FA-85266 / Fantasy sports scoring / Open access

Ties consume only one bonus position · case 01

After a two-way tie for first, the next player still receives 2 bonus.

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

ROOT CAUSE

The position counter advances by one per tie group instead of by group size.

VERIFIED REPAIR

Advance the position by the number of tied players.

Unsuccessful approach: Resetting the position to the group size forgets positions consumed earlier.

Case contract

Allocate bonus points from a per-match performance index: rank players by index descending; positions 1, 2, 3 earn 3, 2, 1. Tied players all receive the award of the first position their group occupies and consume as many positions as the group size, so a two-way tie for first earns 3 each and the next player 1. Players whose index is 0 or below never receive bonus. Return name -> bonus for awarded players.

Why this case matters

Bonus allocation with ties is a compact but contested rule in football fantasy games.

1 / The failure

Exit 1

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

N = 1
observations = []
def solve(bps):
    ordered = sorted(bps.items(), key=lambda kv: (-kv[1], kv[0]))
    award = [3, 2, 1]
    out = {}
    pos = 0
    i = 0
    while i < len(ordered) and pos < 3:
        j = i
        while j < len(ordered) and ordered[j][1] == ordered[i][1]:
            j += 1
        for name, v in ordered[i:j]:
            if v > 0:
                out[name] = award[pos]
        pos += 1
        i = j
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: position consumption', [{'bo': 34, 'ce': 12, 'ek': 4, 'fu': 34}],
   {'bo': 3, 'ce': 1, 'fu': 3}),
  ('partial repair probe: position consumption',
   [{'ax': 30, 'bo': -2, 'ce': 27, 'di': 32, 'ek': 27, 'fu': 12, 'gi': 34, 'ho': 30}],
   {'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}),
  ('second regression', [{'ax': 0, 'ce': 34, 'di': -2, 'ek': 5, 'fu': 12, 'gi': 27}],
   {'ce': 3, 'fu': 1, 'gi': 2}),
  ('normal control 1', [{'bo': 30, 'ek': 30, 'fu': 34, 'gi': 0, 'ho': -2}], {'bo': 2, 'ek': 2, 'fu': 3}),
  ('normal control 2', [{'ce': 0, 'di': 30, 'ek': 34}], {'di': 2, 'ek': 3}),
  ('normal control 3', [{'ce': 30, 'di': -2, 'fu': -2, 'gi': 0}], {'ce': 3}),
  ('normal control 4', [{'ax': 30, 'bo': -2, 'ce': 30, 'ek': 30}], {'ax': 3, 'ce': 3, 'ek': 3})],
 [('regression: position consumption', [{'ax': 34, 'bo': 30, 'fu': -2, 'gi': 34, 'ho': 0}],
   {'ax': 3, 'bo': 1, 'gi': 3}),
  ('partial repair probe: position consumption', [{'bo': 34, 'ce': 34, 'ek': 30, 'fu': 26}],
   {'bo': 3, 'ce': 3, 'ek': 1}),
  ('second regression', [{'ax': 34, 'ce': 7, 'di': 0, 'gi': 34}], {'ax': 3, 'ce': 1, 'gi': 3}),
  ('normal control 1', [{'ce': 0, 'gi': -2, 'ho': -2}], {}),
  ('normal control 2', [{'ce': 12, 'ek': -2, 'fu': 29, 'ho': 12}], {'ce': 2, 'fu': 3, 'ho': 2}),
  ('normal control 3', [{'ce': -2, 'ek': 34, 'fu': 12}], {'ek': 3, 'fu': 2}),
  ('normal control 4', [{'ce': 34, 'di': -2, 'gi': 30}], {'ce': 3, 'gi': 2})],
 [('regression: position consumption', [{'ax': 34, 'bo': 12, 'ce': 34, 'di': 34, 'fu': 0, 'gi': 30, 'ho': 0}],
   {'ax': 3, 'ce': 3, 'di': 3}),
  ('partial repair probe: position consumption', [{'bo': 0, 'ce': 17, 'fu': 30, 'ho': 34}],
   {'ce': 1, 'fu': 2, 'ho': 3}),
  ('second regression', [{'ax': 34, 'ek': 28, 'gi': 30}], {'ax': 3, 'ek': 1, 'gi': 2}),
  ('normal control 1', [{'ce': 34, 'di': 0, 'ek': 34}], {'ce': 3, 'ek': 3}),
  ('normal control 2', [{'bo': -2, 'di': -2, 'fu': 24}], {'fu': 3}),
  ('normal control 3', [{'ax': 0, 'di': 0, 'fu': 30, 'ho': 12}], {'fu': 3, 'ho': 2}),
  ('normal control 4', [{'ax': 34, 'bo': -2, 'ce': -2, 'ek': 0, 'fu': 12, 'gi': 0, 'ho': -2}],
   {'ax': 3, 'fu': 2})],
 [('regression: position consumption',
   [{'ax': 12, 'bo': 34, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 12, 'gi': 34, 'ho': 27}],
   {'bo': 3, 'ce': 3, 'gi': 3}),
  ('partial repair probe: position consumption', [{'ax': 12, 'ce': 30, 'ek': 27, 'ho': -2}],
   {'ax': 1, 'ce': 3, 'ek': 2}),
  ('second regression', [{'ax': 27, 'bo': 0, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 27, 'gi': 30, 'ho': 0}],
   {'ax': 1, 'ce': 3, 'fu': 1, 'gi': 2}),
  ('normal control 1', [{'bo': 12, 'di': 34, 'fu': 0}], {'bo': 2, 'di': 3}),
  ('normal control 2', [{'ax': 0, 'ce': 0, 'fu': -2}], {}),
  ('normal control 3', [{'ax': 30, 'ek': 30, 'gi': 34}], {'ax': 2, 'ek': 2, 'gi': 3}),
  ('normal control 4', [{'ce': -2, 'di': 0, 'fu': 34, 'ho': 34}], {'fu': 3, 'ho': 3})],
 [('regression: position consumption',
   [{'ax': 12, 'bo': 34, 'ce': 0, 'di': 34, 'fu': 30, 'gi': 34, 'ho': 30}], {'bo': 3, 'di': 3, 'gi': 3}),
  ('partial repair probe: position consumption',
   [{'ax': 30, 'bo': 0, 'ce': 0, 'ek': 27, 'fu': 27, 'gi': 12, 'ho': 34}],
   {'ax': 2, 'ek': 1, 'fu': 1, 'ho': 3}),
  ('second regression', [{'ax': 27, 'ce': 8, 'di': 0, 'fu': 30, 'gi': -2}], {'ax': 2, 'ce': 1, 'fu': 3}),
  ('normal control 1', [{'bo': 34, 'di': 27, 'ek': -2}], {'bo': 3, 'di': 2}),
  ('normal control 2', [{'ax': 30, 'bo': 12, 'ce': 0, 'fu': 12, 'ho': 12}],
   {'ax': 3, 'bo': 2, 'fu': 2, 'ho': 2}),
  ('normal control 3', [{'ax': -2, 'ce': -2, 'di': -2, 'ek': -2}], {}),
  ('normal control 4', [{'bo': -2, 'gi': 0, 'ho': 12}], {'ho': 3})]]
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: position consumption	`{'bo': 3, 'ce': 2, 'ek': 1, 'fu': 3}`	`{'bo': 3, 'ce': 1, 'fu': 3}`	Failed
partial repair probe: position consumption	`{'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}`	`{'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}`	Passed
second regression	`{'ce': 3, 'fu': 1, 'gi': 2}`	`{'ce': 3, 'fu': 1, 'gi': 2}`	Passed
normal control 1	`{'bo': 2, 'ek': 2, 'fu': 3}`	`{'bo': 2, 'ek': 2, 'fu': 3}`	Passed
normal control 2	`{'di': 2, 'ek': 3}`	`{'di': 2, 'ek': 3}`	Passed
normal control 3	`{'ce': 3}`	`{'ce': 3}`	Passed
normal control 4	`{'ax': 3, 'ce': 3, 'ek': 3}`	`{'ax': 3, 'ce': 3, 'ek': 3}`	Passed

SHA-256 / 0818f403ff348a89ee2d4d69068d5f8ff1f09a1d17f2d0b59d49695f60d943e6

2 / The unsuccessful fix

Exit 1

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

N = 1
observations = []
def solve(bps):
    ordered = sorted(bps.items(), key=lambda kv: (-kv[1], kv[0]))
    award = [3, 2, 1]
    out = {}
    pos = 0
    i = 0
    while i < len(ordered) and pos < 3:
        j = i
        while j < len(ordered) and ordered[j][1] == ordered[i][1]:
            j += 1
        for name, v in ordered[i:j]:
            if v > 0:
                out[name] = award[pos]
        pos = j - i
        i = j
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: position consumption', [{'bo': 34, 'ce': 12, 'ek': 4, 'fu': 34}],
   {'bo': 3, 'ce': 1, 'fu': 3}),
  ('partial repair probe: position consumption',
   [{'ax': 30, 'bo': -2, 'ce': 27, 'di': 32, 'ek': 27, 'fu': 12, 'gi': 34, 'ho': 30}],
   {'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}),
  ('second regression', [{'ax': 0, 'ce': 34, 'di': -2, 'ek': 5, 'fu': 12, 'gi': 27}],
   {'ce': 3, 'fu': 1, 'gi': 2}),
  ('normal control 1', [{'bo': 30, 'ek': 30, 'fu': 34, 'gi': 0, 'ho': -2}], {'bo': 2, 'ek': 2, 'fu': 3}),
  ('normal control 2', [{'ce': 0, 'di': 30, 'ek': 34}], {'di': 2, 'ek': 3}),
  ('normal control 3', [{'ce': 30, 'di': -2, 'fu': -2, 'gi': 0}], {'ce': 3}),
  ('normal control 4', [{'ax': 30, 'bo': -2, 'ce': 30, 'ek': 30}], {'ax': 3, 'ce': 3, 'ek': 3})],
 [('regression: position consumption', [{'ax': 34, 'bo': 30, 'fu': -2, 'gi': 34, 'ho': 0}],
   {'ax': 3, 'bo': 1, 'gi': 3}),
  ('partial repair probe: position consumption', [{'bo': 34, 'ce': 34, 'ek': 30, 'fu': 26}],
   {'bo': 3, 'ce': 3, 'ek': 1}),
  ('second regression', [{'ax': 34, 'ce': 7, 'di': 0, 'gi': 34}], {'ax': 3, 'ce': 1, 'gi': 3}),
  ('normal control 1', [{'ce': 0, 'gi': -2, 'ho': -2}], {}),
  ('normal control 2', [{'ce': 12, 'ek': -2, 'fu': 29, 'ho': 12}], {'ce': 2, 'fu': 3, 'ho': 2}),
  ('normal control 3', [{'ce': -2, 'ek': 34, 'fu': 12}], {'ek': 3, 'fu': 2}),
  ('normal control 4', [{'ce': 34, 'di': -2, 'gi': 30}], {'ce': 3, 'gi': 2})],
 [('regression: position consumption', [{'ax': 34, 'bo': 12, 'ce': 34, 'di': 34, 'fu': 0, 'gi': 30, 'ho': 0}],
   {'ax': 3, 'ce': 3, 'di': 3}),
  ('partial repair probe: position consumption', [{'bo': 0, 'ce': 17, 'fu': 30, 'ho': 34}],
   {'ce': 1, 'fu': 2, 'ho': 3}),
  ('second regression', [{'ax': 34, 'ek': 28, 'gi': 30}], {'ax': 3, 'ek': 1, 'gi': 2}),
  ('normal control 1', [{'ce': 34, 'di': 0, 'ek': 34}], {'ce': 3, 'ek': 3}),
  ('normal control 2', [{'bo': -2, 'di': -2, 'fu': 24}], {'fu': 3}),
  ('normal control 3', [{'ax': 0, 'di': 0, 'fu': 30, 'ho': 12}], {'fu': 3, 'ho': 2}),
  ('normal control 4', [{'ax': 34, 'bo': -2, 'ce': -2, 'ek': 0, 'fu': 12, 'gi': 0, 'ho': -2}],
   {'ax': 3, 'fu': 2})],
 [('regression: position consumption',
   [{'ax': 12, 'bo': 34, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 12, 'gi': 34, 'ho': 27}],
   {'bo': 3, 'ce': 3, 'gi': 3}),
  ('partial repair probe: position consumption', [{'ax': 12, 'ce': 30, 'ek': 27, 'ho': -2}],
   {'ax': 1, 'ce': 3, 'ek': 2}),
  ('second regression', [{'ax': 27, 'bo': 0, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 27, 'gi': 30, 'ho': 0}],
   {'ax': 1, 'ce': 3, 'fu': 1, 'gi': 2}),
  ('normal control 1', [{'bo': 12, 'di': 34, 'fu': 0}], {'bo': 2, 'di': 3}),
  ('normal control 2', [{'ax': 0, 'ce': 0, 'fu': -2}], {}),
  ('normal control 3', [{'ax': 30, 'ek': 30, 'gi': 34}], {'ax': 2, 'ek': 2, 'gi': 3}),
  ('normal control 4', [{'ce': -2, 'di': 0, 'fu': 34, 'ho': 34}], {'fu': 3, 'ho': 3})],
 [('regression: position consumption',
   [{'ax': 12, 'bo': 34, 'ce': 0, 'di': 34, 'fu': 30, 'gi': 34, 'ho': 30}], {'bo': 3, 'di': 3, 'gi': 3}),
  ('partial repair probe: position consumption',
   [{'ax': 30, 'bo': 0, 'ce': 0, 'ek': 27, 'fu': 27, 'gi': 12, 'ho': 34}],
   {'ax': 2, 'ek': 1, 'fu': 1, 'ho': 3}),
  ('second regression', [{'ax': 27, 'ce': 8, 'di': 0, 'fu': 30, 'gi': -2}], {'ax': 2, 'ce': 1, 'fu': 3}),
  ('normal control 1', [{'bo': 34, 'di': 27, 'ek': -2}], {'bo': 3, 'di': 2}),
  ('normal control 2', [{'ax': 30, 'bo': 12, 'ce': 0, 'fu': 12, 'ho': 12}],
   {'ax': 3, 'bo': 2, 'fu': 2, 'ho': 2}),
  ('normal control 3', [{'ax': -2, 'ce': -2, 'di': -2, 'ek': -2}], {}),
  ('normal control 4', [{'bo': -2, 'gi': 0, 'ho': 12}], {'ho': 3})]]
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: position consumption	`{'bo': 3, 'ce': 1, 'ek': 2, 'fu': 3}`	`{'bo': 3, 'ce': 1, 'fu': 3}`	Failed
partial repair probe: position consumption	`{'ax': 2, 'ce': 1, 'di': 2, 'ek': 1, 'fu': 1, 'gi': 3, 'ho': 2}`	`{'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}`	Failed
second regression	`{'ce': 3, 'ek': 2, 'fu': 2, 'gi': 2}`	`{'ce': 3, 'fu': 1, 'gi': 2}`	Failed
normal control 1	`{'bo': 2, 'ek': 2, 'fu': 3}`	`{'bo': 2, 'ek': 2, 'fu': 3}`	Passed
normal control 2	`{'di': 2, 'ek': 3}`	`{'di': 2, 'ek': 3}`	Passed
normal control 3	`{'ce': 3}`	`{'ce': 3}`	Passed
normal control 4	`{'ax': 3, 'ce': 3, 'ek': 3}`	`{'ax': 3, 'ce': 3, 'ek': 3}`	Passed

SHA-256 / 1aaa9c351c7b0607d04feb1285f18e5ab0909a908508d9dd8d790d137b6f2265

3 / The verified repair

Exit 0

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

N = 1
observations = []
def solve(bps):
    ordered = sorted(bps.items(), key=lambda kv: (-kv[1], kv[0]))
    award = [3, 2, 1]
    out = {}
    pos = 0
    i = 0
    while i < len(ordered) and pos < 3:
        j = i
        while j < len(ordered) and ordered[j][1] == ordered[i][1]:
            j += 1
        for name, v in ordered[i:j]:
            if v > 0:
                out[name] = award[pos]
        pos += j - i
        i = j
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: position consumption', [{'bo': 34, 'ce': 12, 'ek': 4, 'fu': 34}],
   {'bo': 3, 'ce': 1, 'fu': 3}),
  ('partial repair probe: position consumption',
   [{'ax': 30, 'bo': -2, 'ce': 27, 'di': 32, 'ek': 27, 'fu': 12, 'gi': 34, 'ho': 30}],
   {'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}),
  ('second regression', [{'ax': 0, 'ce': 34, 'di': -2, 'ek': 5, 'fu': 12, 'gi': 27}],
   {'ce': 3, 'fu': 1, 'gi': 2}),
  ('normal control 1', [{'bo': 30, 'ek': 30, 'fu': 34, 'gi': 0, 'ho': -2}], {'bo': 2, 'ek': 2, 'fu': 3}),
  ('normal control 2', [{'ce': 0, 'di': 30, 'ek': 34}], {'di': 2, 'ek': 3}),
  ('normal control 3', [{'ce': 30, 'di': -2, 'fu': -2, 'gi': 0}], {'ce': 3}),
  ('normal control 4', [{'ax': 30, 'bo': -2, 'ce': 30, 'ek': 30}], {'ax': 3, 'ce': 3, 'ek': 3})],
 [('regression: position consumption', [{'ax': 34, 'bo': 30, 'fu': -2, 'gi': 34, 'ho': 0}],
   {'ax': 3, 'bo': 1, 'gi': 3}),
  ('partial repair probe: position consumption', [{'bo': 34, 'ce': 34, 'ek': 30, 'fu': 26}],
   {'bo': 3, 'ce': 3, 'ek': 1}),
  ('second regression', [{'ax': 34, 'ce': 7, 'di': 0, 'gi': 34}], {'ax': 3, 'ce': 1, 'gi': 3}),
  ('normal control 1', [{'ce': 0, 'gi': -2, 'ho': -2}], {}),
  ('normal control 2', [{'ce': 12, 'ek': -2, 'fu': 29, 'ho': 12}], {'ce': 2, 'fu': 3, 'ho': 2}),
  ('normal control 3', [{'ce': -2, 'ek': 34, 'fu': 12}], {'ek': 3, 'fu': 2}),
  ('normal control 4', [{'ce': 34, 'di': -2, 'gi': 30}], {'ce': 3, 'gi': 2})],
 [('regression: position consumption', [{'ax': 34, 'bo': 12, 'ce': 34, 'di': 34, 'fu': 0, 'gi': 30, 'ho': 0}],
   {'ax': 3, 'ce': 3, 'di': 3}),
  ('partial repair probe: position consumption', [{'bo': 0, 'ce': 17, 'fu': 30, 'ho': 34}],
   {'ce': 1, 'fu': 2, 'ho': 3}),
  ('second regression', [{'ax': 34, 'ek': 28, 'gi': 30}], {'ax': 3, 'ek': 1, 'gi': 2}),
  ('normal control 1', [{'ce': 34, 'di': 0, 'ek': 34}], {'ce': 3, 'ek': 3}),
  ('normal control 2', [{'bo': -2, 'di': -2, 'fu': 24}], {'fu': 3}),
  ('normal control 3', [{'ax': 0, 'di': 0, 'fu': 30, 'ho': 12}], {'fu': 3, 'ho': 2}),
  ('normal control 4', [{'ax': 34, 'bo': -2, 'ce': -2, 'ek': 0, 'fu': 12, 'gi': 0, 'ho': -2}],
   {'ax': 3, 'fu': 2})],
 [('regression: position consumption',
   [{'ax': 12, 'bo': 34, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 12, 'gi': 34, 'ho': 27}],
   {'bo': 3, 'ce': 3, 'gi': 3}),
  ('partial repair probe: position consumption', [{'ax': 12, 'ce': 30, 'ek': 27, 'ho': -2}],
   {'ax': 1, 'ce': 3, 'ek': 2}),
  ('second regression', [{'ax': 27, 'bo': 0, 'ce': 34, 'di': 0, 'ek': 0, 'fu': 27, 'gi': 30, 'ho': 0}],
   {'ax': 1, 'ce': 3, 'fu': 1, 'gi': 2}),
  ('normal control 1', [{'bo': 12, 'di': 34, 'fu': 0}], {'bo': 2, 'di': 3}),
  ('normal control 2', [{'ax': 0, 'ce': 0, 'fu': -2}], {}),
  ('normal control 3', [{'ax': 30, 'ek': 30, 'gi': 34}], {'ax': 2, 'ek': 2, 'gi': 3}),
  ('normal control 4', [{'ce': -2, 'di': 0, 'fu': 34, 'ho': 34}], {'fu': 3, 'ho': 3})],
 [('regression: position consumption',
   [{'ax': 12, 'bo': 34, 'ce': 0, 'di': 34, 'fu': 30, 'gi': 34, 'ho': 30}], {'bo': 3, 'di': 3, 'gi': 3}),
  ('partial repair probe: position consumption',
   [{'ax': 30, 'bo': 0, 'ce': 0, 'ek': 27, 'fu': 27, 'gi': 12, 'ho': 34}],
   {'ax': 2, 'ek': 1, 'fu': 1, 'ho': 3}),
  ('second regression', [{'ax': 27, 'ce': 8, 'di': 0, 'fu': 30, 'gi': -2}], {'ax': 2, 'ce': 1, 'fu': 3}),
  ('normal control 1', [{'bo': 34, 'di': 27, 'ek': -2}], {'bo': 3, 'di': 2}),
  ('normal control 2', [{'ax': 30, 'bo': 12, 'ce': 0, 'fu': 12, 'ho': 12}],
   {'ax': 3, 'bo': 2, 'fu': 2, 'ho': 2}),
  ('normal control 3', [{'ax': -2, 'ce': -2, 'di': -2, 'ek': -2}], {}),
  ('normal control 4', [{'bo': -2, 'gi': 0, 'ho': 12}], {'ho': 3})]]
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: position consumption	`{'bo': 3, 'ce': 1, 'fu': 3}`	`{'bo': 3, 'ce': 1, 'fu': 3}`	Passed
partial repair probe: position consumption	`{'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}`	`{'ax': 1, 'di': 2, 'gi': 3, 'ho': 1}`	Passed
second regression	`{'ce': 3, 'fu': 1, 'gi': 2}`	`{'ce': 3, 'fu': 1, 'gi': 2}`	Passed
normal control 1	`{'bo': 2, 'ek': 2, 'fu': 3}`	`{'bo': 2, 'ek': 2, 'fu': 3}`	Passed
normal control 2	`{'di': 2, 'ek': 3}`	`{'di': 2, 'ek': 3}`	Passed
normal control 3	`{'ce': 3}`	`{'ce': 3}`	Passed
normal control 4	`{'ax': 3, 'ce': 3, 'ek': 3}`	`{'ax': 3, 'ce': 3, 'ek': 3}`	Passed

SHA-256 / cd16106aa831cd64a22ecb670e6fdaca6d9cd005db054bb117f147a044d8cd6f

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 2026-09-29T14:50:38.761623+00:00.

Case digest / f578eaec59559bd54790530db7f245a8331cd96d643d580620168684c9564f9f