FA-85281 / Fantasy sports scoring / Open access
Birdie streak bonus repeated on every extra birdie · case 01
Five straight birdies earn three streak bonuses.
ROOT CAUSE
The streak bonus fires on every hole once the run reaches three.
VERIFIED REPAIR
Award the bonus once when a run first reaches three.
Unsuccessful approach: Firing at every multiple of three still pays a six-hole run twice.
Case contract
Score a golf round given [par, strokes] per hole, in tenths: albatross or better 13, eagle 8, birdie 3, par 0.5, bogey -0.5, double bogey or worse -1; any hole-in-one earns +5 on top. Each maximal run of three or more consecutive birdie-or-better holes earns one 3 point streak bonus. A complete 18-hole round with no bogey or worse earns +3; a complete 18-hole round under 70 strokes earns +5.
Why this case matters
Golf fantasy streak and round bonuses depend on precise run detection and completion conditions.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(holes):
pts = 0
run = 0
streaks = 0
for par, strokes in holes:
d = strokes - par
if d <= -3:
pts += 130
elif d == -2:
pts += 80
elif d == -1:
pts += 30
elif d == 0:
pts += 5
elif d == 1:
pts -= 5
else:
pts -= 10
if strokes == 1:
pts += 50
if d < 0:
run += 1
if run >= 3:
streaks += 1
else:
run = 0
pts += 30 * streaks
if len(holes) == 18 and all(s - p <= 0 for p, s in holes):
pts += 30
if len(holes) == 18 and sum(s for _, s in holes) < 70:
pts += 50
return pts
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: streak counted per hole',
[[[3, 3], [5, 5], [3, 1], [3, 3], [5, 7], [3, 2], [4, 2], [3, 2], [4, 3], [3, 2], [4, 6], [3, 2], [4, 2],
[4, 3]]],
525),
('partial repair probe: streak counted per hole',
[[[3, 2], [5, 4], [4, 4], [4, 4], [4, 4], [4, 4], [4, 2], [5, 4], [3, 2], [4, 4], [4, 3], [3, 2], [5, 1],
[4, 3], [3, 1], [3, 1], [5, 5], [5, 5]]],
905),
('second regression',
[[[4, 2], [3, 5], [4, 4], [5, 3], [4, 3], [4, 3], [4, 3], [5, 7], [4, 4], [5, 5], [3, 3], [4, 4], [4, 4],
[4, 4], [4, 3], [4, 4], [4, 4], [3, 3]]],
390),
('normal control 1', [[[5, 5], [5, 7], [3, 2], [4, 4], [5, 5], [4, 4], [5, 4], [3, 5], [4, 6]]], 50),
('normal control 2',
[[[4, 4], [3, 3], [4, 3], [4, 6], [4, 3], [3, 3], [3, 4], [4, 3], [4, 4], [4, 2], [5, 5], [3, 3], [3, 2],
[4, 4], [5, 5], [5, 6], [4, 4], [4, 4]]],
280),
('normal control 3', [[[4, 3], [3, 2], [4, 4], [4, 4], [3, 3], [4, 3], [3, 3], [5, 5], [5, 5]]], 120),
('normal control 4',
[[[4, 6], [5, 6], [3, 2], [4, 3], [5, 4], [5, 5], [3, 5], [4, 6], [4, 3], [4, 2], [4, 4], [4, 3], [4, 4],
[5, 5], [4, 6], [3, 4], [3, 2], [4, 3]]],
290)],
[('regression: streak counted per hole',
[[[3, 3], [3, 2], [4, 3], [4, 4], [4, 4], [5, 4], [3, 3], [3, 3], [3, 3], [4, 2], [4, 3], [3, 1], [4, 3],
[4, 4], [4, 4], [4, 4], [3, 3], [5, 3]]],
600),
('partial repair probe: streak counted per hole',
[[[5, 3], [4, 4], [4, 3], [3, 2], [4, 3], [3, 2], [4, 3], [3, 2], [4, 4], [3, 2], [5, 5], [3, 3], [4, 4],
[4, 5], [4, 4], [4, 4], [4, 3], [5, 5]]],
435),
('second regression',
[[[4, 4], [3, 3], [3, 3], [5, 5], [4, 4], [5, 3], [3, 2], [4, 3], [3, 2], [5, 5], [4, 5], [4, 4], [5, 5],
[4, 4], [5, 7], [5, 1], [4, 4], [3, 1]]],
595),
('normal control 1',
[[[4, 4], [4, 4], [4, 3], [4, 4], [3, 3], [3, 2], [4, 3], [3, 3], [3, 3], [3, 2], [5, 5], [4, 4], [3, 2],
[3, 2]]],
220),
('normal control 2',
[[[3, 2], [4, 3], [5, 4], [5, 5], [5, 5], [5, 5], [4, 6], [5, 3], [3, 4], [4, 4], [4, 4], [3, 1], [3, 3],
[5, 4], [4, 3], [3, 3], [4, 4], [4, 3]]],
495),
('normal control 3',
[[[5, 1], [4, 4], [4, 4], [4, 6], [4, 4], [4, 4], [5, 4], [4, 6], [5, 4], [4, 3], [4, 6], [5, 7], [4, 4],
[3, 3]]],
260),
('normal control 4',
[[[3, 3], [4, 6], [5, 5], [3, 3], [5, 5], [3, 2], [3, 1], [4, 5], [4, 4], [5, 3], [3, 2], [4, 3], [5, 5],
[3, 5]]],
335)],
[('regression: streak counted per hole',
[[[3, 5], [4, 3], [5, 4], [3, 2], [4, 4], [3, 3], [4, 3], [5, 7], [5, 4], [5, 5], [5, 4], [3, 2], [4, 3],
[3, 3], [4, 3], [4, 2], [4, 3], [3, 2]]],
550),
('partial repair probe: streak counted per hole',
[[[3, 3], [4, 3], [4, 1], [5, 5], [4, 1], [3, 2], [4, 3], [4, 3], [4, 3], [4, 4], [4, 6], [3, 2], [4, 3],
[5, 4], [4, 3], [5, 4], [4, 3], [4, 4]]],
810),
('second regression',
[[[3, 3], [3, 2], [3, 2], [5, 4], [4, 4], [4, 4], [5, 5], [3, 3], [3, 2], [4, 4], [5, 5], [4, 4], [3, 2],
[5, 3], [4, 3], [4, 3], [4, 4], [4, 4]]],
480),
('normal control 1',
[[[5, 4], [3, 3], [5, 5], [5, 5], [5, 4], [3, 3], [3, 2], [3, 2], [3, 3], [4, 4], [5, 5], [4, 1], [4, 3],
[4, 4]]],
370),
('normal control 2',
[[[4, 4], [3, 1], [4, 3], [3, 5], [4, 4], [4, 4], [4, 4], [4, 6], [4, 2], [5, 5], [5, 4], [5, 5], [5, 5],
[3, 3]]],
290),
('normal control 3', [[[4, 3], [4, 6], [4, 4], [3, 4], [4, 3], [3, 2], [3, 5], [4, 1], [4, 3]]], 280),
('normal control 4', [[[4, 5], [3, 3], [4, 4], [4, 4], [5, 5], [4, 5], [3, 4], [4, 3], [4, 4]]], 40)],
[('regression: streak counted per hole',
[[[4, 3], [5, 4], [4, 4], [4, 4], [5, 5], [3, 3], [4, 4], [4, 4], [5, 4], [4, 4], [5, 4], [4, 2], [4, 3],
[4, 3], [3, 2], [4, 3], [3, 3], [4, 3]]],
500),
('partial repair probe: streak counted per hole',
[[[5, 5], [5, 4], [4, 3], [5, 4], [4, 3], [3, 3], [4, 3], [5, 5], [4, 3], [5, 4], [3, 2], [5, 4], [5, 4],
[4, 2], [4, 2], [5, 4], [4, 4], [4, 3]]],
680),
('second regression',
[[[5, 1], [3, 2], [4, 2], [4, 2], [5, 7], [3, 5], [4, 2], [3, 3], [3, 3], [5, 5], [4, 4], [3, 3], [5, 5],
[3, 2]]],
520),
('normal control 1',
[[[4, 4], [3, 3], [4, 3], [5, 4], [3, 4], [4, 3], [3, 3], [5, 5], [4, 2], [4, 4], [4, 4], [4, 3], [4, 1],
[4, 4]]],
410),
('normal control 2',
[[[4, 6], [4, 5], [3, 3], [5, 5], [4, 3], [5, 3], [4, 3], [5, 5], [4, 1], [4, 5], [4, 3], [3, 2], [4, 4],
[3, 2]]],
440),
('normal control 3', [[[3, 1], [5, 5], [5, 4], [5, 5], [3, 3], [3, 2], [4, 3], [3, 1], [5, 5]]], 400),
('normal control 4',
[[[4, 2], [4, 3], [3, 3], [5, 4], [5, 5], [4, 4], [3, 2], [4, 5], [4, 2], [4, 4], [4, 4], [3, 2], [3, 2],
[4, 4], [3, 2], [4, 4], [3, 4], [5, 6]]],
410)],
[('regression: streak counted per hole',
[[[5, 5], [3, 3], [4, 4], [5, 4], [4, 3], [5, 6], [4, 4], [5, 5], [4, 3], [4, 1], [3, 2], [3, 2], [4, 1],
[5, 6]]],
555),
('partial repair probe: streak counted per hole',
[[[4, 3], [5, 4], [5, 1], [3, 2], [4, 3], [5, 1], [3, 3], [4, 4], [4, 4], [4, 3], [3, 3], [3, 3], [4, 5],
[5, 5], [5, 4], [5, 4], [4, 4], [4, 4]]],
685),
('second regression',
[[[5, 4], [4, 3], [4, 4], [3, 3], [5, 4], [3, 3], [3, 3], [4, 3], [3, 2], [4, 2], [5, 3], [3, 2], [5, 5],
[4, 3], [4, 4], [3, 3], [3, 1], [3, 2]]],
675),
('normal control 1', [[[4, 2], [4, 6], [5, 4], [4, 6], [4, 5], [4, 4], [3, 3], [4, 3], [4, 3]]], 155),
('normal control 2',
[[[3, 3], [5, 5], [4, 3], [5, 1], [3, 2], [4, 4], [4, 4], [4, 3], [4, 4], [4, 3], [4, 4], [4, 2], [4, 1],
[4, 4], [5, 4], [5, 5], [5, 5], [4, 4]]],
750),
('normal control 3',
[[[5, 4], [4, 3], [4, 3], [4, 4], [4, 3], [4, 3], [5, 5], [3, 3], [4, 4], [3, 2], [4, 3], [5, 7], [3, 2],
[4, 3], [3, 2], [5, 5], [4, 4], [3, 5]]],
420),
('normal control 4',
[[[5, 7], [3, 1], [5, 4], [4, 3], [4, 4], [3, 5], [4, 3], [4, 4], [5, 4], [5, 1], [4, 3], [4, 4], [4, 3],
[5, 5], [5, 4], [4, 3], [3, 3], [4, 4]]],
670)]]
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 fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: streak counted per hole | 585 | 525 | Failed |
| partial repair probe: streak counted per hole | 995 | 905 | Failed |
| second regression | 420 | 390 | Failed |
| normal control 1 | 50 | 50 | Passed |
| normal control 2 | 280 | 280 | Passed |
| normal control 3 | 120 | 120 | Passed |
| normal control 4 | 290 | 290 | Passed |
SHA-256 / c0c544e4fa121ed594f10941165b59e4f86455a05dcafd3f43b2dbba74d25956
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(holes):
pts = 0
run = 0
streaks = 0
for par, strokes in holes:
d = strokes - par
if d <= -3:
pts += 130
elif d == -2:
pts += 80
elif d == -1:
pts += 30
elif d == 0:
pts += 5
elif d == 1:
pts -= 5
else:
pts -= 10
if strokes == 1:
pts += 50
if d < 0:
run += 1
if run % 3 == 0:
streaks += 1
else:
run = 0
pts += 30 * streaks
if len(holes) == 18 and all(s - p <= 0 for p, s in holes):
pts += 30
if len(holes) == 18 and sum(s for _, s in holes) < 70:
pts += 50
return pts
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: streak counted per hole',
[[[3, 3], [5, 5], [3, 1], [3, 3], [5, 7], [3, 2], [4, 2], [3, 2], [4, 3], [3, 2], [4, 6], [3, 2], [4, 2],
[4, 3]]],
525),
('partial repair probe: streak counted per hole',
[[[3, 2], [5, 4], [4, 4], [4, 4], [4, 4], [4, 4], [4, 2], [5, 4], [3, 2], [4, 4], [4, 3], [3, 2], [5, 1],
[4, 3], [3, 1], [3, 1], [5, 5], [5, 5]]],
905),
('second regression',
[[[4, 2], [3, 5], [4, 4], [5, 3], [4, 3], [4, 3], [4, 3], [5, 7], [4, 4], [5, 5], [3, 3], [4, 4], [4, 4],
[4, 4], [4, 3], [4, 4], [4, 4], [3, 3]]],
390),
('normal control 1', [[[5, 5], [5, 7], [3, 2], [4, 4], [5, 5], [4, 4], [5, 4], [3, 5], [4, 6]]], 50),
('normal control 2',
[[[4, 4], [3, 3], [4, 3], [4, 6], [4, 3], [3, 3], [3, 4], [4, 3], [4, 4], [4, 2], [5, 5], [3, 3], [3, 2],
[4, 4], [5, 5], [5, 6], [4, 4], [4, 4]]],
280),
('normal control 3', [[[4, 3], [3, 2], [4, 4], [4, 4], [3, 3], [4, 3], [3, 3], [5, 5], [5, 5]]], 120),
('normal control 4',
[[[4, 6], [5, 6], [3, 2], [4, 3], [5, 4], [5, 5], [3, 5], [4, 6], [4, 3], [4, 2], [4, 4], [4, 3], [4, 4],
[5, 5], [4, 6], [3, 4], [3, 2], [4, 3]]],
290)],
[('regression: streak counted per hole',
[[[3, 3], [3, 2], [4, 3], [4, 4], [4, 4], [5, 4], [3, 3], [3, 3], [3, 3], [4, 2], [4, 3], [3, 1], [4, 3],
[4, 4], [4, 4], [4, 4], [3, 3], [5, 3]]],
600),
('partial repair probe: streak counted per hole',
[[[5, 3], [4, 4], [4, 3], [3, 2], [4, 3], [3, 2], [4, 3], [3, 2], [4, 4], [3, 2], [5, 5], [3, 3], [4, 4],
[4, 5], [4, 4], [4, 4], [4, 3], [5, 5]]],
435),
('second regression',
[[[4, 4], [3, 3], [3, 3], [5, 5], [4, 4], [5, 3], [3, 2], [4, 3], [3, 2], [5, 5], [4, 5], [4, 4], [5, 5],
[4, 4], [5, 7], [5, 1], [4, 4], [3, 1]]],
595),
('normal control 1',
[[[4, 4], [4, 4], [4, 3], [4, 4], [3, 3], [3, 2], [4, 3], [3, 3], [3, 3], [3, 2], [5, 5], [4, 4], [3, 2],
[3, 2]]],
220),
('normal control 2',
[[[3, 2], [4, 3], [5, 4], [5, 5], [5, 5], [5, 5], [4, 6], [5, 3], [3, 4], [4, 4], [4, 4], [3, 1], [3, 3],
[5, 4], [4, 3], [3, 3], [4, 4], [4, 3]]],
495),
('normal control 3',
[[[5, 1], [4, 4], [4, 4], [4, 6], [4, 4], [4, 4], [5, 4], [4, 6], [5, 4], [4, 3], [4, 6], [5, 7], [4, 4],
[3, 3]]],
260),
('normal control 4',
[[[3, 3], [4, 6], [5, 5], [3, 3], [5, 5], [3, 2], [3, 1], [4, 5], [4, 4], [5, 3], [3, 2], [4, 3], [5, 5],
[3, 5]]],
335)],
[('regression: streak counted per hole',
[[[3, 5], [4, 3], [5, 4], [3, 2], [4, 4], [3, 3], [4, 3], [5, 7], [5, 4], [5, 5], [5, 4], [3, 2], [4, 3],
[3, 3], [4, 3], [4, 2], [4, 3], [3, 2]]],
550),
('partial repair probe: streak counted per hole',
[[[3, 3], [4, 3], [4, 1], [5, 5], [4, 1], [3, 2], [4, 3], [4, 3], [4, 3], [4, 4], [4, 6], [3, 2], [4, 3],
[5, 4], [4, 3], [5, 4], [4, 3], [4, 4]]],
810),
('second regression',
[[[3, 3], [3, 2], [3, 2], [5, 4], [4, 4], [4, 4], [5, 5], [3, 3], [3, 2], [4, 4], [5, 5], [4, 4], [3, 2],
[5, 3], [4, 3], [4, 3], [4, 4], [4, 4]]],
480),
('normal control 1',
[[[5, 4], [3, 3], [5, 5], [5, 5], [5, 4], [3, 3], [3, 2], [3, 2], [3, 3], [4, 4], [5, 5], [4, 1], [4, 3],
[4, 4]]],
370),
('normal control 2',
[[[4, 4], [3, 1], [4, 3], [3, 5], [4, 4], [4, 4], [4, 4], [4, 6], [4, 2], [5, 5], [5, 4], [5, 5], [5, 5],
[3, 3]]],
290),
('normal control 3', [[[4, 3], [4, 6], [4, 4], [3, 4], [4, 3], [3, 2], [3, 5], [4, 1], [4, 3]]], 280),
('normal control 4', [[[4, 5], [3, 3], [4, 4], [4, 4], [5, 5], [4, 5], [3, 4], [4, 3], [4, 4]]], 40)],
[('regression: streak counted per hole',
[[[4, 3], [5, 4], [4, 4], [4, 4], [5, 5], [3, 3], [4, 4], [4, 4], [5, 4], [4, 4], [5, 4], [4, 2], [4, 3],
[4, 3], [3, 2], [4, 3], [3, 3], [4, 3]]],
500),
('partial repair probe: streak counted per hole',
[[[5, 5], [5, 4], [4, 3], [5, 4], [4, 3], [3, 3], [4, 3], [5, 5], [4, 3], [5, 4], [3, 2], [5, 4], [5, 4],
[4, 2], [4, 2], [5, 4], [4, 4], [4, 3]]],
680),
('second regression',
[[[5, 1], [3, 2], [4, 2], [4, 2], [5, 7], [3, 5], [4, 2], [3, 3], [3, 3], [5, 5], [4, 4], [3, 3], [5, 5],
[3, 2]]],
520),
('normal control 1',
[[[4, 4], [3, 3], [4, 3], [5, 4], [3, 4], [4, 3], [3, 3], [5, 5], [4, 2], [4, 4], [4, 4], [4, 3], [4, 1],
[4, 4]]],
410),
('normal control 2',
[[[4, 6], [4, 5], [3, 3], [5, 5], [4, 3], [5, 3], [4, 3], [5, 5], [4, 1], [4, 5], [4, 3], [3, 2], [4, 4],
[3, 2]]],
440),
('normal control 3', [[[3, 1], [5, 5], [5, 4], [5, 5], [3, 3], [3, 2], [4, 3], [3, 1], [5, 5]]], 400),
('normal control 4',
[[[4, 2], [4, 3], [3, 3], [5, 4], [5, 5], [4, 4], [3, 2], [4, 5], [4, 2], [4, 4], [4, 4], [3, 2], [3, 2],
[4, 4], [3, 2], [4, 4], [3, 4], [5, 6]]],
410)],
[('regression: streak counted per hole',
[[[5, 5], [3, 3], [4, 4], [5, 4], [4, 3], [5, 6], [4, 4], [5, 5], [4, 3], [4, 1], [3, 2], [3, 2], [4, 1],
[5, 6]]],
555),
('partial repair probe: streak counted per hole',
[[[4, 3], [5, 4], [5, 1], [3, 2], [4, 3], [5, 1], [3, 3], [4, 4], [4, 4], [4, 3], [3, 3], [3, 3], [4, 5],
[5, 5], [5, 4], [5, 4], [4, 4], [4, 4]]],
685),
('second regression',
[[[5, 4], [4, 3], [4, 4], [3, 3], [5, 4], [3, 3], [3, 3], [4, 3], [3, 2], [4, 2], [5, 3], [3, 2], [5, 5],
[4, 3], [4, 4], [3, 3], [3, 1], [3, 2]]],
675),
('normal control 1', [[[4, 2], [4, 6], [5, 4], [4, 6], [4, 5], [4, 4], [3, 3], [4, 3], [4, 3]]], 155),
('normal control 2',
[[[3, 3], [5, 5], [4, 3], [5, 1], [3, 2], [4, 4], [4, 4], [4, 3], [4, 4], [4, 3], [4, 4], [4, 2], [4, 1],
[4, 4], [5, 4], [5, 5], [5, 5], [4, 4]]],
750),
('normal control 3',
[[[5, 4], [4, 3], [4, 3], [4, 4], [4, 3], [4, 3], [5, 5], [3, 3], [4, 4], [3, 2], [4, 3], [5, 7], [3, 2],
[4, 3], [3, 2], [5, 5], [4, 4], [3, 5]]],
420),
('normal control 4',
[[[5, 7], [3, 1], [5, 4], [4, 3], [4, 4], [3, 5], [4, 3], [4, 4], [5, 4], [5, 1], [4, 3], [4, 4], [4, 3],
[5, 5], [5, 4], [4, 3], [3, 3], [4, 4]]],
670)]]
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 fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: streak counted per hole | 525 | 525 | Passed |
| partial repair probe: streak counted per hole | 935 | 905 | Failed |
| second regression | 390 | 390 | Passed |
| normal control 1 | 50 | 50 | Passed |
| normal control 2 | 280 | 280 | Passed |
| normal control 3 | 120 | 120 | Passed |
| normal control 4 | 290 | 290 | Passed |
SHA-256 / c4046654f78fe367f1d7dc03de32edf014d8bea72e06a8909fa37965604ef258
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(holes):
pts = 0
run = 0
streaks = 0
for par, strokes in holes:
d = strokes - par
if d <= -3:
pts += 130
elif d == -2:
pts += 80
elif d == -1:
pts += 30
elif d == 0:
pts += 5
elif d == 1:
pts -= 5
else:
pts -= 10
if strokes == 1:
pts += 50
if d < 0:
run += 1
if run == 3:
streaks += 1
else:
run = 0
pts += 30 * streaks
if len(holes) == 18 and all(s - p <= 0 for p, s in holes):
pts += 30
if len(holes) == 18 and sum(s for _, s in holes) < 70:
pts += 50
return pts
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: streak counted per hole',
[[[3, 3], [5, 5], [3, 1], [3, 3], [5, 7], [3, 2], [4, 2], [3, 2], [4, 3], [3, 2], [4, 6], [3, 2], [4, 2],
[4, 3]]],
525),
('partial repair probe: streak counted per hole',
[[[3, 2], [5, 4], [4, 4], [4, 4], [4, 4], [4, 4], [4, 2], [5, 4], [3, 2], [4, 4], [4, 3], [3, 2], [5, 1],
[4, 3], [3, 1], [3, 1], [5, 5], [5, 5]]],
905),
('second regression',
[[[4, 2], [3, 5], [4, 4], [5, 3], [4, 3], [4, 3], [4, 3], [5, 7], [4, 4], [5, 5], [3, 3], [4, 4], [4, 4],
[4, 4], [4, 3], [4, 4], [4, 4], [3, 3]]],
390),
('normal control 1', [[[5, 5], [5, 7], [3, 2], [4, 4], [5, 5], [4, 4], [5, 4], [3, 5], [4, 6]]], 50),
('normal control 2',
[[[4, 4], [3, 3], [4, 3], [4, 6], [4, 3], [3, 3], [3, 4], [4, 3], [4, 4], [4, 2], [5, 5], [3, 3], [3, 2],
[4, 4], [5, 5], [5, 6], [4, 4], [4, 4]]],
280),
('normal control 3', [[[4, 3], [3, 2], [4, 4], [4, 4], [3, 3], [4, 3], [3, 3], [5, 5], [5, 5]]], 120),
('normal control 4',
[[[4, 6], [5, 6], [3, 2], [4, 3], [5, 4], [5, 5], [3, 5], [4, 6], [4, 3], [4, 2], [4, 4], [4, 3], [4, 4],
[5, 5], [4, 6], [3, 4], [3, 2], [4, 3]]],
290)],
[('regression: streak counted per hole',
[[[3, 3], [3, 2], [4, 3], [4, 4], [4, 4], [5, 4], [3, 3], [3, 3], [3, 3], [4, 2], [4, 3], [3, 1], [4, 3],
[4, 4], [4, 4], [4, 4], [3, 3], [5, 3]]],
600),
('partial repair probe: streak counted per hole',
[[[5, 3], [4, 4], [4, 3], [3, 2], [4, 3], [3, 2], [4, 3], [3, 2], [4, 4], [3, 2], [5, 5], [3, 3], [4, 4],
[4, 5], [4, 4], [4, 4], [4, 3], [5, 5]]],
435),
('second regression',
[[[4, 4], [3, 3], [3, 3], [5, 5], [4, 4], [5, 3], [3, 2], [4, 3], [3, 2], [5, 5], [4, 5], [4, 4], [5, 5],
[4, 4], [5, 7], [5, 1], [4, 4], [3, 1]]],
595),
('normal control 1',
[[[4, 4], [4, 4], [4, 3], [4, 4], [3, 3], [3, 2], [4, 3], [3, 3], [3, 3], [3, 2], [5, 5], [4, 4], [3, 2],
[3, 2]]],
220),
('normal control 2',
[[[3, 2], [4, 3], [5, 4], [5, 5], [5, 5], [5, 5], [4, 6], [5, 3], [3, 4], [4, 4], [4, 4], [3, 1], [3, 3],
[5, 4], [4, 3], [3, 3], [4, 4], [4, 3]]],
495),
('normal control 3',
[[[5, 1], [4, 4], [4, 4], [4, 6], [4, 4], [4, 4], [5, 4], [4, 6], [5, 4], [4, 3], [4, 6], [5, 7], [4, 4],
[3, 3]]],
260),
('normal control 4',
[[[3, 3], [4, 6], [5, 5], [3, 3], [5, 5], [3, 2], [3, 1], [4, 5], [4, 4], [5, 3], [3, 2], [4, 3], [5, 5],
[3, 5]]],
335)],
[('regression: streak counted per hole',
[[[3, 5], [4, 3], [5, 4], [3, 2], [4, 4], [3, 3], [4, 3], [5, 7], [5, 4], [5, 5], [5, 4], [3, 2], [4, 3],
[3, 3], [4, 3], [4, 2], [4, 3], [3, 2]]],
550),
('partial repair probe: streak counted per hole',
[[[3, 3], [4, 3], [4, 1], [5, 5], [4, 1], [3, 2], [4, 3], [4, 3], [4, 3], [4, 4], [4, 6], [3, 2], [4, 3],
[5, 4], [4, 3], [5, 4], [4, 3], [4, 4]]],
810),
('second regression',
[[[3, 3], [3, 2], [3, 2], [5, 4], [4, 4], [4, 4], [5, 5], [3, 3], [3, 2], [4, 4], [5, 5], [4, 4], [3, 2],
[5, 3], [4, 3], [4, 3], [4, 4], [4, 4]]],
480),
('normal control 1',
[[[5, 4], [3, 3], [5, 5], [5, 5], [5, 4], [3, 3], [3, 2], [3, 2], [3, 3], [4, 4], [5, 5], [4, 1], [4, 3],
[4, 4]]],
370),
('normal control 2',
[[[4, 4], [3, 1], [4, 3], [3, 5], [4, 4], [4, 4], [4, 4], [4, 6], [4, 2], [5, 5], [5, 4], [5, 5], [5, 5],
[3, 3]]],
290),
('normal control 3', [[[4, 3], [4, 6], [4, 4], [3, 4], [4, 3], [3, 2], [3, 5], [4, 1], [4, 3]]], 280),
('normal control 4', [[[4, 5], [3, 3], [4, 4], [4, 4], [5, 5], [4, 5], [3, 4], [4, 3], [4, 4]]], 40)],
[('regression: streak counted per hole',
[[[4, 3], [5, 4], [4, 4], [4, 4], [5, 5], [3, 3], [4, 4], [4, 4], [5, 4], [4, 4], [5, 4], [4, 2], [4, 3],
[4, 3], [3, 2], [4, 3], [3, 3], [4, 3]]],
500),
('partial repair probe: streak counted per hole',
[[[5, 5], [5, 4], [4, 3], [5, 4], [4, 3], [3, 3], [4, 3], [5, 5], [4, 3], [5, 4], [3, 2], [5, 4], [5, 4],
[4, 2], [4, 2], [5, 4], [4, 4], [4, 3]]],
680),
('second regression',
[[[5, 1], [3, 2], [4, 2], [4, 2], [5, 7], [3, 5], [4, 2], [3, 3], [3, 3], [5, 5], [4, 4], [3, 3], [5, 5],
[3, 2]]],
520),
('normal control 1',
[[[4, 4], [3, 3], [4, 3], [5, 4], [3, 4], [4, 3], [3, 3], [5, 5], [4, 2], [4, 4], [4, 4], [4, 3], [4, 1],
[4, 4]]],
410),
('normal control 2',
[[[4, 6], [4, 5], [3, 3], [5, 5], [4, 3], [5, 3], [4, 3], [5, 5], [4, 1], [4, 5], [4, 3], [3, 2], [4, 4],
[3, 2]]],
440),
('normal control 3', [[[3, 1], [5, 5], [5, 4], [5, 5], [3, 3], [3, 2], [4, 3], [3, 1], [5, 5]]], 400),
('normal control 4',
[[[4, 2], [4, 3], [3, 3], [5, 4], [5, 5], [4, 4], [3, 2], [4, 5], [4, 2], [4, 4], [4, 4], [3, 2], [3, 2],
[4, 4], [3, 2], [4, 4], [3, 4], [5, 6]]],
410)],
[('regression: streak counted per hole',
[[[5, 5], [3, 3], [4, 4], [5, 4], [4, 3], [5, 6], [4, 4], [5, 5], [4, 3], [4, 1], [3, 2], [3, 2], [4, 1],
[5, 6]]],
555),
('partial repair probe: streak counted per hole',
[[[4, 3], [5, 4], [5, 1], [3, 2], [4, 3], [5, 1], [3, 3], [4, 4], [4, 4], [4, 3], [3, 3], [3, 3], [4, 5],
[5, 5], [5, 4], [5, 4], [4, 4], [4, 4]]],
685),
('second regression',
[[[5, 4], [4, 3], [4, 4], [3, 3], [5, 4], [3, 3], [3, 3], [4, 3], [3, 2], [4, 2], [5, 3], [3, 2], [5, 5],
[4, 3], [4, 4], [3, 3], [3, 1], [3, 2]]],
675),
('normal control 1', [[[4, 2], [4, 6], [5, 4], [4, 6], [4, 5], [4, 4], [3, 3], [4, 3], [4, 3]]], 155),
('normal control 2',
[[[3, 3], [5, 5], [4, 3], [5, 1], [3, 2], [4, 4], [4, 4], [4, 3], [4, 4], [4, 3], [4, 4], [4, 2], [4, 1],
[4, 4], [5, 4], [5, 5], [5, 5], [4, 4]]],
750),
('normal control 3',
[[[5, 4], [4, 3], [4, 3], [4, 4], [4, 3], [4, 3], [5, 5], [3, 3], [4, 4], [3, 2], [4, 3], [5, 7], [3, 2],
[4, 3], [3, 2], [5, 5], [4, 4], [3, 5]]],
420),
('normal control 4',
[[[5, 7], [3, 1], [5, 4], [4, 3], [4, 4], [3, 5], [4, 3], [4, 4], [5, 4], [5, 1], [4, 3], [4, 4], [4, 3],
[5, 5], [5, 4], [4, 3], [3, 3], [4, 4]]],
670)]]
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 fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: streak counted per hole | 525 | 525 | Passed |
| partial repair probe: streak counted per hole | 905 | 905 | Passed |
| second regression | 390 | 390 | Passed |
| normal control 1 | 50 | 50 | Passed |
| normal control 2 | 280 | 280 | Passed |
| normal control 3 | 120 | 120 | Passed |
| normal control 4 | 290 | 290 | Passed |
SHA-256 / 176326b18055171102668283107ec57262de9e90c68af0e03723f47d88714066
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 2026-09-29T14:50:39.001365+00:00.
Case digest / 448fd66b5712ad6b28b615cc85051242f08137d11401d4e40967a2ad23d7949e