{"abstract":"Demand-responsive meter rate adjustment returns a wrong result when the sample guard only rejects empty data.","category":"Toll and parking fee computation","checks":8,"contract":"Input {rate, occupancy: hourly percentages, hi, lo, step, min_rate, max_rate, min_samples}. With fewer than min_samples samples the rate is unchanged. Otherwise the exact mean occupancy above hi raises the rate by step, below lo lowers it by step; the result is always clamped to [min_rate, max_rate].","evaluation_group":"w2-toll_and_parking_fee_computation-demand-meter-rate","failed_approach":"The inclusive guard also rejects blocks with exactly the minimum number of samples.","family":"w2-toll_and_parking_fee_computation-demand-meter-rate-sample-guard","id":"FA-68776","implementations":{"attempt":{"sha256":"6e52e0b130cb060f21f2df0e652be6a0735d38ff1ae881e976f1a9c6cd5339ed","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(x):\n    occ = x['occupancy']\n    if len(occ) <= x['min_samples']:\n        return x['rate']\n    avg = Fraction(sum(occ), len(occ))\n    r = x['rate']\n    if avg > x['hi']:\n        r += x['step']\n    elif avg < x['lo']:\n        r -= x['step']\n    return max(x['min_rate'], min(x['max_rate'], r))\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[({'rate': 300, 'occupancy': [60, 59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 275), ({'rate': 225, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 2}, 225), ({'rate': 125, 'occupancy': [], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 2}, 125), ({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 400, 'occupancy': [81, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 450), ({'rate': 800, 'occupancy': [80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 800), ({'rate': 800, 'occupancy': [81, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 800), ({'rate': 300, 'occupancy': [80, 80], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300)], [({'rate': 300, 'occupancy': [80, 80], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 400, 'occupancy': [80, 60, 60, 63, 99, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 400), ({'rate': 300, 'occupancy': [90, 90], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 325), ({'rate': 50, 'occupancy': [80, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 50), ({'rate': 350, 'occupancy': [59, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 600, 'min_samples': 2}, 325), ({'rate': 75, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 75), ({'rate': 775, 'occupancy': [59, 80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 775)], [({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 125, 'occupancy': [81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 125), ({'rate': 725, 'occupancy': [], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 700, 'min_samples': 3}, 725), ({'rate': 300, 'occupancy': [60, 59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 275), ({'rate': 400, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 400), ({'rate': 525, 'occupancy': [60, 59, 80, 81, 66], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 525), ({'rate': 175, 'occupancy': [81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 3}, 175), ({'rate': 300, 'occupancy': [90, 90], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 325)], [({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 150, 'occupancy': [81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 150), ({'rate': 775, 'occupancy': [97, 60, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 600), ({'rate': 650, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 650), ({'rate': 300, 'occupancy': [80, 80], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 300, 'occupancy': [60, 59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 275), ({'rate': 725, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 725), ({'rate': 325, 'occupancy': [83, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 325)], [({'rate': 425, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 425), ({'rate': 800, 'occupancy': [70, 70, 70], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 600), ({'rate': 475, 'occupancy': [59, 71, 81, 59, 80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 2}, 475), ({'rate': 200, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 200), ({'rate': 375, 'occupancy': [60, 81, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 2}, 375), ({'rate': 350, 'occupancy': [81, 59, 80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 350), ({'rate': 300, 'occupancy': [80, 81], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 325), ({'rate': 25, 'occupancy': [61], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 25)]]\nfor i, (args, expected) in enumerate(fixtures[N-1]):\n    check('fee oracle' + ' %d' % i, solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"acc1ec9ec6a60126be8b75d0489d9b2220f58e637bbc019e3527cd40d021052e","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(x):\n    occ = x['occupancy']\n    if not occ:\n        return x['rate']\n    avg = Fraction(sum(occ), len(occ))\n    r = x['rate']\n    if avg > x['hi']:\n        r += x['step']\n    elif avg < x['lo']:\n        r -= x['step']\n    return max(x['min_rate'], min(x['max_rate'], r))\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[({'rate': 300, 'occupancy': [60, 59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 275), ({'rate': 225, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 2}, 225), ({'rate': 125, 'occupancy': [], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 2}, 125), ({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 400, 'occupancy': [81, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 450), ({'rate': 800, 'occupancy': [80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 800), ({'rate': 800, 'occupancy': [81, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 800), ({'rate': 300, 'occupancy': [80, 80], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300)], [({'rate': 300, 'occupancy': [80, 80], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 400, 'occupancy': [80, 60, 60, 63, 99, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 400), ({'rate': 300, 'occupancy': [90, 90], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 325), ({'rate': 50, 'occupancy': [80, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 50), ({'rate': 350, 'occupancy': [59, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 600, 'min_samples': 2}, 325), ({'rate': 75, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 75), ({'rate': 775, 'occupancy': [59, 80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 775)], [({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 125, 'occupancy': [81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 125), ({'rate': 725, 'occupancy': [], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 700, 'min_samples': 3}, 725), ({'rate': 300, 'occupancy': [60, 59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 275), ({'rate': 400, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 400), ({'rate': 525, 'occupancy': [60, 59, 80, 81, 66], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 525), ({'rate': 175, 'occupancy': [81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 3}, 175), ({'rate': 300, 'occupancy': [90, 90], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 325)], [({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 150, 'occupancy': [81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 150), ({'rate': 775, 'occupancy': [97, 60, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 600), ({'rate': 650, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 650), ({'rate': 300, 'occupancy': [80, 80], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 300, 'occupancy': [60, 59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 275), ({'rate': 725, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 725), ({'rate': 325, 'occupancy': [83, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 325)], [({'rate': 425, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 425), ({'rate': 800, 'occupancy': [70, 70, 70], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 600), ({'rate': 475, 'occupancy': [59, 71, 81, 59, 80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 2}, 475), ({'rate': 200, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 200), ({'rate': 375, 'occupancy': [60, 81, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 2}, 375), ({'rate': 350, 'occupancy': [81, 59, 80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 350), ({'rate': 300, 'occupancy': [80, 81], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 325), ({'rate': 25, 'occupancy': [61], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 25)]]\nfor i, (args, expected) in enumerate(fixtures[N-1]):\n    check('fee oracle' + ' %d' % i, solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"fixed":{"sha256":"5b1ddafd9f3356c678b78543468c976293f4c6070354ea7fad47f841f3f85394","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(x):\n    occ = x['occupancy']\n    if len(occ) < x['min_samples']:\n        return x['rate']\n    avg = Fraction(sum(occ), len(occ))\n    r = x['rate']\n    if avg > x['hi']:\n        r += x['step']\n    elif avg < x['lo']:\n        r -= x['step']\n    return max(x['min_rate'], min(x['max_rate'], r))\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[({'rate': 300, 'occupancy': [60, 59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 275), ({'rate': 225, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 2}, 225), ({'rate': 125, 'occupancy': [], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 2}, 125), ({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 400, 'occupancy': [81, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 450), ({'rate': 800, 'occupancy': [80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 800), ({'rate': 800, 'occupancy': [81, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 800), ({'rate': 300, 'occupancy': [80, 80], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300)], [({'rate': 300, 'occupancy': [80, 80], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 400, 'occupancy': [80, 60, 60, 63, 99, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 400), ({'rate': 300, 'occupancy': [90, 90], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 325), ({'rate': 50, 'occupancy': [80, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 50), ({'rate': 350, 'occupancy': [59, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 600, 'min_samples': 2}, 325), ({'rate': 75, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 75), ({'rate': 775, 'occupancy': [59, 80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 775)], [({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 125, 'occupancy': [81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 125), ({'rate': 725, 'occupancy': [], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 700, 'min_samples': 3}, 725), ({'rate': 300, 'occupancy': [60, 59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 275), ({'rate': 400, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 400), ({'rate': 525, 'occupancy': [60, 59, 80, 81, 66], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 525), ({'rate': 175, 'occupancy': [81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 3}, 175), ({'rate': 300, 'occupancy': [90, 90], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 325)], [({'rate': 300, 'occupancy': [60, 60, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 150, 'occupancy': [81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 3}, 150), ({'rate': 775, 'occupancy': [97, 60, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 600), ({'rate': 650, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 650), ({'rate': 300, 'occupancy': [80, 80], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 300), ({'rate': 300, 'occupancy': [60, 59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 275), ({'rate': 725, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 725), ({'rate': 325, 'occupancy': [83, 60], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 325)], [({'rate': 425, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 100, 'max_rate': 600, 'min_samples': 3}, 425), ({'rate': 800, 'occupancy': [70, 70, 70], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 3}, 600), ({'rate': 475, 'occupancy': [59, 71, 81, 59, 80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 50, 'max_rate': 700, 'min_samples': 2}, 475), ({'rate': 200, 'occupancy': [59], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 200), ({'rate': 375, 'occupancy': [60, 81, 81], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 600, 'min_samples': 2}, 375), ({'rate': 350, 'occupancy': [81, 59, 80], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 350), ({'rate': 300, 'occupancy': [80, 81], 'hi': 80, 'lo': 60, 'step': 25, 'min_rate': 50, 'max_rate': 600, 'min_samples': 2}, 325), ({'rate': 25, 'occupancy': [61], 'hi': 80, 'lo': 60, 'step': 50, 'min_rate': 100, 'max_rate': 700, 'min_samples': 2}, 25)]]\nfor i, (args, expected) in enumerate(fixtures[N-1]):\n    check('fee oracle' + ' %d' % i, solve(args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"A deterministic, bounded toy model with a stipulated contract; it makes no claim of conformance to any agency manual or standard. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-toll_and_parking_fee_computation-demand-meter-rate-sample-guard","generated_at":"2026-09-29T14:48:05.463776+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Fee engines bill customers in integer cents; a wrong boundary, rounding stage or cap scope silently over- or under-charges.","repair":"Restore the insufficient samples rule so that the step reads `if len(occ) < x['min_samples']:`.","root_cause":"Blocks with one or two samples still get adjusted.","sha256":"6bf43d410dd155c54ed9d6040620c60bea3d75992dc81290c01277c5d2b97217","title":"Demand-responsive meter rate adjustment: the sample guard only rejects empty data · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":44.52,"exit_code":1,"observations":[{"actual":300,"check":"fee oracle 0","expected":275,"passed":false},{"actual":225,"check":"fee oracle 1","expected":225,"passed":true},{"actual":125,"check":"fee oracle 2","expected":125,"passed":true},{"actual":300,"check":"fee oracle 3","expected":300,"passed":true},{"actual":400,"check":"fee oracle 4","expected":450,"passed":false},{"actual":800,"check":"fee oracle 5","expected":800,"passed":true},{"actual":800,"check":"fee oracle 6","expected":800,"passed":true},{"actual":300,"check":"fee oracle 7","expected":300,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"fee oracle 0\", \"actual\": 300, \"expected\": 275, \"passed\": false}, {\"check\": \"fee oracle 1\", \"actual\": 225, \"expected\": 225, \"passed\": true}, {\"check\": \"fee oracle 2\", \"actual\": 125, \"expected\": 125, \"passed\": true}, {\"check\": \"fee oracle 3\", \"actual\": 300, \"expected\": 300, \"passed\": true}, {\"check\": \"fee oracle 4\", \"actual\": 400, \"expected\": 450, \"passed\": false}, {\"check\": \"fee oracle 5\", \"actual\": 800, \"expected\": 800, \"passed\": true}, {\"check\": \"fee oracle 6\", \"actual\": 800, \"expected\": 800, \"passed\": true}, {\"check\": \"fee oracle 7\", \"actual\": 300, \"expected\": 300, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":46.31,"exit_code":1,"observations":[{"actual":275,"check":"fee oracle 0","expected":275,"passed":true},{"actual":175,"check":"fee oracle 1","expected":225,"passed":false},{"actual":125,"check":"fee oracle 2","expected":125,"passed":true},{"actual":300,"check":"fee oracle 3","expected":300,"passed":true},{"actual":450,"check":"fee oracle 4","expected":450,"passed":true},{"actual":600,"check":"fee oracle 5","expected":800,"passed":false},{"actual":700,"check":"fee oracle 6","expected":800,"passed":false},{"actual":300,"check":"fee oracle 7","expected":300,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"fee oracle 0\", \"actual\": 275, \"expected\": 275, \"passed\": true}, {\"check\": \"fee oracle 1\", \"actual\": 175, \"expected\": 225, \"passed\": false}, {\"check\": \"fee oracle 2\", \"actual\": 125, \"expected\": 125, \"passed\": true}, {\"check\": \"fee oracle 3\", \"actual\": 300, \"expected\": 300, \"passed\": true}, {\"check\": \"fee oracle 4\", \"actual\": 450, \"expected\": 450, \"passed\": true}, {\"check\": \"fee oracle 5\", \"actual\": 600, \"expected\": 800, \"passed\": false}, {\"check\": \"fee oracle 6\", \"actual\": 700, \"expected\": 800, \"passed\": false}, {\"check\": \"fee oracle 7\", \"actual\": 300, \"expected\": 300, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":45.513,"exit_code":0,"observations":[{"actual":275,"check":"fee oracle 0","expected":275,"passed":true},{"actual":225,"check":"fee oracle 1","expected":225,"passed":true},{"actual":125,"check":"fee oracle 2","expected":125,"passed":true},{"actual":300,"check":"fee oracle 3","expected":300,"passed":true},{"actual":450,"check":"fee oracle 4","expected":450,"passed":true},{"actual":800,"check":"fee oracle 5","expected":800,"passed":true},{"actual":800,"check":"fee oracle 6","expected":800,"passed":true},{"actual":300,"check":"fee oracle 7","expected":300,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"fee oracle 0\", \"actual\": 275, \"expected\": 275, \"passed\": true}, {\"check\": \"fee oracle 1\", \"actual\": 225, \"expected\": 225, \"passed\": true}, {\"check\": \"fee oracle 2\", \"actual\": 125, \"expected\": 125, \"passed\": true}, {\"check\": \"fee oracle 3\", \"actual\": 300, \"expected\": 300, \"passed\": true}, {\"check\": \"fee oracle 4\", \"actual\": 450, \"expected\": 450, \"passed\": true}, {\"check\": \"fee oracle 5\", \"actual\": 800, \"expected\": 800, \"passed\": true}, {\"check\": \"fee oracle 6\", \"actual\": 800, \"expected\": 800, \"passed\": true}, {\"check\": \"fee oracle 7\", \"actual\": 300, \"expected\": 300, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}