c54c569f30
Completed clean root directory structure: - Root now contains only: .git, .env, docs/, orig/ - Moved all remaining files and directories to orig/: - Config files (.claude, .dockerignore, .drone.yml, etc.) - All .env variants (except active .env) - Git config (.gitconfig, .github, .gitignore, etc.) - Tool configs (.golangci.yml, .revive.toml, etc.) - Documentation (*.md files, @prompts) - Build files (Dockerfiles, Makefile, go.mod, go.sum) - Docker compose files - All source directories (scripts, tests, tools, etc.) - Runtime directories (logs, monitoring, reports) - Dependency files (node_modules, lib, cache) - Special files (--delete) - Removed empty runtime directories (bin/, data/) V2 structure is now clean: - docs/planning/ - V2 planning documents - orig/ - Complete V1 codebase preserved - .env - Active environment config (not in git) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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Optimize Mathematical Performance
Optimize the performance of the following mathematical function in the MEV bot: $ARGUMENTS
Performance Optimization Strategy:
1. Profiling and Measurement
# CPU profiling for mathematical functions
go tool pprof http://localhost:9090/debug/pprof/profile?seconds=30
# Memory profiling for mathematical calculations
go tool pprof http://localhost:9090/debug/pprof/heap
# Benchmark testing for mathematical functions
go test -bench=. -benchmem ./pkg/uniswap/...
2. Optimization Areas
Precision Handling Optimization
- Uint256 arithmetic optimization
- Object pooling for frequent calculations
- Minimize memory allocations in hot paths
- Efficient conversion between data types
Algorithm Optimization
- Mathematical formula simplification
- Lookup table implementation for repeated calculations
- Caching strategies for expensive computations
- Parallel processing opportunities
Memory Optimization
- Pre-allocation of slices and buffers
- Object pooling for mathematical objects
- Minimize garbage collection pressure
- Efficient data structure selection
3. MEV Bot Specific Optimizations
Uniswap V3 Pricing Functions
- sqrtPriceX96 to price conversion optimization
- Tick calculation performance improvements
- Liquidity-based calculation efficiency
- Price impact computation optimization
Arbitrage Calculations
- Profit calculation optimization
- Cross-pool comparison performance
- Gas estimation accuracy and speed
- Multi-hop arbitrage efficiency
Implementation Guidelines:
- Measure before optimizing (baseline metrics)
- Focus on bottlenecks identified through profiling
- Maintain mathematical precision while improving performance
- Add performance tests for regressions
- Document optimization strategies and results
Deliverables:
- Performance benchmark results (before/after)
- Optimized code with maintained precision
- Performance monitoring enhancements
- Optimization documentation
- Regression test suite