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 15. Robust Trees

Lists are great for storing a bunch of items, but what about looking up specific elements? In the previous chapter, a skip list greatly outperformed a regular linked list when simply finding an item. Why? Because it was utilizing an iteration strategy that resembles that of a balanced tree structure: there, the internal order lets the algorithm strategically skip items. However, that's only the beginning. Many libraries, databases, and search engines are built on trees; in fact, whenever a program is compiled, the compiler creates an abstract syntax tree.

Tree-based data structures incorporate all kinds of smart ideas that we will explore in this chapter, so you can look forward to the following:

  • Implementing and understanding a binary search tree
  • Learning about self-balancing trees
  • How prefix or suffix trees work
  • What a priority queue uses internally
  • Graphs, the most general tree structure