This tutorial walks you through installing the EasyCode IntelliJ plugin, creating a MySQL database, configuring IDEA’s database connection, setting up Maven dependencies and application.yml, generating entity, DAO, service, and controller code automatically, and finally running the Spring Boot project.
The article traces programming’s journey from manual 0‑and‑1 coding and basic editors, through the copy‑paste era enabled by graphical IDEs and the web, to today’s AI‑driven development where tools like Copilot and Cursor let developers code by prompting, reshaping the craft.
This article examines the shortcomings of the previous Cursor IDE rule set, introduces a three‑layer architecture for AI‑assisted coding, defines a standardized rule format and execution protocol, and provides best‑practice guidelines and phased rollout plans to ensure consistent, high‑quality code generation.
In just three days, the team built the Streams‑to‑River English learning app by leveraging the AI‑driven TRAE IDE, which generated most of the code, integrated large‑model features, and employed a Hertz‑Kitex microservice architecture with MySQL, Redis, and AI services.
This article examines the LiveCodeBench Pro benchmark, revealing that while large language models achieve impressive scores on knowledge‑ and logic‑heavy coding problems, they still fall short of human experts on high‑difficulty, observation‑intensive tasks, especially without external tool support.
Meituan revealed that AI now writes 52% of its new code, using its proprietary LongCat model to handle repetitive tasks, while developers still oversee core logic, prompting a shift toward prompt engineering, careful review, and new strategies to avoid technical debt.
This article explains C preprocessor macros in depth, covering simple constant replacement, parameterized macros, stringification, token‑pasting, predefined macros, variadic macros, conditional compilation tricks, common pitfalls, and best‑practice recommendations for safe usage.
The article examines how AI can speed up code generation yet fails to reduce the fundamental complexities of software development, shifting challenges to new areas such as prompt engineering, consistency, changeability, and invisibility, and argues that future developers must master AI to manage, not replace, complexity.
This guide walks you through integrating Alibaba Cloud DevOps MCP service with the Lingma code generation tool to automatically create code, branches, and merge requests from work item descriptions, covering prerequisites, token setup, service addition, and execution steps.
The DeepSeek‑R1 model upgrade dramatically improves reasoning depth and code‑generation performance, matching top‑tier models on benchmarks like LiveCodeBench, while industry experts warn that such advances could reshape software engineering roles and devalue pure coding skills.
The KwaiPilot team released the KwaiCoder‑AutoThink‑preview model, which introduces a novel automatic‑thinking training paradigm and a process‑supervised reinforcement‑learning method called Step‑SRPO, enabling the model to dynamically switch between thinking and non‑thinking modes, reduce inference cost, and achieve up to 20‑point gains on code and math benchmarks while handling large‑scale codebases.
This article shares a step‑by‑step guide on planning, documenting, templating, configuring, and rule‑setting for the Cursor AI coding assistant, showing how thorough preparation transforms it from a source of buggy code into a reliable development partner.
Recent work from West Lake University's MAPLE Lab introduces a diffusion‑based “Divergent Thought Chain” that treats each intermediate denoising step of a diffusion language model as a reasoning step, using result‑based reinforcement learning to optimize non‑linear token generation and achieving state‑of‑the‑art performance on math and code tasks.
DeepSeek‑R1‑0528, the latest open‑source 660B LLM, dramatically improves coding, reasoning, and long‑context abilities, matching or surpassing top models like Gemini 2.5 Pro and Claude 4 in benchmarks and real‑world tests, while offering faster, more stable, and fully executable outputs.
This article introduces the Mybatis-Plus Generator UI, a highly customizable web‑based code generator that wraps Mybatis‑Plus, explains its features, shows how to integrate it via Maven, run a sample main class, configure generation strategies, customize templates and naming rules, and even extend the frontend with Yarn builds.
This article shares the seven practical practices discovered while building AutoDev Workbench, detailing how AI‑assisted demand analysis, rapid UI prototyping, adaptive front‑end generation, focused refactoring, precise context feeding, automated testing, and lint‑type safeguards can turn chaotic AI‑generated code into a scalable, maintainable development workflow.
The article examines Vibe Coding, an AI‑driven programming approach that lets developers generate software from natural‑language prompts, outlining its efficiency gains, lower entry barriers, cross‑domain collaboration benefits, as well as code‑quality, debugging, over‑reliance risks, and practical guidelines for responsible use.
This guide explores C preprocessor macros in depth, covering basic constant and function‑like macros, stringification, token‑pasting, predefined macros, variadic macros, and practical tricks like conditional logging and simulated try‑catch, while warning about common pitfalls.
This guide explains how to use CursorRules to precisely control the behavior of the Cursor AI programming assistant, covering the rule file structure, global versus project‑specific configurations, rule types, practical examples, best‑practice tips, integration with external documentation, and community resources for continuous improvement.
This article introduces MapStruct, a compile‑time Java bean‑mapping framework, and demonstrates advanced features such as expression‑based mappings, qualifiedByName for custom conversions, nullValueMappingStrategy for handling nulls, and the use of Decorator classes to apply global post‑processing logic.
This article examines the drawbacks of Lombok—such as reduced readability, IDE instability, and debugging challenges—and demonstrates how replacing Lombok annotations with Java Records, explicit constructors, and MapStruct for mapping yields cleaner, type‑safe, and maintainable code while eliminating boilerplate.
This guide outlines a systematic workflow for using the Cursor AI coding assistant—starting with precise requirement planning, creating project documentation, leveraging starter kits, injecting context files, configuring granular project rules, and finally achieving stable, maintainable code output.
This article chronicles how a developer transformed the TransDuck audio‑video SaaS tool into a native desktop application using Tauri, Vue, and ffmpeg, while leveraging the AI‑driven CodeBuddy extension to automate project scaffolding, code generation, error fixing, and UI refinement, cutting development time from days to a few hours.
This guide explains how to install PyQt5, set up Qt Designer, convert .ui files into Python code with pyuic5, and run a basic PyQt5 window, providing step‑by‑step commands, code snippets, and screenshots for a complete GUI development workflow.
The Gemini 2.5 Pro 05‑06 update dramatically improves code‑generation performance, tops the WebDev Arena leaderboard over Claude 3.7 Sonnet, and introduces unique video‑to‑web multimodal abilities, while still facing UI bugs and naming inconsistencies ahead of the upcoming Google I/O conference.
The article introduces Cursor, an AI‑powered coding assistant, outlines its supported large models, demonstrates practical front‑end use cases such as automatic layout creation, button logic, screenshot‑to‑code generation, error fixing and code cleanup, and reflects on prompt engineering and tool selection.
This article introduces Vibe Coding, an AI‑driven programming approach proposed by Andrej Karpathy, explains its core concepts, workflow, advantages, tools, use cases, best practices, and future outlook, and provides a complete example of generating a simple weather app using natural‑language prompts.
At the Create2025 AI Developer Conference, Baidu unveiled the multimodal Wenxin 4.5 Turbo and X1 Turbo models, detailing their innovative architecture, self‑feedback post‑training, composite reasoning chains, data pipelines, and the new Wenxin KuaiMa 3.5 code assistant, while also showcasing ecosystem growth and cultural AI applications.
Vibe Coding, introduced by AI expert Andrej Karpathy in 2025, lets developers describe functionality in natural language and rely on large language models to generate code, shifting the programmer’s role to guiding AI, boosting productivity, lowering entry barriers, and reshaping software development practices.
This article introduces MyBatis‑Plus, an enhancement for MyBatis, outlining its lightweight features, step‑by‑step setup including database creation, Maven dependency, configuration, entity and mapper definitions, CRUD operations, pagination, optimistic locking, logical deletion, condition wrappers, and code generation utilities for rapid backend development.
This article outlines a comprehensive methodology for integrating AI—particularly large language models—into software development workflows by establishing knowledge‑base templates, rule systems, multi‑model collaboration, context management, and task decomposition to transform AI from a whimsical code generator into a trustworthy engineering partner.
This guide explains how to obtain a token, install MasterGo MCP in Cursor, configure the mcp.json file, and use the provided getDSL and getComponentLink tools to retrieve design canvas DSL and generate front‑end code such as React, Vue, or Flutter components.
An in‑depth guide reviews six leading AI‑driven development tools—including GitHub Copilot, Alibaba Cloud CodeWhisperer, Tabnine, Tencent Hunyuan DevBox, Amazon CodeWhisperer, and CodeGeeX—detailing their core features, use cases, security considerations, and selection advice for Java developers seeking to automate code generation, review, configuration, performance tuning, and documentation.
The 2024‑2025 comparative review evaluates cloud‑based AI development platforms, AI‑native code editors, IDE plugins, and their underlying large language models—detailing features, user experience, pricing, open‑source status, strengths and weaknesses, offering recommendations for UI prototyping, full‑stack projects, and forecasting future multimodal, collaborative AI‑assisted development trends.
This article walks through the Model Context Protocol (MCP) as an AI‑centric "USB‑C" for tool integration, explains its core capabilities, shows how to register and call MCP tools using the TypeScript SDK, details the end‑to‑end workflow from ZIP file handling to React code generation, and shares practical implementation tips and future improvements.
This article walks through why repetitive CRUD code wastes development time, reviews existing generators like MyBatis‑Generator and MyBatis‑Plus, and then demonstrates step‑by‑step how to create a custom Java code generator using Freemarker, Maven, and SpringBoot, complete with template and demo code.
This article surveys the rapid evolution of AI-powered developer tools over the past few years, categorizing them by how AI is embedded in workflows—from assistive chatbots to integrated IDE assistants, AI-first environments, rapid prototyping platforms, and autonomous agents—while evaluating their benefits, limitations, and future impact.
Meta's newly released Llama 4 quickly became a controversy as internal leaks reveal training‑data cheating, benchmark over‑optimization, and disappointing code‑generation performance that fails to match even older models, prompting resignations and widespread criticism from the AI community.
The article explains how integrating the Cursor AI assistant into front‑end development reshapes workflow by separating planning from execution, using iterative context loops for analysis, design, and impact assessment, guiding minimal‑change code generation and testing, and ultimately shifting developer skill from memorizing APIs to asking precise questions.
The article provides a comprehensive evaluation of DeepSeek‑V3‑0324, highlighting its superior inference, coding, and long‑text abilities, benchmark rankings that place it near GPT‑4.5, extensive code‑generation tests, and advanced Function Calling features that make it the preferred model for building AI agents.
The article examines Cursor’s Agent mode as a transformative AI‑driven programming paradigm, comparing it with traditional Copilot assistance, showcasing a Go API generation example, and offering practical tips, challenges, and future outlook for developers embracing AI‑powered code collaboration.
Google's Gemini 2.5, billed as its most intelligent AI model, introduces advanced reasoning capabilities that outperform rivals on benchmarks like LMArena and Humanity's Last Exam, excels at web and agent code generation, and is now available to premium users via AI Studio with a 1‑million token context window.
This guide explains why using Figma design files with Cursor AI yields more accurate, collaborative, and scalable front‑end code generation, walks through preparing the Figma API key, configuring the MCP service, step‑by‑step conversion workflows, advanced prompting tips, integration strategies, and troubleshooting common issues.
This article introduces a free, online tool that lets backend developers quickly generate complete frontend management pages—such as CRUD interfaces—by uploading database schemas or descriptor files, detailing step‑by‑step usage, configuration options, and code snippets for rapid, no‑code UI creation.
The live session examines how AI tools impact software development productivity, detailing personal, team, and organizational effects, practical use cases, limitations, industry implications, and a comparison between domestic and foreign AI solutions, concluding that AI boosts individual output but offers limited gains at scale.
By 2025, AIGC is poised to transform full‑stack development, automating requirement analysis, code generation, testing, and deployment, thereby accelerating productivity while prompting developers to upskill and collaborate with AI rather than fear replacement.
This guide lists the most useful Cursor AI editor shortcuts—such as opening the AI chat, using Agent mode, auto‑completing code, generating code blocks, accepting or rejecting suggestions, customizing keys, and accessing settings—so you can dramatically increase productivity while coding.
This article explores how AI-powered programming assistants dramatically improve development efficiency, accelerate learning, and reduce errors, offering detailed evaluations of five leading tools, practical prompt formulas, common pitfalls, future trends, and data-backed recommendations for developers seeking to thrive in the AI era.
This article explains how Cursor Rules let developers constrain AI behavior in the Cursor editor, covering global and project rule types, practical file configurations, best‑practice examples for general, Python, documentation, and Git rules, and tips for effective rule management.
gRPC offers high performance for microservices, but its generated protobuf code, required fields handling, and steep learning curve create ugly, hard‑to‑maintain implementations; this article examines those pain points, showcases examples, and suggests tools and best practices to mitigate them.
Riverpod annotations streamline Flutter state management by using build_runner to generate provider code, where @riverpod on functions creates Provider, FutureProvider, or StreamProvider based on return type, on classes creates NotifierProvider, supports Family‑pattern parameters, keepAlive, dependencies, and produces helper classes for auto‑dispose and scoped overrides.
The JD Cloud frontend team introduced a C2D2C workflow that converts component code into design tokens, generates synchronized Figma controls, and then transforms those designs back into code, aiming to eliminate version gaps, reduce designers' workload, and improve design‑to‑code fidelity across the Mobius design system.
This article describes JD Cloud’s C2D2C (Code‑to‑Design‑to‑Code) workflow that unifies design and development assets, solves version lag and designer distraction, and demonstrates early results and future plans for automating UI component generation.
This article introduces DeepSeek’s 13 ready‑to‑use prompt templates, explains how to rewrite and optimize code, decode algorithm logic, generate full‑stack applications, classify text, produce structured JSON, role‑play personas, craft prose, poetry, outlines, slogans, and even translate technical statements, showcasing the versatility of modern AI prompting.
The author demonstrates how a beginner can create a functional WeChat mini‑program in half an hour by using the "AI programmer" mode of Tongyi Lingma, which leverages DeepSeek V3 and Qwen2.5‑Max models to generate, modify, and debug code through natural‑language prompts.
WeaveFox, Ant Group’s AI‑powered front‑end platform, claims to turn design drafts into fully functional React or Vue code—including precise pixel alignment and interactive effects—in seconds, while offering cross‑terminal support, automated refactoring, performance boosts, and a continuous learning loop, yet the author argues it won’t fully replace developers.
This article explains how AI‑generated code can be fast but unreliable, and demonstrates how applying Test‑Driven Development (TDD) with concrete Python examples catches errors like stack overflows, edge‑case failures, and security issues, ensuring robust, maintainable software.
Claude 3.7 Sonnet demonstrates unprecedented programming speed, realistic physics simulation, advanced reasoning on misleading benchmarks, and strong productivity tools, while Anthropic secures a $3.5 billion funding round, making it a standout AI model in both technical capability and market impact.
This article walks through creating a fully automated Spring Boot and MyBatis code generator using Freemarker templates, detailing each step from extracting table metadata to generating DAO, service, controller, and entity classes, and shows how a single-table CRUD can be produced in seconds.
This article shares a step‑by‑step account of using AI tools such as Trae, Claude 3.5 Sonnet, and GPT‑4o to design, generate, and refine a Vue‑based frontend website within a single day, highlighting core strategies, best practices, and common pitfalls encountered along the way.
This article documents how the author leveraged the Trae AI‑powered IDE to quickly create a three‑page WeChat mini‑program, detailing project setup, code generation, interactive AI assistance, and the resulting development experience.
This article explores how large language models can be leveraged to automate and accelerate frontend development tasks, covering prompt engineering, repo‑level code generation, quality factors, hallucination mitigation, knowledge‑base integration, and practical strategies for improving developer productivity.
KwaiCoder-23BA4-v1 is a 23B wide MoE code‑completion model that achieves state‑of‑the‑art performance on HumanEval, BigCodeBench and Fill‑in‑Middle benchmarks by using high‑quality data, a cost‑effective training pipeline that combines model pruning, knowledge distillation and fine‑grained merging, and extensive ablation studies.
This guide explains Swift 5.9 macros—both attached and freestanding—detailing how the compiler expands them using SwiftSyntax’s AST manipulation, walks through creating and declaring macros, and demonstrates a PeerMacro that automatically generates async counterparts for completion‑handler functions, reducing boilerplate and improving code clarity.
Facing the challenge of maintaining four codebases for Taobao’s post‑purchase information flow, the team leveraged AI‑driven code generation, prompt engineering, and RAG to automate template conversion from DX to Weex, dramatically cutting development cycles, reducing manual effort, and improving monitoring and stability across Android, iOS, and HarmonyOS.
This article demonstrates how Lombok’s advanced annotations such as @RequiredArgsConstructor(onConstructor=@__(@Autowired)), @Delegate, @Cleanup, and the combination of @Builder with @Singular can automatically generate Spring‑compatible constructors, delegate methods, manage resources, and build immutable objects, thereby reducing boilerplate and improving code readability in Java backend development.
In the AI era, Qunar's front‑end tech director presents how D2C and large‑model‑based code generation dramatically improve front‑end productivity across three business scenarios, achieving up to 55% automated code coverage for both C‑end and B‑end applications.
This article introduces EnumHelper, an IntelliJ IDEA plugin that automatically generates common enum utility methods for Java developers, explains how to install and use it, and shares detailed troubleshooting tips and core source code to avoid repetitive boilerplate.
This article evaluates the Cursor AI coding assistant, describing its context‑aware indexing, Composer panel, and code‑generation features, while outlining practical scenarios such as Q&A, test creation, language conversion, and prototype development, and discussing its inherent randomness, domain‑knowledge gaps, and best‑practice recommendations for developers.
Explore how Lombok’s powerful annotations—@onX, @Delegate, @Cleanup, @Singular, and @Builder—can dramatically simplify Java code, enable seamless Spring dependency injection, manage resources automatically, and streamline object construction, while highlighting best practices and potential pitfalls for maintainable backend development.
This article introduces an online SQL-to-ER diagram tool, explains its advantages, provides step‑by‑step usage instructions, showcases example SQL and Java code for parsing and generating ER diagrams, and discusses the underlying design‑pattern architecture such as Strategy, Factory, Dependency Injection, and Singleton.
This article details the Vision animation platform that underpins Kuaishou’s large‑scale online events, covering its overall architecture, core value, existing production and delivery challenges, evolution roadmap, key runtime and format‑conversion features, as well as dynamic replacement and code‑generation capabilities.
This guide walks developers through the entire lifecycle of Qwen2.5‑Coder—covering model sizes, training token expansion, resource requirements, fine‑tuning with SFT/DPO, evaluation on custom and public datasets, and one‑click deployment and compression on Alibaba Cloud's PAI‑QuickStart platform.
This article explains how ArchGuard’s Architecture Analyzer extracts domain and business knowledge from microservice codebases, integrates generative AI to produce structured documentation, and provides practical CLI usage, architecture models, and code‑review strategies for modern software engineering teams.
This article introduces an open‑source tool that automatically generates all Java business code—including entity classes, DAO interfaces, SQL statements, service implementations, and controllers—for new database tables, dramatically reducing the hours spent on repetitive CRUD scaffolding.
This article introduces the Fluent Mybatis ORM framework, explains its design advantages, demonstrates how to implement a complex student‑score aggregation query using Fluent Mybatis, native MyBatis and MyBatis‑Plus, and provides end‑to‑end code examples for entity generation, configuration, and CRUD testing.
This article introduces a Spring Boot code‑generation tool that automatically creates database tables, entity classes, DAO interfaces, service layers and controllers, turning weeks of manual CRUD development for dozens of tables into a matter of minutes, and explains its design, templates, dynamic parameters and usage.
The article argues that depending on AI to write code can deprive developers of learning opportunities, cause skill decay, and ultimately make them vulnerable to being replaced, while acknowledging that some may prefer code review or embrace a post‑work future.
This article demonstrates how Lombok annotations such as @RequiredArgsConstructor, @Delegate, @Cleanup, @Singular, and @Builder can be combined with Spring components to reduce boilerplate, automatically inject dependencies, manage resources, and build immutable objects, providing practical code examples and usage guidelines.
This article introduces Playwright‑Python, a powerful cross‑platform browser automation library, explains how to install it with pip, describes its support for Chromium, Firefox and WebKit, and shows how to use the codegen command to record actions and generate scripts with various options.
Swift 5.9’s new macro system lets developers generate type‑safe code at compile time via external plug‑ins, using role‑based declarations such as @attached and @freestanding to create properties, extensions, or warnings, thereby reducing repetitive boiler‑plate and improving safety in large‑scale architectures like MVVP modules and exposure frameworks.
By binding a Vue single‑file component’s AST to a visual UI, this project parses templates with node‑html‑parser, transforms scripts via Babel, and processes styles with standard loaders, allowing developers to edit component properties visually, automatically regenerate synchronized source code, and preview changes, with a prototype demo and planned drag‑and‑drop, styling, state, AI, and CI/CD extensions.
The article introduces Fluent Mybatis, a compile‑time code‑generating ORM that merges Mybatis‑Plus, Dynamic SQL and JPA features, eliminates XML mappers, offers a fluent, type‑safe Java API, and demonstrates through concise examples how it reduces boilerplate compared with native Mybatis and Mybatis‑Plus.
This article examines the limitations of using JPA for complex queries in SpringBoot projects and demonstrates how MyBatis‑Flex can simplify conditional queries, partial field selection, Kotlin integration, and code generation through clear code examples and practical guidance.
This guide explains how to install the JetBrains AI Assistant plugin, outlines its code‑generation and refactoring features, and provides a practical workaround for mainland China users by adjusting account region, configuring system and IDE proxies, and starting AI‑driven conversations.
This article introduces MapStruct, a compile‑time Java bean‑mapping framework, and demonstrates advanced features such as expression mapping, qualifiedByName for custom conversions, null‑value handling strategies, and the use of decorators to extend mapper behavior, complete with code examples.
This article introduces the rapid rise of large language models, highlights the advantages of the GLM-4-Plus model—including superior language understanding, long‑text handling, and enhanced reasoning—explains how to obtain API credentials, demonstrates request parameters and curl examples, and showcases diverse real‑world use cases such as code generation, social‑media copy, travel planning, and interview question creation.
This article walks through the iterative design of an Ant Design form component, starting with a simple name field, then adding a randomly generated code field, making it editable, and finally implementing a copyable code input with reusable prefix‑text and suffix‑icon components, while comparing implementation approaches.
This guide explains how to integrate the mybatis-plus-generator-ui library into a Spring Boot project, configure database connections, launch the web UI, and use its customizable templates and naming converters to generate Entity, Mapper, Service, and Controller classes for multiple databases with a single click.
This article walks through how a compiler turns human‑readable source code into binary machine instructions, covering tokenization, parsing, abstract syntax tree construction, code generation, optimization, and linking, while highlighting the role of LLVM as a portable backend.
The article details how Taobao’s AI team automated repetitive UI tasks for B2C front‑end development, achieving a 15 % efficiency gain across five projects, and outlines key challenges—prompt cost, low OCR accuracy, hallucinations, excess nodes, and customization variance—along with practical solutions such as a dedicated evaluation platform, OCR translation, model upgrades, prompt segmentation, output simplification, and a reusable component library.
This article explores Rust's macro_rules! system, demonstrating how to create reusable, flexible configuration structures with default values, deprecation handling, and custom validation, while providing step‑by‑step code examples and highlighting the benefits for maintainability and code reuse.
This article explains how a programmer's source code is transformed into CPU‑executable machine instructions through lexical analysis, parsing into an abstract syntax tree, optimization, target‑specific code generation, and linking, highlighting the role of compilers and tools like LLVM.
This article reviews four ACL 2024 papers authored by Meituan’s research team—covering training cost reduction, speculative decoding, code generation optimization, and instruction fine‑tuning—while also announcing a live sharing session at the conference.
This presentation explores how large‑model AIGC reshapes software engineering by leveling developer skills, reducing collaboration overhead, cutting costs, and introducing new human‑AI collaboration modes—from Copilot to multi‑agent facilitators—while detailing practical challenges, technical solutions, and future prospects.
This article explains why manual property copying in layered Java applications is inefficient, compares runtime copiers like BeanUtils and BeanCopier, and demonstrates how MapStruct provides compile‑time, type‑safe, high‑performance bean mapping with support for deep copy, collection mapping, field ignoring, and Lombok integration.
This 2024 guide reviews the most powerful AI coding assistants—from code completion and generation tools like GitHub Copilot and Claude to design‑to‑code converters and security analyzers—showcasing how they accelerate development, improve code quality, and reshape collaborative programming.
This article explains how the TolyUI Flutter UI framework automates the parsing of component demo files and generates corresponding Dart code using annotations, regular expressions, and a command‑line tool, thereby simplifying maintenance and improving development efficiency for mobile applications.
Alibaba Cloud’s Tongyi Lingma code model achieved the highest 4+ rating in the trusted AI code‑model evaluation, and in an interview its product lead explains the model’s capabilities, the rigorous assessment process, real‑world enterprise benefits, and future development plans.
This tutorial demonstrates how to set up a simple MySQL database, create a Spring Boot project, add Mybatis-Plus dependencies, install the MybatisX plugin, configure the connection, generate entity, mapper, service, and controller code, and verify the integration with a sample REST endpoint.
