30 open-source projects similar to zhedahht/codinginterviewchinese2, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best CodingInterviewChinese2 alternative.
This repository serves as a comprehensive library for algorithmic problem solving, providing reference implementations for fundamental computer science challenges. It is designed as a resource for technical interview preparation and competitive programming training, focusing on the mastery of common patterns and data structures required for coding assessments. The project distinguishes itself by offering solutions that emphasize idiomatic Python usage and performance optimization. It covers a wide range of algorithmic techniques, including greedy selection, dynamic programming, graph theory,
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
This project is an algorithm implementation repository and coding interview practice guide. It provides a collection of algorithmic solutions, data structure references, and study materials designed to prepare candidates for software engineering hiring assessments. The repository functions as an algorithm test suite, utilizing a case-driven verification system that executes specific input-output pairs to validate the correctness of the implemented logic. The codebase covers technical interview preparation through the practice of common computer science problems, the implementation of core da
This project is a technical interview study guide and algorithm reference library. It provides a collection of Python implementations for algorithmic challenges and data structure problems common to software engineering coding assessments. The repository serves as a resource for coding interview solutions, featuring documented code samples for sorting, searching, and optimization algorithms. It includes an automated solution test suite to verify the correctness of these implementations across various edge cases. The project emphasizes the use of idiomatic Python patterns and standard library
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
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 project is a technical interview study guide and curated knowledge base designed for software engineering preparation. It provides a collection of questions and answers focused on computer science fundamentals, algorithmic problem solving, and system design. The resource includes a dedicated Java backend knowledge base covering the Java Virtual Machine and enterprise frameworks, as well as a distributed systems reference for exploring database consistency, caching strategies, and high-concurrency architectural trade-offs. The content covers a broad range of engineering domains, includin
This repository is a curated collection of JavaScript implementations for standard algorithmic challenges and technical interview problems. It serves as a structured learning resource for developers to master fundamental data structures and computational logic through the study of verified code solutions. The project distinguishes itself by organizing solutions according to standardized algorithmic patterns, allowing for a focused approach to mastering recurring problem-solving techniques. By categorizing implementations by domain and technical approach, it provides a clear path for navigatin
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 a LeetCode solution repository containing a collection of algorithmic and database problem solutions. It serves as an algorithm implementation guide and a competitive programming reference, providing optimized code to demonstrate data structure usage and efficient coding patterns. The repository includes solutions for complex computational challenges implemented in multiple programming languages and a collection of SQL queries for data retrieval and manipulation across various difficulty levels. These resources are designed for competitive programming study and technical inter
This project is a library of source code implementations designed to solve algorithmic challenges and mathematical problems. It serves as a collection of solved LeetCode problems, providing a reference for data structure usage and efficient logic. The repository is a polyglot code collection, implementing the same algorithmic logic across various programming environments, including general-purpose languages, SQL for database queries, and Bash for shell scripting. The content covers a broad range of computational tasks, including data querying, text processing, and the implementation of compl
leetcode_101 is a curated library of algorithmic problem sets and a repository of solved LeetCode challenges. It serves as a technical interview guide by providing code implementations for common software engineering interview questions. The project supports a technical interview preparation workflow, focusing on LeetCode problem solving and the study of standardized code solutions for data structures and algorithms. It is designed to facilitate coding skill development and the study of technical interview problems. The repository utilizes markdown-based content authoring and a static-file d
This project is a comprehensive knowledge base and study resource designed for mastering technical interviews. It provides structured guides, roadmaps, and curricula focused on data structures, algorithms, system design, and frontend engineering to help candidates prepare for software engineering screenings. The repository distinguishes itself by offering a holistic approach to professional advancement. Beyond technical drills, it includes a career development handbook covering resume optimization, salary benchmarking, and strategic negotiation coaching. It also provides detailed methodologie
This project is a curated library of algorithm implementations and solved programming problems. It serves as a reference repository for competitive programming and data structure implementations, providing optimized solutions for a wide range of coding challenges. The collection organizes code examples by algorithmic technique, specifically focusing on the implementation of trees, graphs, and heaps to optimize time and space complexity. It provides language-specific solutions used for high-performance coding tasks. The repository covers a broad set of capabilities, including graph traversals
This repository serves as an educational resource for mastering computer science fundamentals through a collection of verified data structure and algorithmic implementations. It functions as a library designed to support technical interview preparation and competitive programming training by providing foundational code for common logic puzzles and computational challenges. The project emphasizes modular design, utilizing independent class encapsulation to isolate components and facilitate granular testing. Implementations rely on pointer-based node linking and recursive problem decomposition
data-structures-questions is a collection of fundamental computer science data structures and sorting algorithms written from scratch in Go for technical interview preparation. The repository functions as a curated collection of programming problems and reference solutions designed to help software engineers prepare for technical coding interviews, as well as a library of custom data structures showcasing memory layout and algorithmic efficiency. The project implements foundational collections and primitive nodes using explicit memory addresses and reference pointers rather than high-level ab
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
LeetCode-Go is a competitive programming repository and Go algorithm library. It provides a collection of optimized solutions for LeetCode challenges, focusing on time and space complexity. The project serves as a reference for data structures and algorithms implemented in Go. It covers algorithm problem solving and performance optimization to meet strict memory and runtime constraints. The repository includes capabilities for technical interview preparation and the application of Go language idioms to complex computing problems. Each solution is paired with a test suite to verify correctnes
This repository provides a collection of verified implementations for fundamental data structures and computational algorithms. It serves as both a practical toolkit for integrating standard procedures into software applications and a reference for understanding core computer science concepts. The library covers a wide range of operations, including sorting, searching, graph traversal, and geometric analysis. Each implementation is designed to be modular and reusable, utilizing generic type parametrization to decouple logic from specific data types while maintaining type safety. The project
This project is a technical interview study guide and computer science knowledge base. It provides a curated collection of technical interview questions and expert explanations focused on preparing for assessments at global IT companies. The repository serves as a coding interview roadmap for mastering algorithmic challenges and complexity analysis, alongside a software architecture reference for design principles and system design strategies. It also includes a web security curriculum covering authentication methods, cryptographic concepts, and common vulnerabilities. Content covers compute
This repository serves as a collection of common coding challenges and data structure implementations designed to assist software engineers in preparing for technical interviews. It functions as a study guide for mastering fundamental computer science concepts and standard algorithmic patterns using Python. The project organizes source files into a hierarchical directory structure, grouping problems by category or data structure type to facilitate navigation. By maintaining these implementations as raw script files, the repository allows users to execute code directly within their local Pytho
This is a collection of classic computer science algorithms and data structures implemented from scratch in JavaScript. The project provides reference implementations of fundamental concepts including sorting algorithms, binary search, linked lists, and binary search trees, all built as standalone pure functions with no external dependencies. The implementations cover a range of data structures, including singly-linked, doubly-linked, and circular linked lists with full traversal and mutation operations, as well as binary search trees supporting insertion, deletion, and search. Sorting algori
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 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 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 LeetCode solution repository and algorithm implementation library. It serves as a technical interview study guide, providing a collection of solved programming problems and algorithmic implementations. The repository focuses on coding practice management and algorithm study workflows. It organizes curated coding questions and answers to assist in preparing for technical job evaluations and software engineering assessments. The content is managed through a git-based system using markdown documentation and a category-based directory structure. This allows for the organization
This project is an automated code assessment tool and educational platform designed for frontend interview preparation. It provides a curated collection of technical challenges that allow developers to practice JavaScript mechanics, algorithmic problem solving, and core software engineering concepts. The platform utilizes a component-driven interface to organize and present educational content, which is managed through markdown-based modeling. It distinguishes itself by integrating automated evaluation systems that analyze user-submitted logic through abstract syntax tree analysis and sandbox
This project is a collection of classic computational algorithms and data structures implemented in JavaScript. It serves as a library of standardized procedures for sorting, searching, and graph traversal, alongside foundational data containers such as linked lists, heaps, trees, and hash tables. The library is designed to support computer science education and technical interview preparation by providing clean, readable implementations of fundamental principles. It emphasizes functional logic isolation and type-agnostic design, ensuring that computational tasks remain decoupled from applica
This project is a JavaScript algorithm library and computer science reference. It provides a collection of standard computational logic patterns and data structure implementations, including linked lists, trees, and graphs, for both educational and practical use. The codebase serves as a technical interview study guide, offering a practical resource for practicing common coding challenges and data structure manipulations. It is designed for computer science education, allowing users to study how classic algorithms work by reviewing and running implementations of established logic patterns. T
This project is a computer science education resource and data structures and algorithms implementation library. It provides a structured collection of solved programming exercises and logic templates designed for educational study and technical interview preparation. The repository functions as an algorithmic pattern reference and study guide, offering a curated set of standard implementations used in software engineering coding assessments. It focuses on the practical application of core programming concepts to help students understand how to organize data and solve complex computational pr