{"abstract":"Exact package multiples and zero usage are billed an extra package.","category":"Subscription proration billing","checks":8,"contract":"Input {events in milli-units, free units, div (units per package), round up|down, price per package}. Units = ceil(sum(events)/1000) once per invoice. Billable = max(0, units - free). Packages = ceil or floor(billable/div) by round. Return [units, packages, packages*price].","evaluation_group":"w2-subscription-proration-package-quantity-rounding","failed_approach":"The attempt uses round() on a half-shifted float, which rounds exact multiples to even and still adds packages.","family":"w2-subscription-proration-package-quantity-rounding-round-up-packaging","id":"FA-59821","implementations":{"attempt":{"sha256":"091cc678d94506a3a50b64e1d1f6f5d064f4cbe7c1e32b8248147d29d2f81761","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    milli = sum(x['events'])\n    units = -(-milli // 1000)\n    billable = max(0, units - x['free'])\n    if x['round'] == 'up':\n        packs = round(billable / x['div'] + 0.5)\n    else:\n        packs = billable // x['div']\n    return [units, packs, packs * x['price']]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'events': [1000, 1000, 919, 1000, 4033], 'free': 5, 'div': 1, 'round': 'up', 'price': 250}, [8, 3, 750]), ('regression', {'events': [1000, 452], 'free': 5, 'div': 100, 'round': 'up', 'price': 999}, [2, 0, 0]), ('partial-repair probe', {'events': [673, 4210, 1000, 3643], 'free': 5, 'div': 5, 'round': 'up', 'price': 250}, [10, 1, 250]), ('partial-repair probe', {'events': [3529, 608], 'free': 0, 'div': 5, 'round': 'up', 'price': 250}, [5, 1, 250]), ('normal control', {'events': [4863, 300, 2484, 893, 1000, 741], 'free': 10, 'div': 5, 'round': 'down', 'price': 999}, [11, 0, 0]), ('normal control', {'events': [1332, 1000, 3819, 645, 1000, 333], 'free': 0, 'div': 10, 'round': 'up', 'price': 250}, [9, 1, 250]), ('normal control', {'events': [35, 1000, 2766, 1000, 937], 'free': 0, 'div': 10, 'round': 'up', 'price': 100}, [6, 1, 100]), ('normal control', {'events': [1000, 1000, 577, 2375], 'free': 10, 'div': 1, 'round': 'down', 'price': 250}, [5, 0, 0])], [('regression', {'events': [673, 4210, 1000, 3643], 'free': 5, 'div': 5, 'round': 'up', 'price': 250}, [10, 1, 250]), ('regression', {'events': [], 'free': 10, 'div': 100, 'round': 'up', 'price': 100}, [0, 0, 0]), ('partial-repair probe', {'events': [3529, 608], 'free': 0, 'div': 5, 'round': 'up', 'price': 250}, [5, 1, 250]), ('partial-repair probe', {'events': [982, 260, 2668, 1000, 3988, 800], 'free': 0, 'div': 10, 'round': 'up', 'price': 999}, [10, 1, 999]), ('normal control', {'events': [1000], 'free': 10, 'div': 100, 'round': 'down', 'price': 999}, [1, 0, 0]), ('normal control', {'events': [4706], 'free': 5, 'div': 10, 'round': 'down', 'price': 250}, [5, 0, 0]), ('normal control', {'events': [1000], 'free': 10, 'div': 10, 'round': 'down', 'price': 999}, [1, 0, 0]), ('normal control', {'events': [3902, 1000, 1000, 2138, 771, 1712], 'free': 0, 'div': 10, 'round': 'up', 'price': 100}, [11, 2, 200])], [('regression', {'events': [3529, 608], 'free': 0, 'div': 5, 'round': 'up', 'price': 250}, [5, 1, 250]), ('regression', {'events': [460, 1000], 'free': 10, 'div': 100, 'round': 'up', 'price': 100}, [2, 0, 0]), ('partial-repair probe', {'events': [880, 518, 41, 3687, 1000, 180], 'free': 0, 'div': 1, 'round': 'up', 'price': 250}, [7, 7, 1750]), ('partial-repair probe', {'events': [4250, 1000], 'free': 5, 'div': 1, 'round': 'up', 'price': 250}, [6, 1, 250]), ('normal control', {'events': [1000], 'free': 10, 'div': 1, 'round': 'down', 'price': 999}, [1, 0, 0]), ('normal control', {'events': [576, 688, 449, 1000, 815], 'free': 0, 'div': 5, 'round': 'down', 'price': 999}, [4, 0, 0]), ('normal control', {'events': [339, 1000, 1810, 2557, 4715], 'free': 10, 'div': 100, 'round': 'down', 'price': 100}, [11, 0, 0]), ('normal control', {'events': [391, 8, 2736, 4419], 'free': 5, 'div': 100, 'round': 'up', 'price': 250}, [8, 1, 250])], [('regression', {'events': [982, 260, 2668, 1000, 3988, 800], 'free': 0, 'div': 10, 'round': 'up', 'price': 999}, [10, 1, 999]), ('regression', {'events': [716, 4530], 'free': 10, 'div': 10, 'round': 'up', 'price': 100}, [6, 0, 0]), ('partial-repair probe', {'events': [155, 3403, 470], 'free': 0, 'div': 5, 'round': 'up', 'price': 100}, [5, 1, 100]), ('partial-repair probe', {'events': [1000, 42, 2623, 1000, 3087], 'free': 5, 'div': 1, 'round': 'up', 'price': 100}, [8, 3, 300]), ('normal control', {'events': [4324, 534, 615, 25], 'free': 5, 'div': 100, 'round': 'up', 'price': 999}, [6, 1, 999]), ('normal control', {'events': [959, 514, 670, 1000], 'free': 0, 'div': 1, 'round': 'down', 'price': 250}, [4, 4, 1000]), ('normal control', {'events': [1000, 3934, 1000, 1000], 'free': 10, 'div': 100, 'round': 'down', 'price': 100}, [7, 0, 0]), ('normal control', {'events': [604, 2714, 1000, 776, 1000, 4405], 'free': 5, 'div': 5, 'round': 'up', 'price': 250}, [11, 2, 500])], [('regression', {'events': [880, 518, 41, 3687, 1000, 180], 'free': 0, 'div': 1, 'round': 'up', 'price': 250}, [7, 7, 1750]), ('regression', {'events': [321, 1000, 593, 354, 2136], 'free': 5, 'div': 100, 'round': 'up', 'price': 100}, [5, 0, 0]), ('partial-repair probe', {'events': [235, 462, 166, 353, 1000], 'free': 0, 'div': 1, 'round': 'up', 'price': 250}, [3, 3, 750]), ('partial-repair probe', {'events': [1000, 4365, 1000, 3571, 76], 'free': 0, 'div': 1, 'round': 'up', 'price': 999}, [11, 11, 10989]), ('normal control', {'events': [], 'free': 0, 'div': 10, 'round': 'down', 'price': 999}, [0, 0, 0]), ('normal control', {'events': [487, 2432, 2028, 558], 'free': 0, 'div': 10, 'round': 'up', 'price': 250}, [6, 1, 250]), ('normal control', {'events': [402], 'free': 0, 'div': 5, 'round': 'down', 'price': 100}, [1, 0, 0]), ('normal control', {'events': [1000, 679], 'free': 10, 'div': 1, 'round': 'down', 'price': 250}, [2, 0, 0])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, 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":"daf2b60237ad92e9e6766346960a419f614422979a9113ead32f6fec3782bcdd","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    milli = sum(x['events'])\n    units = -(-milli // 1000)\n    billable = max(0, units - x['free'])\n    if x['round'] == 'up':\n        packs = billable // x['div'] + 1\n    else:\n        packs = billable // x['div']\n    return [units, packs, packs * x['price']]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'events': [1000, 1000, 919, 1000, 4033], 'free': 5, 'div': 1, 'round': 'up', 'price': 250}, [8, 3, 750]), ('regression', {'events': [1000, 452], 'free': 5, 'div': 100, 'round': 'up', 'price': 999}, [2, 0, 0]), ('partial-repair probe', {'events': [673, 4210, 1000, 3643], 'free': 5, 'div': 5, 'round': 'up', 'price': 250}, [10, 1, 250]), ('partial-repair probe', {'events': [3529, 608], 'free': 0, 'div': 5, 'round': 'up', 'price': 250}, [5, 1, 250]), ('normal control', {'events': [4863, 300, 2484, 893, 1000, 741], 'free': 10, 'div': 5, 'round': 'down', 'price': 999}, [11, 0, 0]), ('normal control', {'events': [1332, 1000, 3819, 645, 1000, 333], 'free': 0, 'div': 10, 'round': 'up', 'price': 250}, [9, 1, 250]), ('normal control', {'events': [35, 1000, 2766, 1000, 937], 'free': 0, 'div': 10, 'round': 'up', 'price': 100}, [6, 1, 100]), ('normal control', {'events': [1000, 1000, 577, 2375], 'free': 10, 'div': 1, 'round': 'down', 'price': 250}, [5, 0, 0])], [('regression', {'events': [673, 4210, 1000, 3643], 'free': 5, 'div': 5, 'round': 'up', 'price': 250}, [10, 1, 250]), ('regression', {'events': [], 'free': 10, 'div': 100, 'round': 'up', 'price': 100}, [0, 0, 0]), ('partial-repair probe', {'events': [3529, 608], 'free': 0, 'div': 5, 'round': 'up', 'price': 250}, [5, 1, 250]), ('partial-repair probe', {'events': [982, 260, 2668, 1000, 3988, 800], 'free': 0, 'div': 10, 'round': 'up', 'price': 999}, [10, 1, 999]), ('normal control', {'events': [1000], 'free': 10, 'div': 100, 'round': 'down', 'price': 999}, [1, 0, 0]), ('normal control', {'events': [4706], 'free': 5, 'div': 10, 'round': 'down', 'price': 250}, [5, 0, 0]), ('normal control', {'events': [1000], 'free': 10, 'div': 10, 'round': 'down', 'price': 999}, [1, 0, 0]), ('normal control', {'events': [3902, 1000, 1000, 2138, 771, 1712], 'free': 0, 'div': 10, 'round': 'up', 'price': 100}, [11, 2, 200])], [('regression', {'events': [3529, 608], 'free': 0, 'div': 5, 'round': 'up', 'price': 250}, [5, 1, 250]), ('regression', {'events': [460, 1000], 'free': 10, 'div': 100, 'round': 'up', 'price': 100}, [2, 0, 0]), ('partial-repair probe', {'events': [880, 518, 41, 3687, 1000, 180], 'free': 0, 'div': 1, 'round': 'up', 'price': 250}, [7, 7, 1750]), ('partial-repair probe', {'events': [4250, 1000], 'free': 5, 'div': 1, 'round': 'up', 'price': 250}, [6, 1, 250]), ('normal control', {'events': [1000], 'free': 10, 'div': 1, 'round': 'down', 'price': 999}, [1, 0, 0]), ('normal control', {'events': [576, 688, 449, 1000, 815], 'free': 0, 'div': 5, 'round': 'down', 'price': 999}, [4, 0, 0]), ('normal control', {'events': [339, 1000, 1810, 2557, 4715], 'free': 10, 'div': 100, 'round': 'down', 'price': 100}, [11, 0, 0]), ('normal control', {'events': [391, 8, 2736, 4419], 'free': 5, 'div': 100, 'round': 'up', 'price': 250}, [8, 1, 250])], [('regression', {'events': [982, 260, 2668, 1000, 3988, 800], 'free': 0, 'div': 10, 'round': 'up', 'price': 999}, [10, 1, 999]), ('regression', {'events': [716, 4530], 'free': 10, 'div': 10, 'round': 'up', 'price': 100}, [6, 0, 0]), ('partial-repair probe', {'events': [155, 3403, 470], 'free': 0, 'div': 5, 'round': 'up', 'price': 100}, [5, 1, 100]), ('partial-repair probe', {'events': [1000, 42, 2623, 1000, 3087], 'free': 5, 'div': 1, 'round': 'up', 'price': 100}, [8, 3, 300]), ('normal control', {'events': [4324, 534, 615, 25], 'free': 5, 'div': 100, 'round': 'up', 'price': 999}, [6, 1, 999]), ('normal control', {'events': [959, 514, 670, 1000], 'free': 0, 'div': 1, 'round': 'down', 'price': 250}, [4, 4, 1000]), ('normal control', {'events': [1000, 3934, 1000, 1000], 'free': 10, 'div': 100, 'round': 'down', 'price': 100}, [7, 0, 0]), ('normal control', {'events': [604, 2714, 1000, 776, 1000, 4405], 'free': 5, 'div': 5, 'round': 'up', 'price': 250}, [11, 2, 500])], [('regression', {'events': [880, 518, 41, 3687, 1000, 180], 'free': 0, 'div': 1, 'round': 'up', 'price': 250}, [7, 7, 1750]), ('regression', {'events': [321, 1000, 593, 354, 2136], 'free': 5, 'div': 100, 'round': 'up', 'price': 100}, [5, 0, 0]), ('partial-repair probe', {'events': [235, 462, 166, 353, 1000], 'free': 0, 'div': 1, 'round': 'up', 'price': 250}, [3, 3, 750]), ('partial-repair probe', {'events': [1000, 4365, 1000, 3571, 76], 'free': 0, 'div': 1, 'round': 'up', 'price': 999}, [11, 11, 10989]), ('normal control', {'events': [], 'free': 0, 'div': 10, 'round': 'down', 'price': 999}, [0, 0, 0]), ('normal control', {'events': [487, 2432, 2028, 558], 'free': 0, 'div': 10, 'round': 'up', 'price': 250}, [6, 1, 250]), ('normal control', {'events': [402], 'free': 0, 'div': 5, 'round': 'down', 'price': 100}, [1, 0, 0]), ('normal control', {'events': [1000, 679], 'free': 10, 'div': 1, 'round': 'down', 'price': 250}, [2, 0, 0])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, 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":"34726787d2d4eab6dd31b8f1ebb55c262b0f55c85947af0925b0e30645c4c8e9","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(x):\n    milli = sum(x['events'])\n    units = -(-milli // 1000)\n    billable = max(0, units - x['free'])\n    if x['round'] == 'up':\n        packs = -(-billable // x['div'])\n    else:\n        packs = billable // x['div']\n    return [units, packs, packs * x['price']]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression', {'events': [1000, 1000, 919, 1000, 4033], 'free': 5, 'div': 1, 'round': 'up', 'price': 250}, [8, 3, 750]), ('regression', {'events': [1000, 452], 'free': 5, 'div': 100, 'round': 'up', 'price': 999}, [2, 0, 0]), ('partial-repair probe', {'events': [673, 4210, 1000, 3643], 'free': 5, 'div': 5, 'round': 'up', 'price': 250}, [10, 1, 250]), ('partial-repair probe', {'events': [3529, 608], 'free': 0, 'div': 5, 'round': 'up', 'price': 250}, [5, 1, 250]), ('normal control', {'events': [4863, 300, 2484, 893, 1000, 741], 'free': 10, 'div': 5, 'round': 'down', 'price': 999}, [11, 0, 0]), ('normal control', {'events': [1332, 1000, 3819, 645, 1000, 333], 'free': 0, 'div': 10, 'round': 'up', 'price': 250}, [9, 1, 250]), ('normal control', {'events': [35, 1000, 2766, 1000, 937], 'free': 0, 'div': 10, 'round': 'up', 'price': 100}, [6, 1, 100]), ('normal control', {'events': [1000, 1000, 577, 2375], 'free': 10, 'div': 1, 'round': 'down', 'price': 250}, [5, 0, 0])], [('regression', {'events': [673, 4210, 1000, 3643], 'free': 5, 'div': 5, 'round': 'up', 'price': 250}, [10, 1, 250]), ('regression', {'events': [], 'free': 10, 'div': 100, 'round': 'up', 'price': 100}, [0, 0, 0]), ('partial-repair probe', {'events': [3529, 608], 'free': 0, 'div': 5, 'round': 'up', 'price': 250}, [5, 1, 250]), ('partial-repair probe', {'events': [982, 260, 2668, 1000, 3988, 800], 'free': 0, 'div': 10, 'round': 'up', 'price': 999}, [10, 1, 999]), ('normal control', {'events': [1000], 'free': 10, 'div': 100, 'round': 'down', 'price': 999}, [1, 0, 0]), ('normal control', {'events': [4706], 'free': 5, 'div': 10, 'round': 'down', 'price': 250}, [5, 0, 0]), ('normal control', {'events': [1000], 'free': 10, 'div': 10, 'round': 'down', 'price': 999}, [1, 0, 0]), ('normal control', {'events': [3902, 1000, 1000, 2138, 771, 1712], 'free': 0, 'div': 10, 'round': 'up', 'price': 100}, [11, 2, 200])], [('regression', {'events': [3529, 608], 'free': 0, 'div': 5, 'round': 'up', 'price': 250}, [5, 1, 250]), ('regression', {'events': [460, 1000], 'free': 10, 'div': 100, 'round': 'up', 'price': 100}, [2, 0, 0]), ('partial-repair probe', {'events': [880, 518, 41, 3687, 1000, 180], 'free': 0, 'div': 1, 'round': 'up', 'price': 250}, [7, 7, 1750]), ('partial-repair probe', {'events': [4250, 1000], 'free': 5, 'div': 1, 'round': 'up', 'price': 250}, [6, 1, 250]), ('normal control', {'events': [1000], 'free': 10, 'div': 1, 'round': 'down', 'price': 999}, [1, 0, 0]), ('normal control', {'events': [576, 688, 449, 1000, 815], 'free': 0, 'div': 5, 'round': 'down', 'price': 999}, [4, 0, 0]), ('normal control', {'events': [339, 1000, 1810, 2557, 4715], 'free': 10, 'div': 100, 'round': 'down', 'price': 100}, [11, 0, 0]), ('normal control', {'events': [391, 8, 2736, 4419], 'free': 5, 'div': 100, 'round': 'up', 'price': 250}, [8, 1, 250])], [('regression', {'events': [982, 260, 2668, 1000, 3988, 800], 'free': 0, 'div': 10, 'round': 'up', 'price': 999}, [10, 1, 999]), ('regression', {'events': [716, 4530], 'free': 10, 'div': 10, 'round': 'up', 'price': 100}, [6, 0, 0]), ('partial-repair probe', {'events': [155, 3403, 470], 'free': 0, 'div': 5, 'round': 'up', 'price': 100}, [5, 1, 100]), ('partial-repair probe', {'events': [1000, 42, 2623, 1000, 3087], 'free': 5, 'div': 1, 'round': 'up', 'price': 100}, [8, 3, 300]), ('normal control', {'events': [4324, 534, 615, 25], 'free': 5, 'div': 100, 'round': 'up', 'price': 999}, [6, 1, 999]), ('normal control', {'events': [959, 514, 670, 1000], 'free': 0, 'div': 1, 'round': 'down', 'price': 250}, [4, 4, 1000]), ('normal control', {'events': [1000, 3934, 1000, 1000], 'free': 10, 'div': 100, 'round': 'down', 'price': 100}, [7, 0, 0]), ('normal control', {'events': [604, 2714, 1000, 776, 1000, 4405], 'free': 5, 'div': 5, 'round': 'up', 'price': 250}, [11, 2, 500])], [('regression', {'events': [880, 518, 41, 3687, 1000, 180], 'free': 0, 'div': 1, 'round': 'up', 'price': 250}, [7, 7, 1750]), ('regression', {'events': [321, 1000, 593, 354, 2136], 'free': 5, 'div': 100, 'round': 'up', 'price': 100}, [5, 0, 0]), ('partial-repair probe', {'events': [235, 462, 166, 353, 1000], 'free': 0, 'div': 1, 'round': 'up', 'price': 250}, [3, 3, 750]), ('partial-repair probe', {'events': [1000, 4365, 1000, 3571, 76], 'free': 0, 'div': 1, 'round': 'up', 'price': 999}, [11, 11, 10989]), ('normal control', {'events': [], 'free': 0, 'div': 10, 'round': 'down', 'price': 999}, [0, 0, 0]), ('normal control', {'events': [487, 2432, 2028, 558], 'free': 0, 'div': 10, 'round': 'up', 'price': 250}, [6, 1, 250]), ('normal control', {'events': [402], 'free': 0, 'div': 5, 'round': 'down', 'price': 100}, [1, 0, 0]), ('normal control', {'events': [1000, 679], 'free': 10, 'div': 1, 'round': 'down', 'price': 250}, [2, 0, 0])]]\nfor i, (label, args, expected) in enumerate(fixtures[N-1]):\n    check(\"%s %d\" % (label, 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 teaching model of a stipulated billing rule. It makes no claim to reproduce any billing provider's exact behaviour and is not billing software. 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-subscription-proration-package-quantity-rounding-round-up-packaging","generated_at":"2026-09-29T14:46:39.830699+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Package pricing rounds usage twice, and doing either rounding at the wrong grain changes the bill.","repair":"Restore the contract rule at the round-up packaging step: use `packs = -(-billable // x['div'])`.","root_cause":"Round-up is implemented as floor plus one.","sha256":"7a7f9cd8f877be063ed5243607eac4a8f4c8e04cc7f70914fec8e813044dfe7d","title":"Package pricing with milli-unit usage: round-up packaging · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":39.838,"exit_code":1,"observations":[{"actual":[8,4,1000],"check":"regression 0","expected":[8,3,750],"passed":false},{"actual":[2,0,0],"check":"regression 1","expected":[2,0,0],"passed":true},{"actual":[10,2,500],"check":"partial-repair probe 2","expected":[10,1,250],"passed":false},{"actual":[5,2,500],"check":"partial-repair probe 3","expected":[5,1,250],"passed":false},{"actual":[11,0,0],"check":"normal control 4","expected":[11,0,0],"passed":true},{"actual":[9,1,250],"check":"normal control 5","expected":[9,1,250],"passed":true},{"actual":[6,1,100],"check":"normal control 6","expected":[6,1,100],"passed":true},{"actual":[5,0,0],"check":"normal control 7","expected":[5,0,0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [8, 4, 1000], \"expected\": [8, 3, 750], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [2, 0, 0], \"expected\": [2, 0, 0], \"passed\": true}, {\"check\": \"partial-repair probe 2\", \"actual\": [10, 2, 500], \"expected\": [10, 1, 250], \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": [5, 2, 500], \"expected\": [5, 1, 250], \"passed\": false}, {\"check\": \"normal control 4\", \"actual\": [11, 0, 0], \"expected\": [11, 0, 0], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [9, 1, 250], \"expected\": [9, 1, 250], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [6, 1, 100], \"expected\": [6, 1, 100], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [5, 0, 0], \"expected\": [5, 0, 0], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":41.503,"exit_code":1,"observations":[{"actual":[8,4,1000],"check":"regression 0","expected":[8,3,750],"passed":false},{"actual":[2,1,999],"check":"regression 1","expected":[2,0,0],"passed":false},{"actual":[10,2,500],"check":"partial-repair probe 2","expected":[10,1,250],"passed":false},{"actual":[5,2,500],"check":"partial-repair probe 3","expected":[5,1,250],"passed":false},{"actual":[11,0,0],"check":"normal control 4","expected":[11,0,0],"passed":true},{"actual":[9,1,250],"check":"normal control 5","expected":[9,1,250],"passed":true},{"actual":[6,1,100],"check":"normal control 6","expected":[6,1,100],"passed":true},{"actual":[5,0,0],"check":"normal control 7","expected":[5,0,0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [8, 4, 1000], \"expected\": [8, 3, 750], \"passed\": false}, {\"check\": \"regression 1\", \"actual\": [2, 1, 999], \"expected\": [2, 0, 0], \"passed\": false}, {\"check\": \"partial-repair probe 2\", \"actual\": [10, 2, 500], \"expected\": [10, 1, 250], \"passed\": false}, {\"check\": \"partial-repair probe 3\", \"actual\": [5, 2, 500], \"expected\": [5, 1, 250], \"passed\": false}, {\"check\": \"normal control 4\", \"actual\": [11, 0, 0], \"expected\": [11, 0, 0], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [9, 1, 250], \"expected\": [9, 1, 250], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [6, 1, 100], \"expected\": [6, 1, 100], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [5, 0, 0], \"expected\": [5, 0, 0], \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":42.249,"exit_code":0,"observations":[{"actual":[8,3,750],"check":"regression 0","expected":[8,3,750],"passed":true},{"actual":[2,0,0],"check":"regression 1","expected":[2,0,0],"passed":true},{"actual":[10,1,250],"check":"partial-repair probe 2","expected":[10,1,250],"passed":true},{"actual":[5,1,250],"check":"partial-repair probe 3","expected":[5,1,250],"passed":true},{"actual":[11,0,0],"check":"normal control 4","expected":[11,0,0],"passed":true},{"actual":[9,1,250],"check":"normal control 5","expected":[9,1,250],"passed":true},{"actual":[6,1,100],"check":"normal control 6","expected":[6,1,100],"passed":true},{"actual":[5,0,0],"check":"normal control 7","expected":[5,0,0],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression 0\", \"actual\": [8, 3, 750], \"expected\": [8, 3, 750], \"passed\": true}, {\"check\": \"regression 1\", \"actual\": [2, 0, 0], \"expected\": [2, 0, 0], \"passed\": true}, {\"check\": \"partial-repair probe 2\", \"actual\": [10, 1, 250], \"expected\": [10, 1, 250], \"passed\": true}, {\"check\": \"partial-repair probe 3\", \"actual\": [5, 1, 250], \"expected\": [5, 1, 250], \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": [11, 0, 0], \"expected\": [11, 0, 0], \"passed\": true}, {\"check\": \"normal control 5\", \"actual\": [9, 1, 250], \"expected\": [9, 1, 250], \"passed\": true}, {\"check\": \"normal control 6\", \"actual\": [6, 1, 100], \"expected\": [6, 1, 100], \"passed\": true}, {\"check\": \"normal control 7\", \"actual\": [5, 0, 0], \"expected\": [5, 0, 0], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}