{"paired":{"n":2000,"mean_diff":0.11430012814132348,"se":0.01259620227660592,"worst":[{"seed":5110393,"d":-2.1638873586118166},{"seed":5111422,"d":-2.010847831381625},{"seed":5111734,"d":-1.9597996276498861},{"seed":5110385,"d":-1.9444276895953863},{"seed":5111413,"d":-1.7741021852783092}],"sum_d":228.60025628264697,"sum_d2":660.4689571353483},"retail_edge_delta":{"mean":0.3035056562756815,"se":0.012273310013507547,"n":2000,"sum_d":607.011312551363,"sum_d2":786.4666532559472},"arb_edge_delta":{"mean":-0.1892055281343567,"se":0.006420836501960257,"n":2000,"sum_d":-378.4110562687134,"sum_d2":236.42357501005284},"reconciliation_max_abs":1.7053025658242404e-13,"item":"b","code":"// SPDX-License-Identifier: MIT\npragma solidity ^0.8.24;\n\nimport {AMMStrategyBase} from \"./AMMStrategyBase.sol\";\nimport {TradeInfo} from \"./IAMMStrategy.sol\";\n\ncontract Strategy is AMMStrategyBase {\n    uint256 constant ELAPSED_CAP = 8;\n    uint256 constant SIGNAL_THRESHOLD = WAD / 650;\n    uint256 constant DIR_DECAY = 750000000000000000;\n    uint256 constant ACT_DECAY = 530000000000000000;\n    uint256 constant SIZE_DECAY = 530000000000000000;\n    uint256 constant TOX_DECAY = 910000000000000000;\n    uint256 constant SIGMA_DECAY = 690000000000000000;\n    uint256 constant LAMBDA_DECAY = 990000000000000000;\n    uint256 constant SIZE_BLEND_DECAY = 828000000000000000;\n    uint256 constant TOX_BLEND_DECAY = 51000000000000000;\n    uint256 constant ACT_BLEND_DECAY = 985000000000000000;\n    uint256 constant PHAT_ALPHA = 270000000000000000;\n    uint256 constant PHAT_ALPHA_RETAIL = 60000000000000000;\n    uint256 constant PHAT_ALPHA_SAME = 120000000000000000;\n    uint256 constant REVERT_U = 0;\n    uint256 constant DIR_IMPACT_MULT = 4;\n    uint256 constant GATE_SIGMA_MULT = 7200000000000000000;\n    uint256 constant MIN_GATE = 30000000000000000;\n    uint256 constant TRADE_TOX_BOOST = 3500 * BPS;\n    uint256 constant STALE_ATTRACT_FRAC = 1050000000000000000;\n    uint256 constant RET_CAP = WAD / 35;\n    uint256 constant TOX_CAP = WAD / 5;\n    uint256 constant TRADE_RATIO_CAP = WAD / 5;\n    uint256 constant LAMBDA_CAP = 1820000000000000000;\n    uint256 constant STEP_COUNT_CAP = 64;\n    uint256 constant BASE_FEE = 4 * BPS;\n    uint256 constant SIGMA_COEF = 200000000000000000;\n    uint256 constant LAMBDA_COEF = 12 * BPS;\n    uint256 constant FLOW_SIZE_COEF = 4842 * BPS;\n    uint256 constant TOX_COEF = 300 * BPS;\n    uint256 constant TOX_QUAD_COEF = 15000 * BPS;\n    uint256 constant ACT_COEF = 91843 * BPS;\n    uint256 constant DIR_COEF = 20 * BPS;\n    uint256 constant DIR_TOX_COEF = 100 * BPS;\n    uint256 constant STALE_DIR_COEF = 6850 * BPS;\n    uint256 constant SIGMA_TOX_COEF = 500 * BPS;\n    uint256 constant TAIL_KNEE = 600 * BPS;\n    uint256 constant TAIL_SLOPE_PROTECT = 930000000000000000;\n    uint256 constant TAIL_SLOPE_ATTRACT = 850000000000000000;\n\n    function _anchorSigma(uint256 current, uint256 packed) internal pure returns (uint256) {\n        uint256 mean = uint80(packed >> 80);\n        if (uint32(packed >> 160) == 0) mean = current;\n        return wmul(1047182309813441000, _blend(current, mean, 682794863439784300));\n    }\n\n    function afterInitialize(uint256 initialX, uint256 initialY) external override returns (uint256, uint256) {\n        slots[0] = BASE_FEE; slots[1] = BASE_FEE; slots[3] = WAD; \n        slots[5] = initialX > 0 ? wdiv(initialY, initialX) : 100 * WAD;\n        slots[6] = 950000000000000; slots[7] = 800000000000000000; slots[8] = 2000000000000000;\n        slots[15] = 400000000000000000 | (uint256(2000000000000000) << 160); slots[13] = 902500000000; slots[14] = slots[5]; \n        return (BASE_FEE, BASE_FEE);\n    }\n\n    function afterSwap(TradeInfo calldata trade) external override returns (uint256, uint256) {\n        uint256 prevBidFee = slots[0]; uint256 prevAskFee = slots[1]; uint256 lastTs = uint64(slots[2]);\n        uint256 dirState = slots[3]; uint256 actEma = slots[4]; uint256 pHat = slots[5];\n        uint256 packedSigma = slots[6]; uint256 sigmaHat = uint80(packedSigma); uint256 lambdaHat = slots[7]; uint256 sizeHat = slots[8];\n        uint256 toxEma = slots[9]; uint256 stepTradeCount = slots[10];\n\n        uint256 sigmaForFast = sigmaHat;\n        uint256 fastHat = slots[14];\n        uint256 uncertainty = slots[13];\n        uint256 silent = trade.timestamp > lastTs ? trade.timestamp - lastTs : 0;\n        bool isNewStep = trade.timestamp > lastTs;\n        if (isNewStep) {\n            uint256 elapsedRaw = trade.timestamp - lastTs;\n            uint256 elapsed = elapsedRaw > ELAPSED_CAP ? ELAPSED_CAP : elapsedRaw;\n            dirState = _decayCentered(dirState, DIR_DECAY, elapsed);\n            actEma = wmul(actEma, _powWad(ACT_DECAY, elapsed));\n            sizeHat = wmul(sizeHat, _powWad(SIZE_DECAY, elapsed));\n            toxEma = wmul(toxEma, _powWad(TOX_DECAY, elapsed));\n            if (stepTradeCount > 0 && elapsedRaw > 0) {\n                uint256 lambdaInst = (stepTradeCount * WAD) / elapsedRaw;\n                if (lambdaInst > LAMBDA_CAP) lambdaInst = LAMBDA_CAP;\n                lambdaHat = wmul(lambdaHat, LAMBDA_DECAY) + wmul(lambdaInst, WAD - LAMBDA_DECAY);\n            }\n            // Process variance is propagated inside the censored update.\n            if (uncertainty > 100000000000000) uncertainty = 100000000000000;\n            stepTradeCount = 0;\n        }\n\n        bool firstInStep = stepTradeCount == 0;\n        uint256 spot = trade.reserveX > 0 ? wdiv(trade.reserveY, trade.reserveX) : pHat;\n        if (pHat == 0) pHat = spot;\n\n        uint256 feeUsed = trade.isBuy ? prevBidFee : prevAskFee;\n        uint256 gamma = feeUsed < WAD ? WAD - feeUsed : 0;\n        uint256 pImplied;\n        if (gamma == 0) { pImplied = spot; }\n        else { pImplied = trade.isBuy ? wmul(spot, gamma) : wdiv(spot, gamma); }\n\n        // S: infer a no-trade interval center from the last post-trade spot.\n        uint256 silenceScale = WAD;\n        if (firstInStep && silent > 1) {\n            uint256 g = silent - 1;\n            if (g > 1) g = 1;\n            uint256 w = WAD - _powWad(800000000000000000, g);\n            uint256 s = slots[2] >> 64;\n            if (s == 0) s = pHat;\n            uint256 c = (wmul(s, WAD - prevBidFee) + wdiv(s, WAD - prevAskFee)) / 2;\n            if (c >= pHat) pHat += wmul(w, c - pHat);\n            else pHat -= wmul(w, pHat - c);\n            silenceScale = WAD - wmul(300000000000000000, w);\n        }\n\n        {\n            uint256 ret = pHat > 0 ? wdiv(absDiff(pImplied, pHat), pHat) : 0;\n            uint256 alpha = firstInStep ? PHAT_ALPHA : PHAT_ALPHA_RETAIL;\n            uint256 prePhat = pHat;\n            bool secondPrint = !firstInStep && stepTradeCount == 1;\n            bool sameDir = false; bool oppDir = false;\n            if (secondPrint) {\n                bool up2 = pImplied >= pHat;\n                uint256 d1 = slots[12];\n                if (d1 != 0) { sameDir = (d1 == 1) == up2; oppDir = !sameDir; }\n                if (sameDir) alpha = PHAT_ALPHA_SAME;\n            }\n            if (firstInStep) { slots[12] = pImplied >= pHat ? 1 : 2; }\n            uint256 adaptiveGate = wmul(_anchorSigma(sigmaHat, packedSigma), GATE_SIGMA_MULT);\n            if (adaptiveGate < MIN_GATE) adaptiveGate = MIN_GATE;\n            alpha = wmul(alpha, silenceScale);\n            adaptiveGate = wmul(adaptiveGate, silenceScale);\n            if (ret <= adaptiveGate) { pHat = wmul(pHat, WAD - alpha) + wmul(pImplied, alpha); }\n            if (oppDir && REVERT_U > 0) {\n                uint256 pre = slots[11];\n                if (pre > pHat) pHat = pHat + wmul(pre - pHat, REVERT_U);\n                else pHat = pHat - wmul(pHat - pre, REVERT_U);\n            }\n            if (firstInStep) {\n                if (ret > RET_CAP) ret = RET_CAP;\n                sigmaHat = wmul(sigmaHat, SIGMA_DECAY) + wmul(ret, WAD - SIGMA_DECAY);\n                if (682794863439784300 > 0) {\n                    uint256 count = uint32(packedSigma >> 160);\n                    uint256 mean = uint80(packedSigma >> 80);\n                    if (count < 5377) count++;\n                    if (sigmaHat >= mean) mean += (sigmaHat - mean) / count;\n                    else mean -= (mean - sigmaHat) / count;\n                    packedSigma = (mean << 80) | (count << 160);\n                }\n\n            }\n        }\n\n        // Interior retail routing equalizes fee-adjusted marginal prices.\n        // Subsequent trades in a step cannot be the initial arbitrage trade.\n        if (!firstInStep && feeUsed > 30 * BPS && gamma > 0) {\n            uint256 normalSpot = trade.isBuy\n                ? wdiv(wmul(spot, gamma), WAD - 30 * BPS)\n                : wdiv(wmul(spot, WAD - 30 * BPS), gamma);\n            pHat = wmul(pHat, 90 * WAD / 100) + wmul(normalSpot, 10 * WAD / 100);\n        }\n\n        // Censored assumed-density posterior. No external or future inputs.\n        uint256 arbProbability;\n        (fastHat, uncertainty, arbProbability) = _posterior(PosteriorInput(\n            fastHat, uncertainty, pImplied, spot, slots[2] >> 64,\n            prevBidFee, prevAskFee, firstInStep, silent, trade.isBuy,\n            trade.reserveY > 0 ? wdiv(trade.amountY, trade.reserveY) : 0\n        ));\n        slots[13] = uncertainty;\n        slots[14] = fastHat;\n        uint256 tradeRatio = trade.reserveY > 0 ? wdiv(trade.amountY, trade.reserveY) : 0;\n        if (tradeRatio > TRADE_RATIO_CAP) tradeRatio = TRADE_RATIO_CAP;\n\n        if (tradeRatio > SIGNAL_THRESHOLD) {\n            uint256 push = tradeRatio * DIR_IMPACT_MULT;\n            if (push > WAD / 4) push = WAD / 4;\n            if (trade.isBuy) {\n                dirState = dirState + push;\n                if (dirState > 2 * WAD) dirState = 2 * WAD;\n            } else {\n                dirState = dirState > push ? dirState - push : 0;\n            }\n            actEma = wmul(actEma, ACT_BLEND_DECAY) + wmul(tradeRatio, WAD - ACT_BLEND_DECAY);\n            sizeHat = wmul(sizeHat, SIZE_BLEND_DECAY) + wmul(tradeRatio, WAD - SIZE_BLEND_DECAY);\n            if (sizeHat > WAD) sizeHat = WAD;\n        }\n\n        uint256 tox = pHat > 0 ? wdiv(absDiff(spot, pHat), pHat) : 0;\n        if (tox > TOX_CAP) tox = TOX_CAP;\n        toxEma = wmul(toxEma, TOX_BLEND_DECAY) + wmul(tox, WAD - TOX_BLEND_DECAY);\n        uint256 toxSignal = toxEma;\n\n        stepTradeCount = stepTradeCount + 1;\n        if (stepTradeCount > STEP_COUNT_CAP) stepTradeCount = STEP_COUNT_CAP;\n\n        uint256 originalLambda = lambdaHat; uint256 originalSize = sizeHat;\n\n        if (342406799193418304 > 0) {\n            uint256 packedFlow = slots[15];\n            uint256 rate = uint80(packedFlow);\n            uint256 count = uint80(packedFlow >> 80);\n            uint256 meanSize = uint80(packedFlow >> 160);\n            if (rate == 0) rate = 400000000000000000;\n            if (meanSize == 0) meanSize = 2000000000000000;\n            if (isNewStep) {\n                uint256 inst = count / silent;\n                if (inst > 3 * WAD) inst = 3 * WAD;\n                uint256 retention = _powWad(999000000000000000, silent > 64 ? 64 : silent);\n                rate = wmul(rate, retention) + wmul(inst, WAD-retention);\n                count = 0;\n            }\n            uint256 weight = firstInStep ? WAD-arbProbability : WAD;\n            uint256 correctedWeight = weight;\n            if (2 == 2) {\n                uint256 missing = wmul(feeUsed, 196030880396139429888);\n                if (missing > 333333333333333376) missing = 333333333333333376;\n                correctedWeight = wdiv(weight, WAD-missing);\n            }\n            count += correctedWeight;\n            uint256 learning = wmul(WAD-999000000000000000, weight);\n            meanSize = _blend(meanSize, tradeRatio, learning);\n            slots[15]=rate | (count << 80) | (meanSize << 160);\n            uint256 retailRate = wmul(rate, 366383424913407168);\n            uint256 retailSize = 2 == 0 ? sizeHat : wmul(meanSize,1883296158119298304);\n            lambdaHat = _blend(lambdaHat,retailRate,342406799193418304);\n            sizeHat = _blend(sizeHat,retailSize,342406799193418304);\n        }\n        uint256 flowSize = wmul(lambdaHat, sizeHat);\n        uint256 fBase = BASE_FEE + wmul(SIGMA_COEF, _anchorSigma(sigmaHat, packedSigma)) + wmul(LAMBDA_COEF, lambdaHat) + wmul(FLOW_SIZE_COEF, flowSize);\n        uint256 fMid = fBase + wmul(TOX_COEF, toxSignal) + wmul(TOX_QUAD_COEF, wmul(toxSignal, toxSignal)) + wmul(ACT_COEF, actEma);\n        fMid = fMid + wmul(SIGMA_TOX_COEF, wmul(_anchorSigma(sigmaHat, packedSigma), toxSignal));\n\n        lambdaHat = originalLambda; sizeHat = originalSize;\n        uint256 dirDev; bool sellPressure;\n        if (dirState >= WAD) { dirDev = dirState - WAD; sellPressure = true; }\n        else { dirDev = WAD - dirState; sellPressure = false; }\n\n        uint256 skew = wmul(DIR_COEF, dirDev) + wmul(DIR_TOX_COEF, wmul(dirDev, toxSignal));\n        uint256 bidFee; uint256 askFee;\n        if (sellPressure) {\n            bidFee = fMid + skew;\n            askFee = fMid > skew ? fMid - skew : 0;\n        } else {\n            askFee = fMid + skew;\n            bidFee = fMid > skew ? fMid - skew : 0;\n        }\n\n        {\n            uint256 staleHat = wmul(pHat, 700000000000000000) + wmul(fastHat, 300000000000000000);\n            uint256 staleTox = wdiv(absDiff(spot, staleHat), staleHat);\n            if (staleTox > TOX_CAP) staleTox = TOX_CAP;\n            uint256 staleShift = wmul(STALE_DIR_COEF, staleTox);\n            uint256 attractShift = wmul(staleShift, STALE_ATTRACT_FRAC);\n            if (spot >= staleHat) {\n                bidFee = bidFee + staleShift;\n                askFee = askFee > attractShift ? askFee - attractShift : 0;\n            } else {\n                askFee = askFee + staleShift;\n                bidFee = bidFee > attractShift ? bidFee - attractShift : 0;\n            }\n        }\n\n        {\n            bool tradeAligned = (trade.isBuy && spot >= pHat) || (!trade.isBuy && spot < pHat);\n            if (tradeAligned) {\n                uint256 tradeBoost = wmul(TRADE_TOX_BOOST, tradeRatio);\n                if (!firstInStep && tradeBoost > 16 * BPS) tradeBoost = 16 * BPS;\n                if (trade.isBuy) { bidFee = bidFee + tradeBoost; }\n                else { askFee = askFee + tradeBoost; }\n            }\n        }\n\n        if (sellPressure) {\n            bidFee = clampFee(_compressTailWithSlope(bidFee, TAIL_SLOPE_PROTECT));\n            askFee = clampFee(_compressTailWithSlope(askFee, TAIL_SLOPE_ATTRACT));\n        } else {\n            askFee = clampFee(_compressTailWithSlope(askFee, TAIL_SLOPE_PROTECT));\n            bidFee = clampFee(_compressTailWithSlope(bidFee, TAIL_SLOPE_ATTRACT));\n        }\n\n        if (firstInStep) {\n            if (askFee > bidFee && bidFee > 30 * BPS) bidFee = 30 * BPS;\n            else if (bidFee > askFee && askFee > 30 * BPS) askFee = 30 * BPS;\n        }\n\n        if (bidFee > askFee && askFee > 36 * BPS) askFee = 36 * BPS;\n        else if (askFee > bidFee && bidFee > 36 * BPS) bidFee = 36 * BPS;\n\n        slots[0] = bidFee; slots[1] = askFee; slots[2] = (spot << 64) | trade.timestamp;\n        slots[3] = dirState; slots[4] = actEma; slots[5] = pHat;\n        slots[6] = sigmaHat | (682794863439784300 > 0 ? (packedSigma & ~uint256(type(uint80).max)) : 0); slots[7] = lambdaHat; slots[8] = sizeHat;\n        slots[9] = toxEma; slots[10] = stepTradeCount;\n\n        return (bidFee, askFee);\n    }\n\n\n    struct PosteriorInput {\n        uint256 mu; uint256 v; uint256 obs; uint256 spot; uint256 preSpot;\n        uint256 bid; uint256 ask; bool first; uint256 silent; bool buy; uint256 size;\n    }\n    function _posterior(PosteriorInput memory x) internal pure returns (uint256, uint256, uint256) {\n        if (x.mu == 0) x.mu = x.spot;\n        if (x.v < 10000000000) x.v = 10000000000;\n        uint256 lo = wmul(x.preSpot, WAD-x.bid);\n        uint256 hi = wdiv(x.preSpot, WAD-x.ask);\n        if (x.first) {\n            if (x.silent>1 && x.preSpot>0) {\n                uint256 elapsed=x.silent>8?8:x.silent;\n                x.v += 902500000000*(elapsed-1);\n                (x.mu,x.v)=_band(x.mu,x.v,lo,hi);\n            }\n            x.v+=902500000000;\n        }\n        uint256 mRetail = x.mu;\n        uint256 vRetail = x.v;\n        // A missing own-pool trade is a censored price observation.\n        if (x.first && x.preSpot > 0) {\n            (mRetail, vRetail) = _band(x.mu, x.v, lo, hi);\n        }\n        if (!x.first) {\n            // A later print is retail. Only an interior route is an observation\n            // of the other pool, with explicit observation uncertainty.\n            uint256 fee = x.buy ? x.bid : x.ask;\n            if (fee > 30 * BPS) {\n                uint256 normal = x.buy ? wdiv(wmul(x.spot, WAD-fee), WAD-30*BPS)\n                    : wdiv(wmul(x.spot, WAD-30*BPS), WAD-fee);\n                uint256 residual = wdiv(absDiff(normal, x.mu),x.mu);\n                uint256 noise = 9000000000000 + wmul(residual,residual);\n                uint256 k = wdiv(x.v,x.v+noise);\n                return (_blend(x.mu,normal,k),wmul(x.v,WAD-k),0);\n            }\n            return (x.mu,x.v,0);\n        }\n        uint256 e = wdiv(absDiff(x.obs,x.mu),x.mu);\n        uint256 totalV = x.v + 22500000000;\n        uint256 z = wdiv(wmul(e,e),totalV);\n        uint256 density = _powWad(wdiv(WAD,WAD+z/8),4);\n        uint256 odds = wmul(density,wdiv(4000000000000000,_isqrt(totalV*WAD)));\n        if (x.size > 3000000000000000) odds = wmul(odds,4*WAD/10);\n        if (x.silent > 1) odds = wmul(odds,8*WAD/10);\n        uint256 sd = _isqrt(x.v*WAD);\n        uint256 width = wdiv(hi-lo,x.mu);\n        uint256 distance = x.mu<lo?lo-x.mu:(x.mu>hi?x.mu-hi:0);\n        uint256 zBand = wdiv(wdiv(distance,x.mu),sd);\n        uint256 mass = wmul(wdiv(width,width+2*sd),wdiv(WAD,WAD+wmul(zBand,zBand)));\n        if (mass < WAD/100) mass = WAD/100;\n        odds = wdiv(odds,mass);\n        uint256 prob = wdiv(odds,WAD+odds);\n        uint256 kArb = wdiv(x.v,totalV);\n        uint256 mArb = _blend(x.mu,x.obs,kArb);\n        uint256 mean = _blend(mRetail,mArb,prob);\n        uint256 between = wdiv(absDiff(mArb,mRetail),x.mu);\n        uint256 variance = wmul(prob,wmul(x.v,WAD-kArb)) + wmul(WAD-prob,vRetail)\n            + wmul(wmul(prob,WAD-prob),wmul(between,between));\n        if (variance > 100000000000000) variance = 100000000000000;\n        return (mean,variance,prob);\n    }\n    function _blend(uint256 a,uint256 b,uint256 w) internal pure returns(uint256) {\n        return b>=a ? a+wmul(b-a,w) : a-wmul(a-b,w);\n    }\n    function _band(uint256 mu,uint256 v,uint256 lo,uint256 hi) internal pure returns(uint256,uint256) {\n        // Soft interval likelihood avoids discontinuities at quadrature nodes.\n        uint256 sd=wmul(mu,_isqrt(v*WAD));\n        uint256[3] memory acc;\n        for(uint256 j=0;j<7;j++) {\n            uint256 p=j<3 ? (mu>(3-j)*sd?mu-(3-j)*sd:1) : mu+(j-3)*sd;\n            uint256 w=j==3?72:(j==2||j==4?45:(j==1||j==5?10:1));\n            uint256 distance=p<lo?lo-p:(p>hi?p-hi:0);\n            uint256 z=sd>0?wdiv(distance,sd):0;\n            uint256 likelihood=wdiv(WAD,WAD+4*wmul(z,z));\n            w=wmul(w*WAD,likelihood);\n            acc[0]+=w;acc[1]+=wmul(w,p);\n            uint256 d=wdiv(absDiff(p,mu),mu);\n            acc[2]+=wmul(w,wmul(d,d));\n        }\n        uint256 m=wdiv(acc[1],acc[0]);\n        uint256 d=wdiv(absDiff(m,mu),mu);\n        uint256 second=wdiv(acc[2],acc[0]);\n        return(m,second>wmul(d,d)?second-wmul(d,d):10000000000);\n    }\n\n    function _compressTailWithSlope(uint256 fee, uint256 slope) internal pure returns (uint256) {\n        if (fee <= TAIL_KNEE) return fee;\n        return TAIL_KNEE + wmul(fee - TAIL_KNEE, slope);\n    }\n\n    function _powWad(uint256 factor, uint256 exp) internal pure returns (uint256 result) {\n        result = WAD;\n        while (exp > 0) {\n            if (exp & 1 == 1) result = wmul(result, factor);\n            factor = wmul(factor, factor);\n            exp >>= 1;\n        }\n    }\n\n    function _decayCentered(uint256 centered, uint256 decayFactor, uint256 elapsed) internal pure returns (uint256) {\n        uint256 mul = _powWad(decayFactor, elapsed);\n        if (centered >= WAD) { return WAD + wmul(centered - WAD, mul); }\n        uint256 below = wmul(WAD - centered, mul);\n        return below < WAD ? WAD - below : 0;\n    }\n\n    // Floor square root: bit-length seed and seven Newton steps (all uint256).\n    function _isqrt(uint256 x) internal pure returns (uint256 r) {\n        if (x == 0) return 0;\n        unchecked {\n            uint256 y = x;\n            r = 1;\n            if (y >> 128 != 0) { y >>= 128; r <<= 64; }\n            if (y >> 64 != 0) { y >>= 64; r <<= 32; }\n            if (y >> 32 != 0) { y >>= 32; r <<= 16; }\n            if (y >> 16 != 0) { y >>= 16; r <<= 8; }\n            if (y >> 8 != 0) { y >>= 8; r <<= 4; }\n            if (y >> 4 != 0) { y >>= 4; r <<= 2; }\n            if (y >> 2 != 0) { r <<= 1; }\n            r = (r + x / r) >> 1;\n            r = (r + x / r) >> 1;\n            r = (r + x / r) >> 1;\n            r = (r + x / r) >> 1;\n            r = (r + x / r) >> 1;\n            r = (r + x / r) >> 1;\n            r = (r + x / r) >> 1;\n            uint256 t = x / r;\n            return r < t ? r : t;\n        }\n    }\n\n    function getName() external pure override returns (string memory) { return \"censored_10\"; }\n}\n","sha256":"014ad7bd0e6f412183ab5c0ee1560bbe30182b35b10f18d62464f1df0909cfca","blocked":null,"valid":true,"seeds":{"start":5110000,"end":5111999,"inclusive":true,"n":2000},"vs_stack":{"paired":{"n":2000,"mean_diff":0.4326617415841387,"se":0.016018464814032993,"worst":[{"seed":5110779,"d":-3.115284773603207},{"seed":5111216,"d":-2.428966438662769},{"seed":5111019,"d":-1.7063754613100173},{"seed":5110298,"d":-1.669915916443074},{"seed":5110209,"d":-1.635230367990971}],"sum_d":865.3234831682774,"sum_d2":1400.2440428248951},"retail_edge_delta":{"mean":0.6712794037879084,"se":0.015822130731917662,"n":2000,"sum_d":1342.558807575817,"sum_d2":1902.0906798494775},"arb_edge_delta":{"mean":-0.2386176622037679,"se":0.007611986143929041,"n":2000,"sum_d":-477.2353244075358,"sum_d2":345.5302249865431},"reconciliation_max_abs":1.7053025658242404e-13},"gas":{"max_ok":205159,"init_max_ok":243121,"oog":0,"other_halts":0,"raw_counters":[{"role":"Baseline","callback":"afterInitialize","calls":2000,"ok":2000,"max_ok_gas":21796,"sum_ok_gas":43592000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"afterSwap","calls":21512729,"ok":21512729,"max_ok_gas":22592,"sum_ok_gas":485390671972,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"getName","calls":2000,"ok":2000,"max_ok_gas":21526,"sum_ok_gas":43052000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterInitialize","calls":2000,"ok":2000,"max_ok_gas":243121,"sum_ok_gas":486242000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterSwap","calls":20488747,"ok":20488747,"max_ok_gas":205159,"sum_ok_gas":2451122917983,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"getName","calls":2000,"ok":2000,"max_ok_gas":21629,"sum_ok_gas":43258000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0}]},"per_arm":{"candidate":{"sha256":"014ad7bd0e6f412183ab5c0ee1560bbe30182b35b10f18d62464f1df0909cfca","n":2000,"mean_edge":525.9593804362675,"mean_retail_edge":553.451808340245,"mean_arb_edge":-27.492427903977465,"gas":{"max_ok":205159,"init_max_ok":243121,"oog":0,"other_halts":0,"raw_counters":[{"role":"Baseline","callback":"afterInitialize","calls":2000,"ok":2000,"max_ok_gas":21796,"sum_ok_gas":43592000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"afterSwap","calls":21512729,"ok":21512729,"max_ok_gas":22592,"sum_ok_gas":485390671972,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"getName","calls":2000,"ok":2000,"max_ok_gas":21526,"sum_ok_gas":43052000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterInitialize","calls":2000,"ok":2000,"max_ok_gas":243121,"sum_ok_gas":486242000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterSwap","calls":20488747,"ok":20488747,"max_ok_gas":205159,"sum_ok_gas":2451122917983,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"getName","calls":2000,"ok":2000,"max_ok_gas":21629,"sum_ok_gas":43258000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0}]}},"R":{"sha256":"f24b6ca198b744c380842c3a17964a6dc21f311bb04984b26733afa3fee8eaf2","n":2000,"mean_edge":525.8450803081262,"mean_retail_edge":553.1483026839692,"mean_arb_edge":-27.303222375843106,"gas":{"max_ok":203354,"init_max_ok":243099,"oog":0,"other_halts":0,"raw_counters":[{"role":"Baseline","callback":"afterInitialize","calls":2000,"ok":2000,"max_ok_gas":21796,"sum_ok_gas":43592000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"afterSwap","calls":21362520,"ok":21362520,"max_ok_gas":22592,"sum_ok_gas":482001628800,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"getName","calls":2000,"ok":2000,"max_ok_gas":21526,"sum_ok_gas":43052000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterInitialize","calls":2000,"ok":2000,"max_ok_gas":243099,"sum_ok_gas":486198000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterSwap","calls":20698714,"ok":20698714,"max_ok_gas":203354,"sum_ok_gas":2438308530853,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"getName","calls":2000,"ok":2000,"max_ok_gas":21607,"sum_ok_gas":43214000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0}]}},"K":{"sha256":"2eaafc7960e520b8a7fd322ec8afaff8fa677c730228a961efb509cc30b25719","n":2000,"mean_edge":525.5267186946833,"mean_retail_edge":552.780528936457,"mean_arb_edge":-27.253810241773696,"gas":{"max_ok":214017,"init_max_ok":220962,"oog":0,"other_halts":0,"raw_counters":[{"role":"Baseline","callback":"afterInitialize","calls":2000,"ok":2000,"max_ok_gas":21796,"sum_ok_gas":43592000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"afterSwap","calls":21465058,"ok":21465058,"max_ok_gas":22592,"sum_ok_gas":484315386116,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"getName","calls":2000,"ok":2000,"max_ok_gas":21526,"sum_ok_gas":43052000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterInitialize","calls":2000,"ok":2000,"max_ok_gas":220962,"sum_ok_gas":441924000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterSwap","calls":20670702,"ok":20670702,"max_ok_gas":214017,"sum_ok_gas":2034570537160,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"getName","calls":2000,"ok":2000,"max_ok_gas":21576,"sum_ok_gas":43152000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0}]}}},"calibration":{"mean":525.5258821780834,"valid":true,"raw_counters":[{"role":"Baseline","callback":"afterInitialize","calls":1000,"ok":1000,"max_ok_gas":21796,"sum_ok_gas":21796000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"afterSwap","calls":10741746,"ok":10741746,"max_ok_gas":22592,"sum_ok_gas":242365461576,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Baseline","callback":"getName","calls":1000,"ok":1000,"max_ok_gas":21526,"sum_ok_gas":21526000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterInitialize","calls":1000,"ok":1000,"max_ok_gas":185532,"sum_ok_gas":185532000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"afterSwap","calls":10445223,"ok":10445223,"max_ok_gas":151647,"sum_ok_gas":811927105393,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0},{"role":"Submission","callback":"getName","calls":1000,"ok":1000,"max_ok_gas":21530,"sum_ok_gas":21530000,"oog":0,"revert":0,"other_halt":0,"tx_error":0,"bad_return":0}]},"freeze":{"hashes":{"R":"f24b6ca198b744c380842c3a17964a6dc21f311bb04984b26733afa3fee8eaf2","K":"2eaafc7960e520b8a7fd322ec8afaff8fa677c730228a961efb509cc30b25719","candidate":"014ad7bd0e6f412183ab5c0ee1560bbe30182b35b10f18d62464f1df0909cfca"},"seeds":[5110000,5111999],"n":2000,"time":1794194897.2979536,"harness_sha256":"b8a1e110d746241c7201c95dd7e519f1388efffe7eaa0badeda30c3474e2447b","runner_sha256":"49370b314adae95f621180e3aaf5c97dac2113ed947b202da458510d4c9a48a3"},"harness_source":"\"\"\"Run from the pinned amm-challenge checkout, with the brief's environment active.\npython harness.py --start 5000000 --n 2000 --out measured.json candidate.sol STACK.sol\nDo not use confirmation seeds to choose or change a strategy.\n\"\"\"\nimport argparse,hashlib,json,math\nfrom pathlib import Path\nimport numpy as np\nimport amm_sim_rs as sim\nfrom amm_competition.evm.compiler import SolidityCompiler\n\n\ndef configs(start,n):\n    configs=[]\n    for seed in range(start,start+n):\n        rng=np.random.default_rng(seed)\n        size=rng.uniform(19.,21.)\n        rate=rng.uniform(.6,1.)\n        sigma=rng.uniform(.000882,.001008)\n        configs.append(sim.SimulationConfig(n_steps=10000,initial_price=100.,\n            initial_x=100.,initial_y=10000.,gbm_mu=0.,gbm_sigma=sigma,gbm_dt=1.,\n            retail_arrival_rate=rate,retail_mean_size=size,retail_size_sigma=1.2,\n            retail_buy_prob=.5,seed=seed))\n    return configs\n\n\ndef decomposition(r,initial_fee=.0004):\n    # Fees are outside reserves, so k stays fixed up to floating-point roundoff.\n    # The arb acts before retail, using the preceding step's final spot and fees.\n    steps=r.steps\n    fair=np.array([s.fair_price for s in steps])\n    spots=np.array([r.initial_fair_price]+[s.spot_prices['submission'] for s in steps[:-1]])\n    bids=np.array([initial_fee]+[s.fees['submission'][0] for s in steps[:-1]])\n    asks=np.array([initial_fee]+[s.fees['submission'][1] for s in steps[:-1]])\n    x0,y0=r.initial_reserves['submission'];k=x0*y0\n    x=np.sqrt(k/spots);y=np.sqrt(k*spots)\n    ga=1-asks;gb=1-bids\n    out=np.minimum(np.maximum(x-np.sqrt(k/(ga*fair)),0),.99*x)\n    paid=(k/(x-out)-y)/ga\n    buyprofit=np.where(out>0,np.maximum(out*fair-paid,0),0)\n    gross=np.maximum((np.sqrt(k*gb/fair)-x)/gb,0)\n    received=y-k/(x+gb*gross)\n    sellprofit=np.where(gross>0,np.maximum(received-gross*fair,0),0)\n    arb=-float(np.sum(np.where(spots<fair,buyprofit,sellprofit)))\n    return arb,r.edges['submission']-arb\n\n\ndef aggregate(chunks):\n    out={}\n    for chunk in chunks:\n        for row in chunk['raw']:\n            key=(row['role'],row['callback'])\n            dest=out.setdefault(key,{'role':row['role'],'callback':row['callback']})\n            for k,v in row.items():\n                if k in ['role','callback']:continue\n                dest[k]=max(dest.get(k,0),v) if k=='max_ok_gas' else dest.get(k,0)+v\n    return list(out.values())\n\n\ndef run(source,start,n,vanilla,compiler):\n    compiled=compiler.compile(source)\n    assert compiled.success,compiled.errors\n    rows=[];chunks=[]\n    for first in range(start,start+n,20):\n        count=min(20,start+n-first)\n        sim.gas_stats_reset()\n        batch=sim.run_batch(list(compiled.bytecode),list(vanilla),configs(first,count),8)\n        results=batch.results\n        assert sorted(r.seed for r in results)==list(range(first,first+count))\n        for r in results:\n            arb,retail=decomposition(r)\n            rows.append({'seed':r.seed,'edge':r.edges['submission'],'arb':arb,'retail':retail})\n        chunks.append({'start':first,'raw':sim.gas_stats()})\n        del results,batch\n    return {'sha256':hashlib.sha256(source.encode()).hexdigest(),'rows':rows,\n            'raw_counters':aggregate(chunks),'chunks':chunks}\n\n\ndef stats(d):\n    d=np.asarray(d,dtype=float)\n    return {'mean':float(d.mean()),'se':float(d.std(ddof=1)/np.sqrt(len(d)))}\n\n\ndef compare(candidate,stack):\n    a={r['seed']:r for r in candidate['rows']};b={r['seed']:r for r in stack['rows']}\n    assert a.keys()==b.keys()\n    seeds=sorted(a)\n    d=np.array([a[s]['edge']-b[s]['edge'] for s in seeds])\n    arb=np.array([a[s]['arb']-b[s]['arb'] for s in seeds])\n    retail=np.array([a[s]['retail']-b[s]['retail'] for s in seeds])\n    assert np.max(np.abs(d-arb-retail))<1e-8\n    summary=stats(d)\n    return {'paired':{'n':len(d),'mean_diff':summary['mean'],'se':summary['se'],\n                'worst':[{'seed':seeds[i],'d':float(d[i])} for i in np.argsort(d)[:5]]},\n            'retail_edge_delta':stats(retail),'arb_edge_delta':stats(arb),\n            'reconciliation_max_abs':float(np.max(np.abs(d-arb-retail)))}\n\n\nif __name__=='__main__':\n    p=argparse.ArgumentParser()\n    p.add_argument('--start',type=int,required=True);p.add_argument('--n',type=int,required=True)\n    p.add_argument('--out',required=True);p.add_argument('candidate');p.add_argument('stack')\n    args=p.parse_args()\n    compiler=SolidityCompiler()\n    vanilla=compiler.compile(Path('contracts/src/VanillaStrategy.sol').read_text(),'VanillaStrategy')\n    assert vanilla.success,vanilla.errors\n    candidate=run(Path(args.candidate).read_text(),args.start,args.n,vanilla.bytecode,compiler)\n    stack=run(Path(args.stack).read_text(),args.start,args.n,vanilla.bytecode,compiler)\n    out=compare(candidate,stack);out.update(candidate=candidate,stack=stack)\n    errors=['oog','revert','other_halt','tx_error','bad_return']\n    out['valid']=all(not any(row.get(e,0) for e in errors)\n        for arm in [candidate,stack] for row in arm['raw_counters'])\n    Path(args.out).write_text(json.dumps(out,allow_nan=False))\n    print(json.dumps({k:v for k,v in out.items() if k not in ['candidate','stack']}))\n","confirmation_source":"import json, hashlib, urllib.request, time\nfrom pathlib import Path\nimport numpy as np\nimport harness as h\np=Path('scratch')\nexpected={'R':'f24b6ca198b744c380842c3a17964a6dc21f311bb04984b26733afa3fee8eaf2','K':'2eaafc7960e520b8a7fd322ec8afaff8fa677c730228a961efb509cc30b25719','candidate':'014ad7bd0e6f412183ab5c0ee1560bbe30182b35b10f18d62464f1df0909cfca'}\nfor name,digest in expected.items(): assert hashlib.sha256((p/(name+'.sol')).read_bytes()).hexdigest()==digest\nmeta=json.loads((p/'H.json').read_text())\nch=urllib.request.urlopen(meta['calibration']['source']).read().decode()\n(p/'CH.sol').write_text(ch)\ncompiler=h.SolidityCompiler()\nvanilla=compiler.compile(Path('contracts/src/VanillaStrategy.sol').read_text(),'VanillaStrategy')\nassert vanilla.success,vanilla.errors\nerrors=['oog','revert','other_halt','tx_error','bad_return']\ndef run(name,start,n):\n source=(p/(name+'.sol')).read_text(); rows=[];chunks=[]\n for first in range(start,start+n,20):\n  out=h.run(source,first,min(20,start+n-first),vanilla.bytecode,compiler)\n  rows.extend(out['rows']);chunks.extend(out['chunks'])\n  print(name,first,'elapsed',round(time.monotonic()-t,1),flush=True)\n result={'sha256':out['sha256'],'rows':rows,'chunks':chunks,'raw_counters':h.aggregate(chunks)}\n (p/(name+'-measured.json')).write_text(json.dumps(result,allow_nan=False))\n return result\nt=time.monotonic()\ncal=run('CH',0,1000)\nmean=float(np.mean([r['edge'] for r in cal['rows']]))\nvalid=abs(mean-525.5258821780834)<=1e-6 and all(not any(r.get(e,0) for e in errors) for r in cal['raw_counters'])\n(p/'calibration-result.json').write_text(json.dumps({'mean':mean,'valid':valid,'raw_counters':cal['raw_counters']}))\nassert valid, 'calibration failed'\n(p/'freeze.json').write_text(json.dumps({'hashes':expected,'seeds':[5110000,5111999],'n':2000,'time':time.time(),'harness_sha256':hashlib.sha256((p/'harness.py').read_bytes()).hexdigest(),'runner_sha256':hashlib.sha256(Path(__file__).read_bytes()).hexdigest()}))\nfor name in ['candidate','R','K']: run(name,5110000,2000)\nprint('COMPLETE',flush=True)\n","report_source":"import json,hashlib,math\nfrom pathlib import Path\nimport numpy as np\nimport harness as h\np=Path('scratch'); dest=Path('../../../artifacts/goal/batches/e09-confirm-sigma/items/b')\nload=lambda name: json.loads((p/name).read_text())\narms={k:load(k+'-measured.json') for k in ['candidate','R','K']}\nerrors=['oog','revert','other_halt','tx_error','bad_return']\ndef gas(a):\n rows=a['raw_counters']\n return {'max_ok':max((r['max_ok_gas'] for r in rows if r['role']=='Submission' and r['callback']=='afterSwap'),default=0),'init_max_ok':max((r['max_ok_gas'] for r in rows if r['role']=='Submission' and r['callback']=='afterInitialize'),default=0),'oog':sum(r.get('oog',0) for r in rows),'other_halts':sum(r.get(e,0) for r in rows for e in errors[1:]),'raw_counters':rows}\ndef compare(b):\n a=arms['candidate'];out=h.compare(a,b)\n aa={r['seed']:r for r in a['rows']};bb={r['seed']:r for r in b['rows']}\n for field,key in [('edge','paired'),('retail','retail_edge_delta'),('arb','arb_edge_delta')]:\n  d=np.array([aa[s][field]-bb[s][field] for s in sorted(aa)])\n  out[key].update(n=len(d),sum_d=float(d.sum()),sum_d2=float(d@d))\n return out\nfor a in arms.values():\n assert sorted(r['seed'] for r in a['rows'])==list(range(5110000,5112000))\n assert len(a['chunks'])==100\nout=compare(arms['R'])\nout.update(item='b',code=(p/'candidate.sol').read_text(),sha256=arms['candidate']['sha256'],blocked=None,valid=all(not any(r.get(e,0) for e in errors) for a in arms.values() for r in a['raw_counters']),seeds={'start':5110000,'end':5111999,'inclusive':True,'n':2000},vs_stack=compare(arms['K']),gas=gas(arms['candidate']),per_arm={k:{'sha256':a['sha256'],'n':len(a['rows']),'mean_edge':float(np.mean([r['edge'] for r in a['rows']])),'mean_retail_edge':float(np.mean([r['retail'] for r in a['rows']])),'mean_arb_edge':float(np.mean([r['arb'] for r in a['rows']])),'gas':gas(a)} for k,a in arms.items()},calibration=load('calibration-result.json'),freeze=load('freeze.json'),harness_source=(p/'harness.py').read_text(),confirmation_source=(p/'confirm.py').read_text(),report_source=Path(__file__).read_text(),setup_source=(p/'setup.sh').read_text(),commands=['git clone https://github.com/benedictbrady/amm-challenge checkout','cd checkout && git checkout 6b6921f8d463314aa7c96234e1be25a25245f704','Save setup_source as scratch/setup.sh; run sh scratch/setup.sh once.','Fetch the four artifact JSON URLs in source_urls into scratch/{R,H,K,candidate}.json; extract code verbatim to .sol for R,K,candidate and H.harness_source to scratch/harness.py.','Save confirmation_source to scratch/confirm.py. Run . scratch/env.sh && python scratch/confirm.py','Save report_source to scratch/report.py, runtime as scratch/runtime.json, and compiler_cache_source as scratch/solc-cache-wrapper.py; adjust dest to the desired output directory. Run . scratch/env.sh && python scratch/report.py'],notes=['paired is candidate minus RS2 (R); vs_stack is candidate minus STACK (K).','Each strategy alone against VanillaStrategy, 8 workers, chunks of 20; no fresh-seed retries, tuning or selection.','SE uses sample SD divided by sqrt(n); worst lists five smallest paired differences.','Retail/arb decomposition is supplied H.harness_source decomposition with initial fee 0.0004, validated against all arms initial fee.','Raw gas counters include submission and Vanilla; max_ok and init_max_ok select submission callbacks separately.','Measurements are local; no leaderboard placement is claimed.'])\nids={'R':'19f2ec857df536e8ab62ab1da89ec6623332521ce46849f15bccff402c63e1e5','H':'26cb8e86f05170308de2a4b24821ac7fad2a17077f8d94af6e0f31985343fe89','K':'c33720874aa1285e9dc766540b8a90410118a8e8b840d949ea0dcc211bdb27c1','candidate':'9045cab1f8a51e8f1c6a4c2c93daa2b2f0d9bd274a68de064a1167c079c2a8b4'}\nout['runtime']=load('runtime.json')\nout['commands'].append('For the observed runtime versions, after setup run . scratch/env.sh && uv pip install numpy==2.5.4 py-solc-x==2.1.0 pyrevm==0.3.7 before confirmation.')\nout['compiler_cache_source']=(p/'solc-cache-wrapper.py').read_text()\nout['compiler_cache_note']='During candidate confirmation, after approximately seed 5110320, solc-v0.8.24 was renamed to solc-v0.8.24.real and replaced by this response cache wrapper. Cache keys cover all compiler arguments and input bytes. Only successful compiler responses are cached. No simulation results are cached; no seeds were rerun. The same confirmation_source reproduces the measurements with or without this compile-only optimization.'\nout['source_urls']={k:'https://api.imdnotdead.fun/artifacts/'+v for k,v in ids.items()}\nsources=[]\nfor k,url in out['source_urls'].items():\n quote=load(k+'.json')['sha256'];assert quote in (p/(k+'.json')).read_text();sources.append({'url':url,'quote':quote})\nsources.append({'url':load('H.json')['calibration']['source'],'quote':'uint256 constant BASE_FEE = 4 * BPS;'})\nsources.extend([{'url':'https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/simulation/engine.rs','quote':'Some(seed + 1),'},{'url':'https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py','quote':'rng = np.random.default_rng(seed=i)'}])\ntext=json.dumps(out,allow_nan=False,separators=(',',':'));assert len(text.encode())<=64000,len(text.encode())\ndest.mkdir(parents=True,exist_ok=True);(dest/'result.json').write_text(text);(dest/'sources.json').write_text(json.dumps({'sources':sources}))\nprint(json.dumps({k:v for k,v in out.items() if k in ['valid','paired','vs_stack','retail_edge_delta','arb_edge_delta','gas','calibration']},indent=2));print('bytes',len(text.encode()))\n","setup_source":"set -eu;R=$PWD/scratch;mkdir -p $R/tmp $R/bin $R/solcx\necho \"export TMPDIR=$R/tmp XDG_CACHE_HOME=$R/xc UV_CACHE_DIR=$R/uvc UV_PYTHON_INSTALL_DIR=$R/uvpy SOLCX_BINARY_PATH=$R/solcx VIRTUAL_ENV=$PWD/.venv PATH=$PWD/.venv/bin:$R/bin:\\$PATH\" >$R/env.sh;. $R/env.sh\ncommand -v uv >/dev/null||{ curl -LsSf https://github.com/astral-sh/uv/releases/latest/download/uv-x86_64-unknown-linux-gnu.tar.gz|tar --no-same-owner -xz -C $R/tmp;cp $R/tmp/uv-*/uv $R/bin/;}\nW=amm_sim_rs-0.1.0.post1-cp310-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl;curl -LsSf https://github.com/gtmcknight/amm-sim/releases/download/sim-6b6921f8/$W -o $R/$W\necho \"aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a  $R/$W\"|sha256sum -c -\nuv venv --python 3.12 .venv;uv pip install $R/$W numpy py-solc-x==2.1.0 pyrevm==0.3.7;uv pip install --no-deps -e .\npython -c \"import solcx;solcx.install_solc('0.8.24')\"\namm-match validate contracts/src/StarterStrategy.sol\n","commands":["git clone https://github.com/benedictbrady/amm-challenge checkout","cd checkout && git checkout 6b6921f8d463314aa7c96234e1be25a25245f704","Save setup_source as scratch/setup.sh; run sh scratch/setup.sh once.","Fetch the four artifact JSON URLs in source_urls into scratch/{R,H,K,candidate}.json; extract code verbatim to .sol for R,K,candidate and H.harness_source to scratch/harness.py.","Save confirmation_source to scratch/confirm.py. Run . scratch/env.sh && python scratch/confirm.py","Save report_source to scratch/report.py, runtime as scratch/runtime.json, and compiler_cache_source as scratch/solc-cache-wrapper.py; adjust dest to the desired output directory. Run . scratch/env.sh && python scratch/report.py","For the observed runtime versions, after setup run . scratch/env.sh && uv pip install numpy==2.5.4 py-solc-x==2.1.0 pyrevm==0.3.7 before confirmation."],"notes":["paired is candidate minus RS2 (R); vs_stack is candidate minus STACK (K).","Each strategy alone against VanillaStrategy, 8 workers, chunks of 20; no fresh-seed retries, tuning or selection.","SE uses sample SD divided by sqrt(n); worst lists five smallest paired differences.","Retail/arb decomposition is supplied H.harness_source decomposition with initial fee 0.0004, validated against all arms initial fee.","Raw gas counters include submission and Vanilla; max_ok and init_max_ok select submission callbacks separately.","Measurements are local; no leaderboard placement is claimed."],"runtime":{"python":"3.12.3","packages":{"numpy":"2.5.4","py-solc-x":"2.1.0","pyrevm":"0.3.7","amm-sim-rs":"0.1.0.post1","amm-challenge":"0.1.0"},"solc_version":"0.8.24","solc_binary_sha256":"fb03a29a517452b9f12bcf459ef37d0a543765bb3bbc911e70a87d6a37c30d5f","wheel_sha256":"aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a"},"compiler_cache_source":"#!/usr/bin/python3\nimport hashlib, pathlib, subprocess, sys\npath=pathlib.Path(__file__).resolve()\nreal=str(path)+'.real'\nif '--standard-json' not in sys.argv:\n sys.exit(subprocess.call([real]+sys.argv[1:]))\ndata=sys.stdin.buffer.read()\nkey=hashlib.sha256(repr(sys.argv[1:]).encode()+b'\\0'+data).hexdigest()\ncache=path.parent/('response-'+key)\nif cache.exists():\n sys.stdout.buffer.write(cache.read_bytes());sys.exit(0)\nr=subprocess.run([real]+sys.argv[1:],input=data,stdout=subprocess.PIPE,stderr=subprocess.PIPE)\nif r.returncode==0:\n temp=cache.with_suffix('.tmp');temp.write_bytes(r.stdout);temp.replace(cache)\nsys.stdout.buffer.write(r.stdout);sys.stderr.buffer.write(r.stderr);sys.exit(r.returncode)\n","compiler_cache_note":"During candidate confirmation, after approximately seed 5110320, solc-v0.8.24 was renamed to solc-v0.8.24.real and replaced by this response cache wrapper. Cache keys cover all compiler arguments and input bytes. Only successful compiler responses are cached. No simulation results are cached; no seeds were rerun. The same confirmation_source reproduces the measurements with or without this compile-only optimization.","source_urls":{"R":"https://api.imdnotdead.fun/artifacts/19f2ec857df536e8ab62ab1da89ec6623332521ce46849f15bccff402c63e1e5","H":"https://api.imdnotdead.fun/artifacts/26cb8e86f05170308de2a4b24821ac7fad2a17077f8d94af6e0f31985343fe89","K":"https://api.imdnotdead.fun/artifacts/c33720874aa1285e9dc766540b8a90410118a8e8b840d949ea0dcc211bdb27c1","candidate":"https://api.imdnotdead.fun/artifacts/9045cab1f8a51e8f1c6a4c2c93daa2b2f0d9bd274a68de064a1167c079c2a8b4"}}