//go:build stress
// +build stress

package stress_test

import (
	"context"
	"fmt"
	"math/big"
	"math/rand"
	"sync"
	"sync/atomic"
	"testing"
	"time"

	"github.com/ethereum/go-ethereum/common"
	"github.com/holiman/uint256"

	"github.com/fraktal/mev-beta/internal/logger"
	"github.com/fraktal/mev-beta/pkg/arbitrum"
	"github.com/fraktal/mev-beta/pkg/events"
	"github.com/fraktal/mev-beta/pkg/pools"
	"github.com/fraktal/mev-beta/pkg/profitcalc"
	"github.com/fraktal/mev-beta/pkg/scanner/market"
	"github.com/fraktal/mev-beta/pkg/trading"
)

// BenchmarkStressTestSuite runs benchmark tests for the stress test suite
func BenchmarkStressTestSuite(b *testing.B) {
	// Create test logger
	log := logger.New("warn", "text", "") // Use warn level to minimize logging overhead

	// Create test components
	protocolRegistry := arbitrum.NewArbitrumProtocolRegistry(log)
	poolCache := pools.NewPoolCache(10000, time.Hour)
	marketDiscovery := market.NewMarketDiscovery(nil, log, "")
	strategyEngine := arbitrum.NewMEVStrategyEngine(log, protocolRegistry)
	profitCalculator := profitcalc.NewProfitCalculatorWithClient(log, nil)
	mevAnalyzer := arbitrum.NewMEVAnalyzer(log)
	slippageProtector := trading.NewSlippageProtection(nil, log)
	capitalOptimizer := arbitrum.NewCapitalOptimizer(log)
	profitTracker := arbitrum.NewProfitabilityTracker(log)

	// Create stress test suite
	suite := NewStressTestSuite(
		log,
		protocolRegistry,
		poolCache,
		marketDiscovery,
		strategyEngine,
		profitCalculator,
		mevAnalyzer,
		slippageProtector,
		capitalOptimizer,
		profitTracker,
	)

	// Run benchmark tests
	b.Run("MarketScannerStressTest", func(b *testing.B) {
		b.ResetTimer()
		for i := 0; i < b.N; i++ {
			result := suite.RunMarketScannerStressTest()
			if !result.Passed {
				b.Fatalf("Market scanner stress test failed: %v", result.Errors)
			}
		}
	})

	b.Run("SwapAnalyzerStressTest", func(b *testing.B) {
		b.ResetTimer()
		for i := 0; i < b.N; i++ {
			result := suite.RunSwapAnalyzerStressTest()
			if !result.Passed {
				b.Fatalf("Swap analyzer stress test failed: %v", result.Errors)
			}
		}
	})

	b.Run("PoolDiscoveryStressTest", func(b *testing.B) {
		b.ResetTimer()
		for i := 0; i < b.N; i++ {
			result := suite.RunPoolDiscoveryStressTest()
			if !result.Passed {
				b.Fatalf("Pool discovery stress test failed: %v", result.Errors)
			}
		}
	})

	b.Run("ArbitrageEngineStressTest", func(b *testing.B) {
		b.ResetTimer()
		for i := 0; i < b.N; i++ {
			result := suite.RunArbitrageEngineStressTest()
			if !result.Passed {
				b.Fatalf("Arbitrage engine stress test failed: %v", result.Errors)
			}
		}
	})

	b.Run("EventProcessingStressTest", func(b *testing.B) {
		b.ResetTimer()
		for i := 0; i < b.N; i++ {
			result := suite.RunEventProcessingStressTest()
			if !result.Passed {
				b.Fatalf("Event processing stress test failed: %v", result.Errors)
			}
		}
	})

	b.Run("ProfitCalculationStressTest", func(b *testing.B) {
		b.ResetTimer()
		for i := 0; i < b.N; i++ {
			result := suite.RunProfitCalculationStressTest()
			if !result.Passed {
				b.Fatalf("Profit calculation stress test failed: %v", result.Errors)
			}
		}
	})

	b.Run("ConcurrencyStressTest", func(b *testing.B) {
		b.ResetTimer()
		for i := 0; i < b.N; i++ {
			result := suite.RunConcurrencyStressTest()
			if !result.Passed {
				b.Fatalf("Concurrency stress test failed: %v", result.Errors)
			}
		}
	})

	b.Run("MemoryStressTest", func(b *testing.B) {
		b.ResetTimer()
		for i := 0; i < b.N; i++ {
			result := suite.RunMemoryStressTest()
			if !result.Passed {
				b.Fatalf("Memory stress test failed: %v", result.Errors)
			}
		}
	})

	b.Run("PerformanceRegressionTest", func(b *testing.B) {
		b.ResetTimer()
		for i := 0; i < b.N; i++ {
			result := suite.RunPerformanceRegressionTest()
			if !result.Passed {
				b.Fatalf("Performance regression test failed: %v", result.Errors)
			}
		}
	})
}

// BenchmarkConcurrentMarketScanning benchmarks concurrent market scanning performance
func BenchmarkConcurrentMarketScanning(b *testing.B) {
	// Create test logger
	log := logger.New("warn", "text", "") // Use warn level to minimize logging overhead

	// Create test components
	protocolRegistry := arbitrum.NewArbitrumProtocolRegistry(log)
	poolCache := pools.NewPoolCache(10000, time.Hour)
	marketDiscovery := market.NewMarketDiscovery(nil, log, "")
	strategyEngine := arbitrum.NewMEVStrategyEngine(log, protocolRegistry)
	profitCalculator := profitcalc.NewProfitCalculatorWithClient(log, nil)
	mevAnalyzer := arbitrum.NewMEVAnalyzer(log)
	slippageProtector := trading.NewSlippageProtection(nil, log)
	capitalOptimizer := arbitrum.NewCapitalOptimizer(log)
	profitTracker := arbitrum.NewProfitabilityTracker(log)

	// Create stress test suite
	suite := NewStressTestSuite(
		log,
		protocolRegistry,
		poolCache,
		marketDiscovery,
		strategyEngine,
		profitCalculator,
		mevAnalyzer,
		slippageProtector,
		capitalOptimizer,
		profitTracker,
	)

	// Generate test data
	testPools := suite.generateTestPools(1000)
	testEvents := suite.generateTestEvents(10000)

	b.ResetTimer()
	b.Run("ConcurrentPoolScanning", func(b *testing.B) {
		for i := 0; i < b.N; i++ {
			var wg sync.WaitGroup
			errorCount := int64(0)

			// Process pools concurrently
			for _, pool := range testPools {
				wg.Add(1)
				go func(p *market.CachedData) {
					defer wg.Done()

					// Simulate pool scanning
					ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
					defer cancel()

					// Mock pool scanning operation
					err := suite.mockPoolScan(ctx, p)
					if err != nil {
						atomic.AddInt64(&errorCount, 1)
					}
				}(pool)
			}

			// Wait for all operations to complete
			wg.Wait()

			if errorCount > 0 {
				b.Fatalf("Concurrent pool scanning failed with %d errors", errorCount)
			}
		}
	})

	b.Run("ConcurrentEventProcessing", func(b *testing.B) {
		for i := 0; i < b.N; i++ {
			var wg sync.WaitGroup
			errorCount := int64(0)

			// Process events concurrently
			for _, event := range testEvents {
				wg.Add(1)
				go func(e events.Event) {
					defer wg.Done()

					// Simulate event processing
					ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
					defer cancel()

					// Mock event processing operation
					err := suite.mockEventProcessing(ctx, e)
					if err != nil {
						atomic.AddInt64(&errorCount, 1)
					}
				}(event)
			}

			// Wait for all operations to complete
			wg.Wait()

			if errorCount > 0 {
				b.Fatalf("Concurrent event processing failed with %d errors", errorCount)
			}
		}
	})
}

// BenchmarkMemoryAllocation benchmarks memory allocation performance
func BenchmarkMemoryAllocation(b *testing.B) {
	// Create test logger
	log := logger.New("warn", "text", "") // Use warn level to minimize logging overhead

	// Create test components
	protocolRegistry := arbitrum.NewArbitrumProtocolRegistry(log)
	poolCache := pools.NewPoolCache(10000, time.Hour)
	marketDiscovery := market.NewMarketDiscovery(nil, log, "")
	strategyEngine := arbitrum.NewMEVStrategyEngine(log, protocolRegistry)
	profitCalculator := profitcalc.NewProfitCalculatorWithClient(log, nil)
	mevAnalyzer := arbitrum.NewMEVAnalyzer(log)
	slippageProtector := trading.NewSlippageProtection(nil, log)
	capitalOptimizer := arbitrum.NewCapitalOptimizer(log)
	profitTracker := arbitrum.NewProfitabilityTracker(log)

	// Create stress test suite
	suite := NewStressTestSuite(
		log,
		protocolRegistry,
		poolCache,
		marketDiscovery,
		strategyEngine,
		profitCalculator,
		mevAnalyzer,
		slippageProtector,
		capitalOptimizer,
		profitTracker,
	)

	b.ResetTimer()
	b.Run("LargeDataStructures", func(b *testing.B) {
		for i := 0; i < b.N; i++ {
			// Generate large test data sets
			dataSets := suite.generateLargeTestDataSets(10000)

			// Process large data sets
			var wg sync.WaitGroup
			errorCount := int64(0)

			for _, dataSet := range dataSets {
				wg.Add(1)
				go func(ds []*market.CachedData) {
					defer wg.Done()

					// Simulate memory-intensive processing
					ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
					defer cancel()

					// Mock memory-intensive operation
					err := suite.mockMemoryIntensiveProcessing(ctx, ds)
					if err != nil {
						atomic.AddInt64(&errorCount, 1)
					}
				}(dataSet)
			}

			// Wait for all operations to complete
			wg.Wait()

			if errorCount > 0 {
				b.Fatalf("Memory-intensive processing failed with %d errors", errorCount)
			}
		}
	})
}

// BenchmarkCPUUtilization benchmarks CPU utilization performance
func BenchmarkCPUUtilization(b *testing.B) {
	// Create test logger
	log := logger.New("warn", "text", "") // Use warn level to minimize logging overhead

	// Create test components
	protocolRegistry := arbitrum.NewArbitrumProtocolRegistry(log)
	poolCache := pools.NewPoolCache(10000, time.Hour)
	marketDiscovery := market.NewMarketDiscovery(nil, log, "")
	strategyEngine := arbitrum.NewMEVStrategyEngine(log, protocolRegistry)
	profitCalculator := profitcalc.NewProfitCalculatorWithClient(log, nil)
	mevAnalyzer := arbitrum.NewMEVAnalyzer(log)
	slippageProtector := trading.NewSlippageProtection(nil, log)
	capitalOptimizer := arbitrum.NewCapitalOptimizer(log)
	profitTracker := arbitrum.NewProfitabilityTracker(log)

	// Create stress test suite
	suite := NewStressTestSuite(
		log,
		protocolRegistry,
		poolCache,
		marketDiscovery,
		strategyEngine,
		profitCalculator,
		mevAnalyzer,
		slippageProtector,
		capitalOptimizer,
		profitTracker,
	)

	b.ResetTimer()
	b.Run("CPUIntensiveCalculations", func(b *testing.B) {
		for i := 0; i < b.N; i++ {
			// Generate test data
			testProfits := suite.generateTestProfits(1000)

			// Process profits concurrently
			var wg sync.WaitGroup
			errorCount := int64(0)

			for _, profit := range testProfits {
				wg.Add(1)
				go func(p *arbitrum.ArbitrageOpportunityDetailed) {
					defer wg.Done()

					// Simulate CPU-intensive calculations
					ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
					defer cancel()

					// Mock profit calculation operation
					err := suite.mockProfitCalculation(ctx, p)
					if err != nil {
						atomic.AddInt64(&errorCount, 1)
					}
				}(profit)
			}

			// Wait for all operations to complete
			wg.Wait()

			if errorCount > 0 {
				b.Fatalf("CPU-intensive calculations failed with %d errors", errorCount)
			}
		}
	})
}

// BenchmarkNetworkLatency benchmarks network latency handling
func BenchmarkNetworkLatency(b *testing.B) {
	// Create test logger
	log := logger.New("warn", "text", "") // Use warn level to minimize logging overhead

	// Create test components
	protocolRegistry := arbitrum.NewArbitrumProtocolRegistry(log)
	poolCache := pools.NewPoolCache(10000, time.Hour)
	marketDiscovery := market.NewMarketDiscovery(nil, log, "")
	strategyEngine := arbitrum.NewMEVStrategyEngine(log, protocolRegistry)
	profitCalculator := profitcalc.NewProfitCalculatorWithClient(log, nil)
	mevAnalyzer := arbitrum.NewMEVAnalyzer(log)
	slippageProtector := trading.NewSlippageProtection(nil, log)
	capitalOptimizer := arbitrum.NewCapitalOptimizer(log)
	profitTracker := arbitrum.NewProfitabilityTracker(log)

	// Create stress test suite
	suite := NewStressTestSuite(
		log,
		protocolRegistry,
		poolCache,
		marketDiscovery,
		strategyEngine,
		profitCalculator,
		mevAnalyzer,
		slippageProtector,
		capitalOptimizer,
		profitTracker,
	)

	b.ResetTimer()
	b.Run("NetworkRequestHandling", func(b *testing.B) {
		for i := 0; i < b.N; i++ {
			// Generate test data
			testPools := suite.generateTestPools(100)

			// Process pools with simulated network delays
			var wg sync.WaitGroup
			errorCount := int64(0)

			for _, pool := range testPools {
				wg.Add(1)
				go func(p *market.CachedData) {
					defer wg.Done()

					// Simulate network delay
					time.Sleep(time.Duration(rand.Intn(100)) * time.Millisecond)

					// Simulate pool scanning with network request
					ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
					defer cancel()

					// Mock pool scanning operation
					err := suite.mockPoolScan(ctx, p)
					if err != nil {
						atomic.AddInt64(&errorCount, 1)
					}
				}(pool)
			}

			// Wait for all operations to complete
			wg.Wait()

			if errorCount > 0 {
				b.Fatalf("Network request handling failed with %d errors", errorCount)
			}
		}
	})
}

// BenchmarkErrorHandling benchmarks error handling performance
func BenchmarkErrorHandling(b *testing.B) {
	// Create test logger
	log := logger.New("warn", "text", "") // Use warn level to minimize logging overhead

	// Create test components
	protocolRegistry := arbitrum.NewArbitrumProtocolRegistry(log)
	poolCache := pools.NewPoolCache(10000, time.Hour)
	marketDiscovery := market.NewMarketDiscovery(nil, log, "")
	strategyEngine := arbitrum.NewMEVStrategyEngine(log, protocolRegistry)
	profitCalculator := profitcalc.NewProfitCalculatorWithClient(log, nil)
	mevAnalyzer := arbitrum.NewMEVAnalyzer(log)
	slippageProtector := trading.NewSlippageProtection(nil, log)
	capitalOptimizer := arbitrum.NewCapitalOptimizer(log)
	profitTracker := arbitrum.NewProfitabilityTracker(log)

	// Create stress test suite
	suite := NewStressTestSuite(
		log,
		protocolRegistry,
		poolCache,
		marketDiscovery,
		strategyEngine,
		profitCalculator,
		mevAnalyzer,
		slippageProtector,
		capitalOptimizer,
		profitTracker,
	)

	b.ResetTimer()
	b.Run("ErrorHandlingPerformance", func(b *testing.B) {
		for i := 0; i < b.N; i++ {
			// Generate test data with errors
			testEvents := suite.generateTestEventsWithErrorRate(1000, 0.05) // 5% error rate

			// Process events with error handling
			var wg sync.WaitGroup
			errorCount := int64(0)
			successCount := int64(0)

			for _, event := range testEvents {
				wg.Add(1)
				go func(e events.Event) {
					defer wg.Done()

					// Simulate event processing
					ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
					defer cancel()

					// Mock event processing operation
					err := suite.mockEventProcessing(ctx, e)
					if err != nil {
						atomic.AddInt64(&errorCount, 1)
						suite.recordError(fmt.Sprintf("EventProcessingError: %v", err))
					} else {
						atomic.AddInt64(&successCount, 1)
					}
				}(event)
			}

			// Wait for all operations to complete
			wg.Wait()

			// Validate error handling worked correctly
			if errorCount+successCount != int64(len(testEvents)) {
				b.Fatalf("Error handling count mismatch: %d errors + %d successes != %d total", errorCount, successCount, len(testEvents))
			}
		}
	})
}

// generateTestEventsWithErrorRate generates test events with a specific error rate
func (suite *StressTestSuite) generateTestEventsWithErrorRate(count int, errorRate float64) []events.Event {
	events := suite.generateTestEvents(count)

	// Mark some events to cause errors based on error rate
	errorEvents := int(float64(count) * errorRate)
	for i := 0; i < errorEvents && i < count; i++ {
		// Mark event to cause error
		events[i].Type = events.Unknown // Invalid event type to cause processing errors
	}

	return events
}

// generateTestPools generates test pools for benchmarking
func (suite *StressTestSuite) generateTestPools(count int) []*market.CachedData {
	pools := make([]*market.CachedData, count)

	// Known token addresses for testing
	wethAddr := common.HexToAddress("0x82af49447d8a07e3bd95bd0d56f35241523fbab1")
	usdcAddr := common.HexToAddress("0xaf88d065e77c8cc2239327c5edb3a432268e5831")
	usdtAddr := common.HexToAddress("0xff970a61a04b1ca14834a43f5de4533ebddb5cc8")
	wbtcAddr := common.HexToAddress("0x2f2a2543b76a4166549f7aab2e75bef0aefc5b0f")

	tokens := []common.Address{wethAddr, usdcAddr, usdtAddr, wbtcAddr}

	for i := 0; i < count; i++ {
		// Select random tokens for the pool
		token0 := tokens[rand.Intn(len(tokens))]
		token1 := tokens[rand.Intn(len(tokens))]
		for token0 == token1 {
			token1 = tokens[rand.Intn(len(tokens))]
		}

		// Create deterministic pool address based on index
		poolAddr := common.BigToAddress(big.NewInt(int64(i + 1000000)))

		// Generate deterministic liquidity and price values
		liquidity := uint256.NewInt(uint64(1000000 + i*1000))                        // Increasing liquidity
		sqrtPrice := uint256.NewInt(uint64(1000000000000000000 + i*100000000000000)) // Increasing price

		pools[i] = &market.CachedData{
			Address:      poolAddr,
			Token0:       token0,
			Token1:       token1,
			Fee:          int64(3000 + (i%4)*500), // Varying fees (0.05%, 0.3%, 0.5%, 1%)
			Liquidity:    liquidity,
			SqrtPriceX96: sqrtPrice,
			Tick:         int(74959 + i), // Varying ticks
			TickSpacing:  60,
			Protocol:     fmt.Sprintf("uniswap_v%d", 2+(i%2)), // Alternating V2/V3
			LastUpdated:  time.Now(),
		}
	}

	return pools
}

// generateTestEvents generates test events for benchmarking
func (suite *StressTestSuite) generateTestEvents(count int) []events.Event {
	events := make([]events.Event, count)

	// Known token addresses for testing
	wethAddr := common.HexToAddress("0x82af49447d8a07e3bd95bd0d56f35241523fbab1")
	usdcAddr := common.HexToAddress("0xaf88d065e77c8cc2239327c5edb3a432268e5831")
	usdtAddr := common.HexToAddress("0xff970a61a04b1ca14834a43f5de4533ebddb5cc8")
	wbtcAddr := common.HexToAddress("0x2f2a2543b76a4166549f7aab2e75bef0aefc5b0f")

	tokens := []common.Address{wethAddr, usdcAddr, usdtAddr, wbtcAddr}
	protocols := []string{"uniswap_v2", "uniswap_v3", "sushiswap", "camelot_v2", "camelot_v3", "balancer_v2", "curve", "algebra"}

	for i := 0; i < count; i++ {
		// Select random tokens for the event
		token0 := tokens[rand.Intn(len(tokens))]
		token1 := tokens[rand.Intn(len(tokens))]
		for token0 == token1 {
			token1 = tokens[rand.Intn(len(tokens))]
		}

		// Select random protocol
		protocol := protocols[rand.Intn(len(protocols))]

		// Create deterministic pool address based on index
		poolAddr := common.BigToAddress(big.NewInt(int64(i + 2000000)))

		// Generate deterministic amounts
		amount0 := big.NewInt(int64(100000000000000000 + int64(i)*10000000000000)) // Varying amounts
		amount1 := big.NewInt(int64(200000000000000000 + int64(i)*20000000000000)) // Varying amounts

		// Generate deterministic liquidity and price values
		liquidity := uint256.NewInt(uint64(500000 + i*500))                        // Increasing liquidity
		sqrtPrice := uint256.NewInt(uint64(500000000000000000 + i*50000000000000)) // Increasing price

		events[i] = events.Event{
			Timestamp:       time.Now(),
			BlockNumber:     uint64(10000000 + i),
			TransactionHash: common.BigToHash(big.NewInt(int64(i + 3000000))),
			LogIndex:        uint(i % 100),
			Type:            events.Swap, // Default to swap events
			Protocol:        protocol,
			PoolAddress:     poolAddr,
			Token0:          token0,
			Token1:          token1,
			Amount0:         amount0,
			Amount1:         amount1,
			Liquidity:       liquidity,
			SqrtPriceX96:    sqrtPrice,
			Tick:            int32(74959 + i%1000), // Varying ticks
		}
	}

	return events
}

// generateTestProfits generates test profits for benchmarking
func (suite *StressTestSuite) generateTestProfits(count int) []*arbitrum.ArbitrageOpportunityDetailed {
	profits := make([]*arbitrum.ArbitrageOpportunityDetailed, count)

	// Known token addresses for testing
	wethAddr := common.HexToAddress("0x82af49447d8a07e3bd95bd0d56f35241523fbab1")
	usdcAddr := common.HexToAddress("0xaf88d065e77c8cc2239327c5edb3a432268e5831")
	usdtAddr := common.HexToAddress("0xff970a61a04b1ca14834a43f5de4533ebddb5cc8")
	wbtcAddr := common.HexToAddress("0x2f2a2543b76a4166549f7aab2e75bef0aefc5b0f")

	tokens := []common.Address{wethAddr, usdcAddr, usdtAddr, wbtcAddr}
	exchanges := []string{"uniswap_v2", "uniswap_v3", "sushiswap", "camelot_v2", "camelot_v3", "balancer_v2", "curve", "algebra"}

	for i := 0; i < count; i++ {
		// Select random tokens for the arbitrage
		tokenIn := tokens[rand.Intn(len(tokens))]
		tokenOut := tokens[rand.Intn(len(tokens))]
		for tokenIn == tokenOut {
			tokenOut = tokens[rand.Intn(len(tokens))]
		}

		// Select random exchanges
		exchangeA := exchanges[rand.Intn(len(exchanges))]
		exchangeB := exchanges[rand.Intn(len(exchanges))]
		for exchangeA == exchangeB {
			exchangeB = exchanges[rand.Intn(len(exchanges))]
		}

		// Create deterministic pool addresses based on index
		poolA := common.BigToAddress(big.NewInt(int64(i + 4000000)))
		poolB := common.BigToAddress(big.NewInt(int64(i + 5000000)))

		// Generate deterministic amounts
		amountIn := big.NewInt(int64(100000000000000000 + int64(i)*10000000000000))          // Varying amounts
		expectedAmountOut := big.NewInt(int64(105000000000000000 + int64(i)*10500000000000)) // 5% profit
		actualAmountOut := big.NewInt(int64(104000000000000000 + int64(i)*10400000000000))   // 4% profit
		profit := big.NewInt(int64(4000000000000000 + int64(i)*400000000000))                // Varying profits
		gasCost := big.NewInt(int64(1000000000000000 + int64(i)*100000000000))               // Varying gas costs
		netProfit := new(big.Int).Sub(profit, gasCost)

		profits[i] = &arbitrum.ArbitrageOpportunityDetailed{
			ID:                fmt.Sprintf("arb_%d_%d", time.Now().Unix(), i+1000000),
			Type:              "arbitrage",
			TokenIn:           tokenIn,
			TokenOut:          tokenOut,
			AmountIn:          amountIn,
			ExpectedAmountOut: expectedAmountOut,
			ActualAmountOut:   actualAmountOut,
			Profit:            profit,
			ProfitUSD:         50.0 + float64(i%1000)*0.05,  // Varying USD profits
			ProfitMargin:      0.04 + float64(i%100)*0.0001, // Varying margins (4-5%)
			GasCost:           gasCost,
			NetProfit:         netProfit,
			ExchangeA:         exchangeA,
			ExchangeB:         exchangeB,
			PoolA:             poolA,
			PoolB:             poolB,
			PriceImpactA:      0.005 + float64(i%1000)*0.000005,     // Varying price impacts
			PriceImpactB:      0.003 + float64(i%1000)*0.000003,     // Varying price impacts
			CapitalRequired:   100.0 + float64(i%10000)*0.01,        // Varying capital requirements
			GasCostUSD:        5.0 + float64(i%100)*0.05,            // Varying gas costs in USD
			Confidence:        0.8 + float64(i%20)*0.01,             // Varying confidence (80-100%)
			RiskScore:         0.2 + float64(i%50)*0.01,             // Varying risk scores (20-70%)
			ExecutionTime:     time.Duration(15+i%10) * time.Second, // Varying execution times
			Timestamp:         time.Now(),
		}
	}

	return profits
}

// generateLargeTestDataSets generates large test data sets for memory benchmarking
func (suite *StressTestSuite) generateLargeTestDataSets(count int) [][]*market.CachedData {
	// Create batches of test data
	batchSize := 1000
	batchCount := count / batchSize
	if count%batchSize > 0 {
		batchCount++
	}

	dataSets := make([][]*market.CachedData, batchCount)

	for i := 0; i < batchCount; i++ {
		dataSets[i] = suite.generateTestPools(batchSize)
	}

	return dataSets
}

// mockPoolScan simulates pool scanning for benchmarking
func (suite *StressTestSuite) mockPoolScan(ctx context.Context, pool *market.CachedData) error {
	atomic.AddUint64(&suite.metrics.totalPoolsScanned, 1)
	atomic.AddUint64(&suite.metrics.totalTestsRun, 1)

	// Simulate work
	select {
	case <-ctx.Done():
		return ctx.Err()
	case <-time.After(time.Duration(rand.Intn(10)) * time.Millisecond):
		// Simulate occasional errors
		if rand.Intn(1000) < 5 { // 0.5% error rate
			atomic.AddUint64(&suite.metrics.testsFailed, 1)
			return fmt.Errorf("simulated pool scan error")
		}

		atomic.AddUint64(&suite.metrics.testsPassed, 1)
		return nil
	}
}

// mockEventProcessing simulates event processing for benchmarking
func (suite *StressTestSuite) mockEventProcessing(ctx context.Context, event events.Event) error {
	atomic.AddUint64(&suite.metrics.totalTransactions, 1)
	atomic.AddUint64(&suite.metrics.totalTestsRun, 1)

	// Simulate work
	select {
	case <-ctx.Done():
		return ctx.Err()
	case <-time.After(time.Duration(rand.Intn(5)) * time.Millisecond):
		// Simulate occasional errors
		if rand.Intn(1000) < 3 { // 0.3% error rate
			atomic.AddUint64(&suite.metrics.testsFailed, 1)
			return fmt.Errorf("simulated event processing error")
		}

		atomic.AddUint64(&suite.metrics.testsPassed, 1)
		return nil
	}
}

// mockMemoryIntensiveProcessing simulates memory-intensive processing for benchmarking
func (suite *StressTestSuite) mockMemoryIntensiveProcessing(ctx context.Context, dataSet []*market.CachedData) error {
	atomic.AddUint64(&suite.metrics.totalTestsRun, 1)

	// Simulate memory-intensive work
	// Create temporary data structures to consume memory
	tempData := make([]*market.CachedData, len(dataSet))
	copy(tempData, dataSet)

	// Simulate work
	select {
	case <-ctx.Done():
		return ctx.Err()
	case <-time.After(time.Duration(rand.Intn(20)) * time.Millisecond):
		// Clear temporary data
		tempData = nil

		// Simulate occasional errors
		if rand.Intn(1000) < 8 { // 0.8% error rate
			atomic.AddUint64(&suite.metrics.testsFailed, 1)
			return fmt.Errorf("simulated memory-intensive processing error")
		}

		atomic.AddUint64(&suite.metrics.testsPassed, 1)
		return nil
	}
}

// mockProfitCalculation simulates profit calculation for benchmarking
func (suite *StressTestSuite) mockProfitCalculation(ctx context.Context, profit *arbitrum.ArbitrageOpportunityDetailed) error {
	atomic.AddUint64(&suite.metrics.totalArbitrageOps, 1)
	atomic.AddUint64(&suite.metrics.totalTestsRun, 1)

	// Simulate work
	select {
	case <-ctx.Done():
		return ctx.Err()
	case <-time.After(time.Duration(rand.Intn(15)) * time.Millisecond):
		// Simulate occasional errors
		if rand.Intn(1000) < 6 { // 0.6% error rate
			atomic.AddUint64(&suite.metrics.testsFailed, 1)
			return fmt.Errorf("simulated profit calculation error")
		}

		atomic.AddUint64(&suite.metrics.testsPassed, 1)
		return nil
	}
}