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StarCatcher: 2D Physics & Particle Study

Defold Engine | Lua | Cross-Platform Build

StarCatcher Gameplay Screenshot

Defold Language Status

Engineering Context: This project serves as a technical evaluation of the Defold Game Engine. It demonstrates the ability to rapidly adapt to a "Message-Passing" architecture, contrasting with standard Object-Oriented patterns found in Unity.


🔧 Technical Analysis: Defold vs. Unity

The primary goal of this repository was to translate standard gameplay loops into Defold's component architecture within a compressed timeline.

1. Message-Passing Architecture

Unlike Unity's direct method calls (e.g., GetComponent<T>().DoSomething()), this project utilizes Defold's Message Passing system to handle entity communication.

  • Hash-Based Logic: Implemented msg.post() systems to handle collisions and state changes, ensuring strict decoupling between game objects.
  • Addressable Components: Logic relies on URL-based addressing schemes to locate game object instances at runtime.

2. Tech Art & Particles

  • Particle Integration: Implemented Defold's native particle fx components for visual feedback (collection of stars), analyzing the performance overhead of 2D sprites in a focused timeline.
  • Atlas Management: Utilized texture atlases to optimize draw calls, ensuring efficient rendering on lower-end devices.

3. Cross-Platform Compilation

  • Build Pipeline: Successfully configured the render pipeline to target both Windows (x64) and macOS (ARM64/x64), verifying the cross-platform stability of the Lua codebase.

🤖 Methodology: AI-Accelerated Development

This project was executed using an AI-Augmented Workflow to maximize efficiency.

  • Rapid Adaptation: Leveraged Generative AI (Gemini) to drastically reduce the learning curve of the Defold API. This allowed for the implementation of complex features in days rather than weeks.
  • Concept Mapping: AI tools were used to translate known Engineering concepts (State Machines, Vector Math) into specific Lua syntax, acting as a real-time documentation bridge. The focus remained on Architectural Logic, while AI handled the syntactical heavy lifting.

📦 Releases & Downloads

Current Version: v0.0.6

Version Platform Status
v0.0.6 Windows (x64) Stable. High Score tracking added.
v0.0.6 macOS (Universal) Untested.
v0.0.2 Windows (x64) Prototype. Basic movement only.

👤 Author

Christopher Jepson Technical Artist & Software Engineer LinkedIn | Email

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