Chen’s Notes
Product Engineering
Experience and expertise: Product engineering experience on complex client projects at large enterprises.
Client and Cross-Platform Technologies
Experience and expertise: Expert-level knowledge, with core development and technical leadership experience on large, complex enterprise projects.
Android Framework
- Atlas Dynamic Component Framework: Bundle Loading
- Atlas Dynamic Component Framework: Startup (Part 2)
- Atlas Dynamic Component Framework: Startup (Part 1)
- Atlas Dynamic Component Framework: From Gradle to APK
- Android Source Code: Process Startup
- DroidPlugin: BroadcastReceiver Plugin Support
- DroidPlugin: ContentProvider Plugin Support
- Android Source Code: How Activity Connects with AMS and WMS
- DroidPlugin: Service Plugin Support
- DroidPlugin: Activity Plugin Support
- Android Source Code: Handler
Cross-Platform and Dynamic Frameworks
- A Comparison of Cross-Platform Rendering Approaches
- Compose Architecture and Modules
- Porting Flutter to Embedded Linux Devices: Exploring IoT
- Flutter Engine: AndroidX and Support Library Compatibility
- How the Flutter Hybrid Navigation Stack Works
- Flutter Engine Initialization: Source Analysis and Optimization (Upstream PR)
- Weex Architecture: Design Principles and Concepts
- React Native Source Code: Startup
2D Rendering
- Flutter Rendering Pipeline (Part 2): The GPU Thread
- Flutter Rendering Pipeline (Part 1): The UI Thread
Compilers and Virtual Machines
- An Overview of the Dart Compiler
- An Overview of the Dart VM
- Compose Compiler (1): The Compose Plugin
- Compose Compiler (1): Kotlin Compiler Architecture and KCP
- ART and Dalvik: Key Differences
- Reading Notes: Understanding the JVM — Chapter 7, Class Loading
- Java Singletons, the Memory Model, and Concurrency
- Reading Notes: Understanding the JVM — Chapter 2, Java Memory Areas
AI Technologies
Experience and expertise: A systematic understanding of AI technologies and training and inference principles. Hands-on experience focuses on analyzing and running open-source project code, with no enterprise project experience yet.
- AI Technology Stack: Applications, Training and Inference, Models, and Computing Infrastructure
- Agent Engineering: SDK Requirements and Runtime Architecture
- The LLM Workflow: From Training to Inference with nanochat
- LLM Systems (1): GPT Architecture and Forward Computation
- LLM Systems (2): Training Objectives, Parameter Updates, and Text Generation
- nanochat: Core LLM Architecture and Implementation
Backend Technologies
Experience and expertise: A systematic understanding of backend technologies, early experience developing simple enterprise backend projects, and collaboration with teams responsible for complex backend systems on large client projects.
- Backend Architecture and Technology Stack Map
- Reading Notes: Java Multithreaded Programming
- The Evolution of HTTP Protocol Versions