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Back to trekhleb/javascript-algorithms

Open-source alternatives to Javascript Algorithms

30 open-source projects similar to trekhleb/javascript-algorithms, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Javascript Algorithms alternative.

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    This project is a reference collection for computer science fundamentals, providing a study guide and cheat sheets for algorithms and data structures. It serves as a resource for technical interview preparation, combining theoretical knowledge with practical implementation patterns for coding challenges. The content includes a comparative guide for analyzing the efficiency and characteristics of arrays, linked lists, hash tables, and binary search trees. It provides summaries of academic concepts including time and space complexity, sorting methods, and search strategies. The materials cover

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    algorithm-base is an educational library and study guide designed for simulating algorithms and studying data structures. It functions as an execution visualizer that renders step-by-step state changes and pointer updates through animated simulations to illustrate how data movement works. The project distinguishes itself by mapping conceptual logic directly to multi-language source code implementations. It utilizes a comparative analysis framework to evaluate different algorithmic strategies based on stability, time complexity, and space complexity, while organizing problems by underlying mec

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    This project is a JavaScript algorithm library and computer science reference. It provides a collection of standard computational logic patterns and data structure implementations, including linked lists, trees, and graphs, for both educational and practical use. The codebase serves as a technical interview study guide, offering a practical resource for practicing common coding challenges and data structure manipulations. It is designed for computer science education, allowing users to study how classic algorithms work by reviewing and running implementations of established logic patterns. T

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    AlgorithmsByPython is a reference library and educational repository providing runnable Python implementations of computer science fundamentals. It serves as a comprehensive guide for algorithmic patterns, core data structures, and solutions for competitive programming and technical interview challenges. The project distinguishes itself by offering a wide array of reference implementations, including a dedicated set of solutions for common LeetCode problems. It focuses on translating theoretical computational logic into practical Python code for educational and practical use. The repository

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    This project is an educational code repository providing a curated collection of common algorithms and data structures implemented in JavaScript. It serves as a reference library and a study resource for learning computer science concepts and foundational programming principles. The repository focuses on the practical implementation of standard data structures and algorithmic patterns. It provides a codebase for studying computational problem-solving and practicing the technical requirements often found in software engineering interviews. The codebase covers core data structure implementatio

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    This repository serves as an educational resource for computer science concepts, providing a collection of fundamental data structures and algorithmic patterns implemented in Python. It functions as a programming reference for developers seeking to understand standard software engineering patterns and data manipulation strategies. The project focuses on the construction of essential storage formats, including arrays, graphs, hash tables, linked lists, stacks, and queues. It also provides implementations for standard algorithmic techniques such as dynamic programming, recursion, sorting, and g

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    This project is a comprehensive repository of fundamental computer science algorithms and data structures designed as a reference for academic study, technical interview preparation, and competitive programming. It provides standardized implementations of core computational strategies, serving as an educational resource for developers to master software engineering fundamentals and algorithmic problem-solving. The collection distinguishes itself through a multi-language approach, offering cross-language solutions for complex tasks ranging from graph traversal and dynamic programming to bitwis

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