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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.
This project is a comprehensive collection of C++ libraries and toolkits providing reference implementations for data structures, graph algorithms, and bitwise logic. It serves as a C++ algorithm reference containing over 180 solved coding problems and a specialized toolkit for competitive programming. The repository distinguishes itself through extensive low-level bit manipulation libraries for parity checks, endianness detection, and XOR-based logic. It also provides a wide array of reference solutions for complex algorithmic challenges involving backtracking, graph theory, and dynamic prog
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.
This repository serves as a comprehensive resource for competitive programming and technical interview preparation. It provides a structured collection of source code implementations for fundamental data structures and classic algorithmic problems, designed to help developers master core computer science concepts and efficient coding strategies. Beyond standard problem-solving, the project distinguishes itself by integrating software design patterns into its algorithmic implementations. It demonstrates how to apply structural and behavioral patterns—such as decorators, observers, and singleto
Identifies the contiguous subarray with the largest sum in linear time.