"—which is where the inventor thought to use two colors: red and black.

In literature, the red-black tree is described as a binary search tree that satisfies a set of rules:

  • The root node is always black
  • Each other...