18 مستودعات
Common computational challenges involving array processing, string parsing, queue simulation, and logical puzzle solving.
Explore 18 awesome GitHub repositories matching scientific & mathematical computing · Algorithmic Problems. Refine with filters or upvote what's useful.
هذا المشروع عبارة عن مستودع شامل للتنفيذات الحسابية التي تم التحقق منها والمصممة لتكون مورداً تعليمياً لعلوم الحاسوب وحل المشكلات الخوارزمية. يوفر مجموعة منظمة من أمثلة الكود التي تغطي هياكل البيانات الأساسية، والعمليات الرياضية، ومفاهيم البرمجة الأساسية، مما يسمح للمستخدمين بدراسة المنطق والتعقيد وراء الأساليب الحسابية المختلفة. يتميز المستودع بنمط تنفيذ معياري قائم على المرجع ينظم الكود في مساحات أسماء منطقية. يسهل هذا النهج التنفيذ المستقل والوضوح التعليمي، مما يمكن المستخدمين من استكشاف تطور الاستراتيجيات الحسابية من الأساليب الساذجة (brute-force) إلى الحلول المحسنة عالية الأداء. من خلال فصل تجريدات هيكل البيانات عن العمليات الخوارزمية، يضمن المشروع بقاء التنفيذات قابلة للتبديل وسهلة التحليل. يمتد نطاق القدرات عبر مجموعة واسعة من المجالات التقنية، بما في ذلك تعلم الآلة، والتشفير، والحوسبة العلمية، ورؤية الحاسوب. يتضمن تنفيذات للنمذجة التنبؤية، والشبكات العصبية، والتحليل الإحصائي، إلى جانب أدوات لمعالجة الإشارات الرقمية، وإدارة تدفق الشبكة، والنمذجة المالية. تعالج المجموعة أيضاً الاحتياجات الرياضية المتخصصة، مثل الجبر الخطي، والحسابات الهندسية، ومعالجة البتات، مما يوفر أساساً واسعاً للبحث والتطبيقات الهندسية.
Calculate the most efficient item selection to meet specific capacity constraints while maximizing total value.
This repository is a comprehensive collection of data structures and algorithms implemented in JavaScript, designed primarily as an educational resource for computer science study and technical interview preparation. It provides modular implementations of fundamental programming concepts, allowing developers to explore algorithmic logic and data organization through self-contained, verifiable code examples. The library distinguishes itself by pairing every implementation with formal Big O notation, providing predictable insights into time and space scaling requirements. Each algorithm is stru
Provides implementations for solving complex combinatorial optimization problems like pathfinding and resource allocation.
This project is a comprehensive educational platform designed to facilitate the mastery of computer science algorithms and data structures. It provides a structured learning curriculum, a library of practice problems, and an integrated toolkit that supports both academic study and competitive programming preparation. By combining theoretical roadmaps with practical implementation exercises, the system enables users to build a deep understanding of core computational concepts. The platform distinguishes itself through its focus on integrated learning and visual clarity. It offers AI-powered gu
Validates character sequences and bracket matching through algorithmic logic designed to process and transform string data.
This project is a curated educational resource and solution repository for algorithmic challenges, specifically focused on LeetCode problems. It serves as a technical reference for common data structures and algorithmic patterns, providing verified code implementations across multiple programming languages alongside detailed logic and complexity analysis. The repository functions as a comprehensive study guide for competitive programming and technical interview preparation. It includes specialized learning tools such as an Anki flashcard dataset for spaced repetition and a browser extension t
Generates valid subsets, permutations, and Cartesian products of sets using recursive traversal.
This repository serves as a comprehensive research platform and toolkit for advancing machine learning, quantum computing, and large-scale scientific data analysis. It provides foundational frameworks for developing complex algorithmic systems, offering the necessary infrastructure for distributed training, computational graph execution, and high-performance model development. The project distinguishes itself by integrating specialized research domains with robust, privacy-preserving methodologies. It supports diverse scientific discovery through tools for quantum simulation, physics-informed
Applies specialized algorithms to address complex combinatorial challenges in research and industrial applications.
This project is an educational repository and collection of algorithms implemented in C++. It provides a structured set of code examples covering mathematics, computer science, and physics for reference and learning. The collection includes implementations of data structures for managing hierarchical and linear data, such as binary search trees and AVL trees. It also features simulations of computer science concepts, including CPU scheduling and the resolution of combinatorial puzzles. The repository further covers cryptographic examples through the implementation of classic encryption and e
Solves combinatorial optimization problems using recursive backtracking and discrete logic.
Fasthttp is a high-performance networking framework for Go, designed to maximize throughput and minimize memory overhead in demanding web applications. It functions as a specialized HTTP server and client library that prioritizes efficient resource management, allowing developers to build scalable services capable of handling massive concurrent traffic with minimal garbage collection pressure. The library distinguishes itself through a focus on zero-allocation processing and low-level optimization. It achieves this by recycling temporary request and response objects through managed pools and
Converts raw URL strings into structured objects for programmatic access to components.
OR-Tools is a software suite for combinatorial optimization, constraint programming, and mathematical modeling. It provides a framework for defining complex problems involving variables and logical constraints, enabling the systematic search for feasible or optimal solutions. The project features a high-performance core engine written in C++ that utilizes branch and bound search and local search metaheuristics to navigate large solution spaces. A language-agnostic wrapper layer allows these optimization capabilities to be accessed through idiomatic interfaces in multiple high-level programmin
Enables modeling complex tasks as mathematical programs to evaluate combinations of variables for optimal solutions.
This project is a cryptographic mining protocol that establishes a distributed compute network for solving complex mathematical tasks. It functions as a decentralized infrastructure where registered mining nodes participate in proof of work mining to solve network problems in exchange for rewards. The system specializes in quantum-inspired problem solving by mapping tasks into Ising mathematical structures. These problems are processed using a hardware-agnostic computation model, allowing solvers to execute tasks across CPU, GPU, or quantum processing units. The protocol includes tools for m
Translates network tasks into Ising mathematical structures to compute optimal energy states.
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
Converts string representations of floating point numbers into their actual numeric values.
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
Provides implementations for solving discrete optimization tasks including knapsack and subset sum problems.
Numeral-js is a JavaScript number formatting library used to convert raw numeric values into human-readable strings for currencies, percentages, and abbreviations. It includes a numeric string parser to extract raw values from formatted strings by removing symbols and delimiters. The library provides locale-aware formatting to adjust decimal separators and currency symbols based on regional language settings. It also features a data size converter that transforms byte values into readable measurements using base-1000 or base-1024 standards. The system supports the registration of custom form
Implements string parsing algorithms to extract raw numbers from formatted text.
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
Solves the array degree problem by finding the smallest subarray matching the array's maximum frequency.
scikit-opt is a Python optimization library and numerical framework designed to solve complex global optimization problems. It provides a suite of metaheuristic algorithms and tools for finding global minima or maxima of objective functions. The library implements a variety of nature-inspired and swarm intelligence algorithms, including Genetic Algorithms, Particle Swarm Optimization, Differential Evolution, Simulated Annealing, and Ant Colony Optimization. It includes specialized solvers for discrete combinatorial challenges, such as the Traveling Salesman Problem. The framework supports th
Provides a framework for solving discrete optimization tasks like the Traveling Salesman Problem.
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
Computes optimal solutions for bipartite matching, graph coloring, and set cover problems.
This project is a C++ learning resource and study guide consisting of structured notes and programming examples. It provides practical implementations and exercise solutions covering core language syntax, data types, and control flow. The repository features specialized samples for object-oriented design, including class inheritance, polymorphism, and abstract classes. It includes demonstrations of memory management techniques such as dynamic allocation, move semantics, and placement new, as well as template programming examples for creating generic functions and data structures. The codebas
Provides exercises that simulate queue-based processes and arrival timing constraints.
Meta-typing is a TypeScript metaprogramming toolkit that executes complex algorithms, mathematical operations, and data structure traversals entirely within compile-time type definitions. It functions as a type-level computation engine that evaluates numeric expressions, basic arithmetic, and aggregate calculations through recursive type evaluation and tuple-based data representations during the compilation phase. The library implements a comprehensive collection of advanced algorithms and data structures, including collection manipulation utilities for array slicing, filtering, merging, and
Executes complex computational logic and classic computer science problems directly within type definitions.
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
Identifies all unique combinations of numbers that sum to a target value using backtracking.