Introduction

The algorithm learning collection is a project with the dual purpose of learning basic computer science algorithms and learning to program in the Rust language. Consider it akin to doing a bunch of programming lab homework by an advanced beginner programmer. It includes experiments in timing algorithms and an attempt at good coding practices, such as unit tests, and managing the code here on GitHub. It is not lost on me that I am reinventing many wheels here. That's somewhat the point. I attempt use features specific to Rust such as intentionally distinguishing of ownership of variables and borrowing of variables to test ideas. Please be kind with critiques. :-)

Source Material, Inspiration

Selected algorithms are based on lessons and pseudocode from:

Algorithms Illuminated Part 1: The Basics by Tim Roughgarden

This is an excellent book. Where appropriate I give references to the book chapters in the code and pseudocode is implemented as fair use of the text.

Included Algorithms

• Merge Sort of a Vector using the borrowing model in Rust
• Merge Sort of a Vector by passing ownership in Rust
• Merge Sort of a Vector of coordinate pairs (vector of 2-element arrays) on either x or y value
• Closest Pair Algorithm using a divide and conquer approach for selecting the two pairs in a coordinate vector with the smallest distance NOTE: Closest Pair Algorithm is currently failing tests. Still working on this one.
• Test functions to check that the above algorithms are working as designed using randomized data and more primitive processor-expensive algorithms for comparison.

Versions

Versions are tagged when they run mostly ok with an incrementing integer. No sub versions or numbers.

Use

Prior to first build: cargo update

To run the multiple algorithms with timing details output to console.

cargo run --release The release flag is important unless you want to run really slow. By default it will print out timings of execution so that you can see the timed progression of execution time of increased data.

To run the test suite: cargo test

TODO:

This is an ongoing project as I continue my study. Some general areas of improvement:

• More Algorithms!
• Repair broken algorithms not passing tests.
• Improve error handling.
• Miscellaneous Performance improvements of subroutines.
• Emulate a library for distribution as a crate.
• Detailed TODO items are included in source files.

License

I believe in strong open source licenses, even for small projects like this.

The Algorithm learning collection, a set of basic algorithms for improving programming skills and understanding of computer science principles, Copyright (C) 2021 github user: RustyPyGuy

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

See the file LICENSE for full details of the GPL v3.0.