Awesome GitHub RepositoriesPartition Problem Solving

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

CloudEvents is an open specification for describing event data in a common format across cloud platforms and services. It defines a standard structure and set of metadata attributes for events, enabling interoperability across different systems so producers and consumers can exchange events without custom translation. The specification provides a protocol-agnostic serialization framework that maps CloudEvents attributes and payloads to multiple serialization formats including JSON, Avro, and Protobuf, and defines transport bindings for mapping events onto protocols like HTTP, AMQP, Kafka, MQTT

This repository is a curated guide and implementation library of coding patterns used to solve data structures and algorithms problems. It serves as a technical interview study resource, providing a comprehensive set of strategies and computational logic examples for optimizing time and space complexity. The project focuses on standardized algorithmic patterns, including sliding windows, two pointers, and dynamic programming. It features specific implementations for a wide range of challenges, such as LeetCode problem solutions and specialized techniques like cyclic sort and bitwise XOR opera

MoreLINQ is a functional programming toolkit and extension library for .NET that augments LINQ to Objects with advanced operators for sequence manipulation and analysis. It provides a set of tools for declarative data transformation, leveraging lazy evaluation and composition to handle complex object sequences. The library is distinguished by its specialized capabilities for combinatorial generation, including the production of permutations, subsets, and Cartesian products. It also provides advanced sequence joining options, such as full, left, and right outer joins, and supports complex data

This project is a Go algorithm implementation library and a reference for data structures. It serves as a collection of solved coding interview problems and an algorithmic pattern collection, providing a reference of over 100 common challenges implemented in Go. The library focuses on specific problem-solving strategies, including sliding windows, two pointers, and dynamic programming. It provides coded examples of standard sorting, searching, and graph traversal techniques to facilitate the study of algorithmic patterns. The repository covers a broad range of capabilities, including array a

Ce dépôt sert de ressource complète pour la programmation compétitive et la préparation aux entretiens techniques. Il fournit une collection structurée d'implémentations de code source pour des structures de données fondamentales et des problèmes algorithmiques classiques, conçus pour aider les développeurs à maîtriser les concepts fondamentaux de l'informatique et les stratégies de codage efficaces. Au-delà de la résolution de problèmes standard, le projet se distingue en intégrant des modèles de conception logicielle dans ses implémentations algorithmiques. Il démontre comment appliquer des modèles structurels et comportementaux — tels que les décorateurs, les observateurs et les singletons — pour maintenir un code propre et extensible. De plus, le dépôt couvre les modèles de programmation concurrente, offrant des exemples de gestion de pool de threads et de techniques de synchronisation pour gérer les tâches intensives en ressources. La collection inclut un large éventail de matériaux éducatifs, de l'analyse de complexité et des modèles de résolution de problèmes aux implémentations spécifiques pour le parcours de graphes, la programmation dynamique et les requêtes de plage. Ces ressources sont organisées pour aider à la fois à apprendre les techniques fondamentales et à pratiquer pour les évaluations techniques professionnelles.