Awesome GitHub RepositoriesMinimum Spanning Tree Algorithms

This project serves as a centralized knowledge base and study guide for mastering computer science fundamentals and technical interview preparation. It provides a structured collection of algorithmic implementations, data structure guides, and theoretical references designed to support professional development and problem-solving skills. The repository distinguishes itself through a taxonomy-based organization that maps complex concepts into a hierarchical structure. It standardizes the expression of abstract data structures and algorithms using a consistent programming language, with impleme

This project is a comprehensive collection of common computer science algorithms and data structures implemented in Swift. It serves as an educational reference and library for studying computational complexity, algorithmic logic, and data structure engineering through practical code examples. The repository provides a wide suite of data structure implementations, including various types of linked lists, heaps, hash tables, and an extensive range of hierarchical trees such as Red-Black, B-Tree, and Splay trees. It also covers diverse sorting and searching techniques, from basic bubble sort to

This repository serves as a comprehensive collection of standard computer science algorithms and data structures implemented in the Go programming language. It functions as an educational resource for developers to study idiomatic code examples and master fundamental computational logic through practical, hands-on implementation. The project provides a reference for building and utilizing essential storage containers, such as linked lists, heaps, and hash maps, to organize information efficiently. It also includes a suite of proven mathematical algorithms for performing complex numerical calc

This project is a comprehensive library of reference implementations for fundamental data structures and algorithms, designed to support technical interview preparation and software engineering assessments. It provides a structured collection of computational techniques for solving complex problems involving arrays, strings, graphs, trees, and mathematical analysis. The library distinguishes itself by offering specialized implementations for advanced topics, including concurrent programming patterns and geometric algorithms. It features thread-safe primitives for managing shared state and tas

This project is a comprehensive reference for algorithms and data structures used to solve complex computational problems in competitive programming. It serves as a technical resource for implementing advanced mathematical programming, computational geometry, and graph theory. The repository provides detailed implementation guides for diversifying algorithmic techniques, including top-down and bottom-up dynamic programming optimization, number theory, and linear algebra. It features specific guides for complex tasks such as constructing planar graphs, solving linear Diophantine equations, and

CS-Xmind-Note is a collection of structured mind maps and conceptual diagrams serving as a comprehensive knowledge base for computer science fundamentals. It functions as an academic reference and study guide, organizing core subjects into a visual mapping of interdependent technical concepts. The project utilizes an XMind-compatible schema to model complex domains through hierarchical nodes and relational concept mapping. This approach allows for the visual representation of technical layers, linking hardware specifications to software abstractions. The knowledge base covers several primary

This project is a collection of reference implementations for algorithms, mathematics, cryptography, compression, and machine learning written in C#. It serves as an educational library providing standard implementations of sorting, searching, and graph theory algorithms. The repository covers a wide range of computational domains, including combinatorial optimization for constraint satisfaction and scheduling, as well as symmetric and classical cryptographic ciphers. It also provides reference code for lossless data compression techniques and fundamental machine learning primitives such as r

LogicStack-LeetCode is a curated repository of solved algorithm problems and data structure implementations, primarily drawn from the LeetCode platform. Its core identity is a structured collection of solutions designed to support technical interview preparation and competitive programming practice, with each solution accompanied by complexity analyses to help engineers understand performance trade-offs. The repository distinguishes itself through its breadth of coverage across fundamental algorithmic patterns and data structures. It includes implementations for array manipulation, string pro

Ce projet est une collection complète de bibliothèques et de toolkits C++ fournissant des implémentations de référence pour les structures de données, les algorithmes de graphes et la logique binaire. Il sert de référence d'algorithmes C++ contenant plus de 180 problèmes de programmation résolus et un toolkit spécialisé pour la programmation compétitive. Le dépôt se distingue par ses bibliothèques étendues de manipulation de bits de bas niveau pour les contrôles de parité, la détection d'endianness et la logique basée sur XOR. Il fournit également un large éventail de solutions de référence pour des défis algorithmiques complexes impliquant le backtracking, la théorie des graphes et la programmation dynamique. La surface de fonctionnalités couvre les organisateurs de données linéaires et hiérarchiques fondamentaux, y compris les listes chaînées, les piles, les files d'attente et les arbres de recherche binaire. Il inclut une suite complète d'algorithmes de graphes pour la recherche de chemin et les arbres couvrants, diverses méthodes de tri et de recherche, des transformations de matrices et des utilitaires de traitement de chaînes. De plus, il couvre les fonctions de calcul mathématique, la compression de données sans perte et les chiffrements cryptographiques de base.

This is a collection of classical algorithms and data structures implemented as a header-only C++ library. It provides a suite of tools for general algorithm implementation, including data structure management, graph theory analysis, and string processing. The library is distinguished by its specialized toolkits for cryptographic hashing and encoding, featuring implementations of MD5, SHA-1, and Base64. It also includes advanced capabilities for high-performance string processing via suffix trees and arrays, as well as computational number theory for primality testing and arbitrary-precision

This repository is a comprehensive collection of fully worked solutions to exercises and problems from the standard algorithms textbook by Cormen, Leiserson, Rivest, and Stein (CLRS). It serves as an educational reference for algorithm design and analysis, providing step-by-step reasoning, pseudocode, and mathematical proofs for a wide range of topics. The content spans core computer science areas: algorithm analysis with asymptotic notation, recurrence solving, and amortized cost analysis; data structure implementation and operations for binary search trees, red-black trees, B-trees, Fibonac

Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr

AlgorithmsByPython est une bibliothèque de référence et un dépôt éducatif fournissant des implémentations Python exécutables des fondamentaux de l'informatique. Il sert de guide complet pour les modèles algorithmiques, les structures de données fondamentales et les solutions pour la programmation compétitive et les défis d'entretiens techniques. Le projet se distingue en offrant un large éventail d'implémentations de référence, incluant un ensemble dédié de solutions pour les problèmes LeetCode courants. Il se concentre sur la traduction de la logique computationnelle théorique en code Python pratique pour un usage éducatif et pratique. Le dépôt couvre un large éventail de capacités, incluant la conception de collections linéaires, d'arbres et de graphes, ainsi que l'implémentation de stratégies de recherche et de tri. Il inclut des utilitaires pour la théorie des graphes, tels que les calculs de chemin le plus court et d'arbre couvrant minimal, et fournit des mécanismes pour l'indexation sur disque et la correspondance de motifs textuels.

Ce projet est une bibliothèque d'implémentation d'algorithmes en C++ et une base de code éducative qui traduit le pseudocode théorique des manuels en code source vérifié et exécutable. Il sert de collection d'implémentations de référence conçues pour démontrer l'application pratique des théories classiques de l'informatique à travers un dépôt structuré d'algorithmes computationnels. La bibliothèque utilise la programmation générique basée sur les templates et la bibliothèque standard C++ (STL) pour garantir que les implémentations restent typées et flexibles pour différents types de données. Pour assurer l'exactitude, le projet inclut une suite de tests automatisés qui valide la logique algorithmique en comparant les résultats d'exécution avec des cas de test d'entrée et de sortie standardisés. La base de code couvre un large éventail de domaines fondamentaux de l'informatique, notamment la théorie des graphes pour l'analyse du chemin le plus court et du flux maximum, les structures de données pour la gestion des arbres hiérarchiques et des files de priorité, ainsi que des techniques de traitement de données telles que la programmation dynamique et le tri général. Elle inclut également la recherche de motifs dans les chaînes de caractères et la sélection de statistiques d'ordre. Les guides de référence technique sont générés sous forme de documentation HTML consultable, extraite directement des commentaires structurés du code source.

petgraph is a graph data structure library for the Rust programming language. It provides a collection of tools for representing and manipulating graphs, functioning as a network analysis tool and a comprehensive graph algorithm suite. The library integrates with Graphviz DOT for importing, exporting, and parsing graph data to facilitate visualization. It distinguishes itself by offering specialized network analysis capabilities, such as the detection of cliques, bridge edges, articulation points, and subgraph isomorphisms. Its computational surface covers a wide range of algorithms, includi

This project is a terminal graphics library and command-line visual effects tool designed to create dynamic motion graphics using ANSI escape sequences. It provides a framework for implementing an ANSI text animation engine and a motion processor that handles the movement of characters along paths within a shell environment. The tool is distinguished by its wide array of pre-defined visual effects, ranging from simulated environmental phenomena like thunderstorms and fire to high-tech reveals such as laser etching and decryption animations. It also supports extensibility through a plugin-base