JavaScript Top-Level Data Structures and Algorithms Overview This repository is a comprehensive collection of JavaScript implementations of top-level data structures and algorithms. The goal is to provide a resource for developers to learn and understand fundamental data structures and algorithms commonly used in computer science and software development.
Table of Contents Introduction Data Structures Arrays Linked Lists Stacks Queues Trees Hash Tables Heaps Graphs Algorithms Sorting Searching Recursion Dynamic Programming Greedy Algorithms Graph Algorithms Usage Contributing License Introduction Understanding data structures and algorithms is crucial for writing efficient and scalable code. This repository aims to provide clear and concise JavaScript implementations of various data structures and algorithms, along with explanations of their usage and complexity analysis.
Data Structures Arrays JavaScript arrays are essential for storing and manipulating collections of data.
Linked Lists Linked lists are linear data structures where elements are stored in nodes, and each node points to the next one.
Stacks Stacks follow the Last In, First Out (LIFO) principle and are often used for managing function calls, parsing expressions, and undo mechanisms.
Queues Queues follow the First In, First Out (FIFO) principle and are useful for tasks such as task scheduling and managing resources.
Trees Tree structures are hierarchical and include binary trees, binary search trees, and AVL trees.
Hash Tables Hash tables provide efficient data retrieval by mapping keys to values using a hash function.
Heaps Heaps are tree-based data structures used for implementing priority queues and efficient sorting algorithms.
Graphs Graphs consist of nodes and edges and are used to model relationships between different entities.
Algorithms Sorting Various sorting algorithms such as bubble sort, selection sort, insertion sort, merge sort, and quicksort are implemented.
Searching Searching algorithms include linear search, binary search, and depth-first search.
Recursion Examples of recursive algorithms and their applications.
Dynamic Programming Dynamic programming techniques for solving optimization problems.
Greedy Algorithms Greedy algorithms make locally optimal choices at each stage with the hope of finding a global optimum.
Graph Algorithms Graph traversal algorithms, shortest path algorithms, and depth-first search (DFS) and breadth-first search (BFS) implementations.
Usage Each data structure and algorithm is organized in its own directory with clear documentation and examples. Users can simply include the necessary files in their projects or explore the code for learning purposes.
Contributing Contributions are welcome! If you have improvements, bug fixes, or new data structures/algorithms to add, please follow the contribution guidelines outlined in the CONTRIBUTING.md file.
License This repository is licensed under the MIT License. Feel free to use, modify, and distribute the code for both commercial and non-commercial purposes.
Happy coding! 🚀