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FA-85121 / Fantasy sports scoring / Open access

Triple-double also collects the double-double bonus · case 01

Every triple-double scores 4.5 bonus points instead of 3.

Verified by executionVariant 1 · 7 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The double-double branch is an independent if with >= 2.

VERIFIED REPAIR

Award exactly one bonus tier.

Unsuccessful approach: Still stacks both bonuses for quadruple-doubles.

Case 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.

Why this case matters

Double-double and triple-double bonuses are exclusive tiers in points leagues and are frequently double-awarded.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(line, bonus):
    line = dict(line, reb=line['oreb'] + line['dreb'])
    w = {'pts': 10, 'reb': 12, 'ast': 15, 'stl': 30, 'blk': 30, 'tov': -10, 'fg3m': 5}
    score = sum(w[k] * line[k] for k in w)
    doubles = sum(1 for k in ('pts', 'reb', 'ast', 'stl', 'blk') if line[k] >= 10)
    if doubles >= 3:
        score += bonus['td']
    if doubles >= 2:
        score += bonus['dd']
    return score
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: bonus exclusivity',
   [{'ast': 5, 'blk': 10, 'dreb': 8, 'fg3m': 0, 'oreb': 3, 'pts': 10, 'stl': 10, 'tov': 0},
    {'dd': 15, 'td': 30}],
   937),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 11, 'dreb': 8, 'fg3m': 1, 'oreb': 5, 'pts': 11, 'stl': 10, 'tov': 6},
    {'dd': 15, 'td': 30}],
   1021),
  ('second regression',
   [{'ast': 10, 'blk': 10, 'dreb': 5, 'fg3m': 0, 'oreb': 2, 'pts': 14, 'stl': 3, 'tov': 3},
    {'dd': 15, 'td': 30}],
   764),
  ('normal control 1',
   [{'ast': 9, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 27, 'stl': 1, 'tov': 0},
    {'dd': 15, 'td': 30}],
   658),
  ('normal control 2',
   [{'ast': 7, 'blk': 0, 'dreb': 8, 'fg3m': 0, 'oreb': 1, 'pts': 10, 'stl': 0, 'tov': 5},
    {'dd': 15, 'td': 30}],
   263),
  ('normal control 3',
   [{'ast': 3, 'blk': 0, 'dreb': 4, 'fg3m': 2, 'oreb': 3, 'pts': 10, 'stl': 0, 'tov': 0},
    {'dd': 15, 'td': 30}],
   239),
  ('normal control 4',
   [{'ast': 10, 'blk': 2, 'dreb': 1, 'fg3m': 6, 'oreb': 5, 'pts': 20, 'stl': 1, 'tov': 4},
    {'dd': 15, 'td': 30}],
   517)],
 [('regression: bonus exclusivity',
   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 19, 'stl': 2, 'tov': 3},
    {'dd': 15, 'td': 30}],
   613),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 6, 'oreb': 4, 'pts': 10, 'stl': 10, 'tov': 3},
    {'dd': 15, 'td': 30}],
   754),
  ('second regression',
   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 5, 'oreb': 1, 'pts': 14, 'stl': 0, 'tov': 6},
    {'dd': 15, 'td': 30}],
   720),
  ('normal control 1',
   [{'ast': 2, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 6, 'pts': 21, 'stl': 1, 'tov': 5},
    {'dd': 15, 'td': 30}],
   505),
  ('normal control 2',
   [{'ast': 10, 'blk': 10, 'dreb': 4, 'fg3m': 1, 'oreb': 1, 'pts': 0, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   540),
  ('normal control 3',
   [{'ast': 0, 'blk': 0, 'dreb': 10, 'fg3m': 3, 'oreb': 2, 'pts': 10, 'stl': 3, 'tov': 4},
    {'dd': 15, 'td': 30}],
   324),
  ('normal control 4',
   [{'ast': 2, 'blk': 1, 'dreb': 7, 'fg3m': 4, 'oreb': 2, 'pts': 11, 'stl': 3, 'tov': 5},
    {'dd': 15, 'td': 30}],
   338)],
 [('regression: bonus exclusivity',
   [{'ast': 10, 'blk': 0, 'dreb': 9, 'fg3m': 3, 'oreb': 1, 'pts': 10, 'stl': 3, 'tov': 1},
    {'dd': 15, 'td': 30}],
   495),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 11, 'dreb': 7, 'fg3m': 5, 'oreb': 4, 'pts': 10, 'stl': 3, 'tov': 5},
    {'dd': 15, 'td': 30}],
   807),
  ('second regression',
   [{'ast': 7, 'blk': 10, 'dreb': 5, 'fg3m': 4, 'oreb': 6, 'pts': 36, 'stl': 2, 'tov': 2},
    {'dd': 15, 'td': 30}],
   987),
  ('normal control 1',
   [{'ast': 9, 'blk': 0, 'dreb': 9, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 2, 'tov': 1},
    {'dd': 15, 'td': 30}],
   486),
  ('normal control 2',
   [{'ast': 11, 'blk': 1, 'dreb': 4, 'fg3m': 2, 'oreb': 1, 'pts': 9, 'stl': 3, 'tov': 2},
    {'dd': 15, 'td': 30}],
   425),
  ('normal control 3',
   [{'ast': 12, 'blk': 1, 'dreb': 8, 'fg3m': 5, 'oreb': 6, 'pts': 9, 'stl': 2, 'tov': 0},
    {'dd': 15, 'td': 30}],
   568),
  ('normal control 4',
   [{'ast': 9, 'blk': 10, 'dreb': 5, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 3, 'tov': 2},
    {'dd': 15, 'td': 30}],
   715)],
 [('regression: bonus exclusivity',
   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 6, 'oreb': 5, 'pts': 14, 'stl': 1, 'tov': 1},
    {'dd': 15, 'td': 30}],
   853),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 10, 'stl': 10, 'tov': 0},
    {'dd': 15, 'td': 30}],
   793),
  ('second regression',
   [{'ast': 13, 'blk': 0, 'dreb': 12, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 5},
    {'dd': 15, 'td': 30}],
   474),
  ('normal control 1',
   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 0, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 0},
    {'dd': 15, 'td': 30}],
   421),
  ('normal control 2',
   [{'ast': 9, 'blk': 1, 'dreb': 2, 'fg3m': 2, 'oreb': 1, 'pts': 10, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   321),
  ('normal control 3',
   [{'ast': 10, 'blk': 0, 'dreb': 5, 'fg3m': 2, 'oreb': 5, 'pts': 6, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   365),
  ('normal control 4',
   [{'ast': 9, 'blk': 0, 'dreb': 10, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   424)],
 [('regression: bonus exclusivity',
   [{'ast': 10, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 1, 'pts': 11, 'stl': 1, 'tov': 0},
    {'dd': 15, 'td': 30}],
   530),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 13, 'blk': 11, 'dreb': 10, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   810),
  ('second regression',
   [{'ast': 11, 'blk': 10, 'dreb': 2, 'fg3m': 1, 'oreb': 3, 'pts': 34, 'stl': 0, 'tov': 0},
    {'dd': 15, 'td': 30}],
   900),
  ('normal control 1',
   [{'ast': 9, 'blk': 11, 'dreb': 4, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 2, 'tov': 3},
    {'dd': 15, 'td': 30}],
   702),
  ('normal control 2',
   [{'ast': 10, 'blk': 2, 'dreb': 4, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 1, 'tov': 6},
    {'dd': 15, 'td': 30}],
   378),
  ('normal control 3',
   [{'ast': 11, 'blk': 2, 'dreb': 5, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 0, 'tov': 5},
    {'dd': 15, 'td': 30}],
   428),
  ('normal control 4',
   [{'ast': 5, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 10, 'stl': 2, 'tov': 6},
    {'dd': 15, 'td': 30}],
   398)]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression: bonus exclusivity952937Failed
partial repair probe: bonus exclusivity10361021Failed
second regression779764Failed
normal control 1658658Passed
normal control 2263263Passed
normal control 3239239Passed
normal control 4517517Passed

SHA-256 / 46935cfc9364638645b200b49dda567b1e2a5f5226e1f4526bacb28424b09129

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(line, bonus):
    line = dict(line, reb=line['oreb'] + line['dreb'])
    w = {'pts': 10, 'reb': 12, 'ast': 15, 'stl': 30, 'blk': 30, 'tov': -10, 'fg3m': 5}
    score = sum(w[k] * line[k] for k in w)
    doubles = sum(1 for k in ('pts', 'reb', 'ast', 'stl', 'blk') if line[k] >= 10)
    if doubles >= 3:
        score += bonus['td']
    if doubles == 2 or doubles > 3:
        score += bonus['dd']
    return score
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: bonus exclusivity',
   [{'ast': 5, 'blk': 10, 'dreb': 8, 'fg3m': 0, 'oreb': 3, 'pts': 10, 'stl': 10, 'tov': 0},
    {'dd': 15, 'td': 30}],
   937),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 11, 'dreb': 8, 'fg3m': 1, 'oreb': 5, 'pts': 11, 'stl': 10, 'tov': 6},
    {'dd': 15, 'td': 30}],
   1021),
  ('second regression',
   [{'ast': 10, 'blk': 10, 'dreb': 5, 'fg3m': 0, 'oreb': 2, 'pts': 14, 'stl': 3, 'tov': 3},
    {'dd': 15, 'td': 30}],
   764),
  ('normal control 1',
   [{'ast': 9, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 27, 'stl': 1, 'tov': 0},
    {'dd': 15, 'td': 30}],
   658),
  ('normal control 2',
   [{'ast': 7, 'blk': 0, 'dreb': 8, 'fg3m': 0, 'oreb': 1, 'pts': 10, 'stl': 0, 'tov': 5},
    {'dd': 15, 'td': 30}],
   263),
  ('normal control 3',
   [{'ast': 3, 'blk': 0, 'dreb': 4, 'fg3m': 2, 'oreb': 3, 'pts': 10, 'stl': 0, 'tov': 0},
    {'dd': 15, 'td': 30}],
   239),
  ('normal control 4',
   [{'ast': 10, 'blk': 2, 'dreb': 1, 'fg3m': 6, 'oreb': 5, 'pts': 20, 'stl': 1, 'tov': 4},
    {'dd': 15, 'td': 30}],
   517)],
 [('regression: bonus exclusivity',
   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 19, 'stl': 2, 'tov': 3},
    {'dd': 15, 'td': 30}],
   613),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 6, 'oreb': 4, 'pts': 10, 'stl': 10, 'tov': 3},
    {'dd': 15, 'td': 30}],
   754),
  ('second regression',
   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 5, 'oreb': 1, 'pts': 14, 'stl': 0, 'tov': 6},
    {'dd': 15, 'td': 30}],
   720),
  ('normal control 1',
   [{'ast': 2, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 6, 'pts': 21, 'stl': 1, 'tov': 5},
    {'dd': 15, 'td': 30}],
   505),
  ('normal control 2',
   [{'ast': 10, 'blk': 10, 'dreb': 4, 'fg3m': 1, 'oreb': 1, 'pts': 0, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   540),
  ('normal control 3',
   [{'ast': 0, 'blk': 0, 'dreb': 10, 'fg3m': 3, 'oreb': 2, 'pts': 10, 'stl': 3, 'tov': 4},
    {'dd': 15, 'td': 30}],
   324),
  ('normal control 4',
   [{'ast': 2, 'blk': 1, 'dreb': 7, 'fg3m': 4, 'oreb': 2, 'pts': 11, 'stl': 3, 'tov': 5},
    {'dd': 15, 'td': 30}],
   338)],
 [('regression: bonus exclusivity',
   [{'ast': 10, 'blk': 0, 'dreb': 9, 'fg3m': 3, 'oreb': 1, 'pts': 10, 'stl': 3, 'tov': 1},
    {'dd': 15, 'td': 30}],
   495),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 11, 'dreb': 7, 'fg3m': 5, 'oreb': 4, 'pts': 10, 'stl': 3, 'tov': 5},
    {'dd': 15, 'td': 30}],
   807),
  ('second regression',
   [{'ast': 7, 'blk': 10, 'dreb': 5, 'fg3m': 4, 'oreb': 6, 'pts': 36, 'stl': 2, 'tov': 2},
    {'dd': 15, 'td': 30}],
   987),
  ('normal control 1',
   [{'ast': 9, 'blk': 0, 'dreb': 9, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 2, 'tov': 1},
    {'dd': 15, 'td': 30}],
   486),
  ('normal control 2',
   [{'ast': 11, 'blk': 1, 'dreb': 4, 'fg3m': 2, 'oreb': 1, 'pts': 9, 'stl': 3, 'tov': 2},
    {'dd': 15, 'td': 30}],
   425),
  ('normal control 3',
   [{'ast': 12, 'blk': 1, 'dreb': 8, 'fg3m': 5, 'oreb': 6, 'pts': 9, 'stl': 2, 'tov': 0},
    {'dd': 15, 'td': 30}],
   568),
  ('normal control 4',
   [{'ast': 9, 'blk': 10, 'dreb': 5, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 3, 'tov': 2},
    {'dd': 15, 'td': 30}],
   715)],
 [('regression: bonus exclusivity',
   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 6, 'oreb': 5, 'pts': 14, 'stl': 1, 'tov': 1},
    {'dd': 15, 'td': 30}],
   853),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 10, 'stl': 10, 'tov': 0},
    {'dd': 15, 'td': 30}],
   793),
  ('second regression',
   [{'ast': 13, 'blk': 0, 'dreb': 12, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 5},
    {'dd': 15, 'td': 30}],
   474),
  ('normal control 1',
   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 0, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 0},
    {'dd': 15, 'td': 30}],
   421),
  ('normal control 2',
   [{'ast': 9, 'blk': 1, 'dreb': 2, 'fg3m': 2, 'oreb': 1, 'pts': 10, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   321),
  ('normal control 3',
   [{'ast': 10, 'blk': 0, 'dreb': 5, 'fg3m': 2, 'oreb': 5, 'pts': 6, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   365),
  ('normal control 4',
   [{'ast': 9, 'blk': 0, 'dreb': 10, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   424)],
 [('regression: bonus exclusivity',
   [{'ast': 10, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 1, 'pts': 11, 'stl': 1, 'tov': 0},
    {'dd': 15, 'td': 30}],
   530),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 13, 'blk': 11, 'dreb': 10, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   810),
  ('second regression',
   [{'ast': 11, 'blk': 10, 'dreb': 2, 'fg3m': 1, 'oreb': 3, 'pts': 34, 'stl': 0, 'tov': 0},
    {'dd': 15, 'td': 30}],
   900),
  ('normal control 1',
   [{'ast': 9, 'blk': 11, 'dreb': 4, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 2, 'tov': 3},
    {'dd': 15, 'td': 30}],
   702),
  ('normal control 2',
   [{'ast': 10, 'blk': 2, 'dreb': 4, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 1, 'tov': 6},
    {'dd': 15, 'td': 30}],
   378),
  ('normal control 3',
   [{'ast': 11, 'blk': 2, 'dreb': 5, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 0, 'tov': 5},
    {'dd': 15, 'td': 30}],
   428),
  ('normal control 4',
   [{'ast': 5, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 10, 'stl': 2, 'tov': 6},
    {'dd': 15, 'td': 30}],
   398)]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression: bonus exclusivity952937Failed
partial repair probe: bonus exclusivity10361021Failed
second regression764764Passed
normal control 1658658Passed
normal control 2263263Passed
normal control 3239239Passed
normal control 4517517Passed

SHA-256 / aeda64850f88537d78006a0e463bfc1a2e0b4df0819596e3377c8712267f3076

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(line, bonus):
    line = dict(line, reb=line['oreb'] + line['dreb'])
    w = {'pts': 10, 'reb': 12, 'ast': 15, 'stl': 30, 'blk': 30, 'tov': -10, 'fg3m': 5}
    score = sum(w[k] * line[k] for k in w)
    doubles = sum(1 for k in ('pts', 'reb', 'ast', 'stl', 'blk') if line[k] >= 10)
    if doubles >= 3:
        score += bonus['td']
    elif doubles == 2:
        score += bonus['dd']
    return score
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: bonus exclusivity',
   [{'ast': 5, 'blk': 10, 'dreb': 8, 'fg3m': 0, 'oreb': 3, 'pts': 10, 'stl': 10, 'tov': 0},
    {'dd': 15, 'td': 30}],
   937),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 11, 'dreb': 8, 'fg3m': 1, 'oreb': 5, 'pts': 11, 'stl': 10, 'tov': 6},
    {'dd': 15, 'td': 30}],
   1021),
  ('second regression',
   [{'ast': 10, 'blk': 10, 'dreb': 5, 'fg3m': 0, 'oreb': 2, 'pts': 14, 'stl': 3, 'tov': 3},
    {'dd': 15, 'td': 30}],
   764),
  ('normal control 1',
   [{'ast': 9, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 27, 'stl': 1, 'tov': 0},
    {'dd': 15, 'td': 30}],
   658),
  ('normal control 2',
   [{'ast': 7, 'blk': 0, 'dreb': 8, 'fg3m': 0, 'oreb': 1, 'pts': 10, 'stl': 0, 'tov': 5},
    {'dd': 15, 'td': 30}],
   263),
  ('normal control 3',
   [{'ast': 3, 'blk': 0, 'dreb': 4, 'fg3m': 2, 'oreb': 3, 'pts': 10, 'stl': 0, 'tov': 0},
    {'dd': 15, 'td': 30}],
   239),
  ('normal control 4',
   [{'ast': 10, 'blk': 2, 'dreb': 1, 'fg3m': 6, 'oreb': 5, 'pts': 20, 'stl': 1, 'tov': 4},
    {'dd': 15, 'td': 30}],
   517)],
 [('regression: bonus exclusivity',
   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 19, 'stl': 2, 'tov': 3},
    {'dd': 15, 'td': 30}],
   613),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 6, 'oreb': 4, 'pts': 10, 'stl': 10, 'tov': 3},
    {'dd': 15, 'td': 30}],
   754),
  ('second regression',
   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 5, 'oreb': 1, 'pts': 14, 'stl': 0, 'tov': 6},
    {'dd': 15, 'td': 30}],
   720),
  ('normal control 1',
   [{'ast': 2, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 6, 'pts': 21, 'stl': 1, 'tov': 5},
    {'dd': 15, 'td': 30}],
   505),
  ('normal control 2',
   [{'ast': 10, 'blk': 10, 'dreb': 4, 'fg3m': 1, 'oreb': 1, 'pts': 0, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   540),
  ('normal control 3',
   [{'ast': 0, 'blk': 0, 'dreb': 10, 'fg3m': 3, 'oreb': 2, 'pts': 10, 'stl': 3, 'tov': 4},
    {'dd': 15, 'td': 30}],
   324),
  ('normal control 4',
   [{'ast': 2, 'blk': 1, 'dreb': 7, 'fg3m': 4, 'oreb': 2, 'pts': 11, 'stl': 3, 'tov': 5},
    {'dd': 15, 'td': 30}],
   338)],
 [('regression: bonus exclusivity',
   [{'ast': 10, 'blk': 0, 'dreb': 9, 'fg3m': 3, 'oreb': 1, 'pts': 10, 'stl': 3, 'tov': 1},
    {'dd': 15, 'td': 30}],
   495),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 11, 'dreb': 7, 'fg3m': 5, 'oreb': 4, 'pts': 10, 'stl': 3, 'tov': 5},
    {'dd': 15, 'td': 30}],
   807),
  ('second regression',
   [{'ast': 7, 'blk': 10, 'dreb': 5, 'fg3m': 4, 'oreb': 6, 'pts': 36, 'stl': 2, 'tov': 2},
    {'dd': 15, 'td': 30}],
   987),
  ('normal control 1',
   [{'ast': 9, 'blk': 0, 'dreb': 9, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 2, 'tov': 1},
    {'dd': 15, 'td': 30}],
   486),
  ('normal control 2',
   [{'ast': 11, 'blk': 1, 'dreb': 4, 'fg3m': 2, 'oreb': 1, 'pts': 9, 'stl': 3, 'tov': 2},
    {'dd': 15, 'td': 30}],
   425),
  ('normal control 3',
   [{'ast': 12, 'blk': 1, 'dreb': 8, 'fg3m': 5, 'oreb': 6, 'pts': 9, 'stl': 2, 'tov': 0},
    {'dd': 15, 'td': 30}],
   568),
  ('normal control 4',
   [{'ast': 9, 'blk': 10, 'dreb': 5, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 3, 'tov': 2},
    {'dd': 15, 'td': 30}],
   715)],
 [('regression: bonus exclusivity',
   [{'ast': 11, 'blk': 10, 'dreb': 9, 'fg3m': 6, 'oreb': 5, 'pts': 14, 'stl': 1, 'tov': 1},
    {'dd': 15, 'td': 30}],
   853),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 10, 'blk': 1, 'dreb': 9, 'fg3m': 3, 'oreb': 5, 'pts': 10, 'stl': 10, 'tov': 0},
    {'dd': 15, 'td': 30}],
   793),
  ('second regression',
   [{'ast': 13, 'blk': 0, 'dreb': 12, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 5},
    {'dd': 15, 'td': 30}],
   474),
  ('normal control 1',
   [{'ast': 10, 'blk': 1, 'dreb': 8, 'fg3m': 0, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 0},
    {'dd': 15, 'td': 30}],
   421),
  ('normal control 2',
   [{'ast': 9, 'blk': 1, 'dreb': 2, 'fg3m': 2, 'oreb': 1, 'pts': 10, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   321),
  ('normal control 3',
   [{'ast': 10, 'blk': 0, 'dreb': 5, 'fg3m': 2, 'oreb': 5, 'pts': 6, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   365),
  ('normal control 4',
   [{'ast': 9, 'blk': 0, 'dreb': 10, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   424)],
 [('regression: bonus exclusivity',
   [{'ast': 10, 'blk': 2, 'dreb': 9, 'fg3m': 6, 'oreb': 1, 'pts': 11, 'stl': 1, 'tov': 0},
    {'dd': 15, 'td': 30}],
   530),
  ('partial repair probe: bonus exclusivity',
   [{'ast': 13, 'blk': 11, 'dreb': 10, 'fg3m': 5, 'oreb': 0, 'pts': 10, 'stl': 1, 'tov': 2},
    {'dd': 15, 'td': 30}],
   810),
  ('second regression',
   [{'ast': 11, 'blk': 10, 'dreb': 2, 'fg3m': 1, 'oreb': 3, 'pts': 34, 'stl': 0, 'tov': 0},
    {'dd': 15, 'td': 30}],
   900),
  ('normal control 1',
   [{'ast': 9, 'blk': 11, 'dreb': 4, 'fg3m': 2, 'oreb': 2, 'pts': 11, 'stl': 2, 'tov': 3},
    {'dd': 15, 'td': 30}],
   702),
  ('normal control 2',
   [{'ast': 10, 'blk': 2, 'dreb': 4, 'fg3m': 5, 'oreb': 0, 'pts': 11, 'stl': 1, 'tov': 6},
    {'dd': 15, 'td': 30}],
   378),
  ('normal control 3',
   [{'ast': 11, 'blk': 2, 'dreb': 5, 'fg3m': 4, 'oreb': 4, 'pts': 11, 'stl': 0, 'tov': 5},
    {'dd': 15, 'td': 30}],
   428),
  ('normal control 4',
   [{'ast': 5, 'blk': 1, 'dreb': 10, 'fg3m': 2, 'oreb': 4, 'pts': 10, 'stl': 2, 'tov': 6},
    {'dd': 15, 'td': 30}],
   398)]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression: bonus exclusivity937937Passed
partial repair probe: bonus exclusivity10211021Passed
second regression764764Passed
normal control 1658658Passed
normal control 2263263Passed
normal control 3239239Passed
normal control 4517517Passed

SHA-256 / 2fb632f761978ea9d2869d1823d57e2cac9de86e6ca6c4372744942a254fb6f2

Verification & scope

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.

Observations recorded using Python 3.12.14 at 2026-09-29T14:50:37.396105+00:00.

Case digest / bebb77032e1863f6fb34a41410a8d6d82fe1a03da202c74692ab1325d3b3bb49