{"abstract":"Every triple-double scores 4.5 bonus points instead of 3.","category":"Fantasy sports scoring","checks":7,"contract":"Score a basketball line in tenths: points 1.0, rebounds (offensive + defensive) 1.2, assists 1.5, steals 3, blocks 3, turnovers -1, threes made 0.5 extra. Count double-digit categories among points, rebounds, assists, steals and blocks; three or more earns only the triple-double bonus, exactly two earns the double-double bonus.","evaluation_group":"w2-fantasy-sports-scoring-basketball-double-bonus","failed_approach":"Still stacks both bonuses for quadruple-doubles.","family":"w2-fantasy-sports-scoring-basketball-double-bonus-bonus-exclusivity","id":"FA-85121","implementations":{"attempt":{"sha256":"aeda64850f88537d78006a0e463bfc1a2e0b4df0819596e3377c8712267f3076","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(line, bonus):\n    line = dict(line, reb=line['oreb'] + line['dreb'])\n    w = {'pts': 10, 'reb': 12, 'ast': 15, 'stl': 30, 'blk': 30, 'tov': -10, 'fg3m': 5}\n    score = sum(w[k] * line[k] for k in w)\n    doubles = sum(1 for k in ('pts', 'reb', 'ast', 'stl', 'blk') if line[k] >= 10)\n    if doubles >= 3:\n        score += bonus['td']\n    if doubles == 2 or doubles > 3:\n        score += bonus['dd']\n    return score\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: bonus exclusivity',\n   [{'ast': 5, 'blk': 10, 'dreb': 8, 'fg3m': 0, 'oreb': 3, 'pts': 10, 'stl': 10, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   937),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 11, 'dreb': 8, 'fg3m': 1, 'oreb': 5, 'pts': 11, 'stl': 10, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   1021),\n  ('second regression',\n   [{'ast': 10, 'blk': 10, 'dreb': 5, 'fg3m': 0, 'oreb': 2, 'pts': 14, 'stl': 3, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   764),\n  ('normal control 1',\n   [{'ast': 9, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 27, 'stl': 1, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   658),\n  ('normal control 2',\n   [{'ast': 7, 'blk': 0, 'dreb': 8, 'fg3m': 0, 'oreb': 1, 'pts': 10, 'stl': 0, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   263),\n  ('normal control 3',\n   [{'ast': 3, 'blk': 0, 'dreb': 4, 'fg3m': 2, 'oreb': 3, 'pts': 10, 'stl': 0, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   239),\n  ('normal control 4',\n   [{'ast': 10, 'blk': 2, 'dreb': 1, 'fg3m': 6, 'oreb': 5, 'pts': 20, 'stl': 1, 'tov': 4},\n    {'dd': 15, 'td': 30}],\n   517)],\n [('regression: bonus exclusivity',\n   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 19, 'stl': 2, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   613),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 6, 'oreb': 4, 'pts': 10, 'stl': 10, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   754),\n  ('second regression',\n   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 5, 'oreb': 1, 'pts': 14, 'stl': 0, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   720),\n  ('normal control 1',\n   [{'ast': 2, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 6, 'pts': 21, 'stl': 1, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   505),\n  ('normal control 2',\n   [{'ast': 10, 'blk': 10, 'dreb': 4, 'fg3m': 1, 'oreb': 1, 'pts': 0, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   540),\n  ('normal control 3',\n   [{'ast': 0, 'blk': 0, 'dreb': 10, 'fg3m': 3, 'oreb': 2, 'pts': 10, 'stl': 3, 'tov': 4},\n    {'dd': 15, 'td': 30}],\n   324),\n  ('normal control 4',\n   [{'ast': 2, 'blk': 1, 'dreb': 7, 'fg3m': 4, 'oreb': 2, 'pts': 11, 'stl': 3, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   338)],\n [('regression: bonus exclusivity',\n   [{'ast': 10, 'blk': 0, 'dreb': 9, 'fg3m': 3, 'oreb': 1, 'pts': 10, 'stl': 3, 'tov': 1},\n    {'dd': 15, 'td': 30}],\n   495),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 11, 'dreb': 7, 'fg3m': 5, 'oreb': 4, 'pts': 10, 'stl': 3, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   807),\n  ('second regression',\n   [{'ast': 7, 'blk': 10, 'dreb': 5, 'fg3m': 4, 'oreb': 6, 'pts': 36, 'stl': 2, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   987),\n  ('normal control 1',\n   [{'ast': 9, 'blk': 0, 'dreb': 9, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 2, 'tov': 1},\n    {'dd': 15, 'td': 30}],\n   486),\n  ('normal control 2',\n   [{'ast': 11, 'blk': 1, 'dreb': 4, 'fg3m': 2, 'oreb': 1, 'pts': 9, 'stl': 3, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   425),\n  ('normal control 3',\n   [{'ast': 12, 'blk': 1, 'dreb': 8, 'fg3m': 5, 'oreb': 6, 'pts': 9, 'stl': 2, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   568),\n  ('normal control 4',\n   [{'ast': 9, 'blk': 10, 'dreb': 5, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 3, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   715)],\n [('regression: bonus exclusivity',\n   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 6, 'oreb': 5, 'pts': 14, 'stl': 1, 'tov': 1},\n    {'dd': 15, 'td': 30}],\n   853),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 10, 'stl': 10, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   793),\n  ('second regression',\n   [{'ast': 13, 'blk': 0, 'dreb': 12, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   474),\n  ('normal control 1',\n   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 0, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   421),\n  ('normal control 2',\n   [{'ast': 9, 'blk': 1, 'dreb': 2, 'fg3m': 2, 'oreb': 1, 'pts': 10, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   321),\n  ('normal control 3',\n   [{'ast': 10, 'blk': 0, 'dreb': 5, 'fg3m': 2, 'oreb': 5, 'pts': 6, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   365),\n  ('normal control 4',\n   [{'ast': 9, 'blk': 0, 'dreb': 10, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   424)],\n [('regression: bonus exclusivity',\n   [{'ast': 10, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 1, 'pts': 11, 'stl': 1, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   530),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 13, 'blk': 11, 'dreb': 10, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   810),\n  ('second regression',\n   [{'ast': 11, 'blk': 10, 'dreb': 2, 'fg3m': 1, 'oreb': 3, 'pts': 34, 'stl': 0, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   900),\n  ('normal control 1',\n   [{'ast': 9, 'blk': 11, 'dreb': 4, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 2, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   702),\n  ('normal control 2',\n   [{'ast': 10, 'blk': 2, 'dreb': 4, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 1, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   378),\n  ('normal control 3',\n   [{'ast': 11, 'blk': 2, 'dreb': 5, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 0, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   428),\n  ('normal control 4',\n   [{'ast': 5, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 10, 'stl': 2, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   398)]]\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":"46935cfc9364638645b200b49dda567b1e2a5f5226e1f4526bacb28424b09129","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(line, bonus):\n    line = dict(line, reb=line['oreb'] + line['dreb'])\n    w = {'pts': 10, 'reb': 12, 'ast': 15, 'stl': 30, 'blk': 30, 'tov': -10, 'fg3m': 5}\n    score = sum(w[k] * line[k] for k in w)\n    doubles = sum(1 for k in ('pts', 'reb', 'ast', 'stl', 'blk') if line[k] >= 10)\n    if doubles >= 3:\n        score += bonus['td']\n    if doubles >= 2:\n        score += bonus['dd']\n    return score\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: bonus exclusivity',\n   [{'ast': 5, 'blk': 10, 'dreb': 8, 'fg3m': 0, 'oreb': 3, 'pts': 10, 'stl': 10, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   937),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 11, 'dreb': 8, 'fg3m': 1, 'oreb': 5, 'pts': 11, 'stl': 10, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   1021),\n  ('second regression',\n   [{'ast': 10, 'blk': 10, 'dreb': 5, 'fg3m': 0, 'oreb': 2, 'pts': 14, 'stl': 3, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   764),\n  ('normal control 1',\n   [{'ast': 9, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 27, 'stl': 1, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   658),\n  ('normal control 2',\n   [{'ast': 7, 'blk': 0, 'dreb': 8, 'fg3m': 0, 'oreb': 1, 'pts': 10, 'stl': 0, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   263),\n  ('normal control 3',\n   [{'ast': 3, 'blk': 0, 'dreb': 4, 'fg3m': 2, 'oreb': 3, 'pts': 10, 'stl': 0, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   239),\n  ('normal control 4',\n   [{'ast': 10, 'blk': 2, 'dreb': 1, 'fg3m': 6, 'oreb': 5, 'pts': 20, 'stl': 1, 'tov': 4},\n    {'dd': 15, 'td': 30}],\n   517)],\n [('regression: bonus exclusivity',\n   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 19, 'stl': 2, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   613),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 6, 'oreb': 4, 'pts': 10, 'stl': 10, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   754),\n  ('second regression',\n   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 5, 'oreb': 1, 'pts': 14, 'stl': 0, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   720),\n  ('normal control 1',\n   [{'ast': 2, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 6, 'pts': 21, 'stl': 1, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   505),\n  ('normal control 2',\n   [{'ast': 10, 'blk': 10, 'dreb': 4, 'fg3m': 1, 'oreb': 1, 'pts': 0, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   540),\n  ('normal control 3',\n   [{'ast': 0, 'blk': 0, 'dreb': 10, 'fg3m': 3, 'oreb': 2, 'pts': 10, 'stl': 3, 'tov': 4},\n    {'dd': 15, 'td': 30}],\n   324),\n  ('normal control 4',\n   [{'ast': 2, 'blk': 1, 'dreb': 7, 'fg3m': 4, 'oreb': 2, 'pts': 11, 'stl': 3, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   338)],\n [('regression: bonus exclusivity',\n   [{'ast': 10, 'blk': 0, 'dreb': 9, 'fg3m': 3, 'oreb': 1, 'pts': 10, 'stl': 3, 'tov': 1},\n    {'dd': 15, 'td': 30}],\n   495),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 11, 'dreb': 7, 'fg3m': 5, 'oreb': 4, 'pts': 10, 'stl': 3, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   807),\n  ('second regression',\n   [{'ast': 7, 'blk': 10, 'dreb': 5, 'fg3m': 4, 'oreb': 6, 'pts': 36, 'stl': 2, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   987),\n  ('normal control 1',\n   [{'ast': 9, 'blk': 0, 'dreb': 9, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 2, 'tov': 1},\n    {'dd': 15, 'td': 30}],\n   486),\n  ('normal control 2',\n   [{'ast': 11, 'blk': 1, 'dreb': 4, 'fg3m': 2, 'oreb': 1, 'pts': 9, 'stl': 3, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   425),\n  ('normal control 3',\n   [{'ast': 12, 'blk': 1, 'dreb': 8, 'fg3m': 5, 'oreb': 6, 'pts': 9, 'stl': 2, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   568),\n  ('normal control 4',\n   [{'ast': 9, 'blk': 10, 'dreb': 5, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 3, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   715)],\n [('regression: bonus exclusivity',\n   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 6, 'oreb': 5, 'pts': 14, 'stl': 1, 'tov': 1},\n    {'dd': 15, 'td': 30}],\n   853),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 10, 'stl': 10, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   793),\n  ('second regression',\n   [{'ast': 13, 'blk': 0, 'dreb': 12, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   474),\n  ('normal control 1',\n   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 0, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   421),\n  ('normal control 2',\n   [{'ast': 9, 'blk': 1, 'dreb': 2, 'fg3m': 2, 'oreb': 1, 'pts': 10, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   321),\n  ('normal control 3',\n   [{'ast': 10, 'blk': 0, 'dreb': 5, 'fg3m': 2, 'oreb': 5, 'pts': 6, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   365),\n  ('normal control 4',\n   [{'ast': 9, 'blk': 0, 'dreb': 10, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   424)],\n [('regression: bonus exclusivity',\n   [{'ast': 10, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 1, 'pts': 11, 'stl': 1, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   530),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 13, 'blk': 11, 'dreb': 10, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   810),\n  ('second regression',\n   [{'ast': 11, 'blk': 10, 'dreb': 2, 'fg3m': 1, 'oreb': 3, 'pts': 34, 'stl': 0, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   900),\n  ('normal control 1',\n   [{'ast': 9, 'blk': 11, 'dreb': 4, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 2, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   702),\n  ('normal control 2',\n   [{'ast': 10, 'blk': 2, 'dreb': 4, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 1, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   378),\n  ('normal control 3',\n   [{'ast': 11, 'blk': 2, 'dreb': 5, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 0, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   428),\n  ('normal control 4',\n   [{'ast': 5, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 10, 'stl': 2, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   398)]]\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":"2fb632f761978ea9d2869d1823d57e2cac9de86e6ca6c4372744942a254fb6f2","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(line, bonus):\n    line = dict(line, reb=line['oreb'] + line['dreb'])\n    w = {'pts': 10, 'reb': 12, 'ast': 15, 'stl': 30, 'blk': 30, 'tov': -10, 'fg3m': 5}\n    score = sum(w[k] * line[k] for k in w)\n    doubles = sum(1 for k in ('pts', 'reb', 'ast', 'stl', 'blk') if line[k] >= 10)\n    if doubles >= 3:\n        score += bonus['td']\n    elif doubles == 2:\n        score += bonus['dd']\n    return score\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: bonus exclusivity',\n   [{'ast': 5, 'blk': 10, 'dreb': 8, 'fg3m': 0, 'oreb': 3, 'pts': 10, 'stl': 10, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   937),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 11, 'dreb': 8, 'fg3m': 1, 'oreb': 5, 'pts': 11, 'stl': 10, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   1021),\n  ('second regression',\n   [{'ast': 10, 'blk': 10, 'dreb': 5, 'fg3m': 0, 'oreb': 2, 'pts': 14, 'stl': 3, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   764),\n  ('normal control 1',\n   [{'ast': 9, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 27, 'stl': 1, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   658),\n  ('normal control 2',\n   [{'ast': 7, 'blk': 0, 'dreb': 8, 'fg3m': 0, 'oreb': 1, 'pts': 10, 'stl': 0, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   263),\n  ('normal control 3',\n   [{'ast': 3, 'blk': 0, 'dreb': 4, 'fg3m': 2, 'oreb': 3, 'pts': 10, 'stl': 0, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   239),\n  ('normal control 4',\n   [{'ast': 10, 'blk': 2, 'dreb': 1, 'fg3m': 6, 'oreb': 5, 'pts': 20, 'stl': 1, 'tov': 4},\n    {'dd': 15, 'td': 30}],\n   517)],\n [('regression: bonus exclusivity',\n   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 19, 'stl': 2, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   613),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 6, 'oreb': 4, 'pts': 10, 'stl': 10, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   754),\n  ('second regression',\n   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 5, 'oreb': 1, 'pts': 14, 'stl': 0, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   720),\n  ('normal control 1',\n   [{'ast': 2, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 6, 'pts': 21, 'stl': 1, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   505),\n  ('normal control 2',\n   [{'ast': 10, 'blk': 10, 'dreb': 4, 'fg3m': 1, 'oreb': 1, 'pts': 0, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   540),\n  ('normal control 3',\n   [{'ast': 0, 'blk': 0, 'dreb': 10, 'fg3m': 3, 'oreb': 2, 'pts': 10, 'stl': 3, 'tov': 4},\n    {'dd': 15, 'td': 30}],\n   324),\n  ('normal control 4',\n   [{'ast': 2, 'blk': 1, 'dreb': 7, 'fg3m': 4, 'oreb': 2, 'pts': 11, 'stl': 3, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   338)],\n [('regression: bonus exclusivity',\n   [{'ast': 10, 'blk': 0, 'dreb': 9, 'fg3m': 3, 'oreb': 1, 'pts': 10, 'stl': 3, 'tov': 1},\n    {'dd': 15, 'td': 30}],\n   495),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 11, 'dreb': 7, 'fg3m': 5, 'oreb': 4, 'pts': 10, 'stl': 3, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   807),\n  ('second regression',\n   [{'ast': 7, 'blk': 10, 'dreb': 5, 'fg3m': 4, 'oreb': 6, 'pts': 36, 'stl': 2, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   987),\n  ('normal control 1',\n   [{'ast': 9, 'blk': 0, 'dreb': 9, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 2, 'tov': 1},\n    {'dd': 15, 'td': 30}],\n   486),\n  ('normal control 2',\n   [{'ast': 11, 'blk': 1, 'dreb': 4, 'fg3m': 2, 'oreb': 1, 'pts': 9, 'stl': 3, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   425),\n  ('normal control 3',\n   [{'ast': 12, 'blk': 1, 'dreb': 8, 'fg3m': 5, 'oreb': 6, 'pts': 9, 'stl': 2, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   568),\n  ('normal control 4',\n   [{'ast': 9, 'blk': 10, 'dreb': 5, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 3, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   715)],\n [('regression: bonus exclusivity',\n   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 6, 'oreb': 5, 'pts': 14, 'stl': 1, 'tov': 1},\n    {'dd': 15, 'td': 30}],\n   853),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 10, 'stl': 10, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   793),\n  ('second regression',\n   [{'ast': 13, 'blk': 0, 'dreb': 12, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   474),\n  ('normal control 1',\n   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 0, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   421),\n  ('normal control 2',\n   [{'ast': 9, 'blk': 1, 'dreb': 2, 'fg3m': 2, 'oreb': 1, 'pts': 10, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   321),\n  ('normal control 3',\n   [{'ast': 10, 'blk': 0, 'dreb': 5, 'fg3m': 2, 'oreb': 5, 'pts': 6, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   365),\n  ('normal control 4',\n   [{'ast': 9, 'blk': 0, 'dreb': 10, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   424)],\n [('regression: bonus exclusivity',\n   [{'ast': 10, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 1, 'pts': 11, 'stl': 1, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   530),\n  ('partial repair probe: bonus exclusivity',\n   [{'ast': 13, 'blk': 11, 'dreb': 10, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 2},\n    {'dd': 15, 'td': 30}],\n   810),\n  ('second regression',\n   [{'ast': 11, 'blk': 10, 'dreb': 2, 'fg3m': 1, 'oreb': 3, 'pts': 34, 'stl': 0, 'tov': 0},\n    {'dd': 15, 'td': 30}],\n   900),\n  ('normal control 1',\n   [{'ast': 9, 'blk': 11, 'dreb': 4, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 2, 'tov': 3},\n    {'dd': 15, 'td': 30}],\n   702),\n  ('normal control 2',\n   [{'ast': 10, 'blk': 2, 'dreb': 4, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 1, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   378),\n  ('normal control 3',\n   [{'ast': 11, 'blk': 2, 'dreb': 5, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 0, 'tov': 5},\n    {'dd': 15, 'td': 30}],\n   428),\n  ('normal control 4',\n   [{'ast': 5, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 10, 'stl': 2, 'tov': 6},\n    {'dd': 15, 'td': 30}],\n   398)]]\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-basketball-double-bonus-bonus-exclusivity","generated_at":"2026-09-29T14:50:37.396105+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Double-double and triple-double bonuses are exclusive tiers in points leagues and are frequently double-awarded.","repair":"Award exactly one bonus tier.","root_cause":"The double-double branch is an independent if with >= 2.","sha256":"bebb77032e1863f6fb34a41410a8d6d82fe1a03da202c74692ab1325d3b3bb49","title":"Triple-double also collects the double-double bonus · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":39.186,"exit_code":1,"observations":[{"actual":952,"check":"regression: bonus exclusivity","expected":937,"passed":false},{"actual":1036,"check":"partial repair probe: bonus exclusivity","expected":1021,"passed":false},{"actual":764,"check":"second regression","expected":764,"passed":true},{"actual":658,"check":"normal control 1","expected":658,"passed":true},{"actual":263,"check":"normal control 2","expected":263,"passed":true},{"actual":239,"check":"normal control 3","expected":239,"passed":true},{"actual":517,"check":"normal control 4","expected":517,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: bonus exclusivity\", \"actual\": 952, \"expected\": 937, \"passed\": false}, {\"check\": \"partial repair probe: bonus exclusivity\", \"actual\": 1036, \"expected\": 1021, \"passed\": false}, {\"check\": \"second regression\", \"actual\": 764, \"expected\": 764, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 658, \"expected\": 658, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 263, \"expected\": 263, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 239, \"expected\": 239, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 517, \"expected\": 517, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":41.661,"exit_code":1,"observations":[{"actual":952,"check":"regression: bonus exclusivity","expected":937,"passed":false},{"actual":1036,"check":"partial repair probe: bonus exclusivity","expected":1021,"passed":false},{"actual":779,"check":"second regression","expected":764,"passed":false},{"actual":658,"check":"normal control 1","expected":658,"passed":true},{"actual":263,"check":"normal control 2","expected":263,"passed":true},{"actual":239,"check":"normal control 3","expected":239,"passed":true},{"actual":517,"check":"normal control 4","expected":517,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: bonus exclusivity\", \"actual\": 952, \"expected\": 937, \"passed\": false}, {\"check\": \"partial repair probe: bonus exclusivity\", \"actual\": 1036, \"expected\": 1021, \"passed\": false}, {\"check\": \"second regression\", \"actual\": 779, \"expected\": 764, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": 658, \"expected\": 658, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 263, \"expected\": 263, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 239, \"expected\": 239, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 517, \"expected\": 517, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":39.211,"exit_code":0,"observations":[{"actual":937,"check":"regression: bonus exclusivity","expected":937,"passed":true},{"actual":1021,"check":"partial repair probe: bonus exclusivity","expected":1021,"passed":true},{"actual":764,"check":"second regression","expected":764,"passed":true},{"actual":658,"check":"normal control 1","expected":658,"passed":true},{"actual":263,"check":"normal control 2","expected":263,"passed":true},{"actual":239,"check":"normal control 3","expected":239,"passed":true},{"actual":517,"check":"normal control 4","expected":517,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: bonus exclusivity\", \"actual\": 937, \"expected\": 937, \"passed\": true}, {\"check\": \"partial repair probe: bonus exclusivity\", \"actual\": 1021, \"expected\": 1021, \"passed\": true}, {\"check\": \"second regression\", \"actual\": 764, \"expected\": 764, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 658, \"expected\": 658, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 263, \"expected\": 263, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 239, \"expected\": 239, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": 517, \"expected\": 517, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}