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Hands-On Data Structures and Algorithms with Rust

You're reading from   Hands-On Data Structures and Algorithms with Rust Learn programming techniques to build effective, maintainable, and readable code in Rust 2018

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788995528
Length 316 pages
Edition 1st Edition
Languages
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Author (1):
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Claus Matzinger Claus Matzinger
Author Profile Icon Claus Matzinger
Claus Matzinger
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Table of Contents (15) Chapters Close

Preface 1. Hello Rust! FREE CHAPTER 2. Cargo and Crates 3. Storing Efficiently 4. Lists, Lists, and More Lists 5. Robust Trees 6. Exploring Maps and Sets 7. Collections in Rust 8. Algorithm Evaluation 9. Ordering Things 10. Finding Stuff 11. Random and Combinatorial 12. Algorithms of the Standard Library 13. Assessments 14. Other Books You May Enjoy

Neighborhood search

Neighborhood search is a very trivial algorithm: starting from the node provided, follow every edge and return what you find. In our case, the degree of the relationship is important.

Just like for the tree algorithms shown previously, recursion is a great choice for solving this problem. While an iterative solution will often be more memory-efficient (no stack overflows), recursion is way more descriptive once you get the hang of it. Additionally, some compilers (and partly rustc, but not guaranteed) will expand the recursion into a loop, providing the best of both worlds (look for tail call optimization)! Obviously, the most important thing is to have a projected growth in mind; 100,000 recursive calls are likely to fill up the stack.

However, the function to run the neighborhood is implemented two-fold. First, the public-facing function takes care of validating input data and sees whether the node actually exists:

pub fn connected(&self, from: KeyType, degree...
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