// SPDX-License-Identifier: GPL-3.0-or-later pragma solidity ^0.8.19; import "../src/Optimizer.sol"; import "./mocks/MockKraiken.sol"; import "./mocks/MockStake.sol"; import { ERC1967Proxy } from "@openzeppelin/proxy/ERC1967/ERC1967Proxy.sol"; import "forge-std/Test.sol"; import "forge-std/console.sol"; /// @dev Harness to expose internal _calculateAnchorWidth for direct coverage of the totalWidth < 10 path contract OptimizerHarness is Optimizer { function exposed_calculateAnchorWidth(uint256 percentageStaked, uint256 averageTaxRate) external pure returns (uint24) { return _calculateAnchorWidth(percentageStaked, averageTaxRate); } } contract OptimizerTest is Test { Optimizer optimizer; MockStake mockStake; MockKraiken mockKraiken; function setUp() public { // Deploy mocks mockKraiken = new MockKraiken(); mockStake = new MockStake(); // Deploy Optimizer implementation Optimizer implementation = new Optimizer(); // Deploy proxy and initialize bytes memory initData = abi.encodeWithSelector(Optimizer.initialize.selector, address(mockKraiken), address(mockStake)); // For simplicity, we'll test the implementation directly // In production, you'd use a proper proxy setup optimizer = implementation; optimizer.initialize(address(mockKraiken), address(mockStake)); } /** * @notice Test that anchorWidth adjusts correctly for bull market conditions * @dev High staking, low tax → narrow anchor (30-35%) */ function testBullMarketAnchorWidth() public { // Set bull market conditions: high staking (80%), low tax (10%) mockStake.setPercentageStaked(0.8e18); mockStake.setAverageTaxRate(0.1e18); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Expected: base(40) + staking_adj(20 - 32 = -12) + tax_adj(4 - 10 = -6) = 22 assertEq(anchorWidth, 22, "Bull market should have narrow anchor width"); assertTrue(anchorWidth >= 20 && anchorWidth <= 35, "Bull market width should be 20-35%"); } /** * @notice Test that anchorWidth adjusts correctly for bear market conditions * @dev Low staking, high tax → wide anchor (60-80%) */ function testBearMarketAnchorWidth() public { // Set bear market conditions: low staking (20%), high tax (70%) mockStake.setPercentageStaked(0.2e18); mockStake.setAverageTaxRate(0.7e18); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Expected: base(40) + staking_adj(20 - 8 = 12) + tax_adj(28 - 10 = 18) = 70 assertEq(anchorWidth, 70, "Bear market should have wide anchor width"); assertTrue(anchorWidth >= 60 && anchorWidth <= 80, "Bear market width should be 60-80%"); } /** * @notice Test neutral market conditions * @dev Medium staking, medium tax → balanced anchor (35-50%) */ function testNeutralMarketAnchorWidth() public { // Set neutral conditions: medium staking (50%), medium tax (30%) mockStake.setPercentageStaked(0.5e18); mockStake.setAverageTaxRate(0.3e18); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Expected: base(40) + staking_adj(20 - 20 = 0) + tax_adj(12 - 10 = 2) = 42 assertEq(anchorWidth, 42, "Neutral market should have balanced anchor width"); assertTrue(anchorWidth >= 35 && anchorWidth <= 50, "Neutral width should be 35-50%"); } /** * @notice Test high volatility scenario * @dev High staking with high tax (speculative frenzy) → moderate-wide anchor */ function testHighVolatilityAnchorWidth() public { // High staking (70%) but also high tax (80%) - speculative market mockStake.setPercentageStaked(0.7e18); mockStake.setAverageTaxRate(0.8e18); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Expected: base(40) + staking_adj(20 - 28 = -8) + tax_adj(32 - 10 = 22) = 54 assertEq(anchorWidth, 54, "High volatility should have moderate-wide anchor"); assertTrue(anchorWidth >= 50 && anchorWidth <= 60, "Volatile width should be 50-60%"); } /** * @notice Test stable market conditions * @dev Medium staking with very low tax → narrow anchor for fee optimization */ function testStableMarketAnchorWidth() public { // Medium staking (50%), very low tax (5%) - stable conditions mockStake.setPercentageStaked(0.5e18); mockStake.setAverageTaxRate(0.05e18); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Expected: base(40) + staking_adj(20 - 20 = 0) + tax_adj(2 - 10 = -8) = 32 assertEq(anchorWidth, 32, "Stable market should have narrower anchor"); assertTrue(anchorWidth >= 30 && anchorWidth <= 40, "Stable width should be 30-40%"); } /** * @notice Test minimum bound enforcement * @dev Extreme conditions that would result in width < 10 should clamp to 10 */ function testMinimumWidthBound() public { // Extreme bull: very high staking (95%), zero tax mockStake.setPercentageStaked(0.95e18); mockStake.setAverageTaxRate(0); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Expected: base(40) + staking_adj(20 - 38 = -18) + tax_adj(0 - 10 = -10) = 12 // But should be at least 10 assertEq(anchorWidth, 12, "Should not go below calculated value if above 10"); assertTrue(anchorWidth >= 10, "Width should never be less than 10"); } /** * @notice Test maximum bound enforcement * @dev Extreme conditions that would result in width > 80 should clamp to 80 */ function testMaximumWidthBound() public { // Extreme bear: zero staking, maximum tax mockStake.setPercentageStaked(0); mockStake.setAverageTaxRate(1e18); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Expected: base(40) + staking_adj(20 - 0 = 20) + tax_adj(40 - 10 = 30) = 90 // But should be clamped to 80 assertEq(anchorWidth, 80, "Should clamp to maximum of 80"); assertTrue(anchorWidth <= 80, "Width should never exceed 80"); } /** * @notice Test edge case with exactly minimum staking and tax */ function testEdgeCaseMinimumInputs() public { mockStake.setPercentageStaked(0); mockStake.setAverageTaxRate(0); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Expected: base(40) + staking_adj(20 - 0 = 20) + tax_adj(0 - 10 = -10) = 50 assertEq(anchorWidth, 50, "Zero inputs should give moderate width"); } /** * @notice Test edge case with exactly maximum staking and tax */ function testEdgeCaseMaximumInputs() public { mockStake.setPercentageStaked(1e18); mockStake.setAverageTaxRate(1e18); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Expected: base(40) + staking_adj(20 - 40 = -20) + tax_adj(40 - 10 = 30) = 50 assertEq(anchorWidth, 50, "Maximum inputs should balance out to moderate width"); } /** * @notice Test edge case with high staking and high tax rate * @dev This specific case previously caused an overflow */ function testHighStakingHighTaxEdgeCase() public { // Set conditions that previously caused overflow // ~94.6% staked, ~96.7% tax rate mockStake.setPercentageStaked(946_350_908_835_331_692); mockStake.setAverageTaxRate(966_925_542_613_630_263); (uint256 capitalInefficiency, uint256 anchorShare, uint24 anchorWidth, uint256 discoveryDepth) = optimizer.getLiquidityParams(); // With very high staking (>92%) and high tax, sentiment reaches maximum (1e18) // This results in zero capital inefficiency assertEq(capitalInefficiency, 0, "Max sentiment should result in zero capital inefficiency"); // Anchor share should be at maximum assertEq(anchorShare, 1e18, "Max sentiment should result in maximum anchor share"); // Anchor width should still be within bounds assertTrue(anchorWidth >= 10 && anchorWidth <= 80, "Anchor width should be within bounds"); // Expected: base(40) + staking_adj(20 - 37 = -17) + tax_adj(38 - 10 = 28) = 51 assertEq(anchorWidth, 51, "Should calculate correct width for edge case"); } /** * @notice Fuzz test to ensure anchorWidth always stays within bounds */ function testFuzzAnchorWidthBounds(uint256 percentageStaked, uint256 averageTaxRate) public { // Bound inputs to valid ranges percentageStaked = bound(percentageStaked, 0, 1e18); averageTaxRate = bound(averageTaxRate, 0, 1e18); mockStake.setPercentageStaked(percentageStaked); mockStake.setAverageTaxRate(averageTaxRate); (,, uint24 anchorWidth,) = optimizer.getLiquidityParams(); // Assert bounds are always respected assertTrue(anchorWidth >= 10, "Width should never be less than 10"); assertTrue(anchorWidth <= 80, "Width should never exceed 80"); // Edge cases (10 or 80) are valid and tested by assertions } /** * @notice Test that other liquidity params are still calculated correctly */ function testOtherLiquidityParams() public { mockStake.setPercentageStaked(0.6e18); mockStake.setAverageTaxRate(0.4e18); (uint256 capitalInefficiency, uint256 anchorShare, uint24 anchorWidth, uint256 discoveryDepth) = optimizer.getLiquidityParams(); uint256 sentiment = optimizer.getSentiment(); // Verify relationships assertEq(capitalInefficiency, 1e18 - sentiment, "Capital inefficiency should be 1 - sentiment"); assertEq(anchorShare, sentiment, "Anchor share should equal sentiment"); assertEq(discoveryDepth, sentiment, "Discovery depth should equal sentiment"); // Verify anchor width is calculated independently // Expected: base(40) + staking_adj(20 - 24 = -4) + tax_adj(16 - 10 = 6) = 42 assertEq(anchorWidth, 42, "Anchor width should be independently calculated"); } // ========================================================= // COVERAGE TESTS: calculateSentiment direct call + mid-range tax + zero path // ========================================================= /** * @notice Direct external call to calculateSentiment covers the function in coverage metrics */ function testCalculateSentimentDirect() public view { // 100% staked, any tax → high staking path → very low penalty uint256 sentiment = optimizer.calculateSentiment(0, 1e18); // deltaS = 0, penalty = 0, sentimentValue = 0 assertEq(sentiment, 0, "100% staked, 0 tax: penalty=0 so sentiment=0"); } /** * @notice Cover the else-if (averageTaxRate <= 5e16) branch with a result > 0 * @dev averageTaxRate = 3e16 (in range (1e16, 5e16]), percentageStaked = 0 * baseSentiment = 1e18, ratePenalty = (2e16 * 1e18) / 4e16 = 5e17 * result = 1e18 - 5e17 = 5e17 */ function testCalculateSentimentMidRangeTax() public view { uint256 sentiment = optimizer.calculateSentiment(3e16, 0); assertEq(sentiment, 5e17, "Mid-range tax should apply partial penalty"); } /** * @notice Cover the ternary zero path: baseSentiment > ratePenalty ? ... : 0 * @dev averageTaxRate = 5e16 (boundary), percentageStaked = 0 * baseSentiment = 1e18, ratePenalty = (4e16 * 1e18) / 4e16 = 1e18 * 1e18 > 1e18 is false → sentimentValue = 0 */ function testCalculateSentimentZeroPath() public view { uint256 sentiment = optimizer.calculateSentiment(5e16, 0); assertEq(sentiment, 0, "At boundary 5e16 ratePenalty equals baseSentiment so result is zero"); } // ========================================================= // COVERAGE TESTS: UUPS upgrade flow (_checkAdmin, _authorizeUpgrade, onlyAdmin) // ========================================================= /** * @notice Deploy via ERC1967Proxy and call upgradeTo to cover _authorizeUpgrade + _checkAdmin */ function testUUPSUpgrade() public { Optimizer impl1 = new Optimizer(); ERC1967Proxy proxy = new ERC1967Proxy(address(impl1), abi.encodeWithSelector(Optimizer.initialize.selector, address(mockKraiken), address(mockStake))); Optimizer proxyOptimizer = Optimizer(address(proxy)); // Deployer (this contract) is admin — upgrade should succeed Optimizer impl2 = new Optimizer(); proxyOptimizer.upgradeTo(address(impl2)); // Verify proxy still works after upgrade (,, uint24 w,) = proxyOptimizer.getLiquidityParams(); assertTrue(w >= 10 && w <= 80, "Params should still work after upgrade"); } /** * @notice Cover the require revert branch in calculateSentiment (percentageStaked > 1e18) */ function testCalculateSentimentRevertsAbove100Percent() public { vm.expectRevert("Invalid percentage staked"); optimizer.calculateSentiment(0, 1e18 + 1); } /** * @notice Cover the totalWidth < 10 clamp via OptimizerHarness. * @dev With percentageStaked = 1.5e18 and averageTaxRate = 0: * stakingAdjustment = 20 - 60 = -40 * taxAdjustment = 0 - 10 = -10 * totalWidth = 40 - 40 - 10 = -10 → clamped to 10 */ function testAnchorWidthBelowTenClamp() public { OptimizerHarness harness = new OptimizerHarness(); uint24 w = harness.exposed_calculateAnchorWidth(15e17, 0); assertEq(w, 10, "totalWidth < 10 should be clamped to minimum of 10"); } /** * @notice calculateParams reverts when inputs[0].mantissa is negative */ function testCalculateParamsRevertsOnNegativeMantissa0() public { OptimizerInput[8] memory inputs; inputs[0] = OptimizerInput({mantissa: -1, shift: 0}); vm.expectRevert("negative mantissa"); optimizer.calculateParams(inputs); } /** * @notice calculateParams reverts when inputs[1].mantissa is negative */ function testCalculateParamsRevertsOnNegativeMantissa1() public { OptimizerInput[8] memory inputs; inputs[1] = OptimizerInput({mantissa: -1, shift: 0}); vm.expectRevert("negative mantissa"); optimizer.calculateParams(inputs); } /** * @notice Non-admin calling upgradeTo should revert with UnauthorizedAccount */ function testUnauthorizedUpgradeReverts() public { Optimizer impl1 = new Optimizer(); ERC1967Proxy proxy = new ERC1967Proxy(address(impl1), abi.encodeWithSelector(Optimizer.initialize.selector, address(mockKraiken), address(mockStake))); Optimizer proxyOptimizer = Optimizer(address(proxy)); // Deploy impl2 BEFORE the prank so the prank applies only to upgradeTo Optimizer impl2 = new Optimizer(); address nonAdmin = makeAddr("nonAdmin"); vm.expectRevert(abi.encodeWithSelector(Optimizer.UnauthorizedAccount.selector, nonAdmin)); vm.prank(nonAdmin); proxyOptimizer.upgradeTo(address(impl2)); } }