Welcome to the Data Structures and Algorithm Analysis repository. This repository contains a collection of data structures and algorithms implemented in various programming languages. It is designed to help students and developers understand, practice, and master the fundamentals of data structures and algorithms.
Data structures and algorithms are essential for writing efficient and effective code. This repository aims to provide a comprehensive resource for learning and implementing these concepts. Each data structure and algorithm is accompanied by explanations, use cases, and code examples.
- Implementations of various data structures (e.g., arrays, linked lists, stacks, queues, trees, graphs, hash tables).
- Implementations of common algorithms (e.g., sorting, searching, dynamic programming, graph algorithms).
- Code examples in multiple programming languages.
- Detailed explanations and use cases for each data structure and algorithm.
- Unit tests for each implementation to ensure correctness.
To get started with the code in this repository, follow these steps:
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Clone the repository:
git clone https://github.com/agneepradeep/Data-Structures-And-Algorithm-Analysis.git cd Data-Structures-And-Algorithm-Analysis
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Navigate to the relevant directory: Each data structure and algorithm is organized into separate directories. Navigate to the desired directory to find the implementation and related files.
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Run the code: Follow the instructions in the specific directory's README or comments in the code files to compile and run the implementations.
The repository includes the following data structures:
- Arrays: Dynamic arrays, multi-dimensional arrays.
- Linked Lists: Singly linked list, doubly linked list, circular linked list.
- Stacks: Array-based stack, linked list-based stack.
- Queues: Array-based queue, linked list-based queue, circular queue, priority queue.
- Trees: Binary tree, binary search tree, AVL tree, red-black tree, segment tree, trie.
- Graphs: Adjacency list, adjacency matrix, graph traversal algorithms.
- Hash Tables: Hash functions, collision resolution techniques (chaining, open addressing).
The repository includes implementations of the following algorithms:
- Bubble Sort
- Selection Sort
- Insertion Sort
- Merge Sort
- Quick Sort
- Heap Sort
- Radix Sort
- Linear Search
- Binary Search
- Depth-First Search (DFS)
- Breadth-First Search (BFS)
- Fibonacci Sequence
- Knapsack Problem
- Longest Common Subsequence
- Matrix Chain Multiplication
- Dijkstra's Algorithm
- Kruskal's Algorithm
- Prim's Algorithm
- Floyd-Warshall Algorithm
Contributions are welcome! If you have any improvements, bug fixes, or new implementations to add, please fork the repository and create a pull request. Ensure that your code follows the repository's coding standards and includes appropriate documentation and tests.
This repository is licensed under the MIT License. See the LICENSE file for more details.
If you have any questions, suggestions, or feedback, feel free to contact me.
Happy coding!
Agneepradeep Verma