# Algos
[](https://crates.io/crates/algos)
[](https://docs.rs/algos)
[](https://github.com/Brad-Edwards/algos/actions/workflows/ci.yml)
[](https://github.com/Brad-Edwards/algos/blob/master/LICENSE)
## 🚧 Work in Progress 🚧
This crate is undergoing significant development. It aims to be a comprehensive collection of algorithms implemented in Rust, serving both as a learning resource and a practical library.
## Recent Changes
**Jan 16, 2025 - ADVISORY**: This crate has changed hands and will be maintained by [@Brad-Edwards](https://github.com/Brad-Edwards). The repository has been moved to [a new location](https://github.com/Brad-Edwards/algos).
## Overview
A Rust library implementing a wide range of algorithms, from fundamental computer science concepts to advanced machine learning techniques.
## Implementation Status
### ✅ Currently Implemented
#### Sorting Algorithms
✅ QuickSort
✅ MergeSort
✅ HeapSort
✅ BubbleSort
✅ InsertionSort
✅ SelectionSort
✅ ShellSort
✅ CountingSort
✅ RadixSort
✅ Randomized QuickSelect
✅ Randomized QuickSort
✅ BucketSort
#### Searching Algorithms
✅ Linear Search
✅ Binary Search
✅ Ternary Search
✅ Interpolation Search
✅ Jump Search
✅ Exponential Search
✅ Fibonacci Search
✅ Sublist Search
✅ Depth-First Search
✅ Breadth-First Search
#### String Algorithms
✅ Knuth-Morris-Pratt (KMP)
✅ Rabin-Karp
✅ Boyer-Moore
✅ Z-Algorithm
✅ Aho-Corasick
✅ Suffix Array Construction
✅ Suffix Automaton
✅ Suffix Tree
✅ Rolling Hash
✅ Manacher's Algorithm
#### Graph Algorithms (Part 1)
✅ Dijkstra's Algorithm
✅ Bellman-Ford Algorithm
✅ Floyd-Warshall Algorithm
✅ Prim's Algorithm
✅ Kruskal's Algorithm
✅ Tarjan's Algorithm (SCC)
✅ Kosaraju's Algorithm
✅ Johnson's Algorithm
✅ Warshall's Algorithm
✅ Topological Sort
#### Graph Algorithms (Part 2)
✅ Edmond–Karp (max flow)
✅ Dinic's Algorithm (max flow)
✅ Ford–Fulkerson (max flow)
✅ Hungarian Algorithm (assignment)
✅ Hopcroft–Karp (bipartite matching)
✅ Edmonds' Blossom Algorithm (max matching)
✅ Bron–Kerbosch (maximal clique)
✅ Johnson's Cycle Detection
✅ Floyd's Cycle Detection (Tortoise and Hare)
✅ Euler Tour / Euler Circuit Algorithm
✅ Hierholzer's Algorithm (Euler paths/circuits)
✅ Karger's Min Cut
✅ Randomized Delaunay Triangulation
✅ Randomized Kruskal's MST
✅ Randomized Prim's MST
#### Dynamic Programming
✅ Kadane's Algorithm
✅ Matrix Chain Multiplication
✅ Edit Distance
✅ Coin Change
✅ Longest Common Subsequence
✅ Longest Increasing Subsequence
✅ Weighted Interval Scheduling
✅ Viterbi Algorithm
✅ Bellman Equation-based DP
✅ Knuth Optimization
#### Hashing
✅ Perfect Hashing
✅ Universal Hashing
✅ Cuckoo Hashing
✅ Separate Chaining
✅ Open Addressing (linear/quadratic probing, double hashing)
✅ Polynomial Rolling Hash
✅ FNV (Fowler–Noll–Vo) Hash
✅ CRC32
✅ Jenkins Hash
✅ MurmurHash
#### Classic Machine Learning
✅ k-Means Clustering
✅ k-Nearest Neighbors (k-NN)
✅ Linear Regression (OLS)
✅ Logistic Regression
✅ Decision Tree Learning (ID3, C4.5)
✅ Random Forest
✅ Support Vector Machine (SVM)
✅ Naive Bayes
✅ Gradient Boosting (GBM family)
✅ XGBoost
#### ***DO NOT USE*** Cryptography and Security ***DO NOT USE***
✅ RSA
✅ Diffie–Hellman Key Exchange
✅ ElGamal Encryption
✅ AES (Rijndael)
✅ Blowfish
✅ Twofish
✅ SHA-256
✅ MD5 (legacy)
✅ Elliptic Curve Cryptography (ECC)
✅ DSA (Digital Signature Algorithm)
#### Deep Learning & Neural Network Training
✅ Backpropagation
✅ Stochastic Gradient Descent (SGD)
✅ Adam Optimizer
✅ RMSProp
✅ AdaGrad
✅ RProp (resilient propagation)
✅ Dropout (regularization)
✅ Batch Normalization
✅ Convolution (core of CNNs)
✅ BPTT (Backprop Through Time, RNNs/LSTMs)
#### Reinforcement Learning
✅ Q-Learning
✅ SARSA
✅ Double Q-Learning
✅ Deep Q-Network (DQN)
✅ Monte Carlo Exploring Starts
✅ Policy Gradients (REINFORCE)
✅ Actor–Critic Methods
✅ Proximal Policy Optimization (PPO)
✅ Trust Region Policy Optimization (TRPO)
✅ AlphaZero-Style MCTS + RL
#### Approximation Algorithms
✅ Greedy Set Cover
✅ 2-Approximation for Vertex Cover
✅ PTAS for Knapsack
✅ Christofides' Algorithm (TSP)
✅ Johnson's Algorithm for MAX-SAT
✅ FPTAS for Subset Sum
✅ Local-Ratio Theorem
✅ Primal–Dual Approximation (for covering problems)
✅ LP Rounding (generic approach)
✅ Goemans–Williamson (Max-Cut)
#### Linear & Nonlinear Optimization
✅ Gradient Descent
✅ Newton's Method
✅ Conjugate Gradient
✅ BFGS
✅ L-BFGS
✅ Simplex Method (linear programming)
✅ Interior Point Method (LP/NLP)
✅ Nelder–Mead
✅ Genetic Algorithm
✅ Simulated Annealing
#### Integer Linear Programming Methods
✅ Branch and Bound
✅ Branch and Cut
✅ Branch and Price
✅ Gomory Cutting Planes
✅ Dantzig–Wolfe Decomposition
✅ Benders Decomposition
✅ Mixed Integer Rounding Cuts
✅ Lift-and-Project Cuts
✅ Branch & Reduce
✅ Column Generation
#### Randomized Algorithms
✅ Randomized BFS 2-SAT
✅ Reservoir Sampling
✅ Skip List
#### Monte Carlo Methods
✅ Monte Carlo Integration
#### Combinatorial & Backtracking
✅ Backtracking for Permutations/Combinations
✅ Johnson–Trotter (permutation generation)
✅ Gray Code Generation
✅ Knuth's Dancing Links (Algorithm X)
✅ Zassenhaus Algorithm (group factorization)
✅ Hamiltonian Cycle Backtracking
✅ Subset Generation (binary representation)
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
## License
This project is licensed under the BSD 3-Clause License - see the [LICENSE](LICENSE) file for details.