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245 articles

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Mar 8, 2018 · Fundamentals

Understanding Java Garbage Collection: Young Generation, Old Generation, and Permanent Generation

This article explains Java's garbage collection mechanisms, detailing the roles and algorithms of the young generation (copying algorithm), old generation (mark‑sweep and mark‑compact), and permanent generation, along with object promotion criteria, efficiency comparisons, and memory utilization considerations.

AlgorithmsGarbage CollectionJVM

0 likes · 5 min read

Understanding Java Garbage Collection: Young Generation, Old Generation, and Permanent Generation

Java Architect Essentials

Mar 5, 2018 · Fundamentals

Common Data Structures in Java: Arrays, Lists, Queues, Stacks, Sets, Maps, Trees, and Heaps

This article introduces fundamental data structures such as arrays, linked lists, queues, stacks, sets, maps, various tree types including binary and AVL trees, and heaps, explaining their characteristics, time complexities, Java implementations like ArrayList, LinkedList, HashSet, TreeMap, and providing illustrative diagrams and code snippets.

AVL treeAlgorithmsHashMap

0 likes · 23 min read

Common Data Structures in Java: Arrays, Lists, Queues, Stacks, Sets, Maps, Trees, and Heaps

Java Backend Technology

Jan 27, 2018 · Backend Development

Master 48 Essential JavaScript Snippets in 30 Seconds

This article presents a curated collection of 48 practical JavaScript utilities—from generating anagrams and calculating averages to deep‑flattening arrays and creating UUIDs—each explained in a concise description with ready‑to‑use code examples for front‑end developers.

AlgorithmsJavaScriptcode snippets

0 likes · 16 min read

Master 48 Essential JavaScript Snippets in 30 Seconds

Java Captain

Dec 14, 2017 · Fundamentals

Understanding Java Garbage Collection Mechanisms and Algorithms

Java's garbage collection mechanism, introduced to simplify memory management, employs various algorithms such as reference counting, tracing (mark‑and‑sweep), compacting, copying, and generational collection, each with distinct advantages, drawbacks, and implementation details, while also addressing common memory‑leak pitfalls.

AlgorithmsGarbage CollectionGenerational GC

0 likes · 10 min read

Understanding Java Garbage Collection Mechanisms and Algorithms

Java Captain

Dec 11, 2017 · Fundamentals

Comprehensive Java Interview Topics: Data Structures, Algorithms, JVM, Concurrency, Linux, Frameworks, Databases, Networking, Caching, and Design Patterns

This document compiles a wide range of Java interview questions covering data structures and algorithms, core Java concepts, JVM internals, multithreading, Linux usage, popular frameworks, database fundamentals, network protocols, caching systems, and common design patterns to help candidates prepare comprehensively.

AlgorithmsDesign PatternsJVM

0 likes · 12 min read

Comprehensive Java Interview Topics: Data Structures, Algorithms, JVM, Concurrency, Linux, Frameworks, Databases, Networking, Caching, and Design Patterns

dbaplus Community

Dec 5, 2017 · Operations

Mastering Load Balancing: From Basics to Advanced Algorithms and Tools

This article explains the fundamentals of load balancing, compares layer‑2 to layer‑7 approaches, reviews popular software solutions such as LVS, Nginx and HAProxy, and details both static and dynamic balancing algorithms with practical implementation guidance.

AlgorithmsHAProxyLVS

0 likes · 17 min read

Mastering Load Balancing: From Basics to Advanced Algorithms and Tools

Hulu Beijing

Dec 5, 2017 · Artificial Intelligence

What Is Reinforcement Learning? Core Concepts Explained

This article introduces the fundamental concepts of reinforcement learning, describing its origins, key components such as agents, environments, states, actions, and rewards, explaining the Markov decision process framework, and highlighting common algorithms like Q‑learning, policy gradients, and actor‑critic methods.

AIAlgorithmsMDP

0 likes · 4 min read

What Is Reinforcement Learning? Core Concepts Explained

AI Large-Model Wave and Transformation Guide

Dec 5, 2017 · Artificial Intelligence

10 Must‑Know Machine Learning Algorithms for Engineers

From foundational concepts to practical examples, this guide walks engineers through ten essential supervised and unsupervised machine‑learning algorithms—decision trees, Naïve Bayes, linear regression, logistic regression, SVM, ensemble methods, clustering, PCA, SVD, and ICA—explaining their theory, real‑world uses, and why they matter.

AlgorithmsData ScienceModel Evaluation

0 likes · 11 min read

10 Must‑Know Machine Learning Algorithms for Engineers

21CTO

Dec 2, 2017 · Fundamentals

Why Mastering Computer Science Fundamentals Is the Key to Programming Success

The author reflects on years of programming experience, urging beginners to master core computer science subjects such as discrete math, algorithms, operating systems, and architecture, arguing that solid fundamentals prevent costly missteps when later learning frameworks like .NET, Java, or web technologies.

AlgorithmsOperating Systemscomputer science basics

0 likes · 8 min read

Why Mastering Computer Science Fundamentals Is the Key to Programming Success

Java Captain

Nov 22, 2017 · Backend Development

Understanding Java HashMap: Internal Mechanics of get and put with a Country Example

This article explains Java HashMap internals by walking through a concrete Country‑key example, illustrating how keys are hashed, stored in an internal Entry array, and how the put and get methods handle collisions using linked lists, complemented by full source code snippets.

AlgorithmsData StructuresHashMap

0 likes · 11 min read

Understanding Java HashMap: Internal Mechanics of get and put with a Country Example

21CTO

Nov 1, 2017 · Artificial Intelligence

Essential Machine Learning Algorithms: From Decision Trees to ICA Explained

This article introduces the most common machine learning algorithms, covering supervised methods such as decision trees, Naive Bayes, linear regression, logistic regression, SVM, and ensemble techniques, as well as unsupervised approaches like clustering, PCA, SVD, and ICA, with practical examples and visual illustrations.

AlgorithmsUnsupervised Learningmachine learning

0 likes · 10 min read

Essential Machine Learning Algorithms: From Decision Trees to ICA Explained

Hujiang Technology

Oct 11, 2017 · Artificial Intelligence

An Overview of Machine Learning and Deep Learning: Definitions, Core Concepts, and Typical Architectures

This article provides a comprehensive introduction to machine learning and deep learning, covering their definitions, differences, key concepts such as generalization, regularization, and overfitting, as well as typical algorithms and network architectures like CNN and RNN, illustrated with numerous diagrams.

AlgorithmsNeural Networksmachine learning

0 likes · 22 min read

An Overview of Machine Learning and Deep Learning: Definitions, Core Concepts, and Typical Architectures

ITFLY8 Architecture Home

Aug 24, 2017 · Fundamentals

Classic Algorithms: Divide‑Conquer, DP, Greedy, Backtracking, Branch‑and‑Bound

This article revisits fundamental algorithmic strategies—divide‑and‑conquer, dynamic programming, greedy methods, backtracking, and branch‑and‑bound—detailing their core ideas, applicable problem characteristics, key considerations, procedural steps, and illustrative examples such as merge sort, coin change, Huffman coding, and shortest‑path problems.

AlgorithmsBacktrackingbranch-and-bound

0 likes · 7 min read

Classic Algorithms: Divide‑Conquer, DP, Greedy, Backtracking, Branch‑and‑Bound

MaGe Linux Operations

Aug 16, 2017 · Artificial Intelligence

Ultimate Machine Learning Cheat Sheet: Algorithms, Python Tools & Math Essentials

This article curates over 20 machine‑learning cheat sheets—including algorithm overviews, Python libraries, and essential mathematics—compiled from various online sources and illustrated with downloadable diagrams, offering a comprehensive reference as of June 1 2017.

AlgorithmsData SciencePython

0 likes · 8 min read

Ultimate Machine Learning Cheat Sheet: Algorithms, Python Tools & Math Essentials

21CTO

Aug 15, 2017 · Fundamentals

Challenge Your Algorithm Skills with Four Progressive Puzzle Problems

This article presents four algorithmic puzzles ranging from entry to advanced levels, explains each problem statement, offers solution strategies and Ruby code snippets, and discusses combinatorial calculations, search optimizations, and implementation details to help programmers sharpen their coding and problem‑solving abilities.

AlgorithmsRubycombinatorics

0 likes · 10 min read

Challenge Your Algorithm Skills with Four Progressive Puzzle Problems

ITPUB

May 10, 2017 · Fundamentals

Why Algorithms Feel Hard and How to Truly Understand Huffman Coding

The article explores why many programmers find algorithms difficult, critiques typical textbook explanations, and presents a deeper, step‑by‑step reasoning for Huffman coding that emphasizes understanding proofs, underlying thought processes, and general problem‑solving principles.

AlgorithmsHuffman codingalgorithm design

0 likes · 36 min read

Why Algorithms Feel Hard and How to Truly Understand Huffman Coding

MaGe Linux Operations

May 10, 2017 · Big Data

What Defines Big Data? Core Concepts, Challenges, and Future Directions

This article outlines the fundamental definition of big data, its acquisition, transmission, usability, common algorithmic issues, security concerns, potential reforms in hardware and software, and the major computational and interdisciplinary challenges that must be addressed.

AlgorithmsBig DataData Transmission

0 likes · 3 min read

What Defines Big Data? Core Concepts, Challenges, and Future Directions

ITPUB

May 2, 2017 · Fundamentals

Master Core Algorithms: Sorting, Graph Traversal, Greedy & Complexity Basics

This guide presents concise explanations of essential algorithms—including quick sort, merge sort, bucket and radix sorts, depth‑first and breadth‑first searches, shortest‑path and minimum‑spanning‑tree methods—along with their stability, time‑complexity analyses, greedy strategies, bit‑manipulation tricks, and asymptotic notation, and points to a GitHub repository for reference implementations.

AlgorithmsInterview PrepSorting

0 likes · 10 min read

Master Core Algorithms: Sorting, Graph Traversal, Greedy & Complexity Basics

ITPUB

Apr 24, 2017 · Fundamentals

Essential Algorithm Cheat Sheet: Sorting, Graph, Greedy, and Bit Operations

This article provides a concise reference of core algorithms—including sorting methods, graph traversals, shortest‑path techniques, greedy strategies, bit‑level manipulations, and asymptotic notation—detailing their stability, time complexities, key concepts, and practical examples for interview preparation.

AlgorithmsInterview PreparationSorting

0 likes · 8 min read

Essential Algorithm Cheat Sheet: Sorting, Graph, Greedy, and Bit Operations

ITPUB

Apr 23, 2017 · Fundamentals

Master Core Data Structures: Linked Lists, Trees, Heaps, and More

This comprehensive guide explains fundamental data structures—including linked lists, stacks, queues, various tree types, binary indexed trees, segment trees, heaps, hash tables, and graphs—detailing their definitions, variants, typical operations, and time‑complexity characteristics for efficient algorithm design.

AlgorithmsData Structurescomputer science

0 likes · 9 min read

Master Core Data Structures: Linked Lists, Trees, Heaps, and More

Qunar Tech Salon

Apr 16, 2017 · Fundamentals

String Matching Algorithms: Brute‑Force, KMP, Boyer‑Moore, BMH, Sunday, Shift‑And/Or, and Bitmap

This article introduces several classic string‑matching algorithms—including Brute‑Force, KMP, Boyer‑Moore, BMH, Sunday, Shift‑And/Or, and bitmap techniques—explaining their principles, preprocessing steps, and practical considerations for improving text search performance.

AlgorithmsBoyer-MooreKMP

0 likes · 12 min read

String Matching Algorithms: Brute‑Force, KMP, Boyer‑Moore, BMH, Sunday, Shift‑And/Or, and Bitmap

Architecture Digest

Mar 31, 2017 · Backend Development

Game Server Framework Architecture Overview

This article outlines a four‑layer game server framework—including gateway, logic, record, and database services—detailing their responsibilities, implementation models such as multithreaded reactors and coroutine libraries, service‑driven designs, and the common design patterns and algorithms used in backend game development.

AlgorithmsBackend Architecturegame server

0 likes · 6 min read

Game Server Framework Architecture Overview

21CTO

Mar 24, 2017 · Fundamentals

My Journey Through Data Structures and Algorithms: Lessons, Books, and Real-World Projects

From a careless college student to a seasoned developer, the author chronicles a seven‑year odyssey of learning data structures and algorithms, sharing book recommendations, personal projects, internship experiences, and hard‑won insights on why solid algorithmic foundations are essential for modern software engineering.

AlgorithmsBooksData Structures

0 likes · 19 min read

My Journey Through Data Structures and Algorithms: Lessons, Books, and Real-World Projects

ITFLY8 Architecture Home

Dec 17, 2016 · Fundamentals

Understanding Classic Algorithms: Divide‑and‑Conquer, DP, Greedy, Backtracking

The article revisits fundamental algorithmic strategies—including divide‑and‑conquer, dynamic programming, greedy methods, backtracking, and branch‑and‑bound—detailing their core ideas, applicable problem characteristics, key considerations, procedural steps, and illustrative examples such as merge sort, coin change, Huffman coding, minimum spanning trees, and shortest‑path problems.

AlgorithmsBacktrackingbranch-and-bound

0 likes · 7 min read

Understanding Classic Algorithms: Divide‑and‑Conquer, DP, Greedy, Backtracking

Meituan Technology Team

Dec 2, 2016 · Fundamentals

Mastering Red-Black Trees: From BST Basics to Insertion, Deletion, and Rotations

This article explains binary search trees, their limitations, and introduces red‑black trees as a balanced BST alternative, detailing their properties, node definitions, rotation mechanisms, and step‑by‑step insertion and deletion algorithms with Java code examples and visual illustrations.

AlgorithmsBinary Search TreeData Structures

0 likes · 19 min read

Mastering Red-Black Trees: From BST Basics to Insertion, Deletion, and Rotations

Meituan Technology Team

Jun 24, 2016 · Fundamentals

Deep Dive into Java HashMap: Structure, Implementation, and Performance in JDK 1.7 vs 1.8

This article explains Java’s HashMap internals, compares JDK 1.7 and 1.8 implementations, details the bucket array, linked‑list‑to‑red‑black‑tree conversion, resizing logic, performance gains of up to 100 % in 1.8, and warns against using HashMap in concurrent contexts.

AlgorithmsData StructuresHashMap

0 likes · 20 min read

Deep Dive into Java HashMap: Structure, Implementation, and Performance in JDK 1.7 vs 1.8

ITFLY8 Architecture Home

Jun 9, 2016 · Operations

Understanding Load Balancing Algorithms and Hardware Solutions

This article explains common load‑balancing algorithms—including round‑robin, random, least‑connections, source‑IP hash, and weighted methods—describes their advantages and drawbacks, and examines hardware load‑balancing devices such as F5 and A10, covering functional, performance, stability, security, and cost considerations.

AlgorithmsHardwareload-balancing

0 likes · 5 min read

Understanding Load Balancing Algorithms and Hardware Solutions

21CTO

May 9, 2016 · Fundamentals

How I Cracked Google’s Onsite Interview: My Prep Checklist and Lessons Learned

The author recounts a successful Google onsite interview experience, detailing the preparation steps—including reading key books, reviewing algorithms, practicing white‑board coding, and consulting insiders—to illustrate an effective strategy for tackling software engineering interviews.

AlgorithmsGoogle interviewInterview Preparation

0 likes · 7 min read

How I Cracked Google’s Onsite Interview: My Prep Checklist and Lessons Learned

Qunar Tech Salon

Apr 29, 2016 · Fundamentals

Common Sorting Algorithms: Quick Sort, Merge Sort, Heap Sort, Selection Sort, Bubble Sort, Insertion Sort, and Shell Sort

This article introduces seven classic sorting algorithms—Quick Sort, Merge Sort, Heap Sort, Selection Sort, Bubble Sort, Insertion Sort, and Shell Sort—explaining their principles, step-by-step procedures, and visual performance illustrations to help readers understand their operation and efficiency.

AlgorithmsQuick SortSorting

0 likes · 8 min read

Common Sorting Algorithms: Quick Sort, Merge Sort, Heap Sort, Selection Sort, Bubble Sort, Insertion Sort, and Shell Sort

ITPUB

Apr 20, 2016 · Backend Development

Top 17 C++ Backend Interview Questions with Answers and Code Samples

This article compiles 17 common C++ backend interview questions covering algorithms, data structures, language nuances, Linux process handling, SQL, networking, and system design, providing concise explanations and complete code examples to help candidates prepare effectively.

AlgorithmsC++Linux

0 likes · 18 min read

Top 17 C++ Backend Interview Questions with Answers and Code Samples

21CTO

Mar 8, 2016 · Fundamentals

10 Pioneering Computer Scientists Who Shaped Modern Computing

This article profiles ten influential computer scientists and innovators—from Donald Knuth and Edsger Dijkstra to John Backus and Tony Hoare—highlighting their groundbreaking contributions, awards, and lasting impact on algorithms, programming languages, and the evolution of computer science.

Algorithmscomputer sciencehistory

0 likes · 11 min read

10 Pioneering Computer Scientists Who Shaped Modern Computing

ITPUB

Feb 23, 2016 · Fundamentals

Master 10 Essential Algorithms: From QuickSort to Naive Bayes

This guide introduces ten core algorithms—including QuickSort, HeapSort, MergeSort, Binary Search, BFPRT, DFS, BFS, Dijkstra, Dynamic Programming, and Naive Bayes—explaining their principles, step‑by‑step procedures, and typical use cases for efficient problem solving.

AlgorithmsNaive BayesSearch

0 likes · 14 min read

Master 10 Essential Algorithms: From QuickSort to Naive Bayes

Qunar Tech Salon

Jan 22, 2016 · Fundamentals

My Journey Learning Data Structures and Algorithms

The article recounts the author's seven‑year path learning data structures and algorithms, from neglect in college to self‑study, book recommendations, internships at Microsoft and Baidu, projects such as a T‑SQL parser and a pinyin index, and reflections on the importance of algorithms.

AlgorithmsData StructuresInterview Preparation

0 likes · 19 min read

My Journey Learning Data Structures and Algorithms

21CTO

Jan 19, 2016 · Fundamentals

From Zero to Mastery: My Journey Learning Data Structures & Algorithms

This article chronicles the author's seven‑year evolution from a disinterested student to a seasoned developer, detailing study plans, key algorithm and data‑structure books, internship experiences, custom parsers, performance‑critical mobile features, and the indispensable role of algorithms for serious programmers.

AlgorithmsData Structureslearning

0 likes · 20 min read

From Zero to Mastery: My Journey Learning Data Structures & Algorithms

ITPUB

Jan 6, 2016 · Fundamentals

Mastering C++: Essential Skills Every Beginner Should Learn

This guide outlines the core competencies, project experience, and communication abilities a new C++ programmer should develop, recommending key resources and practical focus areas to accelerate learning and become an effective software developer.

AlgorithmsC++Learning Path

0 likes · 8 min read

Mastering C++: Essential Skills Every Beginner Should Learn

Qunar Tech Salon

Dec 5, 2015 · Fundamentals

Why Learning Data Structures and Algorithms Makes You a Better Developer

This article explains how mastering data structures and algorithm analysis provides a problem‑solving mindset, covering fundamental concepts, Dijkstra’s shortest‑path algorithm, topological sorting for dependency resolution, and Huffman coding for data compression, illustrating their broad impact on software development.

AlgorithmsData StructuresDijkstra

0 likes · 19 min read

Why Learning Data Structures and Algorithms Makes You a Better Developer

21CTO

Oct 12, 2015 · Fundamentals

Master Classic Sorting Algorithms in Python (Insertion to Radix)

This article systematically presents the principles and Python implementations of eight classic sorting algorithms—Insertion, Shell, Bubble, Quick, Selection, Heap, Merge, and Radix—offering complete code examples and detailed explanations to help readers grasp their mechanisms and performance characteristics.

AlgorithmsQuick SortSorting

0 likes · 10 min read

Master Classic Sorting Algorithms in Python (Insertion to Radix)

21CTO

Oct 10, 2015 · Fundamentals

Effective Ways to Study Algorithms: Books, Videos, and Practice Tips

This article compiles practical advice on learning algorithms, recommending beginner‑friendly books, video courses, coding exercises, and optimization tricks while explaining why certain resources like Sedgewick's Algorithms and Princeton's Coursera lectures can be more approachable than the traditional "Introduction to Algorithms".

AlgorithmsData StructuresLearning Resources

0 likes · 11 min read

Effective Ways to Study Algorithms: Books, Videos, and Practice Tips

21CTO

Sep 24, 2015 · Fundamentals

From Zero to Algorithm Mastery: My 7‑Year Journey and Lessons Learned

The author chronicles a seven‑year evolution from a clueless undergraduate to a seasoned programmer, detailing the books, courses, internships, and personal projects that shaped his understanding of data structures and algorithms, while debating the practical value of algorithmic knowledge in software development.

AlgorithmsCareer DevelopmentData Structures

0 likes · 19 min read

From Zero to Algorithm Mastery: My 7‑Year Journey and Lessons Learned

Qunar Tech Salon

Sep 16, 2015 · Fundamentals

A Programming Language Is a System for Encoding, Naming, and Organizing Algorithms

The article explains that a programming language serves as a system to encode, name, and organize algorithms, discusses the misuse of the term “algorithm,” illustrates classic algorithms like Dijkstra’s and Euclid’s with code examples in Forth, PostScript, and Python, and emphasizes the DRY principle and efficiency concerns in software development.

AlgorithmsCode ExamplesDRY principle

0 likes · 8 min read

A Programming Language Is a System for Encoding, Naming, and Organizing Algorithms

21CTO

Aug 11, 2015 · Backend Development

Inside Top Chinese Tech Interviews: Backend Engineer Questions & Answers

This article compiles detailed interview experiences for backend engineering roles at major Chinese tech firms, covering algorithm challenges, system design, networking, compiler concepts, and personal reflections that help candidates prepare effectively.

AlgorithmsBackendNetworking

0 likes · 9 min read

Inside Top Chinese Tech Interviews: Backend Engineer Questions & Answers

Architect

Jul 2, 2015 · R&D Management

How to Interview an Architect: Key Question Types and Evaluation Strategies

This article outlines the essential question categories—technical details, algorithms and data structures, and design thinking—to assess an architect candidate's depth of understanding, problem‑solving mindset, and ability to craft robust, maintainable solutions during interviews.

AlgorithmsSoftware Architectureinterview

0 likes · 11 min read

How to Interview an Architect: Key Question Types and Evaluation Strategies

Qunar Tech Salon

Mar 27, 2015 · Fundamentals

Classic Algorithms that Shaped Modern Computing

This article surveys a collection of seminal algorithms—including Huffman coding, public‑key encryption, Dijkstra's shortest‑path, binary search, quicksort, Karatsuba multiplication, Euclid's GCD, Bresenham's line drawing, and the fast inverse square‑root—explaining their origins, principles, and lasting impact on computer science.

AlgorithmsSearchSorting

0 likes · 7 min read

Classic Algorithms that Shaped Modern Computing

Baidu Tech Salon

Jun 23, 2014 · Artificial Intelligence

Algorithms as Evolving Entities: Lessons from Dog Domestication

Just as wolves gradually became dogs by learning human cues, modern algorithms must evolve to comprehend our intentions and values, turning from opaque decision‑makers into humane partners that enhance daily life without friction, lest their unchecked speed and logic create dangerous mismatches.

AlgorithmsHuman-Computer InteractionTechnology Evolution

0 likes · 13 min read

Algorithms as Evolving Entities: Lessons from Dog Domestication