30 open-source projects similar to ua-nick/data-structures-and-algorithms, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Data Structures And Algorithms alternative.
This project is an educational resource providing a structured curriculum for mastering fundamental computer science concepts, algorithmic logic, and data structure implementation using Python. It serves as a comprehensive tutorial for understanding how to organize information effectively and solve complex computational challenges through systematic programming techniques. The repository focuses on the practical application of core data structures, including arrays, linked lists, hash tables, stacks, queues, and trees. It emphasizes the development of algorithmic problem-solving skills by cov
algorithm-base is an educational library and study guide designed for simulating algorithms and studying data structures. It functions as an execution visualizer that renders step-by-step state changes and pointer updates through animated simulations to illustrate how data movement works. The project distinguishes itself by mapping conceptual logic directly to multi-language source code implementations. It utilizes a comparative analysis framework to evaluate different algorithmic strategies based on stability, time complexity, and space complexity, while organizing problems by underlying mec
AlgorithmsByPython is a reference library and educational repository providing runnable Python implementations of computer science fundamentals. It serves as a comprehensive guide for algorithmic patterns, core data structures, and solutions for competitive programming and technical interview challenges. The project distinguishes itself by offering a wide array of reference implementations, including a dedicated set of solutions for common LeetCode problems. It focuses on translating theoretical computational logic into practical Python code for educational and practical use. The repository
This project is a comprehensive reference guide for computer science fundamentals, providing structured summaries of essential data structures and algorithmic principles. It serves as a technical resource for developers to review core programming concepts, memory layouts, and operational characteristics required for software development and technical assessments. The collection distinguishes itself by offering concise, implementation-focused documentation for a wide range of standard techniques. It covers the mechanics of various sorting and searching algorithms, graph and tree traversal stra
InterviewGuide is a comprehensive technical interview preparation platform that covers the full spectrum of software engineering recruitment, from foundational computer science concepts through to offer negotiation. It provides structured learning paths across algorithms, operating systems, databases, networking, and programming languages, with a particular emphasis on C++ and Go. The platform aggregates real interview experiences and company-specific questions from major tech employers, offering candidates a searchable database of past written exam problems and detailed accounts of actual int
This repository provides a collection of fundamental data structures implemented in Java, designed to serve as an educational resource for understanding core computer science concepts. It includes standard implementations of trees, graphs, queues, and heaps, intended to help developers study the internal mechanics and performance characteristics of these structures. The library emphasizes the use of generics to maintain type safety across different data types and utilizes interface-driven design to ensure consistent method signatures. By building these components from scratch, the project dem
This project is a data structures and algorithms library providing a collection of fifty standard code implementations for managing data and solving common computational problems. It serves as an algorithm implementation reference and study resource for educational use. The codebase covers graph theory implementations for modeling networks and performing searches, as well as string pattern matching libraries for the retrieval of character sequences. It includes a collection of hierarchical data structures, such as binary search trees and priority heaps, and provides optimized solutions for dy
This project is a comprehensive technical interview preparation resource and computer science interview guide. It serves as an educational reference for developers to study core software engineering fundamentals and common coding patterns required for employment screenings. The repository provides detailed guides and references covering data structures and algorithms, networking and security, operating systems, and web development. It specifically focuses on the implementation and complexity analysis of sorting, searching, and graph algorithms. The material encompasses a wide breadth of comp
This project is a reference collection for computer science fundamentals, providing a study guide and cheat sheets for algorithms and data structures. It serves as a resource for technical interview preparation, combining theoretical knowledge with practical implementation patterns for coding challenges. The content includes a comparative guide for analyzing the efficiency and characteristics of arrays, linked lists, hash tables, and binary search trees. It provides summaries of academic concepts including time and space complexity, sorting methods, and search strategies. The materials cover
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
CodingInterviews is a technical interview study resource and algorithm implementation guide. It provides a collection of typical programming challenges and reference implementations focused on the data structures and algorithms used in corporate interviews. The project serves as a coding challenge reference, offering a library of proven algorithmic solutions that act as a baseline for comparing candidate implementations. It includes a data structure implementation library and a set of interview problem sets designed for technical interview preparation. The repository organizes its content th
This repository serves as an educational resource for computer science concepts, providing a collection of fundamental data structures and algorithmic patterns implemented in Python. It functions as a programming reference for developers seeking to understand standard software engineering patterns and data manipulation strategies. The project focuses on the construction of essential storage formats, including arrays, graphs, hash tables, linked lists, stacks, and queues. It also provides implementations for standard algorithmic techniques such as dynamic programming, recursion, sorting, and g
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
This project is an algorithm template library and coding interview study guide providing reusable code patterns for common data structures and algorithms. It serves as a reference for optimized strategies and a structured learning path to build proficiency in algorithmic problem solving and competitive programming. The library focuses on standardized implementations of key algorithmic patterns, including sliding windows, backtracking, dynamic programming, and binary search. It provides specific templates for managing binary search trees, searching rotated sorted arrays, and executing divide-a
This repository is a collection of solved algorithmic problems and data structure exercises designed for technical interview preparation. It serves as a polyglot reference implementation, providing a set of solved exercises based on a standard textbook to help candidates master the logic and complexity analysis required for coding tests. The project implements the same algorithmic logic across multiple programming languages to demonstrate platform-independent problem solving. This polyglot approach allows for the comparison of implementations across different tech stacks to highlight recurrin
This project is an educational code repository providing a curated collection of common algorithms and data structures implemented in JavaScript. It serves as a reference library and a study resource for learning computer science concepts and foundational programming principles. The repository focuses on the practical implementation of standard data structures and algorithmic patterns. It provides a codebase for studying computational problem-solving and practicing the technical requirements often found in software engineering interviews. The codebase covers core data structure implementatio
This project is a comprehensive algorithmic learning repository and competitive programming archive designed to support technical interview preparation and software engineering skill development. It provides a structured collection of verified solutions and implementation patterns, enabling developers to master fundamental computer science concepts through systematic practice and study. The repository distinguishes itself through a solution-centric structure that organizes source code by problem category, algorithm type, and data structure. By mapping specific coding challenges to recurring a
This project is an educational resource and reference library designed to teach fundamental data structures and algorithmic problem-solving. It provides a structured pedagogical framework that organizes complex technical concepts into a logical progression, helping learners understand how data is organized, stored, and processed to solve computational problems efficiently. The repository distinguishes itself through a multi-language codebase that maintains parallel, consistent implementations of core algorithms and data structures across various programming languages. It bridges the gap betwe
This project is a library and educational resource providing implementations of foundational computer science data structures and algorithms written in JavaScript and TypeScript. It serves as a reference for executing standard sorting, searching, and recursive patterns using modern web technologies. The collection includes typed implementations for both basic containers, such as stacks, queues, and linked lists, and advanced organizational patterns, including trees, heaps, tries, and graphs. The material covers algorithmic analysis and problem solving through the use of Big O notation to eva
This repository is a comprehensive educational resource for mastering fundamental computer science concepts through Python. It provides a structured collection of source code implementations for classic data structures and algorithms, serving as a practical guide for building technical proficiency and preparing for coding interviews. The project distinguishes itself by integrating visual aids and diagrams that map complex execution steps to clarify how data structures function. This visual approach is paired with a rigorous automated unit testing framework, which validates the correctness of
This project is a comprehensive technical knowledge base and study guide focused on data structures, algorithms, and computer science fundamentals. It provides a curated collection of tutorials and educational resources designed to support technical growth and academic learning. The repository distinguishes itself through a heavy emphasis on visual learning, utilizing mind maps, diagrams, and illustrated breakdowns to explain complex algorithmic logic. It further supports career readiness by providing a repository of company-specific interview questions and real-world candidate experiences.
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
This project is a collection of reference materials and educational guides providing theoretical foundations and practical patterns for algorithms, artificial intelligence, and professional technical interviews. It serves as a computer science study guide and a practical reference for solving computational problems through curated notes. The resources provide a learning path for machine learning, covering the mathematical foundations and architectures used to build large language models. It also functions as a technical interview preparation resource, containing common software engineering an
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
This project is an algorithm interview preparation guide and reference library. It provides a curated collection of solved programming problems and data structure implementations designed for technical interview practice and competitive programming study. The repository distinguishes itself by organizing coding challenges through a system of patterns, difficulty levels, and company-based filtering. It includes instructional resources such as algorithmic concept notes and video explanations to supplement the solution sets. The library covers a wide range of computational areas, including adva
AlgoNote is an algorithm and data structure tutorial and computer science study manual. It serves as a technical library of algorithm implementations and data structure patterns, providing a comprehensive learning guide focused on technical interview preparation. The project functions as a LeetCode solution guide, containing analyzed and implemented solutions for over one thousand coding challenges. All implementations are written in Python to provide a consistent coding reference. The resource covers the study of algorithm fundamentals, the resolution of diverse coding challenges, and prepa
itsy-bitsy-data-structures is a collection of fundamental computer science data structures implemented in JavaScript. It serves as an educational resource and algorithm study guide, providing simplified code implementations of classic data organization patterns to demonstrate internal logic and usage. The project provides clear and concise JavaScript implementations of stacks, queues, and linked lists. These examples are designed for learning, technical interview preparation, and studying the mechanical behavior of core data structures through code. The implementations utilize various comput
LearningNotes is a technical knowledge base and engineering study guide focused on Android framework internals, system architecture, and mobile performance optimization. It serves as a reference for analyzing the Android boot sequence, process bootstrapping, and system service initialization. The project provides detailed guides on mobile performance, including strategies for reducing memory footprints, identifying memory leaks, and optimizing image decoding. It further covers Android inter-process communication using AIDL and the Binder kernel driver, as well as software architecture manuals
This project is an algorithm learning platform and computer science educational resource. It serves as a technical interview study guide, providing structured lessons on data structures and sorting methods. The site is a markdown-based static site that converts technical documentation and algorithmic explanations into static HTML pages. It functions as a system for markdown content publishing to deliver educational material. The platform covers algorithm complexity analysis, problem solving workflows, and general computer science education. It utilizes a component-based UI structure with fil
This project is a computer science exam study resource and academic knowledge base. It serves as an exam preparation toolkit providing curated textbooks, past exam papers, and study guides specifically for graduate entrance exams. The repository functions as an algorithm and data structures reference library, containing source code and implementation guides for core computer science fundamentals. It organizes conceptual notes, presentation slides, and mind maps for subjects including operating systems and computer organization. The project is implemented as a markdown-based knowledge base an