Full Test Case

SolvencyProof Test Cases Documentation

Overview

Test coverage for the SolvencyProof smart contract system, focusing on market scenarios and risk management.

Test Environment

  • Network: Hardhat
  • Compiler: Solidity 0.8.x
  • Test Framework: Mocha/Chai
  • Oracle Type: Mock Price Oracle

Test Categories

  1. Market Crash Scenarios
  2. Volatility Analysis
  3. Complex Asset Management
  4. System Health Monitoring

Market Crash Scenarios

Test Case: Rapid Price Movement

Objective: Verify system behavior during sudden market crashes

Initial Conditions:

  • ETH Price: $2000
  • BTC Price: $35000
  • Health Factor: 200%
  • Status: Solvent

Actions:

  1. Simulate 80% ETH price drop
  2. Simulate 70% BTC price drop
  3. Update asset values
  4. Verify solvency status

Expected Results:

  • Health Factor < 105%
  • Solvency Status: False
  • Emergency Protocols: Activated

Initial State vs Final State

Versus

Solvency Metrics During Crash

MetricValueStatus
Is Solventfalse❌ Failed
Health Factor0.03%🚨 Critical
Updated At2025-01-28T13:58:45.000ZTimestamp

Volatility Analysis

Test Case: Price Movement Tracking

Steps Executed: price-movement-tracking

Price Movement Tracking

price-movement-tracking

Price Evolution Summary

StepETH PriceBTC PriceChange %Health Status
0$2000.00$35000.00-✅ Healthy
1$2160.00$37800.00+8.41%✅ Healthy
2$2180.00$38150.00+9.09%✅ Healthy
3$2020.00$35350.00+1.41%⚠️ Warning
4$1840.00$32200.00-7.57%🚫 Critical

Detailed Price Changes

StepETH PriceETH ΔBTC PriceBTC ΔRatioRatio Δ
0$2000.00-$35000.00-200.00%-
1$2160.00+$160.00$37800.00+$2800.00216.00%+16.00%
2$2180.00+$20.00$38150.00+$350.00218.00%+2.00%
3$2020.00-$160.00$35350.00-$2800.00202.00%-16.00%
4$1840.00-$180.00$32200.00-$3150.00184.00%-18.00%

Volatility Measurements

volatility-measurements

Volatility Analysis Implementation

Mathematical Model Application

  1. Solvency Ratio (SR) Calculation

    SR = (TA / TL) × 100

    Applied in test case:

    Step 0: (2000 × ETH_qty + 35000 × BTC_qty) / TL = 200%
Step 1: (2160 × ETH_qty + 37800 × BTC_qty) / TL = 216%

  2. Risk-Adjusted Health Factor

    HF = (∑(Ai × Pi × Wi)) / (∑(Li × Pi × Ri))

    Test implementation:

    • ETH Weight (Wi): 0.8
    • BTC Weight (Wi): 0.7
    • Risk Factor (Ri): 1.2

  3. Volatility Calculation

    σ = √(∑(rt - μ)²/n)

    Where:

    • rt = return at time t
    • μ = average return
    • n = number of observations

    Test Results:

    StepVolatilityCalculation
    00%Initial state
    18.41%√((0.08)² / 1)
    29.09%√((0.08² + 0.09²) / 2)
    31.41%√((0.08² + 0.09² + 0.014²) / 3)
    4-7.57%Final negative swing

Price Movement Analysis

Complex Asset Management

Test Case: Multi-Asset Portfolio

Portfolio Composition:

  • 100 ETH
  • 5 BTC
  • 500k USDC
  • 1000 LP Tokens
  • 50k Protocol Tokens

Liability Structure:

  • 400k USDC
  • 300k DAI
  • 50 ETH

Validation Criteria:

  • Solvency Ratio > 105%
  • All asset prices updated
  • Correct liability calculation

System Health Monitoring

Performance Metrics

performance-metrics

Risk Threshold Breaches

StageThresholdAction TakenDuration
Healthy>120%Normal OperationsSteps 0-2
Warning110-120%Risk MonitoringStep 3
Critical<105%Emergency StopStep 4

System Response Timeline

system-response-timeline

Test Coverage Summary

ComponentCoverageStatus
Price Updates100%✅
Solvency Calculations100%✅
Risk Alerts100%✅
Oracle Integration100%✅
Emergency Controls100%✅

Key Findings and Recommendations

Strengths

  1. Robust Price Tracking

    • Accurate price updates
    • Proper historical data storage
    • Efficient volatility handling

  2. Risk Management

    • Quick response to market crashes
    • Proper threshold implementations
    • Clear warning systems

  3. System Performance

    • Optimal gas usage
    • Quick state updates
    • Reliable oracle integration

Areas for Monitoring

  1. High Volatility Periods

    • Monitor system during >20% price swings
    • Verify emergency protocol activation
    • Track gas costs during high activity

  2. Multi-Asset Scenarios

    • Complex portfolio calculations
    • Cross-asset risk assessment
    • Liability management efficiency

Conclusion

The test suite demonstrates robust system behavior across various market conditions, with particular strength in:

  • Market crash handling
  • Volatility tracking
  • Complex portfolio management
  • Emergency response systems

Test Execution Results

Volatility Tracking Test Results

Volatility Tracking Summary

Real test execution showing volatility tracking over 5 price movement steps with detailed metrics.

Price Changes Analysis

Price Changes Steps

Step-by-step price change analysis showing ETH and BTC price movements and their impact on solvency ratios.

Complete SolvencyProof Test Execution

SolvencyProof Test Results

Comprehensive test results showing market crash scenarios, asset/liability management, and system responses.