Cyber Language Server

LSP Implementation for the Cyber Language

Developed a full Language Server Protocol implementation in Rust for the Cyber language with advanced language features including completions, diagnostics, and hover information.

Technical Highlights

• Used tower-lsp for async LSP communication with high performance
• Leveraged tree-sitter for incremental parsing and efficient syntax analysis
• Implemented concurrent document processing with Tokio and DashMap
• Designed thorough error handling with anyhow and custom error types
• Built with tracing for comprehensive logging and diagnostics

Features

• Created advanced language features including completions
• Implemented diagnostics and hover information
• Built document parsing and syntax validation
• Designed with an extensible architecture for future language features

GitHub Repository

Projects Portfolio

Technical Profile

As a versatile software engineer I’ve built a diverse portfolio of personal projects focusing on developer tools, language implementation, and high-performance systems. My work demonstrates particular strength in creating efficient, user-friendly tools that solve real-world development challenges.

Technical Skills Demonstrated

Languages & Frameworks

• Rust: Systems programming with advanced patterns:
  • Async programming with tokio and futures
  • Thread management with mpsc channels and oneshot
  • Error handling with anyhow and Result propagation
  • Command-line interfaces with clap
  • Clean architecture with module separation
  • Language Server Protocol implementation
  • Parser development with tree-sitter integration
• Python: Developer tooling and language processing:
  • Integration with system APIs and libraries
  • Performance optimization for data processing
  • Concurrent processing with asyncio and threading
  • API design and implementation
  • Full-text search and indexing implementation
• JavaScript/C++: Language tooling and parser development:
  • C++ scanner implementation for complex lexical analysis
  • External scanner API integration for advanced parsing features
  • Tree-sitter grammar development in JavaScript
  • DSL implementation for language parsing
• C#/Unity: Performance-oriented developer tooling:
  • Advanced scene automation with intelligent analysis and processing
  • DOTS/ECS architecture with automated GameObject-to-Entity conversion pipelines
  • Performance optimization with Job system and Burst compilation
  • Meticulous IL instruction/code path analysis for optimal SIMD utilization
  • Unity editor tool development with intuitive UI/UX design
  • Diagnostic engine frameworks with automated issue detection and resolution
  • Scene streaming optimization with subscene management

Performance Engineering

• Parallel processing and multi-threading optimization
• Memory management and allocation strategies
• Data structure optimization for minimal overhead
• Cache-aware algorithms and data layout
• CPU/GPU bottleneck identification and resolution
• Profiling and performance metrics analysis

Developer Tools Engineering

• Command-line interface design with user experience focus
• Language server implementation and parsing techniques
• Incremental parser development for code analysis
• Cross-platform tool development and distribution
• Configuration management for flexible deployment
• Automated testing and verification systems

Software Architecture

• Modular design with clear separation of concerns
• Performance-oriented system design
• Data-oriented design principles
• Scalable architecture patterns for large codebases
• Component-based design with well-defined interfaces
• Asynchronous processing patterns
• Plugin-based systems for extensibility
• Cross-platform compatibility considerations

AI/ML Integration

• Vector embeddings for semantic search and retrieval
• Computer vision and object detection models
• Speech recognition and processing

Featured Projects

Vectorizer (Rust)

Text Embedding Generator and Vector Database Integration

ProStream

Advanced Unity Developer Tool for Scene Conversion and Streaming

Created a comprehensive developer tool that automates the conversion of traditional GameObject scenes to DOTS entity subscenes with an intuitive editor interface.

Technical Highlights

Scene Automation & Processing

• Created an intelligent scene analysis system that identifies optimal streaming boundaries based on object density and relationships
• Built automatic layer generation that organizes GameObjects into logical streaming groups based on customizable rule sets
• Implemented a GameObject-to-Entity conversion pipeline with automatic hierarchy preservation and reference maintenance
• Developed a subscene creation system that handles all the complexity of breaking apart monolithic scenes into efficient streaming units

Performance Optimization Tools

• Designed automated frustum culling integration using Unity’s job system with Burst compilation for scenes processed by the tool
• Created a configurable terrain LOD generation system that developers can customize based on their performance requirements
• Implemented performance metrics tracking with Unity’s ProfilerRecorder API to help developers optimize their converted scenes
• Built bounds checking and occlusion systems that are automatically configured during the conversion process

Developer Experience

• Crafted an intuitive Unity editor integration with wizard-style guidance for the conversion workflow
• Built visual feedback systems showing streaming boundaries and performance impact analysis
• Implemented serialized configuration settings allowing developers to save and reuse conversion parameters across projects
• Created automated validation systems to ensure converted scenes will perform well in production

GitHub Repository

Tree-Sitter-Cyber

Custom Parser for the Cyber Language

Developed a complete Tree-sitter grammar for the Cyber scripting language including a custom C++ scanner for handling complex language features.

Technical Highlights

• Created precise grammar definitions in JavaScript using Tree-sitter’s DSL
• Implemented custom precedence rules for complex expression parsing
• Generated optimized Rust parser code from Tree-sitter grammar
• Developed custom highlighting queries for semantic tokens
• Built cross-platform compatibility with WASM compilation support

Custom C++ Scanner Implementation

• Created a sophisticated lexer using Tree-sitter’s external scanner API
• Implemented proper indentation-based scoping with indent/dedent token generation
• Developed robust string literal handling for single, double, and triple quotes
• Built support for multiline strings with appropriate delimiter tracking
• Implemented a delimiter stack system for proper nesting and context tracking
• Added debug facilities for development and troubleshooting
• Utilized modern C++ features for memory safety and performance

GitHub Repository

Vectorizer

Text Embedding Generator and Vector Database Integration

Built a high-performance text embedding tool in Rust that processes project files for AI retrieval. This tool integrates with Qdrant vector database for storage and retrieval of embeddings.

Technical Highlights

• Implemented async processing with Tokio and thread management for optimal performance
• Designed a robust CLI with clap that follows modern design patterns similar to Ruff and uv
• Used mpsc channels and oneshot patterns for efficient inter-thread communication
• Implemented sophisticated error handling with anyhow and custom error propagation
• Created command-line progress indicators with automatic refresh for better UX

Features

• Created a configuration system supporting both global and per-project settings
• Developed Neovim integration for automatic embedding of saved files
• Used the All-MiniLm-L(6/12)-V2 models for generating high-quality text embeddings

GitHub Repository