Stage 1: Basics (Weeks 3-6) Course Summary and Introduction

This phase focuses on dissecting Servo's core modules and developing system-level development capabilities, emphasizing ​architecture analysis, ​standards compliance, and ​Huawei ecosystem integration to establish engineering foundations for advanced phases.

​Week 3: Servo Project Structure Analysis & Code Walkthrough

Core Content:

1. ​Advanced Rust Features

• Async programming ecosystem (async/await with tokio runtime)
• Cross-language interaction (FFI for C/C++ library calls, HarmonyOS kernel interface integration)

1. ​Core Component Architecture

• ​HTML Parser: Tokenizer/parser pipeline design in html5ever
• ​Multi-process Model: IPC mechanisms (message passing & shared memory) across Browser/Renderer/GPU processes
• ​Network Stack: Necko's HTTP/QUIC protocol support and Huawei CloudEngine acceleration

1. ​API Development Standards

• W3C-compliant interface implementation (e.g., WebGL context binding)
• Huawei private API extensions via WebIDL [HongmengDevice] tags

Competency Goal: Master Servo source code debugging and cross-language interface development.

​Week 4: CSS Layout Algorithm Fundamentals

Core Content:

1. ​Style Computation System

• CSSOM construction workflow (selector matching & cascade rules)
• HarmonyOS dynamic theme system integration with CSS variables (var())

1. ​Parallel Layout Engine

• Stylo thread pool scheduling (DOM subtree partitioning & load balancing)
• Huawei HiAI SDK acceleration for CSS Transform matrix operations (NPU offloading)

1. ​Rendering Diagnostics

• Layout performance heatmap generation using HiProf
• Foldable screen media query adaptation

Competency Goal: Acquire layout bottleneck identification and hardware acceleration design skills.

​Week 5: OS API & Servo Integration

Core Content:

1. ​HarmonyOS Kernel Integration

• Binder IPC adaptation for Servo's multi-process model
• Vulkan backend integration via HarmonyOS Graphic service

1. ​Device Capability Mapping

• Sensor API standardization (DeviceMotionEvent via WebIDL)
• TEE-based camera/mic access control

1. ​Resource Scheduling Optimization

• Memory management (Ark Compiler AOT optimization for Servo memory pools)
• Energy-aware rendering process prioritization using Huawei LMK

Competency Goal: Master OS-level API design and browser resource scheduling.

​Week 6: AI Agent Framework Applications

Core Content:

1. ​Framework Integration

• MindSpore Lite inference engine embedding (CSS computation offloading)
• Agent decision flows (page load prediction & resource prefetching)

1. ​Intelligent Enhancement

• LSTM-based user behavior prediction (scroll direction & dwell time modeling)
• Model format conversion (ONNX→MindSpore) for Servo runtime

1. ​Ecosystem Synergy

• HiAI resource scheduling API integration
• Edge-cloud collaborative inference (ModelArts cloud training + edge deployment)

Competency Goal: Develop AI-enhanced browser optimization strategies and edge inference deployment skills.

​Stage Features

1. ​Technical Depth

• Progressive learning: ​Language (Rust async) → ​Architecture (multi-process/GPU pipeline) → ​Algorithms (Stylo/HiAI acceleration)

1. ​Huawei Ecosystem Integration

• ​Tools: HiProf diagnostics → Ark Compiler → ModelArts
• ​Hardware: NPU acceleration → TEE security → HarmonyOS distributed services

1. ​Standards-Compliance & Extensions

• W3C compliance + Huawei-specific extensions (e.g., [HongmengDevice] tags)

This stage builds ​three core competencies:

• ​Code-level engineering (Rust/WebIDL/C++ interop)
• ​Performance optimization (layout algorithms/resource scheduling/hardware acceleration)
• ​AI engineering (edge inference & browser function integration)