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Data Structures

665 articles · Page 5 of 7
Python Programming Learning Circle
Python Programming Learning Circle
Apr 29, 2021 · Fundamentals

Python Basics: Variables, Control Flow, Data Structures, and Object‑Oriented Programming

This tutorial introduces Python fundamentals, covering why to learn the language, variable assignment, conditional statements, loops, lists, dictionaries, iteration techniques, and core object‑oriented concepts such as classes, getters/setters, encapsulation, and inheritance, all illustrated with clear code examples.

Data StructuresInheritanceOOP
0 likes · 20 min read
Python Basics: Variables, Control Flow, Data Structures, and Object‑Oriented Programming
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Apr 27, 2021 · Databases

Why Redis Is Fast: Core Principles and Internal Data Structures

This article explains why Redis achieves extremely high performance by leveraging pure in‑memory operations, a global O(1) hash table, efficient data structures such as SDS, ziplist, quicklist and skiplist, a single‑threaded event loop with non‑blocking I/O multiplexing, and adaptive encoding strategies.

Data StructuresIn-Memoryio-multiplexing
0 likes · 20 min read
Why Redis Is Fast: Core Principles and Internal Data Structures
Open Source Tech Hub
Open Source Tech Hub
Apr 22, 2021 · Databases

Why MySQL Indexes Use B‑Tree, Not Hash: Understanding Index Data Structures

The article explains how MySQL indexes rely on ordered data structures—binary trees, red‑black trees, hash tables, and especially B‑Trees—to accelerate queries, compares their performance characteristics, illustrates how tree height affects I/O operations, and shows why B‑Tree is preferred for range searches.

B+ TreeData StructuresMySQL
0 likes · 5 min read
Why MySQL Indexes Use B‑Tree, Not Hash: Understanding Index Data Structures
Tencent Cloud Developer
Tencent Cloud Developer
Apr 20, 2021 · Databases

Advanced Guide to Redis: Data Structures, Usage, Internals, Performance Issues, and Security

This comprehensive Redis guide explains core data structures like strings, lists, sets, hashes and sorted sets, explores advanced features such as Bloom filters, distributed locks and clustering, details internal mechanisms, performance bottlenecks, and provides essential security best practices for safe, high‑performance deployment.

Data StructuresPerformancesecurity
0 likes · 13 min read
Advanced Guide to Redis: Data Structures, Usage, Internals, Performance Issues, and Security
Intelligent Backend & Architecture
Intelligent Backend & Architecture
Apr 2, 2021 · Fundamentals

Master Java Collections: From ArrayList to ConcurrentHashMap Explained

This article provides a comprehensive overview of Java's collection framework, detailing the roles of interfaces, implementations, and algorithms, comparing collections with arrays, describing common List, Set, and Map classes, their underlying data structures, thread‑safety characteristics, and best practices for iteration and usage.

CollectionsConcurrentHashMapData Structures
0 likes · 48 min read
Master Java Collections: From ArrayList to ConcurrentHashMap Explained
Sohu Tech Products
Sohu Tech Products
Mar 31, 2021 · Databases

Why Redis Is Fast: Core Principles, Data Structures, and Architecture

This article explains why Redis achieves exceptionally high performance by combining pure in‑memory operations, a global hash table with O(1) lookups, efficient data structures such as SDS, ziplist, quicklist and skiplist, a single‑threaded event loop with non‑blocking I/O multiplexing, and adaptive encoding strategies.

Data StructuresIO MultiplexingIn-Memory Database
0 likes · 20 min read
Why Redis Is Fast: Core Principles, Data Structures, and Architecture
Python Crawling & Data Mining
Python Crawling & Data Mining
Mar 30, 2021 · Fundamentals

Boost Your Python Skills with a Free Exam Simulation Tool

This article introduces a free Python certification exam simulator, explains how to download, install, and crack the software, and shows how to use its diverse question sets to assess and improve your Python fundamentals, data‑structure knowledge, and overall coding confidence.

Data StructuresPythonSoftware Tutorial
0 likes · 7 min read
Boost Your Python Skills with a Free Exam Simulation Tool
dbaplus Community
dbaplus Community
Mar 28, 2021 · Databases

Why Redis Is So Fast: Inside Its Core Architecture

This article explains why Redis achieves exceptional speed by examining its memory‑only architecture, single‑threaded event loop, and the specialized data structures—global hash tables, SDS strings, ziplist, quicklist, skiplist, and intset—that provide O(1) or O(log N) operations, along with non‑blocking I/O multiplexing.

Data StructuresI/O multiplexingIn-Memory Database
0 likes · 20 min read
Why Redis Is So Fast: Inside Its Core Architecture
Top Architect
Top Architect
Mar 22, 2021 · Fundamentals

Understanding Red‑Black Trees and Related Balanced Tree Structures

This article explains the concepts, properties, and operations of binary trees, binary search trees, AVL trees, 2‑3 and 2‑3‑4 trees, B‑trees, and especially red‑black trees, illustrating how they maintain balance through rotations and why they are widely used in ordered data storage.

AlgorithmsBalanced TreesData Structures
0 likes · 12 min read
Understanding Red‑Black Trees and Related Balanced Tree Structures
Top Architect
Top Architect
Mar 15, 2021 · Fundamentals

Analysis of JDK 1.8 HashMap Implementation Compared to JDK 1.7

This article explains the major differences between JDK 1.8 and JDK 1.7 HashMap implementations, detailing the initialization process, the putVal algorithm steps, how collisions are handled with linked lists and red‑black trees, and the changes in resizing behavior.

CollectionsData StructuresHashMap
0 likes · 5 min read
Analysis of JDK 1.8 HashMap Implementation Compared to JDK 1.7
Liangxu Linux
Liangxu Linux
Mar 14, 2021 · Fundamentals

Master Red-Black Trees with Illustrated Comics: From Basics to Insertion & Deletion

An illustrated guide walks readers through the fundamentals of red‑black trees, explaining binary search tree basics, their limitations, and the red‑black tree’s balancing operations—including node rotations, insertion, and deletion cases—while providing complete source code tested with massive random operations.

AlgorithmsData StructuresIllustrated Tutorial
0 likes · 5 min read
Master Red-Black Trees with Illustrated Comics: From Basics to Insertion & Deletion
Open Source Linux
Open Source Linux
Mar 12, 2021 · Backend Development

Redis vs Memcached: Which In‑Memory Database Wins for Your Projects?

This article compares Redis and Memcached across thread model, data structures, eviction policies, pipelining, persistence, high availability, and clustering, helping developers choose the most suitable in‑memory database for their specific performance and feature requirements.

CachingData StructuresIn-Memory Database
0 likes · 9 min read
Redis vs Memcached: Which In‑Memory Database Wins for Your Projects?
21CTO
21CTO
Mar 11, 2021 · Fundamentals

14 Essential Coding Interview Patterns Every Developer Should Master

This article outlines fourteen common algorithmic patterns that appear in programming interviews, explains how to recognize each pattern, and provides example problems for each, helping developers focus their preparation and solve interview questions more efficiently without endless brute‑force practice.

Data Structuresalgorithm patternscoding interview
0 likes · 17 min read
14 Essential Coding Interview Patterns Every Developer Should Master
Practical DevOps Architecture
Practical DevOps Architecture
Mar 11, 2021 · Fundamentals

Python Dictionary and Set Basics

This article introduces Python's built‑in dictionary and set types, explaining their characteristics, common operations, and providing example code to demonstrate creation, element access, and membership testing, while also highlighting key differences such as mutability of values and the use of hashable elements as keys.

Data StructuresPythondictionary
0 likes · 5 min read
Python Dictionary and Set Basics
58 Tech
58 Tech
Mar 8, 2021 · Fundamentals

Real‑Time Inverted Index Update Techniques in the 58 Search Engine

This article explains how the 58 search engine achieves millisecond‑level real‑time inverted‑index updates by redesigning the underlying data structures, combining static and dynamic indexing, using a chain‑array hybrid, segment merging strategies, and lock‑free read‑write concurrency while maintaining search performance.

Data StructuresReal-Time UpdateSegment Merging
0 likes · 18 min read
Real‑Time Inverted Index Update Techniques in the 58 Search Engine
Python Programming Learning Circle
Python Programming Learning Circle
Mar 2, 2021 · Fundamentals

30 Minimal Python Tasks and Code Snippets for Beginners

This article presents 30 concise Python tasks, each demonstrating a specific technique such as duplicate detection, memory usage, string manipulation, list chunking, dictionary merging, and more, allowing beginners to practice and developers to discover useful code patterns.

AlgorithmsCoding ExercisesData Structures
0 likes · 13 min read
30 Minimal Python Tasks and Code Snippets for Beginners
Baidu Geek Talk
Baidu Geek Talk
Feb 22, 2021 · Fundamentals

Can Embracing Hash Collisions Boost Performance? Inside B16 Hash Table

This article revisits traditional hash table design, then introduces a novel approach that deliberately leverages a controlled probability of hash collisions combined with SIMD parallelism, presenting the B16 and B16Compact hash tables, their structures, algorithms, and experimental results showing superior speed and space efficiency compared to unordered_map and F14.

B16C++Data Structures
0 likes · 17 min read
Can Embracing Hash Collisions Boost Performance? Inside B16 Hash Table
Python Crawling & Data Mining
Python Crawling & Data Mining
Feb 20, 2021 · Fundamentals

Unlock Python’s Speed: Master dict and set for Fast Data Lookup

This article explains Python’s built-in dict and set structures, comparing them with lists, demonstrating their fast key-value lookups, handling missing keys, and common operations like insertion, deletion, and set algebra, while providing clear code examples and practical tips for effective use.

Data StructuresImmutable ObjectsPython
0 likes · 9 min read
Unlock Python’s Speed: Master dict and set for Fast Data Lookup
Architect
Architect
Feb 12, 2021 · Backend Development

Understanding Nginx Architecture: Daemon Processes, Workers, Connections, and Core Data Structures

This article explains Nginx's high‑performance architecture, covering its daemon mode with master and worker processes, the thundering‑herd problem, advantages of process‑based concurrency, asynchronous non‑blocking I/O, connection handling, keep‑alive and pipeline techniques, as well as key internal data structures such as arrays, queues, lists, strings, memory pools, hash tables, and red‑black trees.

Backend DevelopmentData StructuresNginx
0 likes · 18 min read
Understanding Nginx Architecture: Daemon Processes, Workers, Connections, and Core Data Structures
Efficient Ops
Efficient Ops
Feb 3, 2021 · Databases

Master Redis: Core Data Types, Commands, and Advanced Features Explained

This article introduces Redis as an open‑source, in‑memory data‑structure store, explains its role as a NoSQL database, details its five fundamental data types, common commands, expiration handling, pipelines, and transactions, and shows how it fits into modern scaling architectures.

CachingData StructuresNoSQL
0 likes · 14 min read
Master Redis: Core Data Types, Commands, and Advanced Features Explained
Programmer DD
Programmer DD
Jan 31, 2021 · Fundamentals

Understanding Git Internals: How the Version Control System Works Under the Hood

This article delves into Git’s core architecture, explaining its fast, distributed nature, immutable objects, porcelain and plumbing commands, the content‑addressable version database, and how init, add, and commit manipulate the working directory, index, and repository to create snapshots of project history.

Data StructuresGitinternals
0 likes · 12 min read
Understanding Git Internals: How the Version Control System Works Under the Hood
IT Xianyu
IT Xianyu
Dec 30, 2020 · Fundamentals

Quick Introduction to 8 Common Data Structures

This article provides a concise overview of eight essential data structures—arrays, linked lists, stacks, queues, hash tables, trees, heaps, and graphs—explaining their definitions, core operations, and typical applications in software development and computer science.

AlgorithmsData StructuresQueue
0 likes · 12 min read
Quick Introduction to 8 Common Data Structures
DataFunTalk
DataFunTalk
Dec 25, 2020 · Fundamentals

Curated Collection of Algorithm and Data Structure Problems with Solution Articles

This article compiles a comprehensive list of over 400 algorithm and data‑structure problem solutions—including dynamic programming, backtracking, DFS/BFS, binary‑tree, linked‑list, stack, sorting, searching and classic puzzles—organized by topic and linked to detailed explanations for easy reference.

AlgorithmsData Structuresbacktracking
0 likes · 9 min read
Curated Collection of Algorithm and Data Structure Problems with Solution Articles
Architecture Digest
Architecture Digest
Dec 23, 2020 · Databases

Understanding Redis Object Types and Their Underlying Data Structures

This article explains the five core Redis object types—strings, lists, hashes, sets, and sorted sets—their possible encodings, and the underlying data structures such as SDS, linked lists, hash tables, ziplists, intsets, and skiplists, including details of the redisObject layout and rehash mechanisms.

Data Structuresdatabasesencoding
0 likes · 22 min read
Understanding Redis Object Types and Their Underlying Data Structures
Architect's Tech Stack
Architect's Tech Stack
Dec 18, 2020 · Databases

How to Use Redis to Count Website Visits: Hash, Bitset, and Probabilistic Algorithms

This article explains three Redis-based approaches—using Hashes, Bitsets, and the HyperLogLog probabilistic algorithm—to count daily website visits, detailing command usage, advantages, disadvantages, and implementation considerations for high‑traffic sites, including handling logged‑in and anonymous users, memory consumption, and accuracy trade‑offs.

Backend DevelopmentData StructuresProbabilistic Algorithms
0 likes · 6 min read
How to Use Redis to Count Website Visits: Hash, Bitset, and Probabilistic Algorithms
360 Tech Engineering
360 Tech Engineering
Dec 11, 2020 · Fundamentals

Heap Sort: Theory, Implementation, and Step‑by‑Step Explanation

This article explains the heap sort algorithm, describing the heap data structure, the process of building a max‑heap, the sorting loop with element swaps, and provides detailed Java code examples along with key points and an illustrative example array.

Data StructuresSorting Algorithmalgorithm tutorial
0 likes · 5 min read
Heap Sort: Theory, Implementation, and Step‑by‑Step Explanation
ITPUB
ITPUB
Dec 7, 2020 · Databases

Why Redis Is So Fast: Inside Its Memory Design and Data Structures

This article explains how Redis achieves high performance by using an in‑memory architecture, specialized data structures such as SDS, doubly linked lists, ziplists and skip‑lists, efficient encoding strategies, and a single‑threaded I/O multiplexing model that eliminates costly context switches.

BackendData StructuresIn-Memory Database
0 likes · 12 min read
Why Redis Is So Fast: Inside Its Memory Design and Data Structures
New Oriental Technology
New Oriental Technology
Dec 7, 2020 · Fundamentals

Efficient Circuit Connection Modeling with a Circular Doubly Linked List

The article compares an adjacency‑list approach and a circular doubly linked list for representing circuit connections, showing that the linked‑list method achieves O(1) connect/disconnect operations with linear space, making it the most efficient and simple solution for graph‑based circuit modeling.

Data Structuresalgorithmcircuit modeling
0 likes · 4 min read
Efficient Circuit Connection Modeling with a Circular Doubly Linked List
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Dec 1, 2020 · Databases

Why Redis Dominates Modern Caching: Features, Architecture, and Best Practices

Redis, an in‑memory C‑language database, offers ultra‑fast read/write speeds, rich data structures, persistence, clustering, and multi‑threaded I/O, making it ideal for distributed caching, locks, queues, and more; this guide explains its fundamentals, comparisons with Memcached, data types, eviction policies, and operational best practices.

Data StructuresPerformanceRedis
0 likes · 36 min read
Why Redis Dominates Modern Caching: Features, Architecture, and Best Practices
Architecture Digest
Architecture Digest
Nov 18, 2020 · Backend Development

Deep Dive into Java ConcurrentHashMap: Implementation, Concurrency Mechanisms, and Core Methods

This article provides a comprehensive analysis of Java's ConcurrentHashMap, covering its historical evolution, key internal fields, the thread‑safe put and remove operations, the complex resizing and transfer mechanisms, and auxiliary methods such as size, get, and clear, all illustrated with original source code.

ConcurrentHashMapData StructuresJDK
0 likes · 24 min read
Deep Dive into Java ConcurrentHashMap: Implementation, Concurrency Mechanisms, and Core Methods
MaGe Linux Operations
MaGe Linux Operations
Oct 28, 2020 · Fundamentals

Master Python Tricks: Function Chaining, Default Argument Pitfalls, CSV I/O, and More

This article showcases a collection of practical Python snippets covering function chaining, mutable default argument traps, CSV reading and writing, number base conversion, JSON formatting, list flattening and merging, most‑common character counting, safe eval usage, matrix transposition, list comprehensions, permutations/combinations, defaultdict usage, and dictionary reversal techniques.

AlgorithmsData StructuresPython
0 likes · 6 min read
Master Python Tricks: Function Chaining, Default Argument Pitfalls, CSV I/O, and More
Python Programming Learning Circle
Python Programming Learning Circle
Oct 27, 2020 · Fundamentals

Useful Python Code Snippets for Everyday Tasks

This article presents a collection of practical Python snippets covering string reversal, title‑casing, set‑based deduplication, list multiplication, list comprehensions, variable swapping, splitting, joining, palindrome checking, Counter usage, dictionary merging, timing, flattening, random sampling, digit extraction, uniqueness testing and more, each illustrated with clear code examples.

AlgorithmsData StructuresPython
0 likes · 10 min read
Useful Python Code Snippets for Everyday Tasks
Architecture Digest
Architecture Digest
Oct 22, 2020 · Backend Development

Kafka Timing Wheel: Design, Operation, and Code Walkthrough

The article explains how Kafka handles timeout‑based requests using a Timing Wheel data structure, detailing its design, parameters, operation principles, overflow handling, and providing Scala code examples that illustrate O(1) task insertion compared to traditional O(logN) delay queues.

Data StructuresKafkaScala
0 likes · 10 min read
Kafka Timing Wheel: Design, Operation, and Code Walkthrough
Programmer DD
Programmer DD
Oct 19, 2020 · Fundamentals

ArrayList vs LinkedList: When Each Data Structure Truly Shines

This article benchmarks Java's ArrayList and LinkedList by measuring insertion and lookup times at the head, tail, and middle of a list with 100,000 elements, then explains the underlying source‑code mechanisms that cause the observed performance differences.

BenchmarkData StructuresJava
0 likes · 10 min read
ArrayList vs LinkedList: When Each Data Structure Truly Shines
Sohu Tech Products
Sohu Tech Products
Oct 14, 2020 · Fundamentals

Understanding JavaScript Arrays and Objects: Operations and Big O Complexity

This article explains when to use JavaScript arrays versus objects by describing their memory layout, common operations such as adding, removing, and searching elements, and analyzing each operation's time complexity using Big O notation, while also covering hash collisions and practical performance considerations.

Big OComplexityData Structures
0 likes · 12 min read
Understanding JavaScript Arrays and Objects: Operations and Big O Complexity
IT Xianyu
IT Xianyu
Oct 10, 2020 · Fundamentals

How to Choose Between HashMap and TreeMap in Java

HashMap and TreeMap serve different purposes in Java: HashMap offers fast, unordered access using hash codes, while TreeMap maintains keys in sorted order via a red‑black tree, and the article explains their implementations, performance trade‑offs, and how to customize TreeMap ordering with comparators.

CollectionsComparatorData Structures
0 likes · 5 min read
How to Choose Between HashMap and TreeMap in Java
Liangxu Linux
Liangxu Linux
Oct 9, 2020 · Fundamentals

Master Interview‑Ready Algorithms & Data Structures with This Open‑Source Guide

This article introduces a popular open‑source repository that compiles essential algorithms and data‑structure concepts for technical interviews, providing concise definitions, time‑complexity analyses, and example code for structures such as stacks, queues, trees, graphs, and sorting algorithms, along with a GitHub link.

AlgorithmsComplexity AnalysisData Structures
0 likes · 9 min read
Master Interview‑Ready Algorithms & Data Structures with This Open‑Source Guide
Architecture Digest
Architecture Digest
Oct 3, 2020 · Databases

Redis vs Memcached: A Comprehensive Comparison

This article systematically compares Redis and Memcached across thread models, data structures, eviction policies, pipelining and transactions, persistence, high availability, and clustering, helping developers choose the most suitable in‑memory database for their specific business requirements.

CachingData StructuresIn-Memory Database
0 likes · 11 min read
Redis vs Memcached: A Comprehensive Comparison
OPPO Kernel Craftsman
OPPO Kernel Craftsman
Sep 18, 2020 · Fundamentals

Linux SCSI Subsystem Architecture and Design Framework

The article thoroughly examines the Linux SCSI subsystem architecture, illustrating how abstract hardware topology—hosts, channels, IDs, and LUNs—is modeled in software through structs such as scsi_host and scsi_device, and detailing initialization, scanning, path establishment, power management, and block‑layer integration to guide kernel storage driver design.

Block LayerData StructuresLinux kernel
0 likes · 20 min read
Linux SCSI Subsystem Architecture and Design Framework
vivo Internet Technology
vivo Internet Technology
Sep 16, 2020 · Backend Development

How ConcurrentHashMap Guarantees Thread‑Safe Reads and Writes: A Deep Dive into C13Map Internals

This article explains the fundamentals of HashMap, then dissects the internal fields, node‑array safety, read‑path guarantees, write‑path locking, atomic compute methods, resize‑transfer mechanics, traverser design, and bulk‑task support that together make Java's ConcurrentHashMap (C13Map) a highly concurrent, lock‑free data structure.

ConcurrentHashMapData StructuresHashMap
0 likes · 49 min read
How ConcurrentHashMap Guarantees Thread‑Safe Reads and Writes: A Deep Dive into C13Map Internals
ITPUB
ITPUB
Sep 11, 2020 · Fundamentals

How Redis Implements Binary‑Safe Strings with Simple Dynamic Strings (SDS)

This article explains the design and evolution of Redis's Simple Dynamic Strings (SDS), covering the original pre‑3.2 structure, the newer type‑specific headers, the core API functions for creating, clearing, and concatenating SDS objects, and the memory‑reallocation strategy that ensures binary safety and efficient storage.

Binary SafetyC++Data Structures
0 likes · 13 min read
How Redis Implements Binary‑Safe Strings with Simple Dynamic Strings (SDS)
Hulu Beijing
Hulu Beijing
Sep 11, 2020 · Fundamentals

Crack Hulu’s 2020 Campus Coding Test: 4 Algorithm Challenges Explained

This article walks you through Hulu's 2021 campus recruitment update, explains the online programming test schedule and format, shares interview tips, and provides detailed statements, sample I/O, and solution analyses for four algorithmic problems covering probability, array maxima, maze navigation, and segment‑tree optimization.

Data Structuresalgorithmcoding interview
0 likes · 15 min read
Crack Hulu’s 2020 Campus Coding Test: 4 Algorithm Challenges Explained
Wukong Talks Architecture
Wukong Talks Architecture
Sep 9, 2020 · Fundamentals

Comprehensive Guide to Java Queue Family: 18 Types, Interfaces, and Implementations

This article provides an in‑depth, illustrated overview of Java's Queue hierarchy, covering 18 concrete queue classes, their inheritance relationships, core methods, blocking and non‑blocking variants, practical usage examples, and code snippets to help developers master queue-based data structures and concurrency utilities.

BlockingQueueData StructuresJava
0 likes · 26 min read
Comprehensive Guide to Java Queue Family: 18 Types, Interfaces, and Implementations
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Sep 4, 2020 · Databases

Comprehensive Guide to Redis Data Structures, Persistence, Transactions, Clustering, and Applications

This article provides an in‑depth technical overview of Redis, covering its core data structures, memory allocation strategies, eviction policies, persistence mechanisms (RDB and AOF), transaction model, sentinel and cluster architectures, Pub/Sub messaging, and multiple approaches to implementing distributed locks.

ClusteringData StructuresPersistence
0 likes · 89 min read
Comprehensive Guide to Redis Data Structures, Persistence, Transactions, Clustering, and Applications
MaGe Linux Operations
MaGe Linux Operations
Sep 1, 2020 · Fundamentals

Boost Python Speed: 10 Proven Tricks to Accelerate Your Code

This article presents practical Python performance‑boosting techniques—including avoiding global variables, minimizing attribute access, eliminating unnecessary abstractions, reducing data copies, optimizing loops, leveraging built‑in functions, and using tools like numba—each illustrated with before‑and‑after code snippets and measured speed improvements.

Data StructuresOptimizationPerformance
0 likes · 19 min read
Boost Python Speed: 10 Proven Tricks to Accelerate Your Code
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 12, 2020 · Fundamentals

Unlock Core Data Structures, Algorithms, and Sorting Basics

This article provides a comprehensive introduction to fundamental data structures, core algorithm concepts, and classic sorting techniques, explaining their definitions, basic operations, time and space complexities, stability considerations, and practical use cases for developers seeking to strengthen their programming foundations.

AlgorithmsComplexityData Structures
0 likes · 20 min read
Unlock Core Data Structures, Algorithms, and Sorting Basics
Architect's Tech Stack
Architect's Tech Stack
Aug 10, 2020 · Fundamentals

Understanding Java HashMap and ConcurrentHashMap: Structure, Operations, and Performance

This article explains the internal structure of Java's HashMap and ConcurrentHashMap, covering hash calculations, bucket arrays, linked‑list and red‑black tree conversions, load factor and resizing behavior, as well as the differences in concurrency control between JDK 1.7 and 1.8 implementations.

ConcurrentHashMapData StructuresHashMap
0 likes · 13 min read
Understanding Java HashMap and ConcurrentHashMap: Structure, Operations, and Performance
Programmer DD
Programmer DD
Jul 23, 2020 · Fundamentals

When to Use HashMap vs TreeMap in Java? A Practical Guide

This article explains the differences between Java's HashMap and TreeMap, covering their underlying implementations, performance characteristics, thread safety, and how to customize TreeMap for descending order, helping developers choose the right map for their needs.

CollectionsData StructuresHashMap
0 likes · 7 min read
When to Use HashMap vs TreeMap in Java? A Practical Guide
Liulishuo Tech Team
Liulishuo Tech Team
Jul 22, 2020 · Fundamentals

Exploring Recursive Types in Go: Tries, Finite Automata, Stacks, Pointers, Balanced Braces, Y Combinator, and Church Numerals

This article demonstrates how Go's support for recursive types enables elegant implementations of data structures such as tries and finite automata, functional constructs like stacks and pointers, and classic concepts including balanced braces, the Y combinator, and Church numerals, providing practical code examples throughout.

AlgorithmsData StructuresGo
0 likes · 16 min read
Exploring Recursive Types in Go: Tries, Finite Automata, Stacks, Pointers, Balanced Braces, Y Combinator, and Church Numerals
Liangxu Linux
Liangxu Linux
Jul 20, 2020 · Fundamentals

Essential Big O Cheat Sheet: Quick Reference for Algorithm Complexity

This article presents a concise Big O cheat sheet that aggregates the time‑complexity notations for common data structures, sorting algorithms, graph and heap operations, and visualizes performance curves, helping readers quickly recall best‑, worst‑, and average‑case scenarios.

Algorithm ComplexityBig OCheat Sheet
0 likes · 3 min read
Essential Big O Cheat Sheet: Quick Reference for Algorithm Complexity
Selected Java Interview Questions
Selected Java Interview Questions
Jul 14, 2020 · Backend Development

Deep Dive into Java HashMap: Implementation Details, Internals, and Interview Questions

This article explains the internal design of Java's HashMap—including its default capacity, load factor, underlying array‑list‑tree structure, hash calculation, resizing algorithm, treeification, and common interview questions—while providing complete source code snippets and practical usage tips for developers.

CollectionsData StructuresHashMap
0 likes · 22 min read
Deep Dive into Java HashMap: Implementation Details, Internals, and Interview Questions
OPPO Kernel Craftsman
OPPO Kernel Craftsman
Jul 10, 2020 · Information Security

Linux Kernel Crypto Framework: Architecture, Data Structures, and Application in File System Encryption

The Linux kernel’s generic crypto framework, introduced in version 2.5.45, defines core structures such as crypto_template, crypto_alg, crypto_instance and crypto_tfm to dynamically register and combine algorithms (e.g., ecb(aes)), providing a uniform API for symmetric, asymmetric, hash and other primitives, supporting user‑space access via AF_ALG and practical use cases like Android file‑based encryption with built‑in self‑tests for correctness.

Data StructuresLinux kernelSelf-test
0 likes · 11 min read
Linux Kernel Crypto Framework: Architecture, Data Structures, and Application in File System Encryption
Programmer DD
Programmer DD
Jun 27, 2020 · Fundamentals

Why Does Java’s HashMap Use a 0.75 Load Factor? The Math Behind It

This article explains why Java's HashMap adopts a default load factor of 0.75, covering hash table basics, collision‑resolution strategies, the Poisson‑distribution analysis that justifies the value, and the trade‑offs between space efficiency and lookup performance.

Data StructuresHashMapJava
0 likes · 11 min read
Why Does Java’s HashMap Use a 0.75 Load Factor? The Math Behind It
Open Source Tech Hub
Open Source Tech Hub
Jun 25, 2020 · Backend Development

Mastering Redis: Core Data Structures and Practical Commands Explained

This comprehensive guide explores Redis fundamentals, detailing its six primary data structures—strings, lists, hashes, sets, sorted sets, and streams—along with practical command examples, internal implementations, and usage patterns for high‑performance backend development.

Data StructuresRediscache
0 likes · 17 min read
Mastering Redis: Core Data Structures and Practical Commands Explained
Python Programming Learning Circle
Python Programming Learning Circle
Jun 15, 2020 · Fundamentals

30 Python Best Practices, Tips, and Tricks

This article presents thirty practical Python best‑practice tips covering version checks, IPython usage, list comprehensions, memory inspection, multiple return values, data classes, variable swapping, dictionary merging, string manipulation, ternary operators, counters, comparison chaining, color output, date parsing, integer division, character‑set detection and more, each illustrated with concise code examples.

Data StructuresPerformancebest practices
0 likes · 17 min read
30 Python Best Practices, Tips, and Tricks
AntTech
AntTech
Jun 8, 2020 · Fundamentals

What Is Programming? A Simple Introduction Using a Cooking Analogy

The article explains programming fundamentals by likening code to cooking, defining programming as algorithms plus data structures, illustrating basic concepts such as conditionals, loops, and abstraction through simple code examples, and emphasizing the difference between novice and expert approaches.

AlgorithmsData Structuresabstraction
0 likes · 8 min read
What Is Programming? A Simple Introduction Using a Cooking Analogy
Liangxu Linux
Liangxu Linux
Jun 6, 2020 · Fundamentals

Why Programmers Must Master Data Structures, OS, Compilers & Architecture

This answer explains why ordinary programmers should study core computer science subjects—data structures and algorithms, operating systems, compiler theory, and computer organization—illustrating each with practical examples, typical use cases, and the benefits they bring to real‑world software development.

AlgorithmsData StructuresOperating Systems
0 likes · 10 min read
Why Programmers Must Master Data Structures, OS, Compilers & Architecture
macrozheng
macrozheng
Jun 3, 2020 · Fundamentals

Master the 10 Essential Data Structures: From Arrays to Graphs

This article provides a comprehensive visual guide to ten fundamental data structures—including arrays, linked lists, skip lists, stacks, queues, trees, heaps, hash tables, and graphs—explaining their concepts, characteristics, and typical use cases for programmers and interview preparation.

AlgorithmsData Structurescomputer science
0 likes · 22 min read
Master the 10 Essential Data Structures: From Arrays to Graphs
Liangxu Linux
Liangxu Linux
May 31, 2020 · Fundamentals

Master the Top 10 Classic Sorting Algorithms with Code and Visualizations

This article systematically presents ten classic sorting algorithms—bubble, selection, insertion, quick, heap, merge, shell, counting, bucket, and radix—detailing their concepts, time and space complexities, step‑by‑step logic, animated illustrations, and complete source code examples in C++ and JavaScript.

C++Data StructuresJavaScript
0 likes · 19 min read
Master the Top 10 Classic Sorting Algorithms with Code and Visualizations
ITPUB
ITPUB
May 26, 2020 · Databases

Master Redis: Core Data Types, Commands, and Advanced Features Explained

Redis is a high‑performance, open‑source key‑value store offering persistence, rich data structures, replication, pub/sub, transactions, and clustering; this guide explains its fundamentals, data types (string, hash, list, set, sorted set), essential commands, and advanced features such as persistence options, replication, Sentinel, and sharding.

Data StructuresPersistenceRedis
0 likes · 16 min read
Master Redis: Core Data Types, Commands, and Advanced Features Explained
Selected Java Interview Questions
Selected Java Interview Questions
May 26, 2020 · Fundamentals

Eight Common Data Structures Every Programmer Should Know

This article introduces eight fundamental data structures—arrays, linked lists, stacks, queues, hash tables, trees, heaps, and graphs—explaining their definitions, core operations, typical applications, and visual illustrations to help programmers master essential concepts for software development and technical interviews.

Data StructuresQueuearray
0 likes · 12 min read
Eight Common Data Structures Every Programmer Should Know
Sohu Tech Products
Sohu Tech Products
May 20, 2020 · Fundamentals

Understanding Red‑Black Tree Insertion Cases and Rotations

This article provides a comprehensive tutorial on red‑black trees, covering binary search tree fundamentals, the five classic insertion cases, recoloring rules, left and right rotations, and a step‑by‑step example of inserting a new node while preserving all red‑black properties.

AlgorithmsData StructuresInsertion
0 likes · 8 min read
Understanding Red‑Black Tree Insertion Cases and Rotations
Python Crawling & Data Mining
Python Crawling & Data Mining
May 16, 2020 · Fundamentals

Master Python Sets: Unique Collections, Operations, and Practical Tips

This article introduces Python's set collection, covering its definition, unique characteristics, creation methods, common operations such as adding, updating, deleting, immutable frozenset usage, and set mathematics, while comparing it with lists, tuples, and dictionaries to highlight proper data‑structure selection.

CodingData StructuresPython
0 likes · 7 min read
Master Python Sets: Unique Collections, Operations, and Practical Tips
Laravel Tech Community
Laravel Tech Community
May 16, 2020 · Fundamentals

Master PHP Sorting Algorithms: Insertion, Selection, Bubble, Quick, Shell & More

This comprehensive guide walks through classic PHP sorting techniques—including insertion, selection, bubble, quick, and shell sorts—along with essential string utilities such as length calculation, reversal, comparison, substring search, replacement, insertion, deletion, copying, concatenation, simple encoding/decoding, and basic encryption/decryption, providing clear explanations and ready‑to‑run code examples for each algorithm.

AlgorithmsData StructuresPHP
0 likes · 15 min read
Master PHP Sorting Algorithms: Insertion, Selection, Bubble, Quick, Shell & More
Full-Stack Internet Architecture
Full-Stack Internet Architecture
May 15, 2020 · Fundamentals

Understanding Red-Black Tree Insertion Operations

This article provides a comprehensive, step‑by‑step explanation of red‑black tree insertion, covering binary search tree basics, red‑black properties, the five insertion cases, color changes, left and right rotations, and detailed visual examples to help readers fully master the data structure.

BalancingData StructuresInsertion
0 likes · 8 min read
Understanding Red-Black Tree Insertion Operations
Sohu Tech Products
Sohu Tech Products
May 13, 2020 · Fundamentals

Deep Dive into Java HashMap: Implementation, hashCode/equals, Collision Handling, and Interview Questions

This article provides a comprehensive overview of Java's HashMap, covering its place in the Set and Map families, internal implementation details, the relationship between hashCode() and equals(), collision resolution strategies, basic operations, differences from Hashtable, and several classic interview problems such as Top‑K frequency and LRU cache design.

CollisionData StructuresHashMap
0 likes · 14 min read
Deep Dive into Java HashMap: Implementation, hashCode/equals, Collision Handling, and Interview Questions
Python Crawling & Data Mining
Python Crawling & Data Mining
May 13, 2020 · Fundamentals

Master Python Lists, Tuples, and Dictionaries: Essential Guide with Code Examples

This article introduces Python’s core data structures—lists, tuples, and dictionaries—explaining their definitions, indexing, slicing, iteration, modification, and common operations, and provides clear code examples for creating, accessing, updating, and deleting elements, helping beginners deepen their programming fundamentals.

Data StructuresListProgramming Fundamentals
0 likes · 13 min read
Master Python Lists, Tuples, and Dictionaries: Essential Guide with Code Examples
Selected Java Interview Questions
Selected Java Interview Questions
May 6, 2020 · Fundamentals

Understanding HashMap Internals: Table Initialization, Resizing, and Load Factor

This article explains the inner workings of Java's HashMap, covering its array‑plus‑linked‑list (or red‑black tree) structure, lazy table initialization, default capacity and threshold, resizing mechanics, the rationale behind power‑of‑two table lengths, index calculation using bitwise AND, and the significance of the 0.75 load factor.

Data StructuresHashMapJava
0 likes · 18 min read
Understanding HashMap Internals: Table Initialization, Resizing, and Load Factor
Architect's Tech Stack
Architect's Tech Stack
May 2, 2020 · Fundamentals

Comprehensive Overview of the Java Collection Framework: Interfaces, Implementations, and Usage

This article provides a detailed walkthrough of Java's collection framework, covering the hierarchy of interfaces and abstract classes, the characteristics of List, Set, and Map implementations, iterator mechanisms, common pitfalls, and practical code examples to help developers choose and use the appropriate collection types effectively.

CollectionsData Structuresiterators
0 likes · 31 min read
Comprehensive Overview of the Java Collection Framework: Interfaces, Implementations, and Usage
Selected Java Interview Questions
Selected Java Interview Questions
Apr 30, 2020 · Fundamentals

Java Collections Framework Interview Questions and Answers

This article compiles a comprehensive set of Java Collections Framework interview questions, explaining its purpose, advantages, generic benefits, core interfaces, iterator behavior, fail‑fast vs fail‑safe, map views, differences among implementations, thread‑safety, and sorting mechanisms.

CollectionsData StructuresIterator
0 likes · 18 min read
Java Collections Framework Interview Questions and Answers
macrozheng
macrozheng
Apr 29, 2020 · Fundamentals

Mastering Java HashMap: From Basics to Interview Mastery

This article explains the fundamentals of Java's HashMap, covering its relationship to Set and Map families, internal implementation details, hashCode/equals contracts, collision resolution strategies, basic operations with code examples, and common interview questions such as Top‑K and LRU cache design.

Data StructuresHashMapJava
0 likes · 18 min read
Mastering Java HashMap: From Basics to Interview Mastery
Efficient Ops
Efficient Ops
Apr 28, 2020 · Databases

Master Redis: Core Concepts, Commands, and Data Types Explained

This article introduces Redis as an open‑source in‑memory data‑structure store, explains its role as a NoSQL database, covers fundamental data types, common commands, expiration handling, and advanced features like pipelines and transactions, providing a comprehensive guide for developers.

Data StructuresIn-Memory DatabaseNoSQL
0 likes · 15 min read
Master Redis: Core Concepts, Commands, and Data Types Explained
Full-Stack Internet Architecture
Full-Stack Internet Architecture
Apr 26, 2020 · Fundamentals

Understanding ConcurrentHashMap: Implementation Differences between JDK 1.7 and JDK 1.8

This article explains why ConcurrentHashMap provides thread‑safe and high‑performance map operations, compares it with HashMap and Hashtable, and details the architectural changes from JDK 1.7’s segment‑lock design to JDK 1.8’s array‑list‑red‑black‑tree and CAS‑based implementation.

ConcurrentHashMapData StructuresJDK7
0 likes · 7 min read
Understanding ConcurrentHashMap: Implementation Differences between JDK 1.7 and JDK 1.8
OPPO Kernel Craftsman
OPPO Kernel Craftsman
Apr 24, 2020 · Fundamentals

Evolution from Radix Tree to XArray in the Linux Kernel

The Linux kernel’s page‑cache indexing migrated from the classic radix‑tree structure—using shift‑based multi‑way nodes, RCU‑protected insert, lookup, and delete operations—to the newer XArray API introduced in 4.20, which retains the radix layout while offering automatic resizing, built‑in locking, richer marking, and a cleaner, safer interface.

Data StructuresLinux kernelRCU
0 likes · 17 min read
Evolution from Radix Tree to XArray in the Linux Kernel