For a collection of software engineering interview questions, the strongest matches are yangshun/tech-interview-handbook (The Tech Interview Handbook is a comprehensive, structured collection), xbox1994/java-interview (This repository provides a focused collection of technical interview) and forthespada/interviewguide (InterviewGuide is a comprehensive technical interview preparation platform offering). khan4019/front-end-interview-questions and youngyangyang04/leetcode-master round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
This collection features open-source repositories containing coding challenges, system design guides, and technical interview practice questions.
This repository provides a comprehensive collection of educational materials and strategies designed to assist technical professionals in preparing for the various stages of the software engineering interview process. It covers core competencies including algorithmic problem-solving, behavioral interview techniques, system design architecture, and general career development. The content is organized into structured study plans and tactical guides that address specific interview formats, ranging from initial phone screens to final onsite sessions. It includes resources for mastering data struc
The Tech Interview Handbook is a comprehensive, structured collection covering algorithms, system design, behavioral interviews, and study guides, directly matching the search for a software engineering interview preparation question bank.
Java-Interview is a collection of technical reference guides and study materials designed for Java backend developer interviews. It provides a comprehensive knowledge base covering the Java Virtual Machine, multi-threaded programming, and distributed systems. The project differentiates itself by combining technical content with interview strategy frameworks. It includes structured templates for articulating project experiences and personal introductions, alongside high-frequency question sets and scenario-driven design patterns. The resource covers backend system design for high-concurrency
This repository provides a focused collection of technical interview materials for Java backend developers, including algorithm and system design questions, JVM internals, and high-concurrency patterns, making it a solid fit for the interview preparation category despite its narrower scope.
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
InterviewGuide is a comprehensive technical interview preparation platform offering structured learning paths, real interview experiences, and company-specific questions across algorithms, system design, and multiple programming languages, which directly matches the need for a curated question bank and learning guide.
This project is a curated educational resource and technical interview preparation kit. It provides a comprehensive collection of study guides and question banks focused on front-end web development, JavaScript algorithms, and professional coding assessments. The repository includes a technical interview question bank and specialized study sets for JavaScript algorithms. These resources cover conceptual explanations and programming challenges designed to help developers master common coding patterns and theoretical questions. The content covers core web development fundamentals, including HT
A focused front-end interview question bank with JavaScript algorithm questions, but it does not cover system design, multiple languages, or company-specific sets, making it narrower than the comprehensive software engineering prep you are looking for.
This project is a comprehensive algorithmic interview resource and coding practice repository. It provides a structured curriculum of programming challenges and source code implementations designed to help software engineers master efficient problem-solving techniques and prepare for technical assessments. The repository functions as a curated roadmap, organizing computer science fundamentals by data structure and algorithm topic to facilitate systematic skill development. By moving away from random practice, it supports career advancement training for those seeking to improve their professio
This repository is a curated algorithmic interview resource with solutions in multiple languages and a structured learning path, fitting the search for technical interview preparation, though it focuses on data structures and algorithms without covering system design or behavioral questions.
This project is a technical interview question bank and coding interview study guide. It serves as a company-specific assessment aggregator that organizes curated collections of algorithmic problems and solutions by company and role. The study guide is built as a static site that pre-renders markdown data files into HTML pages. It features a client-side search engine that enables instant filtering of interview questions directly in the browser without server requests. The system manages a broad set of capabilities for technical interview preparation, including the aggregation of company asse
This repository is a technical interview question bank and study guide that aggregates algorithmic problems and solutions by company and role, with a client-side search engine—directly meeting the core need for interview preparation, though it focuses mainly on algorithmic and company-specific questions rather than covering system design, behavioral topics, or multiple languages.
AI-Job-Notes is a curated job hunting guide and technical interview curriculum specifically for artificial intelligence and computer vision roles. It functions as a markdown knowledge base and static site repository that organizes recruitment data, study materials, and company lists. The project provides resources for AI algorithm job hunting, including company directories and salary benchmarks based on geography and educational background. It covers campus recruitment planning through the tracking of application windows and internship cycles. The repository includes materials for technical
This repository is a curated interview question bank and job-hunting guide, but it is specialized for AI and computer vision roles rather than general software engineering, so it matches the category in a narrower scope.
This is a Chinese-language technical interview preparation resource focused on algorithms and data structures. It compiles real-world written exam questions and interview experiences to provide practical, scenario-specific guidance for candidates preparing for technical assessments. The content is organized into distinct topic modules covering machine learning, deep learning, computer vision, natural language processing, and mathematics. Each module reviews core concepts, architectures, and techniques commonly addressed in interview questions, with explanations curated around actual assessmen
This Chinese-language repository compiles real-world algorithm and machine learning interview questions with curated explanations, fitting the technical interview question bank category, though it lacks system design, behavioral, and company-specific coverage.
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 repository provides solutions to data structures and algorithms problems from the standard interview-prep textbook, with implementations in multiple languages—a focused DSA question bank, but it does not cover system design, behavioral questions, or a broader curated roadmap.
This repository is a structured database of coding interview problems designed to support software engineering career development. It functions as a centralized knowledge base that aggregates technical practice questions, mapping them to specific employer requirements and recurring computer science topics. The project distinguishes itself by clustering interview questions into company-specific collections and labeling them by technical domain. This organization allows users to identify recurring algorithmic patterns and analyze the unique testing styles associated with different organizations
This repository offers a curated database of coding interview problems organized by specific companies, directly matching the request for a technical interview preparation question bank, though it focuses solely on algorithmic LeetCode problems and does not include solutions, system design, or behavioral questions.
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 offers a library of algorithmic coding challenges and reference solutions for interview preparation, but it is narrowly focused on data structures and algorithms in C++ without covering system design, behavioral questions, or company-specific sets.
This project is a collaborative repository and static site generator designed to help software engineers prepare for technical hiring assessments. It functions as a structured knowledge base that organizes algorithmic coding challenges and interview questions into a searchable, web-based interface. The platform distinguishes itself by categorizing practice material based on historical appearance frequency and company-specific interview patterns. Users can filter these coding challenges according to their preparation timeline, allowing for targeted study sessions that prioritize the most relev
This collaborative repository organizes company-specific algorithmic coding challenges into a searchable, web-based interface, making it a direct fit for technical interview preparation, though it may not cover system design or behavioral questions extensively.
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 repository provides structured guides, roadmaps, and curricula for technical interview preparation across data structures, algorithms, system design, and frontend engineering, fitting the intent as a comprehensive study resource, though its focus on Python and machine-learning topics narrows the breadth compared to a multi-language question bank.
tech-vault is a command-line technical interview bank and knowledge base designed for practicing engineering questions across various technical domains. It functions as a terminal-based application that stores structured study materials and interview questions as markdown files, which are then rendered directly within the system console. The project distinguishes itself through a delivery model that uses command-line argument parsing to filter content by topic or difficulty. It also includes a random selection algorithm to pick individual questions from the collection for spontaneous study se
tech-vault is a command-line technical interview bank that stores and renders question materials in markdown, making it a genuine question-bank tool for software engineering interview prep, though it may not include all the specific features like company-specific sets or behavioral questions.
This project is a technical interview question bank and study resource designed for software engineering interviews focusing on JavaScript. It serves as a curated guide containing technical questions and coding challenges to test proficiency in the language and its runtime. The repository provides a structured collection of core programming concepts and problem solving exercises. It covers frontend technical training and coding interview practice through a series of curated problems and theoretical questions. The content is organized into a topic-categorized information hierarchy using markd
This repository is a JavaScript-focused technical interview question bank, making it a genuine fit for the category, but its narrow scope on one language and the absence of system design, behavioral, or company-specific questions mean it covers only part of the comprehensive preparation the visitor seeks.
This project is a community-driven knowledge base and diagnostic suite designed to evaluate and improve a developer's grasp of JavaScript. It functions as an interactive learning repository, providing a structured collection of technical questions and detailed explanations that target core language mechanics, runtime nuances, and common edge cases. The repository distinguishes itself through a collaborative approach to technical education, offering a wide array of challenging problems that serve as both a skill assessment tool and a resource for interview preparation. By organizing complex co
This repository is a JavaScript-specific question bank with explanations, squarely fitting the technical interview preparation category, but it covers only one language and lacks system design, behavioral, and multi-language problems, so it is a narrower match rather than a comprehensive answer.
FAQGURU is a technical interview question bank and coding interview study guide. It serves as a software engineering career resource and programming language reference, providing a curated collection of common technical questions and concise answers. The project functions as a markdown knowledge base that pairs theoretical explanations with practical implementation examples across various programming languages and frameworks. These resources focus on algorithmic and architectural patterns used during technical hiring processes. Content is organized via a nested directory hierarchy and a cate
FAQGURU is a curated markdown-based interview question bank with code examples in multiple languages, squarely a technical interview preparation resource, though it does not explicitly cover system design, behavioral, or company-specific question sets.
This project is a collection of comprehensive guides and reference materials designed for technical interviews, machine learning system design, and professional development. It serves as a technical knowledge base and a career coaching manual, providing structured resources to help candidates navigate the machine learning hiring landscape. The resource distinguishes itself by offering detailed frameworks for comparing industry roles, analyzing company types, and planning long-term career progression. It provides specific guidance on evaluating employer organizational health, identifying resea
This repository is a collection of guides and reference materials specifically for machine learning technical interviews, but the visitor is looking for a broader software engineering interview question bank covering data structures, algorithms, system design, and behavioral topics across multiple languages.
This project is a deep learning interview guide and AI technical study resource. It serves as a structured machine learning knowledge base containing curated reference guides and technical questions designed for professional interviews. The resource covers a broad spectrum of artificial intelligence domains, including machine learning fundamentals and essential mathematics. It provides specialized study materials for computer vision, natural language processing, and SLAM. Beyond AI-specific topics, the collection includes technical interview coaching for data structures and algorithms typica
This repository is a specialized question bank for deep learning and AI interviews; while it covers some data structures and algorithms, it focuses on machine learning roles rather than the broad software engineering interview preparation with system design, behavioral, and company-specific sets you are looking for.
This project is a comprehensive technical knowledge base designed to support developers in mastering systems programming and preparing for technical assessments. It provides a structured collection of fundamental computer science concepts, mapping high-level language constructs to low-level hardware memory layouts, runtime object lifecycles, and system-level operations. The repository distinguishes itself through a hierarchical approach that bridges the gap between theoretical principles and practical implementation. It offers detailed guidance on C++ language mechanisms, standard library usa
This repository is a focused technical knowledge base for C++ and systems programming interviews, covering data structures, algorithms, and low-level concepts, but it lacks system design, behavioral questions, and multi-language examples, fitting your intent as a narrower but genuine interview preparation resource.
This project is a curated repository of specialized technical questions and assessment guides used to evaluate proficiency in core web technologies. It serves as a question bank and assessment guide for testing knowledge of browser APIs, CSS, JavaScript, and HTTP protocols. The repository provides a technical skill evaluation framework consisting of open-ended prompts. These are used for front-end candidate evaluation, standardizing technical hiring workflows, and facilitating interview preparation for web developers. The content is organized via a category-driven information architecture an
This repository is a curated question bank for technical interviews, but it is narrowly scoped to front-end web development (browser APIs, CSS, JavaScript, HTTP) rather than covering the broad software engineering topics—such as data structures, algorithms, system design, and behavioral questions—that this search targets for general software engineering interview preparation.
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 repository is a curated collection of LeetCode problem solutions in multiple languages, focused on data structures and algorithms — a strong fit for coding interview prep, but it lacks system design, behavioral, and company-specific question sets and a curated roadmap.
This project serves as a centralized knowledge base and study guide for mastering computer science fundamentals and technical interview preparation. It provides a structured collection of algorithmic implementations, data structure guides, and theoretical references designed to support professional development and problem-solving skills. The repository distinguishes itself through a taxonomy-based organization that maps complex concepts into a hierarchical structure. It standardizes the expression of abstract data structures and algorithms using a consistent programming language, with impleme
This repository is a curated study guide and reference for algorithm-focused technical interview preparation, with Java implementations structured around data structures and theory topics. It fits your search for a question bank, though it does not cover system design, behavioral questions, company-specific sets, or provide coding examples in multiple languages.
This project is a curated frontend interview question bank and technical assessment guide. It serves as a web development interview resource for assessing candidates on frontend development, web accessibility, and browser performance. The collection provides a standardized set of questions to evaluate a developer's knowledge of HTML, CSS, JavaScript, and networking. It is designed to assist in the developer hiring process, engineering team recruiting, and personal technical interview preparation. The content is organized as a flat-file knowledge base using markdown-based storage and topic-ba
This curated question bank focuses exclusively on frontend development (HTML, CSS, JavaScript, networking) and lacks the data structures, algorithms, system design, and behavioral questions needed for a comprehensive software engineering interview prep, making it a narrow but genuine instance of an interview question bank.
This project is a curated collection of technical questions and answers designed to assist developers in preparing for software engineering interviews within the iOS ecosystem. It serves as a structured study tool for evaluating proficiency in mobile application architecture, system design, and core programming concepts. The repository provides a comprehensive reference for essential development topics, including memory management, concurrency, design patterns, and data persistence. By covering these foundational areas, it enables users to review common industry interview subjects and test th
This is a curated list of iOS interview questions and answers, so it squarely fits the category of a technical interview question bank, but it is limited to the iOS platform and does not cover the broad range of topics (data structures, algorithms, system design, behavioral) that a comprehensive preparation resource would.
This project is a comprehensive technical interview question repository designed to assist software engineers in their professional development. It serves as a structured study guide that aggregates curated questions and answers covering full-stack development, algorithmic challenges, and system design concepts. The resource distinguishes itself by organizing content into specialized technical domains, allowing candidates to focus their preparation on specific skill sets such as data science and machine learning. It provides a centralized library of architectural patterns and complex problem-
This repository is a substantial collection of full-stack, coding, and system design interview questions with answers, fitting the technical interview question bank category well, though it lacks explicit behavioral and company-specific question sets.
This project is a structured repository of technical interview questions and professional development resources designed for software engineering career advancement. It serves as a comprehensive database of high-frequency assessment materials sourced from real-world candidate experiences at major global technology companies. The collection is organized into a hierarchical directory structure categorized by company names and technical domains to facilitate navigation. By utilizing plain text serialization and static markdown content, the project ensures that all interview data remains human-re
This repository is a curated collection of real interview questions from major tech companies like Google, Amazon, and Tencent, fitting as a technical interview question bank, but it lacks explicit system design, behavioral, or roadmap features and may not include solutions or multi-language examples.
This project is a learning platform and study guide focused on the principles of distributed systems and software architecture. It provides a collection of architectural scenarios and technical problem statements designed to help engineers practice system design, capacity planning, and trade-off analysis for high-scale services. The repository distinguishes itself by offering functional prototypes and models for complex engineering challenges. Rather than providing purely theoretical documentation, it includes executable representations of system components—such as storage services, load bala
This repository provides problem statements for system design and software architecture interviews, making it a legitimate but narrowly focused question bank; it covers only one topic area, lacking data structures, algorithms, coding examples, and other key features of a comprehensive preparation resource.
This repository is a curated collection of technical interview materials designed to assist software engineering candidates in their professional preparation. It functions as a version-controlled knowledge base that organizes common coding challenges and conceptual questions into a structured, navigable format. The project focuses on backend engineering and Java-specific technical assessments, providing a taxonomy of topics that cover core programming concepts and system design principles. By utilizing a hierarchical directory structure and markdown-based documentation, the repository enables
This repository offers interview preparation materials tailored for Java developers, genuinely fitting the technical interview question bank category, though it is narrowly scoped to one language and likely lacks the broader multi-language and system design coverage you want.
This repository serves as a comprehensive knowledge base and study guide for developers preparing for technical assessments and job screenings focused on React. It provides a structured collection of common industry inquiries and answers designed to build proficiency in the core concepts and patterns required for modern web interface development. The resource covers the fundamental pillars of the library, including component-based architecture, declarative rendering, and unidirectional data flow. It details essential patterns for managing both local and global application state, as well as te
This repository is a focused list of React interview questions and answers, so it fits the technical interview preparation category but is limited to React topics rather than the broad set of subjects you need for general software engineering interviews.
This repository serves as a comprehensive knowledge base for software engineering interview preparation. It provides a curated collection of technical questions and answers designed to assist developers in reviewing core concepts across the entire software development stack. The project covers a broad range of topics, including full-stack engineering principles, programming language proficiency, and software architecture design. By focusing on high-level system design patterns and technical trade-offs, the content helps candidates prepare for both coding and architectural discussions during p
This repository is a straightforward collection of full-stack developer interview questions and answers, squarely fitting the technical interview preparation question bank category, though its scope is limited to full-stack topics rather than covering the broader software engineering spectrum requested.
Grokking the Coding Interview: Patterns for Coding Questions Alternative
This repository offers coding interview problems organized by patterns with solutions and explanations, making it a focused resource for data-structures-and-algorithms preparation, but it does not cover system design, behavioral questions, or company-specific sets as requested.
This project is a curated collection of educational resources and study materials designed to assist developers in preparing for frontend engineering interviews. It provides a structured set of coding challenges, conceptual guides, and technical assessment problems focused on evaluating proficiency in JavaScript and core web development standards. The repository serves as a practice framework for technical interviews, offering targeted exercises that simulate real-world programming scenarios. By covering both language fundamentals and functional programming patterns, the content helps users i
This repo offers answers to a specific set of frontend interview questions, primarily in JavaScript and functional programming, so it is a question bank in the category, but its narrow focus on frontend and missing features like system design and company-specific sets make it less comprehensive than what the visitor likely wants.
This repository serves as a curated knowledge base and study resource for professionals preparing for technical interviews in infrastructure and operations. It provides a comprehensive collection of questions and answers covering core engineering concepts, including cloud platforms, infrastructure automation, and industry-standard practices. The project functions as a collaborative documentation repository, utilizing version-controlled text files to maintain technical accuracy. By leveraging community-driven peer review and feedback loops, the content remains structured and verifiable. The re
This repository is a curated collection of DevOps interview questions, which places it squarely in the technical interview preparation category, but its narrow focus on DevOps means it does not cover the broader software engineering topics like data structures and algorithms or system design that you are looking for.
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 repository provides a curated collection of frontend interview challenges with automated evaluation, but it focuses only on JavaScript and CSS topics rather than system design, behavioral questions, or multi-language coding examples.
go-questions is a technical knowledge base and study resource for the Go programming language. It serves as a curated collection of interview questions and detailed explanations focused on the internal principles and advanced patterns of the Go ecosystem. The project is implemented as a static site generated from markdown files, which separates the technical educational content from the presentation logic. The site uses a file-system-based content hierarchy to automate navigation and maps folder structures directly to public URLs. The platform covers areas of technical knowledge synthesis, l
This repository is a focused technical interview question bank for the Go language, providing curated questions and detailed explanations on internal principles and advanced patterns, but it does not cover multiple languages, system design, or behavioral questions.
This project is a comprehensive curriculum for mastering computer science fundamentals and preparing for technical interviews. It provides over 120 interactive Python coding challenges that focus on algorithmic skill development, data structure implementation, and logical problem solving. The learning experience is delivered through a series of executable notebooks that combine instructional content with hands-on coding exercises. Each challenge is self-contained and relies on automated unit tests to verify the correctness of user-implemented solutions against predefined constraints and edge
This repository provides over 120 interactive Python coding challenges with automated tests, squarely targeting the algorithm and data structure portion of technical interview preparation, though it lacks system design, behavioral, and multi-language coverage.
This project is a technical interview preparation resource focused on JavaScript. It provides a collection of common technical questions, detailed answers, and conceptual quizzes designed to help users master core language fundamentals and browser APIs. The resource utilizes an interactive infrastructure that includes a coding workspace with in-browser runtime execution and an automated test suite to validate code correctness. It organizes content through curated learning paths and modular concept mapping to decompose complex language fundamentals into searchable study modules. The curriculu
Greatfrontend's top-javascript-interview-questions is a focused question bank for JavaScript and front-end interviews with interactive coding workspaces and detailed answers, but it does not cover system design, behavioral questions, or other languages, making it a narrower fit for a comprehensive interview preparation resource.
This project is a comprehensive reference library and preparation guide for Python technical interviews. It combines theoretical guides on computer science fundamentals and language runtime internals with practical implementation examples of algorithms and data structures. The repository serves as a curated knowledge base that maps theoretical interview questions to concrete code snippets. It provides technical analysis of Python language internals, including memory management, garbage collection, and the global interpreter lock, alongside a library of creational and structural software desig
This repository is a Python-focused technical interview question bank that provides algorithms, data structures, and language runtime explanations with code snippets, making it a relevant preparation resource but narrower than the comprehensive multi-language and multi-topic bank you described.
| Repository | Stars | Language | License | Last push |
|---|---|---|---|---|
| yangshun/tech-interview-handbook | 140.3K | TypeScript | MIT | |
| xbox1994/java-interview | 5.2K | — | MIT | |
| forthespada/interviewguide | 5.8K | — | apache-2.0 | |
| khan4019/front-end-interview-questions | 3.1K | HTML | — | |
| youngyangyang04/leetcode-master | 61.7K | Shell | — | |
| perixtar/2025-tech-oa-by-fastprep | 2.9K | — | — | |
| amusi/ai-job-notes | 6.1K | — | — | |
| darliner/algorithm_interview_notes-chinese | 2.5K | Python | — | |
| careercup/ctci-6th-edition | 11.5K | Java | — | |
| hxu296/leetcode-company-wise-problems-2022 | 11K | Jupyter Notebook | mit |