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The Interviews Repository is a comprehensive technical interview preparation resource for software engineering candidates. This repository serves as a centralized collection of data structures, algorithms, and coding problems commonly encountered in technical interviews at top technology companies. The material is organized to support both conceptual learning and targeted preparation for specific companies.

This page provides a high-level overview of the repository's organization, content, and usage. For detailed information about specific data structures, see Data Structures Reference, and for algorithms, see Algorithms Reference.

仓库目的

The primary goal of this repository is to provide

  1. A comprehensive reference for common data structures and algorithms
  2. A collection of coding problems organized by both topic and company
  3. Analysis of time and space complexity for all implementations
  4. Supplementary resources for technical interview preparation

The repository contains both theoretical explanations and practical implementations, making it suitable for candidates at all levels of preparation.

Sources: README.md1-7 README.md12-27

仓库组织结构

The Interviews repository is organized according to two main classification systems

  1. By Topic: Solutions grouped by data structure or algorithm type
  2. By Company: Problems organized according to companies known to ask them

This dual organization allows you to either focus on mastering specific concepts or target your preparation for interviews with particular companies.

目录结构

The repository follows a consistent structure for organizing code

  1. Top-level directories represent either data structures/algorithms (e.g., Array/, LinkedList/) or companies (e.g., company/amazon/, company/google/)
  2. Each problem is implemented as a standalone Java file
  3. Identical solutions may appear in multiple directories to support both organizational schemes

Sources: README.md374-521 company/airbnb/HouseRobber.java1-26 company/linkedin/HouseRobber.java1-26 leetcode/dynamic-programming/HouseRobber.java1-26

核心组件

数据结构参考

The repository includes implementations and explanations of key data structures

Each data structure includes

  • Java 实现
  • Time complexity analysis for operations
  • Space complexity considerations
  • 常见用例

Sources: README.md61-187

算法参考

The repository covers essential algorithms used in technical interviews

  1. 排序算法:

    • Quicksort, Mergesort, Bucket Sort, Radix Sort

  2. 图算法:

    • Depth-First Search, Breadth-First Search, Topological Sort
    • Shortest Path: Dijkstra's, Bellman-Ford, Floyd-Warshall
    • Minimum Spanning Tree: Prim's, Kruskal's

  3. 动态规划

  4. 回溯

  5. 贪心算法

  6. 位操作

For each algorithm, the repository provides

  • 实现细节
  • Runtime analysis
  • 示例应用程序

Sources: README.md188-308

问题解决方案

The repository contains solutions to common interview problems, organized by both topic and company. Each solution includes

  • 注释中的问题描述
  • Complete Java implementation
  • Time and space complexity analysis (implicit in the implementation)

Table of problem solution categories

类别描述示例
数组Array manipulation problemsContainsDuplicates, MergeIntervals
链表List traversal and manipulationLinkedListCycle, MergeKSortedLists
动态规划优化问题HouseRobber, EditDistance
树Tree traversal and manipulationValidateBST, InvertBinaryTree
哈希表Hashing techniquesTwoSum, GroupAnagrams
栈/队列LIFO/FIFO data structuresValidParentheses, MinStack
位操作Bit-level operationsCountingBits, SingleNumber

Sources: company/airbnb/ContainsDuplicatesII.java1-18 company/microsoft/LinkedListCycle.java1-32 leetcode/array/ContainsDuplicatesII.java1-18

Example: Cross-Referenced Solutions

Solutions are cross-referenced to appear in both topic and company directories. For example, the HouseRobber problem appears in

  1. leetcode/dynamic-programming/HouseRobber.java
  2. company/airbnb/HouseRobber.java
  3. company/linkedin/HouseRobber.java

This cross-referencing allows you to find solutions either when studying a specific algorithm type or when preparing for a particular company's interview.

Sources: company/airbnb/HouseRobber.java1-26 company/linkedin/HouseRobber.java1-26 leetcode/dynamic-programming/HouseRobber.java1-26

Runtime Analysis Reference

The repository includes a comprehensive guide to algorithm complexity analysis and Big O notation

  1. Big O Notation - Upper bound of algorithm complexity
  2. Big Ω (Omega) Notation - Lower bound of algorithm complexity
  3. Big Θ (Theta) Notation - Tight bound of algorithm complexity
  4. Little o and Little ω Notation - Non-asymptotically tight bounds

Each data structure implementation includes time complexity information for its operations.

Sources: README.md330-353

The repository is designed to support a structured approach to interview preparation

最佳实践

  1. For beginners: Start with data structures (Arrays, LinkedLists) before moving to more complex topics
  2. For company preparation: Focus on the directory for your target company
  3. For concept mastery: Study problems grouped by topic to understand patterns
  4. For comprehensive preparation:
    • Implement data structures from scratch
    • Solve problems without looking at solutions first
    • Analyze time and space complexity for each solution

其他资源

The repository also provides links to supplementary resources, including

  1. Online Judges: LeetCode, HackerRank, CodeFights, etc.
  2. Live Coding Practice: Pramp, Gainlo, Interviewing.io
  3. Video Lectures: UC Berkeley, MIT courses on data structures and algorithms
  4. Interview Books: Recommended reading materials

Sources: README.md41-54 README.md55-59 README.md355-368

仓库维护

The repository is maintained by Kevin Naughton Jr. and includes translations for multiple languages

  • 英语（主要）
  • Chinese (simplified)

Video solutions to many of the problems are available on the maintainer's YouTube channel.

Sources: README.md6-10