wangzheng0822/algo
Algo
This project is a data structures and algorithms library providing a collection of fifty standard code implementations for managing data and solving common computational problems. It serves as an algorithm implementation reference and study resource for educational use.
The codebase covers graph theory implementations for modeling networks and performing searches, as well as string pattern matching libraries for the retrieval of character sequences. It includes a collection of hierarchical data structures, such as binary search trees and priority heaps, and provides optimized solutions for dynamic programming.
The library implements capabilities for sorting data collections, searching ordered data, and calculating shortest paths. It also provides implementations for fundamental data structures, including dynamic arrays, linked lists, stacks, and queues.
Features
- Algorithm Implementations - Provides a comprehensive collection of standard algorithm implementations for educational study.
- Adjacency Lists - Implements adjacency lists to represent graph topology for efficient network traversal.
- Stacks - Implements first-in-last-out structures for ordered data processing.
- Divide And Conquer Algorithms - Provides implementations of algorithms that decompose complex problems into smaller sub-problems.
- Graph Traversal Algorithms - Implements breadth-first and depth-first search algorithms for traversing complex graph networks.
- Pathfinding - Implements algorithms to find the most efficient paths between nodes in weighted graphs.
- Algorithmic Reference Implementations - Provides modular code patterns demonstrating standard computational logic for educational purposes.
- Fundamental Data Structures - Implements foundational structures including stacks, queues, linked lists, and heaps for data management.
- Graph Theory Algorithms - Implements graph theory algorithms including shortest path and network modeling for educational study.
- Sorting Algorithms - Implements various comparison and partitioning strategies to organize data collections.
- Algorithms and Data Structures - Provides a collection of fifty standard implementations of fundamental computational logic and data structures.
- Binary Search Trees - Builds binary search trees to support efficient sorted insertion, deletion, and traversal.
- Binary Search Algorithms - Locates specific elements within sorted collections using divide-and-conquer techniques.
- Dynamic Programming - Optimizes complex calculations by storing previously computed states to avoid redundant work.
- Dynamic Programming Techniques - Provides algorithmic strategies for solving complex optimization problems using overlapping subproblems and intermediate result storage.
- Shortest Path Algorithms - Implements algorithms to calculate the most efficient path between nodes in a graph.
- Sorting Algorithms - Implements various comparison and partitioning strategies to organize data collections.
- Dynamic Arrays - Implements resizable arrays that manage capacity and element storage dynamically.
- Linked Lists - Implements sequential node linking for constant-time insertions and deletions.
- Memoization Caches - Provides utilities for caching function results to avoid redundant computations in dynamic programming.
- Priority Heaps - Implements heap-based structures for efficient priority queue management.
- Priority Queues - Implements priority queues for efficiently extracting the highest or lowest value elements.
- String Matching Algorithms - Implements tree-based structures for fast string pattern matching and lookups.
- Tries - Organizes character sequences into a hierarchical structure for fast string pattern retrieval.
- Dynamic Programming Strategies - Provides educational resources on dynamic programming strategies for solving optimization problems.
- Recursive Problem Solving - Provides implementations for solving mathematical sequences and permutations using recursive decomposition.
- Topological Sorting - Determines linear ordering of elements to resolve dependencies in a network.
- Dynamic Programming Solvers - Implements optimization solutions using memoization and recursive decomposition.
- Recursive Algorithms - Employs the call stack to resolve nested dependencies and compute permutations.
- Trie-Based Matching - Organizes character sets into tree structures for fast string matching and lookups.
- Algorithms and Data Structures - Essential data structures and algorithm implementations.
