{"abstract":"In an odd league the median team always takes a median loss.","category":"Fantasy sports scoring","checks":7,"contract":"Weekly fantasy scores are integer hundredths. Each head-to-head pair records a win/loss or a tie on equal scores (an odd team out has no head-to-head game). Every team also plays the league median: the middle score for an odd team count or the mean of the two middle scores for an even count; above the median is a win, below a loss, equal a tie. Return team -> [wins, losses, ties].","contract_signature":"pairs, scores","evaluation_group":"w2-fantasy-sports-scoring-median-game-record","failed_approach":"Recording the equal case as a win is the opposite bias, not a tie.","family":"w2-fantasy-sports-scoring-median-game-record-median-tie-result","id":"FA-85021","implementations":{"attempt":{"sha256":"09de50a71163e4ee63d621fc611f9a9c5471af7207f979610e2529a5849f47ad","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(pairs, scores):\n    rec = {t: [0, 0, 0] for t in scores}\n    for a, b in pairs:\n        if scores[a] > scores[b]:\n            rec[a][0] += 1; rec[b][1] += 1\n        elif scores[a] < scores[b]:\n            rec[a][1] += 1; rec[b][0] += 1\n        else:\n            rec[a][2] += 1; rec[b][2] += 1\n    vals = sorted(scores.values())\n    n = len(vals)\n    twice_median = vals[n // 2] * 2 if n % 2 else vals[n // 2 - 1] + vals[n // 2]\n    for t, s in scores.items():\n        if 2 * s > twice_median:\n            rec[t][0] += 1\n        elif 2 * s < twice_median:\n            rec[t][1] += 1\n        else:\n            rec[t][0] += 1\n    return rec\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: median tie result',\n   [[['T5', 'T2'], ['T6', 'T3'], ['T1', 'T0']],\n    {'T0': 9025, 'T1': 12000, 'T2': 10111, 'T3': 9025, 'T4': 10110, 'T5': 10526, 'T6': 9025}],\n   {'T0': [0, 2, 0],\n    'T1': [2, 0, 0],\n    'T2': [1, 1, 0],\n    'T3': [0, 1, 1],\n    'T4': [0, 0, 1],\n    'T5': [2, 0, 0],\n    'T6': [0, 1, 1]}),\n  ('partial repair probe: median tie result',\n   [[['T0', 'T1'], ['T3', 'T2']], {'T0': 12000, 'T1': 12993, 'T2': 12770, 'T3': 8850, 'T4': 10011}],\n   {'T0': [0, 1, 1], 'T1': [2, 0, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0], 'T4': [0, 1, 0]}),\n  ('second regression',\n   [[['T3', 'T1'], ['T0', 'T7'], ['T5', 'T4'], ['T6', 'T2']],\n    {'T0': 8850, 'T1': 8850, 'T2': 12000, 'T3': 8850, 'T4': 12000, 'T5': 8721, 'T6': 11240, 'T7': 7826}],\n   {'T0': [1, 0, 1],\n    'T1': [0, 0, 2],\n    'T2': [2, 0, 0],\n    'T3': [0, 0, 2],\n    'T4': [2, 0, 0],\n    'T5': [0, 2, 0],\n    'T6': [1, 1, 0],\n    'T7': [0, 2, 0]}),\n  ('normal control 1',\n   [[['T4', 'T3'], ['T0', 'T2'], ['T1', 'T5']],\n    {'T0': 9025, 'T1': 9025, 'T2': 10110, 'T3': 10110, 'T4': 8850, 'T5': 10111}],\n   {'T0': [0, 2, 0], 'T1': [0, 2, 0], 'T2': [2, 0, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [2, 0, 0]}),\n  ('normal control 2',\n   [[['T0', 'T3'], ['T5', 'T1'], ['T2', 'T4']],\n    {'T0': 10110, 'T1': 12000, 'T2': 11240, 'T3': 8850, 'T4': 10111, 'T5': 9025}],\n   {'T0': [1, 1, 0], 'T1': [2, 0, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0], 'T4': [1, 1, 0], 'T5': [0, 2, 0]}),\n  ('normal control 3',\n   [[['T1', 'T4'], ['T5', 'T3'], ['T2', 'T0']],\n    {'T0': 10111, 'T1': 10111, 'T2': 9025, 'T3': 12000, 'T4': 8850, 'T5': 8850}],\n   {'T0': [2, 0, 0], 'T1': [2, 0, 0], 'T2': [0, 2, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [0, 2, 0]}),\n  ('normal control 4',\n   [[['T3', 'T5'], ['T4', 'T7'], ['T0', 'T2'], ['T1', 'T6']],\n    {'T0': 10110, 'T1': 10110, 'T2': 9025, 'T3': 9025, 'T4': 12000, 'T5': 8850, 'T6': 9025, 'T7': 11240}],\n   {'T0': [2, 0, 0],\n    'T1': [2, 0, 0],\n    'T2': [0, 2, 0],\n    'T3': [1, 1, 0],\n    'T4': [2, 0, 0],\n    'T5': [0, 2, 0],\n    'T6': [0, 2, 0],\n    'T7': [1, 1, 0]})],\n [('regression: median tie result',\n   [[['T3', 'T4'], ['T5', 'T1'], ['T0', 'T2']],\n    {'T0': 11240, 'T1': 9025, 'T2': 9025, 'T3': 11240, 'T4': 9025, 'T5': 11240, 'T6': 9025}],\n   {'T0': [2, 0, 0],\n    'T1': [0, 1, 1],\n    'T2': [0, 1, 1],\n    'T3': [2, 0, 0],\n    'T4': [0, 1, 1],\n    'T5': [2, 0, 0],\n    'T6': [0, 0, 1]}),\n  ('partial repair probe: median tie result',\n   [[['T0', 'T1'], ['T5', 'T6'], ['T4', 'T2']],\n    {'T0': 10110, 'T1': 10111, 'T2': 10111, 'T3': 9025, 'T4': 12000, 'T5': 10111, 'T6': 8119}],\n   {'T0': [0, 2, 0],\n    'T1': [1, 0, 1],\n    'T2': [0, 1, 1],\n    'T3': [0, 1, 0],\n    'T4': [2, 0, 0],\n    'T5': [1, 0, 1],\n    'T6': [0, 2, 0]}),\n  ('second regression',\n   [[['T5', 'T4'], ['T2', 'T6'], ['T1', 'T3']],\n    {'T0': 11240, 'T1': 8850, 'T2': 10110, 'T3': 8850, 'T4': 9025, 'T5': 10110, 'T6': 8018}],\n   {'T0': [1, 0, 0],\n    'T1': [0, 1, 1],\n    'T2': [2, 0, 0],\n    'T3': [0, 1, 1],\n    'T4': [0, 1, 1],\n    'T5': [2, 0, 0],\n    'T6': [0, 2, 0]}),\n  ('normal control 1', [[['T2', 'T1'], ['T0', 'T3']], {'T0': 10111, 'T1': 9025, 'T2': 10110, 'T3': 9025}],\n   {'T0': [2, 0, 0], 'T1': [0, 2, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0]}),\n  ('normal control 2',\n   [[['T5', 'T1'], ['T4', 'T0'], ['T2', 'T3']],\n    {'T0': 10110, 'T1': 9025, 'T2': 9025, 'T3': 12000, 'T4': 11240, 'T5': 13052}],\n   {'T0': [0, 2, 0], 'T1': [0, 2, 0], 'T2': [0, 2, 0], 'T3': [2, 0, 0], 'T4': [2, 0, 0], 'T5': [2, 0, 0]}),\n  ('normal control 3', [[['T2', 'T3'], ['T1', 'T0']], {'T0': 8850, 'T1': 12000, 'T2': 10111, 'T3': 9025}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0]}),\n  ('normal control 4',\n   [[['T2', 'T0'], ['T1', 'T5'], ['T3', 'T4']],\n    {'T0': 10110, 'T1': 12000, 'T2': 10696, 'T3': 12000, 'T4': 9025, 'T5': 9025}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [2, 0, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [0, 2, 0]})],\n [('regression: median tie result',\n   [[['T4', 'T3'], ['T0', 'T1']], {'T0': 10111, 'T1': 12000, 'T2': 10110, 'T3': 10110, 'T4': 11240}],\n   {'T0': [0, 1, 1], 'T1': [2, 0, 0], 'T2': [0, 1, 0], 'T3': [0, 2, 0], 'T4': [2, 0, 0]}),\n  ('partial repair probe: median tie result',\n   [[['T4', 'T2'], ['T0', 'T1']], {'T0': 12000, 'T1': 12000, 'T2': 7976, 'T3': 9025, 'T4': 8017}],\n   {'T0': [1, 0, 1], 'T1': [1, 0, 1], 'T2': [0, 2, 0], 'T3': [0, 0, 1], 'T4': [1, 1, 0]}),\n  ('second regression',\n   [[['T1', 'T5'], ['T3', 'T6'], ['T0', 'T4']],\n    {'T0': 9025, 'T1': 9025, 'T2': 10110, 'T3': 9025, 'T4': 9025, 'T5': 9025, 'T6': 10111}],\n   {'T0': [0, 0, 2],\n    'T1': [0, 0, 2],\n    'T2': [1, 0, 0],\n    'T3': [0, 1, 1],\n    'T4': [0, 0, 2],\n    'T5': [0, 0, 2],\n    'T6': [2, 0, 0]}),\n  ('normal control 1',\n   [[['T0', 'T3'], ['T4', 'T1'], ['T2', 'T5']],\n    {'T0': 11240, 'T1': 9025, 'T2': 10110, 'T3': 10111, 'T4': 12000, 'T5': 8850}],\n   {'T0': [2, 0, 0], 'T1': [0, 2, 0], 'T2': [1, 1, 0], 'T3': [1, 1, 0], 'T4': [2, 0, 0], 'T5': [0, 2, 0]}),\n  ('normal control 2', [[['T3', 'T0'], ['T2', 'T1']], {'T0': 10110, 'T1': 10111, 'T2': 9025, 'T3': 11240}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [0, 2, 0], 'T3': [2, 0, 0]}),\n  ('normal control 3',\n   [[['T1', 'T0'], ['T3', 'T4'], ['T2', 'T5']],\n    {'T0': 10111, 'T1': 11240, 'T2': 9025, 'T3': 10151, 'T4': 11240, 'T5': 9025}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [0, 1, 1], 'T3': [1, 1, 0], 'T4': [2, 0, 0], 'T5': [0, 1, 1]}),\n  ('normal control 4',\n   [[['T3', 'T0'], ['T1', 'T2'], ['T4', 'T5']],\n    {'T0': 10110, 'T1': 8850, 'T2': 12820, 'T3': 9025, 'T4': 9233, 'T5': 12000}],\n   {'T0': [2, 0, 0], 'T1': [0, 2, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0], 'T4': [0, 2, 0], 'T5': [2, 0, 0]})],\n [('regression: median tie result',\n   [[['T2', 'T3'], ['T4', 'T1']], {'T0': 9025, 'T1': 12000, 'T2': 8766, 'T3': 8380, 'T4': 11240}],\n   {'T0': [0, 0, 1], 'T1': [2, 0, 0], 'T2': [1, 1, 0], 'T3': [0, 2, 0], 'T4': [1, 1, 0]}),\n  ('partial repair probe: median tie result',\n   [[['T2', 'T1'], ['T0', 'T3'], ['T6', 'T4'], ['T5', 'T7']],\n    {'T0': 9025, 'T1': 10110, 'T2': 11186, 'T3': 10111, 'T4': 10111, 'T5': 11240, 'T6': 9025, 'T7': 10111}],\n   {'T0': [0, 2, 0],\n    'T1': [0, 2, 0],\n    'T2': [2, 0, 0],\n    'T3': [1, 0, 1],\n    'T4': [1, 0, 1],\n    'T5': [2, 0, 0],\n    'T6': [0, 2, 0],\n    'T7': [0, 1, 1]}),\n  ('second regression',\n   [[['T6', 'T1'], ['T2', 'T0'], ['T5', 'T4']],\n    {'T0': 10111, 'T1': 9025, 'T2': 11996, 'T3': 8850, 'T4': 8850, 'T5': 10110, 'T6': 9025}],\n   {'T0': [1, 1, 0],\n    'T1': [0, 0, 2],\n    'T2': [2, 0, 0],\n    'T3': [0, 1, 0],\n    'T4': [0, 2, 0],\n    'T5': [2, 0, 0],\n    'T6': [0, 0, 2]}),\n  ('normal control 1',\n   [[['T5', 'T4'], ['T7', 'T1'], ['T3', 'T0'], ['T6', 'T2']],\n    {'T0': 11240, 'T1': 12000, 'T2': 9025, 'T3': 9025, 'T4': 9025, 'T5': 10111, 'T6': 8850, 'T7': 11240}],\n   {'T0': [2, 0, 0],\n    'T1': [2, 0, 0],\n    'T2': [1, 1, 0],\n    'T3': [0, 2, 0],\n    'T4': [0, 2, 0],\n    'T5': [2, 0, 0],\n    'T6': [0, 2, 0],\n    'T7': [1, 1, 0]}),\n  ('normal control 2',\n   [[['T0', 'T3'], ['T2', 'T7'], ['T6', 'T5'], ['T4', 'T1']],\n    {'T0': 10110, 'T1': 9025, 'T2': 13675, 'T3': 10111, 'T4': 9025, 'T5': 8506, 'T6': 13138, 'T7': 8850}],\n   {'T0': [1, 1, 0],\n    'T1': [0, 1, 1],\n    'T2': [2, 0, 0],\n    'T3': [2, 0, 0],\n    'T4': [0, 1, 1],\n    'T5': [0, 2, 0],\n    'T6': [2, 0, 0],\n    'T7': [0, 2, 0]}),\n  ('normal control 3', [[['T1', 'T3'], ['T0', 'T2']], {'T0': 8850, 'T1': 11240, 'T2': 10110, 'T3': 12000}],\n   {'T0': [0, 2, 0], 'T1': [1, 1, 0], 'T2': [1, 1, 0], 'T3': [2, 0, 0]}),\n  ('normal control 4',\n   [[['T0', 'T3'], ['T5', 'T1'], ['T2', 'T4']],\n    {'T0': 8850, 'T1': 11822, 'T2': 9025, 'T3': 11032, 'T4': 8317, 'T5': 10111}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [1, 1, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [1, 1, 0]})],\n [('regression: median tie result',\n   [[['T5', 'T2'], ['T3', 'T0'], ['T4', 'T1']],\n    {'T0': 8850, 'T1': 10111, 'T2': 9025, 'T3': 8775, 'T4': 9025, 'T5': 12000}],\n   {'T0': [1, 1, 0], 'T1': [2, 0, 0], 'T2': [0, 1, 1], 'T3': [0, 2, 0], 'T4': [0, 1, 1], 'T5': [2, 0, 0]}),\n  ('partial repair probe: median tie result',\n   [[['T4', 'T1'], ['T0', 'T5'], ['T3', 'T2']],\n    {'T0': 10111, 'T1': 10111, 'T2': 10110, 'T3': 12000, 'T4': 8850, 'T5': 13771}],\n   {'T0': [0, 1, 1], 'T1': [1, 0, 1], 'T2': [0, 2, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [2, 0, 0]}),\n  ('second regression',\n   [[['T0', 'T1'], ['T2', 'T4']], {'T0': 10111, 'T1': 11240, 'T2': 8850, 'T3': 10111, 'T4': 10111}],\n   {'T0': [0, 1, 1], 'T1': [2, 0, 0], 'T2': [0, 2, 0], 'T3': [0, 0, 1], 'T4': [1, 0, 1]}),\n  ('normal control 1', [[['T3', 'T0'], ['T2', 'T1']], {'T0': 8850, 'T1': 9025, 'T2': 8850, 'T3': 10110}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [0, 2, 0], 'T3': [2, 0, 0]}),\n  ('normal control 2',\n   [[['T4', 'T0'], ['T2', 'T7'], ['T1', 'T5'], ['T3', 'T6']],\n    {'T0': 10111, 'T1': 12153, 'T2': 10110, 'T3': 11240, 'T4': 11240, 'T5': 9025, 'T6': 12000, 'T7': 10111}],\n   {'T0': [0, 2, 0],\n    'T1': [2, 0, 0],\n    'T2': [0, 2, 0],\n    'T3': [1, 1, 0],\n    'T4': [2, 0, 0],\n    'T5': [0, 2, 0],\n    'T6': [2, 0, 0],\n    'T7': [1, 1, 0]}),\n  ('normal control 3',\n   [[['T2', 'T5'], ['T0', 'T4'], ['T7', 'T6'], ['T1', 'T3']],\n    {'T0': 9025, 'T1': 12000, 'T2': 10111, 'T3': 13608, 'T4': 9025, 'T5': 9025, 'T6': 10110, 'T7': 9025}],\n   {'T0': [0, 1, 1],\n    'T1': [1, 1, 0],\n    'T2': [2, 0, 0],\n    'T3': [2, 0, 0],\n    'T4': [0, 1, 1],\n    'T5': [0, 2, 0],\n    'T6': [2, 0, 0],\n    'T7': [0, 2, 0]}),\n  ('normal control 4',\n   [[['T2', 'T6'], ['T3', 'T7'], ['T4', 'T5'], ['T1', 'T0']],\n    {'T0': 12000, 'T1': 12000, 'T2': 10110, 'T3': 11240, 'T4': 10111, 'T5': 12000, 'T6': 9025, 'T7': 12000}],\n   {'T0': [1, 0, 1],\n    'T1': [1, 0, 1],\n    'T2': [1, 1, 0],\n    'T3': [0, 2, 0],\n    'T4': [0, 2, 0],\n    'T5': [2, 0, 0],\n    'T6': [0, 2, 0],\n    'T7': [2, 0, 0]})]]\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":"d3f67bc2e000f40b8d952bcaee02490280f777ad593767701bd13d387b03c5bb","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(pairs, scores):\n    rec = {t: [0, 0, 0] for t in scores}\n    for a, b in pairs:\n        if scores[a] > scores[b]:\n            rec[a][0] += 1; rec[b][1] += 1\n        elif scores[a] < scores[b]:\n            rec[a][1] += 1; rec[b][0] += 1\n        else:\n            rec[a][2] += 1; rec[b][2] += 1\n    vals = sorted(scores.values())\n    n = len(vals)\n    twice_median = vals[n // 2] * 2 if n % 2 else vals[n // 2 - 1] + vals[n // 2]\n    for t, s in scores.items():\n        if 2 * s > twice_median:\n            rec[t][0] += 1\n        elif 2 * s < twice_median:\n            rec[t][1] += 1\n        else:\n            rec[t][1] += 1\n    return rec\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: median tie result',\n   [[['T5', 'T2'], ['T6', 'T3'], ['T1', 'T0']],\n    {'T0': 9025, 'T1': 12000, 'T2': 10111, 'T3': 9025, 'T4': 10110, 'T5': 10526, 'T6': 9025}],\n   {'T0': [0, 2, 0],\n    'T1': [2, 0, 0],\n    'T2': [1, 1, 0],\n    'T3': [0, 1, 1],\n    'T4': [0, 0, 1],\n    'T5': [2, 0, 0],\n    'T6': [0, 1, 1]}),\n  ('partial repair probe: median tie result',\n   [[['T0', 'T1'], ['T3', 'T2']], {'T0': 12000, 'T1': 12993, 'T2': 12770, 'T3': 8850, 'T4': 10011}],\n   {'T0': [0, 1, 1], 'T1': [2, 0, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0], 'T4': [0, 1, 0]}),\n  ('second regression',\n   [[['T3', 'T1'], ['T0', 'T7'], ['T5', 'T4'], ['T6', 'T2']],\n    {'T0': 8850, 'T1': 8850, 'T2': 12000, 'T3': 8850, 'T4': 12000, 'T5': 8721, 'T6': 11240, 'T7': 7826}],\n   {'T0': [1, 0, 1],\n    'T1': [0, 0, 2],\n    'T2': [2, 0, 0],\n    'T3': [0, 0, 2],\n    'T4': [2, 0, 0],\n    'T5': [0, 2, 0],\n    'T6': [1, 1, 0],\n    'T7': [0, 2, 0]}),\n  ('normal control 1',\n   [[['T4', 'T3'], ['T0', 'T2'], ['T1', 'T5']],\n    {'T0': 9025, 'T1': 9025, 'T2': 10110, 'T3': 10110, 'T4': 8850, 'T5': 10111}],\n   {'T0': [0, 2, 0], 'T1': [0, 2, 0], 'T2': [2, 0, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [2, 0, 0]}),\n  ('normal control 2',\n   [[['T0', 'T3'], ['T5', 'T1'], ['T2', 'T4']],\n    {'T0': 10110, 'T1': 12000, 'T2': 11240, 'T3': 8850, 'T4': 10111, 'T5': 9025}],\n   {'T0': [1, 1, 0], 'T1': [2, 0, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0], 'T4': [1, 1, 0], 'T5': [0, 2, 0]}),\n  ('normal control 3',\n   [[['T1', 'T4'], ['T5', 'T3'], ['T2', 'T0']],\n    {'T0': 10111, 'T1': 10111, 'T2': 9025, 'T3': 12000, 'T4': 8850, 'T5': 8850}],\n   {'T0': [2, 0, 0], 'T1': [2, 0, 0], 'T2': [0, 2, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [0, 2, 0]}),\n  ('normal control 4',\n   [[['T3', 'T5'], ['T4', 'T7'], ['T0', 'T2'], ['T1', 'T6']],\n    {'T0': 10110, 'T1': 10110, 'T2': 9025, 'T3': 9025, 'T4': 12000, 'T5': 8850, 'T6': 9025, 'T7': 11240}],\n   {'T0': [2, 0, 0],\n    'T1': [2, 0, 0],\n    'T2': [0, 2, 0],\n    'T3': [1, 1, 0],\n    'T4': [2, 0, 0],\n    'T5': [0, 2, 0],\n    'T6': [0, 2, 0],\n    'T7': [1, 1, 0]})],\n [('regression: median tie result',\n   [[['T3', 'T4'], ['T5', 'T1'], ['T0', 'T2']],\n    {'T0': 11240, 'T1': 9025, 'T2': 9025, 'T3': 11240, 'T4': 9025, 'T5': 11240, 'T6': 9025}],\n   {'T0': [2, 0, 0],\n    'T1': [0, 1, 1],\n    'T2': [0, 1, 1],\n    'T3': [2, 0, 0],\n    'T4': [0, 1, 1],\n    'T5': [2, 0, 0],\n    'T6': [0, 0, 1]}),\n  ('partial repair probe: median tie result',\n   [[['T0', 'T1'], ['T5', 'T6'], ['T4', 'T2']],\n    {'T0': 10110, 'T1': 10111, 'T2': 10111, 'T3': 9025, 'T4': 12000, 'T5': 10111, 'T6': 8119}],\n   {'T0': [0, 2, 0],\n    'T1': [1, 0, 1],\n    'T2': [0, 1, 1],\n    'T3': [0, 1, 0],\n    'T4': [2, 0, 0],\n    'T5': [1, 0, 1],\n    'T6': [0, 2, 0]}),\n  ('second regression',\n   [[['T5', 'T4'], ['T2', 'T6'], ['T1', 'T3']],\n    {'T0': 11240, 'T1': 8850, 'T2': 10110, 'T3': 8850, 'T4': 9025, 'T5': 10110, 'T6': 8018}],\n   {'T0': [1, 0, 0],\n    'T1': [0, 1, 1],\n    'T2': [2, 0, 0],\n    'T3': [0, 1, 1],\n    'T4': [0, 1, 1],\n    'T5': [2, 0, 0],\n    'T6': [0, 2, 0]}),\n  ('normal control 1', [[['T2', 'T1'], ['T0', 'T3']], {'T0': 10111, 'T1': 9025, 'T2': 10110, 'T3': 9025}],\n   {'T0': [2, 0, 0], 'T1': [0, 2, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0]}),\n  ('normal control 2',\n   [[['T5', 'T1'], ['T4', 'T0'], ['T2', 'T3']],\n    {'T0': 10110, 'T1': 9025, 'T2': 9025, 'T3': 12000, 'T4': 11240, 'T5': 13052}],\n   {'T0': [0, 2, 0], 'T1': [0, 2, 0], 'T2': [0, 2, 0], 'T3': [2, 0, 0], 'T4': [2, 0, 0], 'T5': [2, 0, 0]}),\n  ('normal control 3', [[['T2', 'T3'], ['T1', 'T0']], {'T0': 8850, 'T1': 12000, 'T2': 10111, 'T3': 9025}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0]}),\n  ('normal control 4',\n   [[['T2', 'T0'], ['T1', 'T5'], ['T3', 'T4']],\n    {'T0': 10110, 'T1': 12000, 'T2': 10696, 'T3': 12000, 'T4': 9025, 'T5': 9025}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [2, 0, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [0, 2, 0]})],\n [('regression: median tie result',\n   [[['T4', 'T3'], ['T0', 'T1']], {'T0': 10111, 'T1': 12000, 'T2': 10110, 'T3': 10110, 'T4': 11240}],\n   {'T0': [0, 1, 1], 'T1': [2, 0, 0], 'T2': [0, 1, 0], 'T3': [0, 2, 0], 'T4': [2, 0, 0]}),\n  ('partial repair probe: median tie result',\n   [[['T4', 'T2'], ['T0', 'T1']], {'T0': 12000, 'T1': 12000, 'T2': 7976, 'T3': 9025, 'T4': 8017}],\n   {'T0': [1, 0, 1], 'T1': [1, 0, 1], 'T2': [0, 2, 0], 'T3': [0, 0, 1], 'T4': [1, 1, 0]}),\n  ('second regression',\n   [[['T1', 'T5'], ['T3', 'T6'], ['T0', 'T4']],\n    {'T0': 9025, 'T1': 9025, 'T2': 10110, 'T3': 9025, 'T4': 9025, 'T5': 9025, 'T6': 10111}],\n   {'T0': [0, 0, 2],\n    'T1': [0, 0, 2],\n    'T2': [1, 0, 0],\n    'T3': [0, 1, 1],\n    'T4': [0, 0, 2],\n    'T5': [0, 0, 2],\n    'T6': [2, 0, 0]}),\n  ('normal control 1',\n   [[['T0', 'T3'], ['T4', 'T1'], ['T2', 'T5']],\n    {'T0': 11240, 'T1': 9025, 'T2': 10110, 'T3': 10111, 'T4': 12000, 'T5': 8850}],\n   {'T0': [2, 0, 0], 'T1': [0, 2, 0], 'T2': [1, 1, 0], 'T3': [1, 1, 0], 'T4': [2, 0, 0], 'T5': [0, 2, 0]}),\n  ('normal control 2', [[['T3', 'T0'], ['T2', 'T1']], {'T0': 10110, 'T1': 10111, 'T2': 9025, 'T3': 11240}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [0, 2, 0], 'T3': [2, 0, 0]}),\n  ('normal control 3',\n   [[['T1', 'T0'], ['T3', 'T4'], ['T2', 'T5']],\n    {'T0': 10111, 'T1': 11240, 'T2': 9025, 'T3': 10151, 'T4': 11240, 'T5': 9025}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [0, 1, 1], 'T3': [1, 1, 0], 'T4': [2, 0, 0], 'T5': [0, 1, 1]}),\n  ('normal control 4',\n   [[['T3', 'T0'], ['T1', 'T2'], ['T4', 'T5']],\n    {'T0': 10110, 'T1': 8850, 'T2': 12820, 'T3': 9025, 'T4': 9233, 'T5': 12000}],\n   {'T0': [2, 0, 0], 'T1': [0, 2, 0], 'T2': [2, 0, 0], 'T3': [0, 2, 0], 'T4': [0, 2, 0], 'T5': [2, 0, 0]})],\n [('regression: median tie result',\n   [[['T2', 'T3'], ['T4', 'T1']], {'T0': 9025, 'T1': 12000, 'T2': 8766, 'T3': 8380, 'T4': 11240}],\n   {'T0': [0, 0, 1], 'T1': [2, 0, 0], 'T2': [1, 1, 0], 'T3': [0, 2, 0], 'T4': [1, 1, 0]}),\n  ('partial repair probe: median tie result',\n   [[['T2', 'T1'], ['T0', 'T3'], ['T6', 'T4'], ['T5', 'T7']],\n    {'T0': 9025, 'T1': 10110, 'T2': 11186, 'T3': 10111, 'T4': 10111, 'T5': 11240, 'T6': 9025, 'T7': 10111}],\n   {'T0': [0, 2, 0],\n    'T1': [0, 2, 0],\n    'T2': [2, 0, 0],\n    'T3': [1, 0, 1],\n    'T4': [1, 0, 1],\n    'T5': [2, 0, 0],\n    'T6': [0, 2, 0],\n    'T7': [0, 1, 1]}),\n  ('second regression',\n   [[['T6', 'T1'], ['T2', 'T0'], ['T5', 'T4']],\n    {'T0': 10111, 'T1': 9025, 'T2': 11996, 'T3': 8850, 'T4': 8850, 'T5': 10110, 'T6': 9025}],\n   {'T0': [1, 1, 0],\n    'T1': [0, 0, 2],\n    'T2': [2, 0, 0],\n    'T3': [0, 1, 0],\n    'T4': [0, 2, 0],\n    'T5': [2, 0, 0],\n    'T6': [0, 0, 2]}),\n  ('normal control 1',\n   [[['T5', 'T4'], ['T7', 'T1'], ['T3', 'T0'], ['T6', 'T2']],\n    {'T0': 11240, 'T1': 12000, 'T2': 9025, 'T3': 9025, 'T4': 9025, 'T5': 10111, 'T6': 8850, 'T7': 11240}],\n   {'T0': [2, 0, 0],\n    'T1': [2, 0, 0],\n    'T2': [1, 1, 0],\n    'T3': [0, 2, 0],\n    'T4': [0, 2, 0],\n    'T5': [2, 0, 0],\n    'T6': [0, 2, 0],\n    'T7': [1, 1, 0]}),\n  ('normal control 2',\n   [[['T0', 'T3'], ['T2', 'T7'], ['T6', 'T5'], ['T4', 'T1']],\n    {'T0': 10110, 'T1': 9025, 'T2': 13675, 'T3': 10111, 'T4': 9025, 'T5': 8506, 'T6': 13138, 'T7': 8850}],\n   {'T0': [1, 1, 0],\n    'T1': [0, 1, 1],\n    'T2': [2, 0, 0],\n    'T3': [2, 0, 0],\n    'T4': [0, 1, 1],\n    'T5': [0, 2, 0],\n    'T6': [2, 0, 0],\n    'T7': [0, 2, 0]}),\n  ('normal control 3', [[['T1', 'T3'], ['T0', 'T2']], {'T0': 8850, 'T1': 11240, 'T2': 10110, 'T3': 12000}],\n   {'T0': [0, 2, 0], 'T1': [1, 1, 0], 'T2': [1, 1, 0], 'T3': [2, 0, 0]}),\n  ('normal control 4',\n   [[['T0', 'T3'], ['T5', 'T1'], ['T2', 'T4']],\n    {'T0': 8850, 'T1': 11822, 'T2': 9025, 'T3': 11032, 'T4': 8317, 'T5': 10111}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [1, 1, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [1, 1, 0]})],\n [('regression: median tie result',\n   [[['T5', 'T2'], ['T3', 'T0'], ['T4', 'T1']],\n    {'T0': 8850, 'T1': 10111, 'T2': 9025, 'T3': 8775, 'T4': 9025, 'T5': 12000}],\n   {'T0': [1, 1, 0], 'T1': [2, 0, 0], 'T2': [0, 1, 1], 'T3': [0, 2, 0], 'T4': [0, 1, 1], 'T5': [2, 0, 0]}),\n  ('partial repair probe: median tie result',\n   [[['T4', 'T1'], ['T0', 'T5'], ['T3', 'T2']],\n    {'T0': 10111, 'T1': 10111, 'T2': 10110, 'T3': 12000, 'T4': 8850, 'T5': 13771}],\n   {'T0': [0, 1, 1], 'T1': [1, 0, 1], 'T2': [0, 2, 0], 'T3': [2, 0, 0], 'T4': [0, 2, 0], 'T5': [2, 0, 0]}),\n  ('second regression',\n   [[['T0', 'T1'], ['T2', 'T4']], {'T0': 10111, 'T1': 11240, 'T2': 8850, 'T3': 10111, 'T4': 10111}],\n   {'T0': [0, 1, 1], 'T1': [2, 0, 0], 'T2': [0, 2, 0], 'T3': [0, 0, 1], 'T4': [1, 0, 1]}),\n  ('normal control 1', [[['T3', 'T0'], ['T2', 'T1']], {'T0': 8850, 'T1': 9025, 'T2': 8850, 'T3': 10110}],\n   {'T0': [0, 2, 0], 'T1': [2, 0, 0], 'T2': [0, 2, 0], 'T3': [2, 0, 0]}),\n  ('normal control 2',\n   [[['T4', 'T0'], ['T2', 'T7'], ['T1', 'T5'], ['T3', 'T6']],\n    {'T0': 10111, 'T1': 12153, 'T2': 10110, 'T3': 11240, 'T4': 11240, 'T5': 9025, 'T6': 12000, 'T7': 10111}],\n   {'T0': [0, 2, 0],\n    'T1': [2, 0, 0],\n    'T2': [0, 2, 0],\n    'T3': [1, 1, 0],\n    'T4': [2, 0, 0],\n    'T5': [0, 2, 0],\n    'T6': [2, 0, 0],\n    'T7': [1, 1, 0]}),\n  ('normal control 3',\n   [[['T2', 'T5'], ['T0', 'T4'], ['T7', 'T6'], ['T1', 'T3']],\n    {'T0': 9025, 'T1': 12000, 'T2': 10111, 'T3': 13608, 'T4': 9025, 'T5': 9025, 'T6': 10110, 'T7': 9025}],\n   {'T0': [0, 1, 1],\n    'T1': [1, 1, 0],\n    'T2': [2, 0, 0],\n    'T3': [2, 0, 0],\n    'T4': [0, 1, 1],\n    'T5': [0, 2, 0],\n    'T6': [2, 0, 0],\n    'T7': [0, 2, 0]}),\n  ('normal control 4',\n   [[['T2', 'T6'], ['T3', 'T7'], ['T4', 'T5'], ['T1', 'T0']],\n    {'T0': 12000, 'T1': 12000, 'T2': 10110, 'T3': 11240, 'T4': 10111, 'T5': 12000, 'T6': 9025, 'T7': 12000}],\n   {'T0': [1, 0, 1],\n    'T1': [1, 0, 1],\n    'T2': [1, 1, 0],\n    'T3': [0, 2, 0],\n    'T4': [0, 2, 0],\n    'T5': [2, 0, 0],\n    'T6': [0, 2, 0],\n    'T7': [2, 0, 0]})]]\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-median-game-record-median-tie-result","generated_at":"2026-09-29T14:50:36.540924+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Median-scoring leagues award a second result each week; the median definition and half-point comparisons decide playoff races.","root_cause":"Equality with the median falls into the loss counter.","sha256":"da4b9a70bad23794f7f243b1e224f4a38c9e872407aa158e6271b80f31993538","title":"Scoring exactly the median recorded as a loss · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":43.039,"exit_code":1,"observations":[{"actual":{"T0":[0,2,0],"T1":[2,0,0],"T2":[1,1,0],"T3":[0,1,1],"T4":[1,0,0],"T5":[2,0,0],"T6":[0,1,1]},"check":"regression: median tie result","expected":{"T0":[0,2,0],"T1":[2,0,0],"T2":[1,1,0],"T3":[0,1,1],"T4":[0,0,1],"T5":[2,0,0],"T6":[0,1,1]},"passed":false},{"actual":{"T0":[1,1,0],"T1":[2,0,0],"T2":[2,0,0],"T3":[0,2,0],"T4":[0,1,0]},"check":"partial repair probe: median tie result","expected":{"T0":[0,1,1],"T1":[2,0,0],"T2":[2,0,0],"T3":[0,2,0],"T4":[0,1,0]},"passed":false},{"actual":{"T0":[2,0,0],"T1":[1,0,1],"T2":[2,0,0],"T3":[1,0,1],"T4":[2,0,0],"T5":[0,2,0],"T6":[1,1,0],"T7":[0,2,0]},"check":"second regression","expected":{"T0":[1,0,1],"T1":[0,0,2],"T2":[2,0,0],"T3":[0,0,2],"T4":[2,0,0],"T5":[0,2,0],"T6":[1,1,0],"T7":[0,2,0]},"passed":false},{"actual":{"T0":[0,2,0],"T1":[0,2,0],"T2":[2,0,0],"T3":[2,0,0],"T4":[0,2,0],"T5":[2,0,0]},"check":"normal control 1","expected":{"T0":[0,2,0],"T1":[0,2,0],"T2":[2,0,0],"T3":[2,0,0],"T4":[0,2,0],"T5":[2,0,0]},"passed":true},{"actual":{"T0":[1,1,0],"T1":[2,0,0],"T2":[2,0,0],"T3":[0,2,0],"T4":[1,1,0],"T5":[0,2,0]},"check":"normal control 2","expected":{"T0":[1,1,0],"T1":[2,0,0],"T2":[2,0,0],"T3":[0,2,0],"T4":[1,1,0],"T5":[0,2,0]},"passed":true},{"actual":{"T0":[2,0,0],"T1":[2,0,0],"T2":[0,2,0],"T3":[2,0,0],"T4":[0,2,0],"T5":[0,2,0]},"check":"normal control 3","expected":{"T0":[2,0,0],"T1":[2,0,0],"T2":[0,2,0],"T3":[2,0,0],"T4":[0,2,0],"T5":[0,2,0]},"passed":true},{"actual":{"T0":[2,0,0],"T1":[2,0,0],"T2":[0,2,0],"T3":[1,1,0],"T4":[2,0,0],"T5":[0,2,0],"T6":[0,2,0],"T7":[1,1,0]},"check":"normal control 4","expected":{"T0":[2,0,0],"T1":[2,0,0],"T2":[0,2,0],"T3":[1,1,0],"T4":[2,0,0],"T5":[0,2,0],"T6":[0,2,0],"T7":[1,1,0]},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: median tie result\", \"actual\": {\"T0\": [0, 2, 0], \"T1\": [2, 0, 0], \"T2\": [1, 1, 0], \"T3\": [0, 1, 1], \"T4\": [1, 0, 0], \"T5\": [2, 0, 0], \"T6\": [0, 1, 1]}, \"expected\": {\"T0\": [0, 2, 0], \"T1\": [2, 0, 0], \"T2\": [1, 1, 0], \"T3\": [0, 1, 1], \"T4\": [0, 0, 1], \"T5\": [2, 0, 0], \"T6\": [0, 1, 1]}, \"passed\": false}, {\"check\": \"partial repair probe: median tie result\", \"actual\": {\"T0\": [1, 1, 0], \"T1\": [2, 0, 0], \"T2\": [2, 0, 0], \"T3\": [0, 2, 0], \"T4\": [0, 1, 0]}, \"expected\": {\"T0\": [0, 1, 1], \"T1\": [2, 0, 0], \"T2\": [2, 0, 0], \"T3\": [0, 2, 0], \"T4\": [0, 1, 0]}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"T0\": [2, 0, 0], \"T1\": [1, 0, 1], \"T2\": [2, 0, 0], \"T3\": [1, 0, 1], \"T4\": [2, 0, 0], \"T5\": [0, 2, 0], \"T6\": [1, 1, 0], \"T7\": [0, 2, 0]}, \"expected\": {\"T0\": [1, 0, 1], \"T1\": [0, 0, 2], \"T2\": [2, 0, 0], \"T3\": [0, 0, 2], \"T4\": [2, 0, 0], \"T5\": [0, 2, 0], \"T6\": [1, 1, 0], \"T7\": [0, 2, 0]}, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": {\"T0\": [0, 2, 0], \"T1\": [0, 2, 0], \"T2\": [2, 0, 0], \"T3\": [2, 0, 0], \"T4\": [0, 2, 0], \"T5\": [2, 0, 0]}, \"expected\": {\"T0\": [0, 2, 0], \"T1\": [0, 2, 0], \"T2\": [2, 0, 0], \"T3\": [2, 0, 0], \"T4\": [0, 2, 0], \"T5\": [2, 0, 0]}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"T0\": [1, 1, 0], \"T1\": [2, 0, 0], \"T2\": [2, 0, 0], \"T3\": [0, 2, 0], \"T4\": [1, 1, 0], \"T5\": [0, 2, 0]}, \"expected\": {\"T0\": [1, 1, 0], \"T1\": [2, 0, 0], \"T2\": [2, 0, 0], \"T3\": [0, 2, 0], \"T4\": [1, 1, 0], \"T5\": [0, 2, 0]}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"T0\": [2, 0, 0], \"T1\": [2, 0, 0], \"T2\": [0, 2, 0], \"T3\": [2, 0, 0], \"T4\": [0, 2, 0], \"T5\": [0, 2, 0]}, \"expected\": {\"T0\": [2, 0, 0], \"T1\": [2, 0, 0], \"T2\": [0, 2, 0], \"T3\": [2, 0, 0], \"T4\": [0, 2, 0], \"T5\": [0, 2, 0]}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"T0\": [2, 0, 0], \"T1\": [2, 0, 0], \"T2\": [0, 2, 0], \"T3\": [1, 1, 0], \"T4\": [2, 0, 0], \"T5\": [0, 2, 0], \"T6\": [0, 2, 0], \"T7\": [1, 1, 0]}, \"expected\": {\"T0\": [2, 0, 0], \"T1\": [2, 0, 0], \"T2\": [0, 2, 0], \"T3\": [1, 1, 0], \"T4\": [2, 0, 0], \"T5\": [0, 2, 0], \"T6\": [0, 2, 0], \"T7\": [1, 1, 0]}, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":45.447,"exit_code":1,"observations":[{"actual":{"T0":[0,2,0],"T1":[2,0,0],"T2":[1,1,0],"T3":[0,1,1],"T4":[0,1,0],"T5":[2,0,0],"T6":[0,1,1]},"check":"regression: median tie result","expected":{"T0":[0,2,0],"T1":[2,0,0],"T2":[1,1,0],"T3":[0,1,1],"T4":[0,0,1],"T5":[2,0,0],"T6":[0,1,1]},"passed":false},{"actual":{"T0":[0,2,0],"T1":[2,0,0],"T2":[2,0,0],"T3":[0,2,0],"T4":[0,1,0]},"check":"partial repair probe: median tie result","expected":{"T0":[0,1,1],"T1":[2,0,0],"T2":[2,0,0],"T3":[0,2,0],"T4":[0,1,0]},"passed":false},{"actual":{"T0":[1,1,0],"T1":[0,1,1],"T2":[2,0,0],"T3":[0,1,1],"T4":[2,0,0],"T5":[0,2,0],"T6":[1,1,0],"T7":[0,2,0]},"check":"second 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4","expected":{"T0":[2,0,0],"T1":[2,0,0],"T2":[0,2,0],"T3":[1,1,0],"T4":[2,0,0],"T5":[0,2,0],"T6":[0,2,0],"T7":[1,1,0]},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: median tie result\", \"actual\": {\"T0\": [0, 2, 0], \"T1\": [2, 0, 0], \"T2\": [1, 1, 0], \"T3\": [0, 1, 1], \"T4\": [0, 1, 0], \"T5\": [2, 0, 0], \"T6\": [0, 1, 1]}, \"expected\": {\"T0\": [0, 2, 0], \"T1\": [2, 0, 0], \"T2\": [1, 1, 0], \"T3\": [0, 1, 1], \"T4\": [0, 0, 1], \"T5\": [2, 0, 0], \"T6\": [0, 1, 1]}, \"passed\": false}, {\"check\": \"partial repair probe: median tie result\", \"actual\": {\"T0\": [0, 2, 0], \"T1\": [2, 0, 0], \"T2\": [2, 0, 0], \"T3\": [0, 2, 0], \"T4\": [0, 1, 0]}, \"expected\": {\"T0\": [0, 1, 1], \"T1\": [2, 0, 0], \"T2\": [2, 0, 0], \"T3\": [0, 2, 0], \"T4\": [0, 1, 0]}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"T0\": [1, 1, 0], \"T1\": [0, 1, 1], \"T2\": [2, 0, 0], \"T3\": [0, 1, 1], \"T4\": [2, 0, 0], \"T5\": [0, 2, 0], \"T6\": [1, 1, 0], \"T7\": [0, 2, 0]}, \"expected\": {\"T0\": [1, 0, 1], \"T1\": [0, 0, 2], \"T2\": [2, 0, 0], \"T3\": [0, 0, 2], \"T4\": [2, 0, 0], \"T5\": [0, 2, 0], \"T6\": [1, 1, 0], \"T7\": [0, 2, 0]}, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": {\"T0\": [0, 2, 0], \"T1\": [0, 2, 0], \"T2\": [2, 0, 0], \"T3\": [2, 0, 0], \"T4\": [0, 2, 0], \"T5\": [2, 0, 0]}, \"expected\": {\"T0\": [0, 2, 0], \"T1\": [0, 2, 0], \"T2\": [2, 0, 0], \"T3\": [2, 0, 0], \"T4\": [0, 2, 0], \"T5\": [2, 0, 0]}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"T0\": [1, 1, 0], \"T1\": [2, 0, 0], \"T2\": [2, 0, 0], \"T3\": [0, 2, 0], \"T4\": [1, 1, 0], \"T5\": [0, 2, 0]}, \"expected\": {\"T0\": [1, 1, 0], \"T1\": [2, 0, 0], \"T2\": [2, 0, 0], \"T3\": [0, 2, 0], \"T4\": [1, 1, 0], \"T5\": [0, 2, 0]}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"T0\": [2, 0, 0], \"T1\": [2, 0, 0], \"T2\": [0, 2, 0], \"T3\": [2, 0, 0], \"T4\": [0, 2, 0], \"T5\": [0, 2, 0]}, \"expected\": {\"T0\": [2, 0, 0], \"T1\": [2, 0, 0], \"T2\": [0, 2, 0], \"T3\": [2, 0, 0], \"T4\": [0, 2, 0], \"T5\": [0, 2, 0]}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"T0\": [2, 0, 0], \"T1\": [2, 0, 0], \"T2\": [0, 2, 0], \"T3\": [1, 1, 0], \"T4\": [2, 0, 0], \"T5\": [0, 2, 0], \"T6\": [0, 2, 0], \"T7\": [1, 1, 0]}, \"expected\": {\"T0\": [2, 0, 0], \"T1\": [2, 0, 0], \"T2\": [0, 2, 0], \"T3\": [1, 1, 0], \"T4\": [2, 0, 0], \"T5\": [0, 2, 0], \"T6\": [0, 2, 0], \"T7\": [1, 1, 0]}, \"passed\": true}], \"passed\": false}\n"}},"member_only":{"stages":["fixed"],"fields":["implementations.fixed","verification.fixed","harness","repair"],"note":"The verified repair, its recorded checks, the repair description, and the scoring harness are available to members."}}