Algorithm Cookbook in Rust
A collection of classic data structures and algorithms, emphasizing beauty and clarity over full generality. As such, this should be viewed not as a blackbox library, but as a whitebox cookbook demonstrating the design and implementation of algorithms. I hope it will be useful to students and educators, as well as competition programmers.
This repository is distributed under the MIT License. The license text need not be included in contest submissions, though I would appreciate linking back to this repo for others to find. Enjoy!
For Students and Educators
When learning a new algorithm or data structure, it's often helpful to see or play with a concrete implementation. As such, this repository catalogues several classic algorithms in their simplest forms.
In addition, the Rust language has outstanding pedagogical attributes. Its compiler acts as a teacher, enforcing strict discipline while pointing to clearer ways to structure one's logic.
For Programming Contests
The original intent of this project was to build a reference for use in programming contests such as Codeforces, Hackerrank, and the Google Code Jam. As a result, it contains algorithms that are frequently useful to have in one's toolkit, with an emphasis on making the code concise and easy to modify under time pressure.
Most competition programmers rely on C++ for its fast execution time. However, it's notoriously unsafe, diverting a considerable share of the contestant's time and attention on mistake prevention and debugging. Java is the next most popular choice, offering a little safety at some expense to speed of coding and execution.
To my delight, I found that Rust provides even more bug-safety without the visual clutter, and it's fast. A proficient Rust programmer might stand to gain a competitive advantage as well as a more pleasant experience!
Programming Language Advocacy
My other goal is to appeal to developers who feel limited by older mainstream languages, to raise awareness that it doesn't have to be this way.
- Basic graph representations: adjacency lists, minimum spanning tree, Euler path, disjoint set union
- Network flows: Dinic's blocking flow, Hopcroft-Karp bipartite matching, min cost max flow
- Connected components: 2-edge-, 2-vertex- and strongly connected components, bridges, articulation points, topological sort, 2-SAT
- Associative range query: known colloquially as segtrees
- Math: Euclid's GCD algorithm, Bezout's identity
- Scanner: utility for reading input data
- String processing: Knuth-Morris-Pratt string matching, suffix arrays, Manacher's palindrome search