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The Complete Rust Programming Reference Guide

You're reading from   The Complete Rust Programming Reference Guide Design, develop, and deploy effective software systems using the advanced constructs of Rust

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Product type Course
Published in May 2019
Publisher Packt
ISBN-13 9781838828103
Length 698 pages
Edition 1st Edition
Languages
Concepts
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Authors (3):
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Vesa Kaihlavirta Vesa Kaihlavirta
Author Profile Icon Vesa Kaihlavirta
Vesa Kaihlavirta
Rahul Sharma Rahul Sharma
Author Profile Icon Rahul Sharma
Rahul Sharma
Claus Matzinger Claus Matzinger
Author Profile Icon Claus Matzinger
Claus Matzinger
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Toc

Table of Contents (29) Chapters Close

Title Page
Copyright
About Packt
Contributors
Preface
1. Getting Started with Rust FREE CHAPTER 2. Managing Projects with Cargo 3. Tests, Documentation, and Benchmarks 4. Types, Generics, and Traits 5. Memory Management and Safety 6. Error Handling 7. Advanced Concepts 8. Concurrency 9. Metaprogramming with Macros 10. Unsafe Rust and Foreign Function Interfaces 11. Logging 12. Network Programming in Rust 13. Building Web Applications with Rust 14. Lists, Lists, and More Lists 15. Robust Trees 16. Exploring Maps and Sets 17. Collections in Rust 18. Algorithm Evaluation 19. Ordering Things 20. Finding Stuff 21. Random and Combinatorial 22. Algorithms of the Standard Library 1. Other Books You May Enjoy Index

Summary


Search, as a part of the information retrieval (among others) process, is an elementary way of finding something independently of the data structure being used. There are three popular types of algorithm: linear search, jump search, and binary search. Completely different approaches (such as locally-sensitive hashing) have been discussed in an earlier chapter about maps and sets, but they still need a mechanism to compare quickly.

A linear search is the least complex approach: iterate over a collection and compare the items with the element that is to be found. This has also been implemented in Rust's iterator and exhibits O(n) runtime complexity.

Jump searches are superior. By operating on a sorted collection, they can use a step size that is greater than 1 (like a linear search) in order to skip to the required parts faster by checking whether the relevant section has already passed. While faster in absolute terms, the worst-case runtime complexity is still O(n).

The (at the time...

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