8 dépôts
Algorithms for finding the shortest contiguous subarray whose sum meets a specified threshold.
Distinct from Subarray Sum Algorithms: Distinct from general Subarray Sum Algorithms: specifically finds the shortest contiguous subarray meeting a sum threshold, not just any subarray sum.
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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
Implements the classic maximum subarray sum problem using Kadane's algorithm and prefix-sum techniques.
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.
Implements Kadane's algorithm to find the contiguous subarray with the highest total sum.
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
Finds the contiguous subarray with the largest sum within a numeric array.
LeetCode-Swift is a collection of algorithm solutions written in Swift, designed for coding interview preparation. Each solution is implemented as a self-contained function with no external dependencies, making it easy to run and test. The repository organizes solutions by topic and company, and every file includes time and space complexity annotations, allowing quick evaluation of algorithmic efficiency. What sets this repository apart is its flat file structure and the way solutions are tagged with the companies that asked them in interviews, enabling targeted practice. All code resides in
Uses two pointers to find the smallest contiguous subarray whose sum is at least a given target value.
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
Implements window-based processing to identify contiguous subarrays based on sum or length targets.
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
Provides algorithms for finding the contiguous subarray with the largest total sum.
This project is a collection of optimized computational routines and standardized implementations of fundamental computer science algorithms. It serves as an educational library for studying and applying core algorithmic patterns, including dynamic programming, greedy strategies, and recursive decomposition, within a TypeScript environment. The library distinguishes itself by providing generalized solvers for complex optimization and analysis tasks. It includes specific implementations for resource allocation, such as rod cutting, interval scheduling, and change-making problems, alongside seq
Locates the contiguous segment within a numerical sequence that yields the highest possible sum to identify peak performance periods.
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.
Identifies the contiguous subarray with the largest sum in linear time.