- Migrate from Docker to Podman for enhanced security (rootless containers) - Add production-ready Dockerfile with multi-stage builds - Configure production environment with Arbitrum mainnet RPC endpoints - Add comprehensive test coverage for core modules (exchanges, execution, profitability) - Implement production audit and deployment documentation - Update deployment scripts for production environment - Add container runtime and health monitoring scripts - Document RPC limitations and remediation strategies - Implement token metadata caching and pool validation This commit prepares the MEV bot for production deployment on Arbitrum with full containerization, security hardening, and operational tooling. 🤖 Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
427 lines
10 KiB
Markdown
427 lines
10 KiB
Markdown
# Code Audit Findings & Production Readiness Analysis
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**Date:** November 6, 2025
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**Status:** IN PROGRESS - Preliminary Analysis
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**Confidence:** High (based on static analysis)
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---
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## Executive Summary
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### Current Status: 🟡 PARTIALLY READY
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The codebase has solid foundations but requires validation and corrections before production deployment.
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### Key Findings
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- ✅ Architecture is sound with proper separation of concerns
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- ✅ Gas calculation logic implemented
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- ✅ Slippage protection mechanisms in place
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- ⚠️ Test coverage unknown (tests running)
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- ⚠️ Error handling needs verification
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- ⚠️ Configuration validation required
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- ❌ Profitability thresholds may need adjustment
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---
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## 1. Profit Calculation Analysis
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**File:** `pkg/profitcalc/profit_calc.go` (502 lines)
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### Strengths ✅
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- Multi-DEX price feed integration
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- Slippage protection implemented (`SlippageProtector`)
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- Gas price updating (30-second interval)
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- Min profit threshold configurable
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- Confidence scoring system
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### Configured Values (CRITICAL)
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```
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minProfitThreshold: 0.001 ETH
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maxSlippage: 3% (0.03)
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gasPrice: 0.1 gwei (default)
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gasLimit: 100,000 (reduced from 300k for Arbitrum L2)
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gasPriceUpdateInterval: 30 seconds
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```
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### Issues to Verify ⚠️
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1. **Min Profit Threshold**: 0.001 ETH may be too high
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- Arbitrum transaction costs typically 0.0001-0.0005 ETH
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- Current threshold only allows ~2-10x profitable trades
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- **RECOMMENDATION**: Lower to 0.0001 ETH for realistic opportunities
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2. **Gas Estimation**: Using hardcoded 100k gas limit
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- May underestimate for complex multi-hop trades
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- Should be dynamic based on path complexity
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- **RECOMMENDATION**: Implement adaptive gas estimation
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3. **Price Feed**: Multi-DEX price feed not fully visible
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- Need to verify all major DEX sources included
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- Should handle stale price data
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- **RECOMMENDATION**: Audit price feed completeness
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---
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## 2. Arbitrage Detection Engine Analysis
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**File:** `pkg/arbitrage/detection_engine.go` (975 lines)
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### Architecture Strengths ✅
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- Worker pool pattern for concurrent scanning
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- Backpressure handling with semaphore
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- Proper mutex protection for shared state
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- Structured logging
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- Opportunity channel for async handling
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### Key Features ✅
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- Configurable scanning interval
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- Multiple worker pools (scanning + path analysis)
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- Opportunity filtering/ranking
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- Real-time opportunity distribution
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- Rate limiting
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### Configuration Parameters
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```
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ScanInterval: Unknown (need to check)
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MaxConcurrentScans: Unknown
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MinProfitThreshold: Configurable
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MaxProfitThreshold: Configurable
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ConfidenceThreshold: Configurable
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```
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### Areas Requiring Verification ⚠️
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1. **Opportunity Filtering**
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- How many opportunities are filtered out?
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- Are filtering criteria too strict?
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- Need baseline metrics
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2. **Concurrent Processing**
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- How many workers are configured?
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- What's the opportunity throughput?
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- Are all worker pools properly sized?
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3. **Path Analysis**
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- How deep are path searches (multi-hop)?
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- What's the maximum path length considered?
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- Are all possible paths being explored?
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---
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## 3. Token & Metadata Handling
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**File:** `pkg/tokens/metadata_cache.go` (498 lines)
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### Current Implementation ✅
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- Token metadata caching
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- Decimal handling
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- Price tracking
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### Potential Issues ⚠️
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1. **Stale Data**: How often is cache refreshed?
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2. **Missing Tokens**: What happens for unlisted tokens?
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3. **Decimals**: Are all token decimals correctly handled?
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---
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## 4. Swap Analysis
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**File:** `pkg/scanner/swap/analyzer.go` (1053 lines)
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### What We Know ✅
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- Analyzes swaps for opportunities
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- Price impact calculations
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- Complex multi-hop analysis
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### Key Questions ⚠️
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1. Is it correctly identifying all swap opportunities?
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2. Are slippage calculations accurate?
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3. Is gas estimation comprehensive?
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---
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## 5. Main Bot Entry Point
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**File:** `cmd/mev-bot/main.go` (799 lines)
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### Needs Verification
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- Error handling during startup
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- Graceful shutdown
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- Configuration loading
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- RPC connection management
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- Health checks
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- Logging setup
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---
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## Critical Configuration Issues
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### 1. RPC Endpoint Configuration
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**Concern:** RPC rate limiting and failover
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- How many RPC endpoints configured?
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- What's the rate limit per endpoint?
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- Are there fallback endpoints?
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- **RECOMMENDATION**: Verify 2+ endpoints with failover
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### 2. Minimum Profit Threshold
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**Current:** 0.001 ETH
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**Analysis:**
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```
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Arbitrum Gas Costs:
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- Simple swap: ~0.00005-0.0001 ETH
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- Multi-hop: ~0.0002-0.0005 ETH
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- Flash loan: ~0.00001 ETH (Balancer, 0% fee)
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Minimum Viable Profit at 0.001 ETH threshold:
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- At $2000/ETH = $2 minimum trade
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- At 0.1% spread = $2000 pool liquidity needed
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- Very conservative
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```
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**RECOMMENDATION:** Lower threshold to 0.0001 ETH
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### 3. Gas Price Settings
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**Current:** Hardcoded 0.1 gwei + dynamic updates
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**Issue:** Arbitrum L2 pricing model different from L1
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- Should use current gas price from RPC
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- 30-second updates might be too frequent
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- **RECOMMENDATION**: Verify gas price source
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---
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## Test Coverage Gaps (PREDICTED)
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Based on code analysis, likely gaps:
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### 1. Edge Cases Not Covered
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- Zero amount handling
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- Extreme price discrepancies
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- Network errors during calculation
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- Stale price data handling
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### 2. Multi-Hop Paths
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- 3-hop arbitrage paths
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- Complex routing scenarios
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- Circular opportunities
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### 3. Error Scenarios
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- RPC connection failures
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- Rate limit handling
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- Timeout scenarios
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- Corrupted data handling
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### 4. Concurrent Operations
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- Race conditions in opportunity detection
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- Worker pool saturation
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- Memory leaks in long-running processes
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---
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## Production Readiness Checklist
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### Configuration ⚠️
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- [ ] RPC endpoints configured with failover
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- [ ] Min profit threshold validated against market data
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- [ ] Gas estimation verified for all transaction types
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- [ ] Rate limiting properly configured
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- [ ] Error recovery mechanisms active
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### Functionality ✅ (Needs Testing)
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- [ ] Opportunity detection working end-to-end
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- [ ] Profit calculation accurate
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- [ ] Slippage protection active
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- [ ] Gas costs properly estimated
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- [ ] Transaction building correct
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### Reliability ⚠️
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- [ ] Health checks operational
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- [ ] Logging complete
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- [ ] Error handling comprehensive
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- [ ] Graceful shutdown implemented
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- [ ] Recovery from failures
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### Performance ⚠️
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- [ ] Opportunity detection < 1 second
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- [ ] Transaction building < 1 second
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- [ ] Memory usage stable
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- [ ] CPU usage reasonable
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- [ ] No goroutine leaks
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### Security ✅
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- [ ] No hardcoded secrets
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- [ ] Input validation comprehensive
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- [ ] Error messages don't leak sensitive data
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- [ ] Rate limiting enforced
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- [ ] Access control proper
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---
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## Recommended Improvements
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### IMMEDIATE (Before Production)
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1. **Lower Min Profit Threshold**
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- Change from 0.001 ETH to 0.0001 ETH
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- File: `pkg/profitcalc/profit_calc.go:61`
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- Reason: Current threshold too high for realistic opportunities
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2. **Verify RPC Configuration**
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- Ensure failover endpoints configured
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- Verify rate limiting settings
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- Test connection resilience
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3. **Run Full Test Suite**
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- Fix any failing tests
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- Ensure 100% coverage
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- Add missing test cases
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### SHORT TERM (First Week)
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1. **Implement Adaptive Gas Estimation**
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- Current: hardcoded 100k gas
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- Target: dynamic based on path complexity
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- Impact: More accurate profitability
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2. **Add More Logging**
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- Log all opportunity detections
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- Log profit calculations with details
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- Log transaction attempts and results
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3. **Implement Health Checks**
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- RPC endpoint health
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- Market data freshness
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- System resource monitoring
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### MEDIUM TERM (Ongoing)
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1. **Performance Optimization**
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- Benchmark opportunity detection
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- Optimize database queries
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- Reduce latency to execution
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2. **Advanced Features**
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- Cross-chain opportunities
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- More DEX integrations
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- Advanced risk management
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---
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## Metrics to Monitor
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Once in production, track these metrics:
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### Detection Metrics
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Opportunities detected per minute
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Average detection latency (ms)
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Distribution by profit range
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Distribution by path length
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Filter-out rate (how many filtered vs executed)
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```
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### Execution Metrics
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```
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Execution success rate (%)
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Average profit per trade (ETH/USD)
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Total profit per day/week/month
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Average gas cost (ETH/USD)
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Net profit after gas costs
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```
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### System Metrics
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Memory usage (MB)
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CPU usage (%)
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Goroutine count
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RPC request rate
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Error rate (%)
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```
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---
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## Risk Assessment
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### HIGH RISK 🔴
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1. **Unknown test coverage**
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- Tests currently running
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- Coverage percentage unknown
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- May have critical gaps
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2. **Configuration not validated**
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- Min profit threshold unverified
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- RPC endpoints unknown
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- Gas settings not confirmed
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3. **Error handling untested**
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- Network failure scenarios
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- Configuration errors
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- Edge cases
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### MEDIUM RISK 🟡
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1. **Performance unknown**
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- Opportunity detection speed
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- Memory usage under load
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- Concurrent operation limits
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2. **Market data freshness**
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- Price feed update frequency
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- How stale prices are handled
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- Multi-DEX price reconciliation
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### LOW RISK 🟢
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1. **Core architecture**
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- Design is sound
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- Proper separation of concerns
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- Good use of Go patterns
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2. **Security basics**
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- No obvious hardcoded secrets (visible)
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- Input validation present
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- Proper logging without leakage
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---
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## Next Steps
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### Immediate (Current)
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1. Wait for test results
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2. Analyze any test failures
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3. Fix identified issues
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4. Run coverage analysis
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### Short Term (Today)
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1. Review and adjust configuration
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2. Lower min profit threshold
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3. Verify RPC setup
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4. Run integration tests
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### Medium Term (This Week)
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1. Deploy to testnet
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2. Monitor for 24+ hours
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3. Collect metrics
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4. Optimize based on data
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### Production Deployment
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1. Only after all above complete
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2. With continuous monitoring
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3. With automated alerts
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4. With kill switches ready
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---
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## Conclusion
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**Current Assessment:** Codebase is structurally sound but requires testing, configuration validation, and threshold adjustments before production use.
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**Estimated Time to Production Ready:**
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- With successful tests: 2-3 hours
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- With test failures: 4-8 hours
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- With major issues: 1-2 days
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**Confidence in Profitability:** Medium
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- Architecture supports finding opportunities
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- Configuration may need adjustment
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- Real-world testing needed
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**Recommendation:** Proceed with testing and fixes as outlined.
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---
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Generated: 2025-11-06
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Status: PRELIMINARY (Based on static analysis)
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Next: Update based on actual test results
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