472 lines
No EOL
19 KiB
Solidity
472 lines
No EOL
19 KiB
Solidity
// SPDX-License-Identifier: GPL-3.0-or-later
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pragma solidity ^0.8.19;
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import "forge-std/Test.sol";
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import {TestEnvironment} from "../test/helpers/TestBase.sol";
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import {IUniswapV3Pool} from "@uniswap/v3-core/contracts/interfaces/IUniswapV3Pool.sol";
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import {IUniswapV3Factory} from "@uniswap/v3-core/contracts/interfaces/IUniswapV3Factory.sol";
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import {IWETH9} from "../src/interfaces/IWETH9.sol";
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import {Kraiken} from "../src/Kraiken.sol";
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import {Stake} from "../src/Stake.sol";
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import {LiquidityManager} from "../src/LiquidityManager.sol";
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import {ThreePositionStrategy} from "../src/abstracts/ThreePositionStrategy.sol";
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import {UniswapHelpers} from "../src/helpers/UniswapHelpers.sol";
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import "../test/mocks/BullMarketOptimizer.sol";
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import "../test/mocks/WhaleOptimizer.sol";
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import "./helpers/CSVManager.sol";
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import "./helpers/SwapExecutor.sol";
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/**
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* @title ImprovedFuzzingAnalysis
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* @notice Enhanced fuzzing with larger trades designed to reach discovery position
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* @dev Uses more aggressive trading patterns to explore the full liquidity range
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*/
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contract ImprovedFuzzingAnalysis is Test, CSVManager {
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TestEnvironment testEnv;
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IUniswapV3Factory factory;
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IUniswapV3Pool pool;
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IWETH9 weth;
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Kraiken harberg;
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Stake stake;
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LiquidityManager lm;
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bool token0isWeth;
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// Reusable swap executor to avoid repeated deployments
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SwapExecutor swapExecutor;
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address account = makeAddr("trader");
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address whale = makeAddr("whale");
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address feeDestination = makeAddr("fees");
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// Analysis metrics
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uint256 public scenariosAnalyzed;
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uint256 public profitableScenarios;
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uint256 public discoveryReachedCount;
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// Configuration
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uint256 public fuzzingRuns;
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bool public trackPositions;
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string public optimizerClass;
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function run() public virtual {
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_loadConfiguration();
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console.log("=== IMPROVED Fuzzing Analysis ===");
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console.log("Designed to reach discovery position with larger trades");
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console.log(string.concat("Optimizer: ", optimizerClass));
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console.log(string.concat("Fuzzing runs: ", vm.toString(fuzzingRuns)));
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console.log("");
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testEnv = new TestEnvironment(feeDestination);
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// Deploy factory once for all runs (gas optimization)
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factory = UniswapHelpers.deployUniswapFactory();
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// Get optimizer
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address optimizerAddress = _getOptimizerByClass(optimizerClass);
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// Track profitable scenarios
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string memory profitableCSV = "Scenario,Seed,Initial Balance,Final Balance,Profit,Profit %,Discovery Reached\n";
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uint256 profitableCount;
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for (uint256 seed = 0; seed < fuzzingRuns; seed++) {
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if (seed % 10 == 0 && seed > 0) {
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console.log(string.concat("Progress: ", vm.toString(seed), "/", vm.toString(fuzzingRuns)));
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}
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// Create fresh environment with existing factory
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(factory, pool, weth, harberg, stake, lm,, token0isWeth) =
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testEnv.setupEnvironmentWithExistingFactory(factory, seed % 2 == 0, feeDestination, optimizerAddress);
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// Fund LiquidityManager with MORE ETH for deeper liquidity
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vm.deal(address(lm), 200 ether); // Increased from 50
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// Fund accounts with MORE capital
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uint256 traderFund = 50 ether + (uint256(keccak256(abi.encodePacked(seed, "trader"))) % 150 ether); // 50-200 ETH
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uint256 whaleFund = 200 ether + (uint256(keccak256(abi.encodePacked(seed, "whale"))) % 300 ether); // 200-500 ETH
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vm.deal(account, traderFund * 2);
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vm.deal(whale, whaleFund * 2);
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vm.prank(account);
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weth.deposit{value: traderFund}();
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vm.prank(whale);
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weth.deposit{value: whaleFund}();
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// Create SwapExecutor once per scenario to avoid repeated deployments
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swapExecutor = new SwapExecutor(pool, weth, harberg, token0isWeth);
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uint256 initialBalance = weth.balanceOf(account);
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// Initial recenter
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vm.prank(feeDestination);
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lm.recenter();
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// Initialize position tracking for each seed
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if (trackPositions) {
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// Initialize CSV header for each seed (after clearCSV from previous run)
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initializePositionsCSV();
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_recordPositionData("Initial");
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}
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// Run improved trading scenario
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(uint256 finalBalance, bool reachedDiscovery) = _runImprovedScenario(seed);
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scenariosAnalyzed++;
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if (reachedDiscovery) {
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discoveryReachedCount++;
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}
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// Check profitability
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if (finalBalance > initialBalance) {
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uint256 profit = finalBalance - initialBalance;
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uint256 profitPct = (profit * 100) / initialBalance;
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profitableScenarios++;
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console.log(string.concat("PROFITABLE! Seed: ", vm.toString(seed)));
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console.log(string.concat(" Profit: ", vm.toString(profit / 1e15), " finney (", vm.toString(profitPct), "%)"));
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console.log(string.concat(" Discovery reached: ", reachedDiscovery ? "YES" : "NO"));
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profitableCSV = string.concat(
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profitableCSV,
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optimizerClass, ",",
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vm.toString(seed), ",",
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vm.toString(initialBalance), ",",
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vm.toString(finalBalance), ",",
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vm.toString(profit), ",",
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vm.toString(profitPct), ",",
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reachedDiscovery ? "true" : "false", "\n"
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);
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profitableCount++;
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}
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// Write position CSV if tracking
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if (trackPositions) {
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_recordPositionData("Final");
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string memory positionFilename = string.concat(
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"improved_positions_", optimizerClass, "_", vm.toString(seed), ".csv"
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);
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writeCSVToFile(positionFilename);
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clearCSV(); // Clear buffer for next run
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}
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}
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// Summary
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console.log("\n=== ANALYSIS COMPLETE ===");
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console.log(string.concat("Total scenarios: ", vm.toString(scenariosAnalyzed)));
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console.log(string.concat("Profitable scenarios: ", vm.toString(profitableScenarios)));
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console.log(string.concat("Discovery reached: ", vm.toString(discoveryReachedCount), " times"));
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console.log(string.concat("Discovery rate: ", vm.toString((discoveryReachedCount * 100) / scenariosAnalyzed), "%"));
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console.log(string.concat("Profit rate: ", vm.toString((profitableScenarios * 100) / scenariosAnalyzed), "%"));
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if (profitableCount > 0) {
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string memory filename = string.concat("improved_profitable_", vm.toString(block.timestamp), ".csv");
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vm.writeFile(filename, profitableCSV);
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console.log(string.concat("\nResults written to: ", filename));
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}
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}
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function _runImprovedScenario(uint256 seed) internal virtual returns (uint256 finalBalance, bool reachedDiscovery) {
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uint256 rand = uint256(keccak256(abi.encodePacked(seed, block.timestamp)));
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// Get initial discovery position
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(, int24 discoveryLower, int24 discoveryUpper) = lm.positions(ThreePositionStrategy.Stage.DISCOVERY);
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// Strategy selection based on seed
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uint256 strategy = seed % 5;
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if (strategy == 0) {
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// STRATEGY 1: Massive coordinated sell to push into discovery
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_executeDiscoveryPush(rand);
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} else if (strategy == 1) {
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// STRATEGY 2: Whale manipulation
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_executeWhaleManipulation(rand);
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} else if (strategy == 2) {
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// STRATEGY 3: Volatile swings
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_executeVolatileSwings(rand);
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} else if (strategy == 3) {
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// STRATEGY 4: Sustained pressure
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_executeSustainedPressure(rand);
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} else {
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// STRATEGY 5: Random large trades
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_executeRandomLargeTrades(rand);
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}
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// Check if we reached discovery
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(, int24 currentTick,,,,,) = pool.slot0();
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reachedDiscovery = (currentTick >= discoveryLower && currentTick < discoveryUpper);
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if (reachedDiscovery) {
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console.log(" [DISCOVERY REACHED] at tick", vm.toString(currentTick));
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if (trackPositions) {
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_recordPositionData("Discovery_Reached");
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}
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}
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// Final cleanup: sell all KRAIKEN
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uint256 finalKraiken = harberg.balanceOf(account);
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if (finalKraiken > 0) {
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_executeSell(account, finalKraiken);
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}
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finalBalance = weth.balanceOf(account);
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}
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function _executeDiscoveryPush(uint256 rand) internal virtual {
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console.log(" Strategy: Discovery Push");
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// Both accounts buy large amounts first
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uint256 traderBuy = weth.balanceOf(account) * 7 / 10; // 70% of balance
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uint256 whaleBuy = weth.balanceOf(whale) * 8 / 10; // 80% of balance
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_executeBuy(account, traderBuy);
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_executeBuy(whale, whaleBuy);
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if (trackPositions) {
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_recordPositionData("MassiveBuy");
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}
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// Now coordinated massive sell to push price down
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uint256 whaleKraiken = harberg.balanceOf(whale);
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_executeSell(whale, whaleKraiken); // Whale dumps all
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if (trackPositions) {
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_recordPositionData("WhaleDump");
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}
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// Trader tries to profit from the movement
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uint256 traderKraiken = harberg.balanceOf(account);
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if (traderKraiken > 0) {
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// Sell half during crash
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_executeSell(account, traderKraiken / 2);
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// Recenter during low price
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vm.warp(block.timestamp + 1 hours);
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vm.prank(feeDestination);
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try lm.recenter{gas: 50_000_000}() {} catch {}
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// Buy back at low price
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uint256 remainingWeth = weth.balanceOf(account);
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if (remainingWeth > 0) {
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_executeBuy(account, remainingWeth / 2);
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}
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}
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}
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function _executeWhaleManipulation(uint256 rand) internal {
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console.log(" Strategy: Whale Manipulation");
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// Whale does large trades to move price significantly
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for (uint256 i = 0; i < 5; i++) {
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uint256 action = (rand >> i) % 3;
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if (action == 0) {
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// Large buy
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uint256 buyAmount = weth.balanceOf(whale) / 2;
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if (buyAmount > 0) {
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_executeBuy(whale, buyAmount);
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}
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} else if (action == 1) {
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// Large sell
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uint256 sellAmount = harberg.balanceOf(whale) / 2;
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if (sellAmount > 0) {
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_executeSell(whale, sellAmount);
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}
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} else {
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// Trigger recenter
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vm.warp(block.timestamp + 30 minutes);
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vm.prank(feeDestination);
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try lm.recenter{gas: 50_000_000}() {} catch {}
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}
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// Trader tries to follow/counter
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if (harberg.balanceOf(account) > 0) {
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_executeSell(account, harberg.balanceOf(account) / 4);
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} else if (weth.balanceOf(account) > 0) {
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_executeBuy(account, weth.balanceOf(account) / 4);
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}
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if (trackPositions && i % 2 == 0) {
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_recordPositionData(string.concat("Whale_", vm.toString(i)));
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}
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}
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}
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function _executeVolatileSwings(uint256 rand) internal {
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console.log(" Strategy: Volatile Swings");
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// Create large price swings
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for (uint256 i = 0; i < 8; i++) {
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if (i % 2 == 0) {
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// Swing down - coordinated sells
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uint256 traderSell = harberg.balanceOf(account);
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uint256 whaleSell = harberg.balanceOf(whale);
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if (traderSell > 0) _executeSell(account, traderSell);
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if (whaleSell > 0) _executeSell(whale, whaleSell);
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// If we pushed price low enough, recenter
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(, int24 tick,,,,,) = pool.slot0();
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(, int24 discoveryLower,) = lm.positions(ThreePositionStrategy.Stage.DISCOVERY);
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if (tick < discoveryLower + 1000) {
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vm.warp(block.timestamp + 1 hours);
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vm.prank(feeDestination);
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try lm.recenter{gas: 50_000_000}() {} catch {}
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}
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} else {
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// Swing up - coordinated buys
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uint256 traderBuy = weth.balanceOf(account) * 6 / 10;
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uint256 whaleBuy = weth.balanceOf(whale) * 7 / 10;
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if (traderBuy > 0) _executeBuy(account, traderBuy);
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if (whaleBuy > 0) _executeBuy(whale, whaleBuy);
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}
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if (trackPositions) {
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_recordPositionData(string.concat("Swing_", vm.toString(i)));
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}
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}
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}
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function _executeSustainedPressure(uint256 rand) internal {
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console.log(" Strategy: Sustained Sell Pressure");
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// First accumulate KRAIKEN
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_executeBuy(account, weth.balanceOf(account) * 9 / 10); // 90% buy
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_executeBuy(whale, weth.balanceOf(whale) * 9 / 10); // 90% buy
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if (trackPositions) {
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_recordPositionData("Accumulation");
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}
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// Now sustained selling pressure
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uint256 totalKraiken = harberg.balanceOf(account) + harberg.balanceOf(whale);
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uint256 sellsPerAccount = 10;
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uint256 amountPerSell = totalKraiken / (sellsPerAccount * 2);
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for (uint256 i = 0; i < sellsPerAccount; i++) {
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// Alternate sells between accounts
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if (harberg.balanceOf(account) >= amountPerSell) {
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_executeSell(account, amountPerSell);
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}
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if (harberg.balanceOf(whale) >= amountPerSell) {
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_executeSell(whale, amountPerSell);
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}
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// Check if we're approaching discovery
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(, int24 currentTick,,,,,) = pool.slot0();
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(, int24 discoveryUpper,) = lm.positions(ThreePositionStrategy.Stage.DISCOVERY);
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if (currentTick < discoveryUpper + 500) {
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console.log(" Approaching discovery, tick:", vm.toString(currentTick));
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// Recenter while near discovery
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vm.warp(block.timestamp + 30 minutes);
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vm.prank(feeDestination);
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try lm.recenter{gas: 50_000_000}() {} catch {}
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if (trackPositions) {
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_recordPositionData("Near_Discovery");
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}
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}
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}
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}
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function _executeRandomLargeTrades(uint256 rand) internal {
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console.log(" Strategy: Random Large Trades");
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for (uint256 i = 0; i < 15; i++) {
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rand = uint256(keccak256(abi.encodePacked(rand, i)));
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uint256 actor = rand % 2; // 0 = trader, 1 = whale
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uint256 action = (rand >> 8) % 3; // buy, sell, recenter
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address actorAddr = actor == 0 ? account : whale;
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if (action == 0) {
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// Large buy (30-80% of balance)
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uint256 buyPct = 30 + (rand % 51);
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uint256 buyAmount = weth.balanceOf(actorAddr) * buyPct / 100;
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if (buyAmount > 0) {
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_executeBuy(actorAddr, buyAmount);
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}
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} else if (action == 1) {
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// Large sell (30-100% of KRAIKEN)
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uint256 sellPct = 30 + (rand % 71);
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uint256 sellAmount = harberg.balanceOf(actorAddr) * sellPct / 100;
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if (sellAmount > 0) {
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_executeSell(actorAddr, sellAmount);
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}
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} else {
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// Recenter
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vm.warp(block.timestamp + (rand % 2 hours));
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vm.prank(feeDestination);
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try lm.recenter{gas: 50_000_000}() {} catch {}
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}
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if (trackPositions && i % 3 == 0) {
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_recordPositionData(string.concat("Random_", vm.toString(i)));
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}
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}
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}
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function _executeBuy(address buyer, uint256 amount) internal virtual {
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if (amount == 0 || weth.balanceOf(buyer) < amount) return;
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vm.prank(buyer);
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weth.transfer(address(swapExecutor), amount);
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try swapExecutor.executeBuy(amount, buyer) {} catch {}
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}
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function _executeSell(address seller, uint256 amount) internal virtual {
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if (amount == 0 || harberg.balanceOf(seller) < amount) return;
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vm.prank(seller);
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harberg.transfer(address(swapExecutor), amount);
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try swapExecutor.executeSell(amount, seller) {} catch {}
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}
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function _getOptimizerByClass(string memory class) internal returns (address) {
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if (keccak256(bytes(class)) == keccak256("BullMarketOptimizer")) {
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return address(new BullMarketOptimizer());
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} else if (keccak256(bytes(class)) == keccak256("WhaleOptimizer")) {
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return address(new WhaleOptimizer());
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} else {
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return address(new BullMarketOptimizer());
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}
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}
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function _loadConfiguration() internal {
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fuzzingRuns = vm.envOr("FUZZING_RUNS", uint256(20));
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trackPositions = vm.envOr("TRACK_POSITIONS", false);
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optimizerClass = vm.envOr("OPTIMIZER_CLASS", string("BullMarketOptimizer"));
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}
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function _recordPositionData(string memory label) internal {
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(,int24 currentTick,,,,,) = pool.slot0();
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(uint128 floorLiq, int24 floorLower, int24 floorUpper) = lm.positions(ThreePositionStrategy.Stage.FLOOR);
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(uint128 anchorLiq, int24 anchorLower, int24 anchorUpper) = lm.positions(ThreePositionStrategy.Stage.ANCHOR);
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(uint128 discoveryLiq, int24 discoveryLower, int24 discoveryUpper) = lm.positions(ThreePositionStrategy.Stage.DISCOVERY);
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string memory row = string.concat(
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label, ",",
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vm.toString(currentTick), ",",
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vm.toString(floorLower), ",",
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vm.toString(floorUpper), ",",
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vm.toString(floorLiq), ",",
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vm.toString(anchorLower), ",",
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vm.toString(anchorUpper), ",",
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vm.toString(anchorLiq), ",",
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vm.toString(discoveryLower), ",",
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vm.toString(discoveryUpper), ",",
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vm.toString(discoveryLiq), ",",
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token0isWeth ? "true" : "false"
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);
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appendCSVRow(row);
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}
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} |