{"abstract":"Every non-cashing entry appears in the payout report with 0 cents.","category":"Fantasy sports scoring","checks":7,"contract":"Daily contest entries are [entry id, score in hundredths]; payouts[r] is the prize in cents for finishing position r (0-based), positions past the list pay 0. Entries with equal scores share the positions they jointly occupy: their prizes are summed and split equally, whole cents only, with leftover cents given one each to the tied entries in ascending id order. Return id -> cents for entries receiving more than 0.","evaluation_group":"w2-fantasy-sports-scoring-contest-payout-ties","failed_approach":"Filtering on the base share drops entries whose only prize is a remainder cent.","family":"w2-fantasy-sports-scoring-contest-payout-ties-remainder-only-recipients","id":"FA-85046","implementations":{"attempt":{"sha256":"acc1ec3d8f50a2dbe904b767cdd2e38fed7ab2621987d5b2e1aa99c1e64c4e88","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(entries, payouts):\n    ordered = sorted(entries, key=lambda e: (-e[1], e[0]))\n    out = {}\n    i = 0\n    while i < len(ordered):\n        j = i\n        while j < len(ordered) and ordered[j][1] == ordered[i][1]:\n            j += 1\n        pool = sum(payouts[i:j])\n        group = sorted(e[0] for e in ordered[i:j])\n        share, extra = divmod(pool, len(group))\n        for k, eid in enumerate(group):\n            amt = share + (1 if k < extra else 0)\n            if share > 0:\n                out[eid] = amt\n        i = j\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: remainder-only recipients',\n   [[['e22', 1500], ['e06', 1497], ['e27', 1495], ['e28', 1500], ['e09', 1495], ['e02', 1493], ['e01', 1500],\n     ['e16', 1500], ['e11', 1495]],\n    [250, 100, 77]],\n   {'e01': 107, 'e16': 107, 'e22': 107, 'e28': 106}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e06', 1333], ['e19', 1328], ['e10', 1278], ['e20', 1328], ['e29', 1323], ['e11', 1333], ['e23', 1333],\n     ['e13', 1333]],\n    [1000, 501, 500, 250, 1]],\n   {'e06': 563, 'e11': 563, 'e13': 563, 'e19': 1, 'e23': 562}),\n  ('second regression',\n   [[['e15', 1413], ['e03', 1365], ['e11', 1420], ['e05', 1413], ['e02', 1410], ['e27', 1413], ['e25', 1410],\n     ['e21', 1417]],\n    [501, 500, 301, 301, 100]],\n   {'e05': 234, 'e11': 501, 'e15': 234, 'e21': 500, 'e27': 234}),\n  ('normal control 1', [[['e20', 1490], ['e24', 1500], ['e18', 1495]], [1000, 1000, 250, 2]],\n   {'e18': 1000, 'e20': 250, 'e24': 1000}),\n  ('normal control 2', [[['e03', 1490], ['e11', 1500], ['e23', 1500], ['e21', 1500]], [501, 199, 199, 2, 1]],\n   {'e03': 2, 'e11': 300, 'e21': 300, 'e23': 299}),\n  ('normal control 3', [[['e06', 1365], ['e19', 1410], ['e10', 1365]], [1000, 301, 250, 77, 77]],\n   {'e06': 276, 'e10': 275, 'e19': 1000}),\n  ('normal control 4',\n   [[['e17', 1490], ['e27', 1495], ['e23', 1490], ['e11', 1490], ['e07', 1490], ['e15', 1495], ['e21', 1490]],\n    [1000, 250, 100, 1, 1]],\n   {'e07': 21, 'e11': 21, 'e15': 625, 'e17': 20, 'e21': 20, 'e23': 20, 'e27': 625})],\n [('regression: remainder-only recipients',\n   [[['e06', 1415], ['e16', 1365], ['e12', 1415], ['e26', 1415], ['e05', 1410]], [500, 301]],\n   {'e06': 267, 'e12': 267, 'e26': 267}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e05', 1330], ['e29', 1323], ['e15', 1333], ['e28', 1326], ['e27', 1278], ['e01', 1323]],\n    [501, 500, 250, 1]],\n   {'e01': 1, 'e05': 500, 'e15': 501, 'e28': 250}),\n  ('second regression',\n   [[['e22', 1490], ['e28', 1495], ['e14', 1493], ['e13', 1500], ['e03', 1500], ['e21', 1495], ['e29', 1445]],\n    [500, 301, 100]],\n   {'e03': 401, 'e13': 400, 'e21': 50, 'e28': 50}),\n  ('normal control 1', [[['e08', 1420], ['e19', 1420], ['e17', 1413]], [501, 77, 77, 1]],\n   {'e08': 289, 'e17': 77, 'e19': 289}),\n  ('normal control 2', [[['e25', 1497], ['e13', 1490], ['e26', 1445], ['e10', 1445]], [1000, 100, 77, 2, 2]],\n   {'e10': 40, 'e13': 100, 'e25': 1000, 'e26': 39}),\n  ('normal control 3', [[['e09', 1415], ['e11', 1417], ['e04', 1417]], [199, 199, 1]],\n   {'e04': 199, 'e09': 1, 'e11': 199}),\n  ('normal control 4',\n   [[['e02', 1413], ['e21', 1417], ['e06', 1415], ['e01', 1365], ['e20', 1415]], [1000, 1000, 501, 501, 1]],\n   {'e01': 1, 'e02': 501, 'e06': 751, 'e20': 750, 'e21': 1000})],\n [('regression: remainder-only recipients',\n   [[['e09', 1490], ['e13', 1493], ['e24', 1500], ['e28', 1500], ['e02', 1445], ['e17', 1493], ['e15', 1495],\n     ['e04', 1490]],\n    [1000, 501, 301, 2, 1]],\n   {'e13': 2, 'e15': 301, 'e17': 1, 'e24': 751, 'e28': 750}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e19', 1417], ['e11', 1415], ['e18', 1420], ['e27', 1415]], [199, 1, 1]],\n   {'e11': 1, 'e18': 199, 'e19': 1}),\n  ('second regression',\n   [[['e25', 1333], ['e13', 1328], ['e01', 1333], ['e05', 1323], ['e22', 1278], ['e29', 1323], ['e08', 1326],\n     ['e15', 1333], ['e09', 1278]],\n    [301, 250, 77]],\n   {'e01': 210, 'e15': 209, 'e25': 209}),\n  ('normal control 1', [[['e01', 1417], ['e26', 1420], ['e17', 1415], ['e25', 1420]], [1000, 500, 500, 301]],\n   {'e01': 500, 'e17': 301, 'e25': 750, 'e26': 750}),\n  ('normal control 2', [[['e01', 1365], ['e10', 1417], ['e29', 1365]], [1000, 501, 250, 199]],\n   {'e01': 376, 'e10': 1000, 'e29': 375}),\n  ('normal control 3', [[['e17', 1490], ['e08', 1493], ['e03', 1500]], [1000, 501, 500, 500, 2]],\n   {'e03': 1000, 'e08': 501, 'e17': 500}),\n  ('normal control 4', [[['e05', 1333], ['e10', 1278], ['e27', 1326]], [250, 199, 77]],\n   {'e05': 250, 'e10': 77, 'e27': 199})],\n [('regression: remainder-only recipients',\n   [[['e18', 1415], ['e06', 1420], ['e21', 1410], ['e02', 1415]], [1000, 100]],\n   {'e02': 50, 'e06': 1000, 'e18': 50}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e21', 1323], ['e25', 1328], ['e06', 1328], ['e23', 1323], ['e03', 1333], ['e27', 1278], ['e01', 1330]],\n    [500, 77, 1]],\n   {'e01': 77, 'e03': 500, 'e06': 1}),\n  ('second regression',\n   [[['e02', 1415], ['e16', 1420], ['e18', 1420], ['e19', 1420], ['e09', 1420], ['e08', 1413], ['e11', 1420]],\n    [199, 100]],\n   {'e09': 60, 'e11': 60, 'e16': 60, 'e18': 60, 'e19': 59}),\n  ('normal control 1',\n   [[['e24', 1500], ['e29', 1493], ['e10', 1500], ['e21', 1500], ['e13', 1493]], [1000, 1000, 1000, 500, 2]],\n   {'e10': 1000, 'e13': 251, 'e21': 1000, 'e24': 1000, 'e29': 251}),\n  ('normal control 2', [[['e21', 1333], ['e03', 1333], ['e07', 1333]], [1000, 1000, 501, 250, 1]],\n   {'e03': 834, 'e07': 834, 'e21': 833}),\n  ('normal control 3', [[['e02', 1420], ['e25', 1413], ['e27', 1365]], [501, 500, 77, 2]],\n   {'e02': 501, 'e25': 500, 'e27': 77}),\n  ('normal control 4', [[['e20', 1445], ['e24', 1495], ['e28', 1490], ['e05', 1445]], [1000, 77, 77, 1]],\n   {'e05': 39, 'e20': 39, 'e24': 1000, 'e28': 77})],\n [('regression: remainder-only recipients',\n   [[['e13', 1365], ['e02', 1413], ['e28', 1410], ['e15', 1420], ['e10', 1420], ['e26', 1413], ['e07', 1415],\n     ['e18', 1410]],\n    [1000, 501, 500, 77]],\n   {'e02': 39, 'e07': 500, 'e10': 751, 'e15': 750, 'e26': 38}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e05', 1330], ['e09', 1330], ['e12', 1328], ['e06', 1333], ['e13', 1328], ['e25', 1326], ['e29', 1323]],\n    [199, 1]],\n   {'e05': 1, 'e06': 199}),\n  ('second regression',\n   [[['e13', 1333], ['e10', 1326], ['e21', 1333], ['e27', 1328], ['e04', 1278], ['e14', 1278], ['e23', 1323],\n     ['e28', 1323]],\n    [501, 2, 1]],\n   {'e13': 252, 'e21': 251, 'e27': 1}),\n  ('normal control 1', [[['e05', 1326], ['e26', 1278], ['e04', 1328]], [250, 199, 100, 100]],\n   {'e04': 250, 'e05': 199, 'e26': 100}),\n  ('normal control 2',\n   [[['e15', 1333], ['e27', 1333], ['e24', 1333], ['e04', 1326]], [1000, 1000, 77, 77, 2]],\n   {'e04': 77, 'e15': 693, 'e24': 692, 'e27': 692}),\n  ('normal control 3', [[['e06', 1278], ['e18', 1323], ['e10', 1333]], [500, 199, 77]],\n   {'e06': 77, 'e10': 500, 'e18': 199}),\n  ('normal control 4',\n   [[['e06', 1500], ['e03', 1445], ['e04', 1445], ['e29', 1490], ['e17', 1500]], [250, 199, 100, 100]],\n   {'e03': 50, 'e04': 50, 'e06': 225, 'e17': 224, 'e29': 100})]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, 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":"1c6cde373f43fededcb3fa8266cb465868add360ee80e2de54486a376a1f6e81","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(entries, payouts):\n    ordered = sorted(entries, key=lambda e: (-e[1], e[0]))\n    out = {}\n    i = 0\n    while i < len(ordered):\n        j = i\n        while j < len(ordered) and ordered[j][1] == ordered[i][1]:\n            j += 1\n        pool = sum(payouts[i:j])\n        group = sorted(e[0] for e in ordered[i:j])\n        share, extra = divmod(pool, len(group))\n        for k, eid in enumerate(group):\n            amt = share + (1 if k < extra else 0)\n            if amt >= 0:\n                out[eid] = amt\n        i = j\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: remainder-only recipients',\n   [[['e22', 1500], ['e06', 1497], ['e27', 1495], ['e28', 1500], ['e09', 1495], ['e02', 1493], ['e01', 1500],\n     ['e16', 1500], ['e11', 1495]],\n    [250, 100, 77]],\n   {'e01': 107, 'e16': 107, 'e22': 107, 'e28': 106}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e06', 1333], ['e19', 1328], ['e10', 1278], ['e20', 1328], ['e29', 1323], ['e11', 1333], ['e23', 1333],\n     ['e13', 1333]],\n    [1000, 501, 500, 250, 1]],\n   {'e06': 563, 'e11': 563, 'e13': 563, 'e19': 1, 'e23': 562}),\n  ('second regression',\n   [[['e15', 1413], ['e03', 1365], ['e11', 1420], ['e05', 1413], ['e02', 1410], ['e27', 1413], ['e25', 1410],\n     ['e21', 1417]],\n    [501, 500, 301, 301, 100]],\n   {'e05': 234, 'e11': 501, 'e15': 234, 'e21': 500, 'e27': 234}),\n  ('normal control 1', [[['e20', 1490], ['e24', 1500], ['e18', 1495]], [1000, 1000, 250, 2]],\n   {'e18': 1000, 'e20': 250, 'e24': 1000}),\n  ('normal control 2', [[['e03', 1490], ['e11', 1500], ['e23', 1500], ['e21', 1500]], [501, 199, 199, 2, 1]],\n   {'e03': 2, 'e11': 300, 'e21': 300, 'e23': 299}),\n  ('normal control 3', [[['e06', 1365], ['e19', 1410], ['e10', 1365]], [1000, 301, 250, 77, 77]],\n   {'e06': 276, 'e10': 275, 'e19': 1000}),\n  ('normal control 4',\n   [[['e17', 1490], ['e27', 1495], ['e23', 1490], ['e11', 1490], ['e07', 1490], ['e15', 1495], ['e21', 1490]],\n    [1000, 250, 100, 1, 1]],\n   {'e07': 21, 'e11': 21, 'e15': 625, 'e17': 20, 'e21': 20, 'e23': 20, 'e27': 625})],\n [('regression: remainder-only recipients',\n   [[['e06', 1415], ['e16', 1365], ['e12', 1415], ['e26', 1415], ['e05', 1410]], [500, 301]],\n   {'e06': 267, 'e12': 267, 'e26': 267}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e05', 1330], ['e29', 1323], ['e15', 1333], ['e28', 1326], ['e27', 1278], ['e01', 1323]],\n    [501, 500, 250, 1]],\n   {'e01': 1, 'e05': 500, 'e15': 501, 'e28': 250}),\n  ('second regression',\n   [[['e22', 1490], ['e28', 1495], ['e14', 1493], ['e13', 1500], ['e03', 1500], ['e21', 1495], ['e29', 1445]],\n    [500, 301, 100]],\n   {'e03': 401, 'e13': 400, 'e21': 50, 'e28': 50}),\n  ('normal control 1', [[['e08', 1420], ['e19', 1420], ['e17', 1413]], [501, 77, 77, 1]],\n   {'e08': 289, 'e17': 77, 'e19': 289}),\n  ('normal control 2', [[['e25', 1497], ['e13', 1490], ['e26', 1445], ['e10', 1445]], [1000, 100, 77, 2, 2]],\n   {'e10': 40, 'e13': 100, 'e25': 1000, 'e26': 39}),\n  ('normal control 3', [[['e09', 1415], ['e11', 1417], ['e04', 1417]], [199, 199, 1]],\n   {'e04': 199, 'e09': 1, 'e11': 199}),\n  ('normal control 4',\n   [[['e02', 1413], ['e21', 1417], ['e06', 1415], ['e01', 1365], ['e20', 1415]], [1000, 1000, 501, 501, 1]],\n   {'e01': 1, 'e02': 501, 'e06': 751, 'e20': 750, 'e21': 1000})],\n [('regression: remainder-only recipients',\n   [[['e09', 1490], ['e13', 1493], ['e24', 1500], ['e28', 1500], ['e02', 1445], ['e17', 1493], ['e15', 1495],\n     ['e04', 1490]],\n    [1000, 501, 301, 2, 1]],\n   {'e13': 2, 'e15': 301, 'e17': 1, 'e24': 751, 'e28': 750}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e19', 1417], ['e11', 1415], ['e18', 1420], ['e27', 1415]], [199, 1, 1]],\n   {'e11': 1, 'e18': 199, 'e19': 1}),\n  ('second regression',\n   [[['e25', 1333], ['e13', 1328], ['e01', 1333], ['e05', 1323], ['e22', 1278], ['e29', 1323], ['e08', 1326],\n     ['e15', 1333], ['e09', 1278]],\n    [301, 250, 77]],\n   {'e01': 210, 'e15': 209, 'e25': 209}),\n  ('normal control 1', [[['e01', 1417], ['e26', 1420], ['e17', 1415], ['e25', 1420]], [1000, 500, 500, 301]],\n   {'e01': 500, 'e17': 301, 'e25': 750, 'e26': 750}),\n  ('normal control 2', [[['e01', 1365], ['e10', 1417], ['e29', 1365]], [1000, 501, 250, 199]],\n   {'e01': 376, 'e10': 1000, 'e29': 375}),\n  ('normal control 3', [[['e17', 1490], ['e08', 1493], ['e03', 1500]], [1000, 501, 500, 500, 2]],\n   {'e03': 1000, 'e08': 501, 'e17': 500}),\n  ('normal control 4', [[['e05', 1333], ['e10', 1278], ['e27', 1326]], [250, 199, 77]],\n   {'e05': 250, 'e10': 77, 'e27': 199})],\n [('regression: remainder-only recipients',\n   [[['e18', 1415], ['e06', 1420], ['e21', 1410], ['e02', 1415]], [1000, 100]],\n   {'e02': 50, 'e06': 1000, 'e18': 50}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e21', 1323], ['e25', 1328], ['e06', 1328], ['e23', 1323], ['e03', 1333], ['e27', 1278], ['e01', 1330]],\n    [500, 77, 1]],\n   {'e01': 77, 'e03': 500, 'e06': 1}),\n  ('second regression',\n   [[['e02', 1415], ['e16', 1420], ['e18', 1420], ['e19', 1420], ['e09', 1420], ['e08', 1413], ['e11', 1420]],\n    [199, 100]],\n   {'e09': 60, 'e11': 60, 'e16': 60, 'e18': 60, 'e19': 59}),\n  ('normal control 1',\n   [[['e24', 1500], ['e29', 1493], ['e10', 1500], ['e21', 1500], ['e13', 1493]], [1000, 1000, 1000, 500, 2]],\n   {'e10': 1000, 'e13': 251, 'e21': 1000, 'e24': 1000, 'e29': 251}),\n  ('normal control 2', [[['e21', 1333], ['e03', 1333], ['e07', 1333]], [1000, 1000, 501, 250, 1]],\n   {'e03': 834, 'e07': 834, 'e21': 833}),\n  ('normal control 3', [[['e02', 1420], ['e25', 1413], ['e27', 1365]], [501, 500, 77, 2]],\n   {'e02': 501, 'e25': 500, 'e27': 77}),\n  ('normal control 4', [[['e20', 1445], ['e24', 1495], ['e28', 1490], ['e05', 1445]], [1000, 77, 77, 1]],\n   {'e05': 39, 'e20': 39, 'e24': 1000, 'e28': 77})],\n [('regression: remainder-only recipients',\n   [[['e13', 1365], ['e02', 1413], ['e28', 1410], ['e15', 1420], ['e10', 1420], ['e26', 1413], ['e07', 1415],\n     ['e18', 1410]],\n    [1000, 501, 500, 77]],\n   {'e02': 39, 'e07': 500, 'e10': 751, 'e15': 750, 'e26': 38}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e05', 1330], ['e09', 1330], ['e12', 1328], ['e06', 1333], ['e13', 1328], ['e25', 1326], ['e29', 1323]],\n    [199, 1]],\n   {'e05': 1, 'e06': 199}),\n  ('second regression',\n   [[['e13', 1333], ['e10', 1326], ['e21', 1333], ['e27', 1328], ['e04', 1278], ['e14', 1278], ['e23', 1323],\n     ['e28', 1323]],\n    [501, 2, 1]],\n   {'e13': 252, 'e21': 251, 'e27': 1}),\n  ('normal control 1', [[['e05', 1326], ['e26', 1278], ['e04', 1328]], [250, 199, 100, 100]],\n   {'e04': 250, 'e05': 199, 'e26': 100}),\n  ('normal control 2',\n   [[['e15', 1333], ['e27', 1333], ['e24', 1333], ['e04', 1326]], [1000, 1000, 77, 77, 2]],\n   {'e04': 77, 'e15': 693, 'e24': 692, 'e27': 692}),\n  ('normal control 3', [[['e06', 1278], ['e18', 1323], ['e10', 1333]], [500, 199, 77]],\n   {'e06': 77, 'e10': 500, 'e18': 199}),\n  ('normal control 4',\n   [[['e06', 1500], ['e03', 1445], ['e04', 1445], ['e29', 1490], ['e17', 1500]], [250, 199, 100, 100]],\n   {'e03': 50, 'e04': 50, 'e06': 225, 'e17': 224, 'e29': 100})]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, 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":"2b859324531ffd3bf531748776ce35afd23f6ec3c3d410aadc206a15d6642b41","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(entries, payouts):\n    ordered = sorted(entries, key=lambda e: (-e[1], e[0]))\n    out = {}\n    i = 0\n    while i < len(ordered):\n        j = i\n        while j < len(ordered) and ordered[j][1] == ordered[i][1]:\n            j += 1\n        pool = sum(payouts[i:j])\n        group = sorted(e[0] for e in ordered[i:j])\n        share, extra = divmod(pool, len(group))\n        for k, eid in enumerate(group):\n            amt = share + (1 if k < extra else 0)\n            if amt > 0:\n                out[eid] = amt\n        i = j\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: remainder-only recipients',\n   [[['e22', 1500], ['e06', 1497], ['e27', 1495], ['e28', 1500], ['e09', 1495], ['e02', 1493], ['e01', 1500],\n     ['e16', 1500], ['e11', 1495]],\n    [250, 100, 77]],\n   {'e01': 107, 'e16': 107, 'e22': 107, 'e28': 106}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e06', 1333], ['e19', 1328], ['e10', 1278], ['e20', 1328], ['e29', 1323], ['e11', 1333], ['e23', 1333],\n     ['e13', 1333]],\n    [1000, 501, 500, 250, 1]],\n   {'e06': 563, 'e11': 563, 'e13': 563, 'e19': 1, 'e23': 562}),\n  ('second regression',\n   [[['e15', 1413], ['e03', 1365], ['e11', 1420], ['e05', 1413], ['e02', 1410], ['e27', 1413], ['e25', 1410],\n     ['e21', 1417]],\n    [501, 500, 301, 301, 100]],\n   {'e05': 234, 'e11': 501, 'e15': 234, 'e21': 500, 'e27': 234}),\n  ('normal control 1', [[['e20', 1490], ['e24', 1500], ['e18', 1495]], [1000, 1000, 250, 2]],\n   {'e18': 1000, 'e20': 250, 'e24': 1000}),\n  ('normal control 2', [[['e03', 1490], ['e11', 1500], ['e23', 1500], ['e21', 1500]], [501, 199, 199, 2, 1]],\n   {'e03': 2, 'e11': 300, 'e21': 300, 'e23': 299}),\n  ('normal control 3', [[['e06', 1365], ['e19', 1410], ['e10', 1365]], [1000, 301, 250, 77, 77]],\n   {'e06': 276, 'e10': 275, 'e19': 1000}),\n  ('normal control 4',\n   [[['e17', 1490], ['e27', 1495], ['e23', 1490], ['e11', 1490], ['e07', 1490], ['e15', 1495], ['e21', 1490]],\n    [1000, 250, 100, 1, 1]],\n   {'e07': 21, 'e11': 21, 'e15': 625, 'e17': 20, 'e21': 20, 'e23': 20, 'e27': 625})],\n [('regression: remainder-only recipients',\n   [[['e06', 1415], ['e16', 1365], ['e12', 1415], ['e26', 1415], ['e05', 1410]], [500, 301]],\n   {'e06': 267, 'e12': 267, 'e26': 267}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e05', 1330], ['e29', 1323], ['e15', 1333], ['e28', 1326], ['e27', 1278], ['e01', 1323]],\n    [501, 500, 250, 1]],\n   {'e01': 1, 'e05': 500, 'e15': 501, 'e28': 250}),\n  ('second regression',\n   [[['e22', 1490], ['e28', 1495], ['e14', 1493], ['e13', 1500], ['e03', 1500], ['e21', 1495], ['e29', 1445]],\n    [500, 301, 100]],\n   {'e03': 401, 'e13': 400, 'e21': 50, 'e28': 50}),\n  ('normal control 1', [[['e08', 1420], ['e19', 1420], ['e17', 1413]], [501, 77, 77, 1]],\n   {'e08': 289, 'e17': 77, 'e19': 289}),\n  ('normal control 2', [[['e25', 1497], ['e13', 1490], ['e26', 1445], ['e10', 1445]], [1000, 100, 77, 2, 2]],\n   {'e10': 40, 'e13': 100, 'e25': 1000, 'e26': 39}),\n  ('normal control 3', [[['e09', 1415], ['e11', 1417], ['e04', 1417]], [199, 199, 1]],\n   {'e04': 199, 'e09': 1, 'e11': 199}),\n  ('normal control 4',\n   [[['e02', 1413], ['e21', 1417], ['e06', 1415], ['e01', 1365], ['e20', 1415]], [1000, 1000, 501, 501, 1]],\n   {'e01': 1, 'e02': 501, 'e06': 751, 'e20': 750, 'e21': 1000})],\n [('regression: remainder-only recipients',\n   [[['e09', 1490], ['e13', 1493], ['e24', 1500], ['e28', 1500], ['e02', 1445], ['e17', 1493], ['e15', 1495],\n     ['e04', 1490]],\n    [1000, 501, 301, 2, 1]],\n   {'e13': 2, 'e15': 301, 'e17': 1, 'e24': 751, 'e28': 750}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e19', 1417], ['e11', 1415], ['e18', 1420], ['e27', 1415]], [199, 1, 1]],\n   {'e11': 1, 'e18': 199, 'e19': 1}),\n  ('second regression',\n   [[['e25', 1333], ['e13', 1328], ['e01', 1333], ['e05', 1323], ['e22', 1278], ['e29', 1323], ['e08', 1326],\n     ['e15', 1333], ['e09', 1278]],\n    [301, 250, 77]],\n   {'e01': 210, 'e15': 209, 'e25': 209}),\n  ('normal control 1', [[['e01', 1417], ['e26', 1420], ['e17', 1415], ['e25', 1420]], [1000, 500, 500, 301]],\n   {'e01': 500, 'e17': 301, 'e25': 750, 'e26': 750}),\n  ('normal control 2', [[['e01', 1365], ['e10', 1417], ['e29', 1365]], [1000, 501, 250, 199]],\n   {'e01': 376, 'e10': 1000, 'e29': 375}),\n  ('normal control 3', [[['e17', 1490], ['e08', 1493], ['e03', 1500]], [1000, 501, 500, 500, 2]],\n   {'e03': 1000, 'e08': 501, 'e17': 500}),\n  ('normal control 4', [[['e05', 1333], ['e10', 1278], ['e27', 1326]], [250, 199, 77]],\n   {'e05': 250, 'e10': 77, 'e27': 199})],\n [('regression: remainder-only recipients',\n   [[['e18', 1415], ['e06', 1420], ['e21', 1410], ['e02', 1415]], [1000, 100]],\n   {'e02': 50, 'e06': 1000, 'e18': 50}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e21', 1323], ['e25', 1328], ['e06', 1328], ['e23', 1323], ['e03', 1333], ['e27', 1278], ['e01', 1330]],\n    [500, 77, 1]],\n   {'e01': 77, 'e03': 500, 'e06': 1}),\n  ('second regression',\n   [[['e02', 1415], ['e16', 1420], ['e18', 1420], ['e19', 1420], ['e09', 1420], ['e08', 1413], ['e11', 1420]],\n    [199, 100]],\n   {'e09': 60, 'e11': 60, 'e16': 60, 'e18': 60, 'e19': 59}),\n  ('normal control 1',\n   [[['e24', 1500], ['e29', 1493], ['e10', 1500], ['e21', 1500], ['e13', 1493]], [1000, 1000, 1000, 500, 2]],\n   {'e10': 1000, 'e13': 251, 'e21': 1000, 'e24': 1000, 'e29': 251}),\n  ('normal control 2', [[['e21', 1333], ['e03', 1333], ['e07', 1333]], [1000, 1000, 501, 250, 1]],\n   {'e03': 834, 'e07': 834, 'e21': 833}),\n  ('normal control 3', [[['e02', 1420], ['e25', 1413], ['e27', 1365]], [501, 500, 77, 2]],\n   {'e02': 501, 'e25': 500, 'e27': 77}),\n  ('normal control 4', [[['e20', 1445], ['e24', 1495], ['e28', 1490], ['e05', 1445]], [1000, 77, 77, 1]],\n   {'e05': 39, 'e20': 39, 'e24': 1000, 'e28': 77})],\n [('regression: remainder-only recipients',\n   [[['e13', 1365], ['e02', 1413], ['e28', 1410], ['e15', 1420], ['e10', 1420], ['e26', 1413], ['e07', 1415],\n     ['e18', 1410]],\n    [1000, 501, 500, 77]],\n   {'e02': 39, 'e07': 500, 'e10': 751, 'e15': 750, 'e26': 38}),\n  ('partial repair probe: remainder-only recipients',\n   [[['e05', 1330], ['e09', 1330], ['e12', 1328], ['e06', 1333], ['e13', 1328], ['e25', 1326], ['e29', 1323]],\n    [199, 1]],\n   {'e05': 1, 'e06': 199}),\n  ('second regression',\n   [[['e13', 1333], ['e10', 1326], ['e21', 1333], ['e27', 1328], ['e04', 1278], ['e14', 1278], ['e23', 1323],\n     ['e28', 1323]],\n    [501, 2, 1]],\n   {'e13': 252, 'e21': 251, 'e27': 1}),\n  ('normal control 1', [[['e05', 1326], ['e26', 1278], ['e04', 1328]], [250, 199, 100, 100]],\n   {'e04': 250, 'e05': 199, 'e26': 100}),\n  ('normal control 2',\n   [[['e15', 1333], ['e27', 1333], ['e24', 1333], ['e04', 1326]], [1000, 1000, 77, 77, 2]],\n   {'e04': 77, 'e15': 693, 'e24': 692, 'e27': 692}),\n  ('normal control 3', [[['e06', 1278], ['e18', 1323], ['e10', 1333]], [500, 199, 77]],\n   {'e06': 77, 'e10': 500, 'e18': 199}),\n  ('normal control 4',\n   [[['e06', 1500], ['e03', 1445], ['e04', 1445], ['e29', 1490], ['e17', 1500]], [250, 199, 100, 100]],\n   {'e03': 50, 'e04': 50, 'e06': 225, 'e17': 224, 'e29': 100})]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, 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 toy scoring contract stipulated for this example; it is not the rulebook of any real fantasy platform. 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-fantasy-sports-scoring-contest-payout-ties-remainder-only-recipients","generated_at":"2026-09-29T14:50:36.667195+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Tie splitting in paid contests moves real money; cent remainders and the pooled positions must be exact.","repair":"Record only positive amounts.","root_cause":"The payout filter accepts zero amounts.","sha256":"57b10fbeabcea593013fc3b9ad62d4fc4baebda732bd29b35fd3aa3e5b2bf80a","title":"Zero-cent entries listed as winners · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":40.513,"exit_code":1,"observations":[{"actual":{"e01":107,"e16":107,"e22":107,"e28":106},"check":"regression: remainder-only recipients","expected":{"e01":107,"e16":107,"e22":107,"e28":106},"passed":true},{"actual":{"e06":563,"e11":563,"e13":563,"e23":562},"check":"partial repair probe: remainder-only recipients","expected":{"e06":563,"e11":563,"e13":563,"e19":1,"e23":562},"passed":false},{"actual":{"e05":234,"e11":501,"e15":234,"e21":500,"e27":234},"check":"second regression","expected":{"e05":234,"e11":501,"e15":234,"e21":500,"e27":234},"passed":true},{"actual":{"e18":1000,"e20":250,"e24":1000},"check":"normal control 1","expected":{"e18":1000,"e20":250,"e24":1000},"passed":true},{"actual":{"e03":2,"e11":300,"e21":300,"e23":299},"check":"normal control 2","expected":{"e03":2,"e11":300,"e21":300,"e23":299},"passed":true},{"actual":{"e06":276,"e10":275,"e19":1000},"check":"normal control 3","expected":{"e06":276,"e10":275,"e19":1000},"passed":true},{"actual":{"e07":21,"e11":21,"e15":625,"e17":20,"e21":20,"e23":20,"e27":625},"check":"normal control 4","expected":{"e07":21,"e11":21,"e15":625,"e17":20,"e21":20,"e23":20,"e27":625},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: remainder-only recipients\", \"actual\": {\"e01\": 107, \"e16\": 107, \"e22\": 107, \"e28\": 106}, \"expected\": {\"e01\": 107, \"e16\": 107, \"e22\": 107, \"e28\": 106}, \"passed\": true}, {\"check\": \"partial repair probe: remainder-only recipients\", \"actual\": {\"e06\": 563, \"e11\": 563, \"e13\": 563, \"e23\": 562}, \"expected\": {\"e06\": 563, \"e11\": 563, \"e13\": 563, \"e19\": 1, \"e23\": 562}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"e11\": 501, \"e21\": 500, \"e05\": 234, \"e15\": 234, \"e27\": 234}, \"expected\": {\"e05\": 234, \"e11\": 501, \"e15\": 234, \"e21\": 500, \"e27\": 234}, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": {\"e24\": 1000, \"e18\": 1000, \"e20\": 250}, \"expected\": {\"e18\": 1000, \"e20\": 250, \"e24\": 1000}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"e11\": 300, \"e21\": 300, \"e23\": 299, \"e03\": 2}, \"expected\": {\"e03\": 2, \"e11\": 300, \"e21\": 300, \"e23\": 299}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"e19\": 1000, \"e06\": 276, \"e10\": 275}, \"expected\": {\"e06\": 276, \"e10\": 275, \"e19\": 1000}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"e15\": 625, \"e27\": 625, \"e07\": 21, \"e11\": 21, \"e17\": 20, \"e21\": 20, \"e23\": 20}, \"expected\": {\"e07\": 21, \"e11\": 21, \"e15\": 625, \"e17\": 20, \"e21\": 20, \"e23\": 20, \"e27\": 625}, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":40.555,"exit_code":1,"observations":[{"actual":{"e01":107,"e02":0,"e06":0,"e09":0,"e11":0,"e16":107,"e22":107,"e27":0,"e28":106},"check":"regression: remainder-only recipients","expected":{"e01":107,"e16":107,"e22":107,"e28":106},"passed":false},{"actual":{"e06":563,"e10":0,"e11":563,"e13":563,"e19":1,"e20":0,"e23":562,"e29":0},"check":"partial repair probe: remainder-only recipients","expected":{"e06":563,"e11":563,"e13":563,"e19":1,"e23":562},"passed":false},{"actual":{"e02":0,"e03":0,"e05":234,"e11":501,"e15":234,"e21":500,"e25":0,"e27":234},"check":"second regression","expected":{"e05":234,"e11":501,"e15":234,"e21":500,"e27":234},"passed":false},{"actual":{"e18":1000,"e20":250,"e24":1000},"check":"normal control 1","expected":{"e18":1000,"e20":250,"e24":1000},"passed":true},{"actual":{"e03":2,"e11":300,"e21":300,"e23":299},"check":"normal control 2","expected":{"e03":2,"e11":300,"e21":300,"e23":299},"passed":true},{"actual":{"e06":276,"e10":275,"e19":1000},"check":"normal control 3","expected":{"e06":276,"e10":275,"e19":1000},"passed":true},{"actual":{"e07":21,"e11":21,"e15":625,"e17":20,"e21":20,"e23":20,"e27":625},"check":"normal control 4","expected":{"e07":21,"e11":21,"e15":625,"e17":20,"e21":20,"e23":20,"e27":625},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: remainder-only recipients\", \"actual\": {\"e01\": 107, \"e16\": 107, \"e22\": 107, \"e28\": 106, \"e06\": 0, \"e09\": 0, \"e11\": 0, \"e27\": 0, \"e02\": 0}, \"expected\": {\"e01\": 107, \"e16\": 107, \"e22\": 107, \"e28\": 106}, \"passed\": false}, {\"check\": \"partial repair probe: remainder-only recipients\", \"actual\": {\"e06\": 563, \"e11\": 563, \"e13\": 563, \"e23\": 562, \"e19\": 1, \"e20\": 0, \"e29\": 0, \"e10\": 0}, \"expected\": {\"e06\": 563, \"e11\": 563, \"e13\": 563, \"e19\": 1, \"e23\": 562}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"e11\": 501, \"e21\": 500, \"e05\": 234, \"e15\": 234, \"e27\": 234, \"e02\": 0, \"e25\": 0, \"e03\": 0}, \"expected\": {\"e05\": 234, \"e11\": 501, \"e15\": 234, \"e21\": 500, \"e27\": 234}, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": {\"e24\": 1000, \"e18\": 1000, \"e20\": 250}, \"expected\": {\"e18\": 1000, \"e20\": 250, \"e24\": 1000}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"e11\": 300, \"e21\": 300, \"e23\": 299, \"e03\": 2}, \"expected\": {\"e03\": 2, \"e11\": 300, \"e21\": 300, \"e23\": 299}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"e19\": 1000, \"e06\": 276, \"e10\": 275}, \"expected\": {\"e06\": 276, \"e10\": 275, \"e19\": 1000}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"e15\": 625, \"e27\": 625, \"e07\": 21, \"e11\": 21, \"e17\": 20, \"e21\": 20, \"e23\": 20}, \"expected\": {\"e07\": 21, \"e11\": 21, \"e15\": 625, \"e17\": 20, \"e21\": 20, \"e23\": 20, \"e27\": 625}, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":39.627,"exit_code":0,"observations":[{"actual":{"e01":107,"e16":107,"e22":107,"e28":106},"check":"regression: remainder-only recipients","expected":{"e01":107,"e16":107,"e22":107,"e28":106},"passed":true},{"actual":{"e06":563,"e11":563,"e13":563,"e19":1,"e23":562},"check":"partial repair probe: remainder-only recipients","expected":{"e06":563,"e11":563,"e13":563,"e19":1,"e23":562},"passed":true},{"actual":{"e05":234,"e11":501,"e15":234,"e21":500,"e27":234},"check":"second regression","expected":{"e05":234,"e11":501,"e15":234,"e21":500,"e27":234},"passed":true},{"actual":{"e18":1000,"e20":250,"e24":1000},"check":"normal control 1","expected":{"e18":1000,"e20":250,"e24":1000},"passed":true},{"actual":{"e03":2,"e11":300,"e21":300,"e23":299},"check":"normal control 2","expected":{"e03":2,"e11":300,"e21":300,"e23":299},"passed":true},{"actual":{"e06":276,"e10":275,"e19":1000},"check":"normal control 3","expected":{"e06":276,"e10":275,"e19":1000},"passed":true},{"actual":{"e07":21,"e11":21,"e15":625,"e17":20,"e21":20,"e23":20,"e27":625},"check":"normal control 4","expected":{"e07":21,"e11":21,"e15":625,"e17":20,"e21":20,"e23":20,"e27":625},"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: remainder-only recipients\", \"actual\": {\"e01\": 107, \"e16\": 107, \"e22\": 107, \"e28\": 106}, \"expected\": {\"e01\": 107, \"e16\": 107, \"e22\": 107, \"e28\": 106}, \"passed\": true}, {\"check\": \"partial repair probe: remainder-only recipients\", \"actual\": {\"e06\": 563, \"e11\": 563, \"e13\": 563, \"e23\": 562, \"e19\": 1}, \"expected\": {\"e06\": 563, \"e11\": 563, \"e13\": 563, \"e19\": 1, \"e23\": 562}, \"passed\": true}, {\"check\": \"second regression\", \"actual\": {\"e11\": 501, \"e21\": 500, \"e05\": 234, \"e15\": 234, \"e27\": 234}, \"expected\": {\"e05\": 234, \"e11\": 501, \"e15\": 234, \"e21\": 500, \"e27\": 234}, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": {\"e24\": 1000, \"e18\": 1000, \"e20\": 250}, \"expected\": {\"e18\": 1000, \"e20\": 250, \"e24\": 1000}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"e11\": 300, \"e21\": 300, \"e23\": 299, \"e03\": 2}, \"expected\": {\"e03\": 2, \"e11\": 300, \"e21\": 300, \"e23\": 299}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"e19\": 1000, \"e06\": 276, \"e10\": 275}, \"expected\": {\"e06\": 276, \"e10\": 275, \"e19\": 1000}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"e15\": 625, \"e27\": 625, \"e07\": 21, \"e11\": 21, \"e17\": 20, \"e21\": 20, \"e23\": 20}, \"expected\": {\"e07\": 21, \"e11\": 21, \"e15\": 625, \"e17\": 20, \"e21\": 20, \"e23\": 20, \"e27\": 625}, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}