Hands-On Data Structures and Algorithms with Rust: Learn programming techniques to build effective, maintainable, and readable code in Rust 2018

Hands-On Data Structures and Algorithms with Rust: Learn programming techniques to build effective, maintainable, and readable code in Rust 2018

English | 2019 | ISBN: 978-1788995528 | 316 Pages | PDF, EPUB | 15 MB

Design and implement professional level programs by exploring modern data structures and algorithms in Rust.
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.
What you will learn

  • Design and implement complex data structures in Rust
  • Analyze, implement, and improve searching and sorting algorithms in Rust
  • Create and use well-tested and reusable components with Rust
  • Understand the basics of multithreaded programming and advanced algorithm design
  • Become familiar with application profiling based on benchmarking and testing
  • Explore the borrowing complexity of implementing algorithms
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