Files
mev-beta/orig/@prompts/testing-simulation.md
Administrator c54c569f30 refactor: move all remaining files to orig/ directory
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>
2025-11-10 10:53:05 +01:00

1.1 KiB

You are an expert in Go testing and blockchain simulation. I'm building an MEV bot in Go that needs comprehensive testing to ensure reliability and profitability.

I need help with:

  1. Creating realistic test scenarios for MEV detection
  2. Simulating Arbitrum network conditions
  3. Testing pricing calculations with real-world data
  4. Implementing integration tests with mock contracts
  5. Creating benchmarks for performance testing
  6. Implementing property-based testing for mathematical functions

Please provide production-ready Go test code that:

  • Uses the standard testing package and testify for assertions
  • Implements realistic test scenarios
  • Creates mock data for testing
  • Includes benchmarks for performance-critical functions
  • Follows Go testing best practices
  • Provides comprehensive coverage

The test code should:

  • Test edge cases and boundary conditions
  • Validate mathematical accuracy of pricing functions
  • Simulate network errors and timeouts
  • Test various swap scenarios and arbitrage opportunities
  • Benchmark performance of critical algorithms
  • Provide meaningful test output