FAILURE MAP
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FA-85921 / Game economy crafting balance / Open access

Banner pity counter: Hard pity pull can miss · case 01

The 90th pull may fail to award a top-rarity item.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The hard-pity comparison is strict, so pull 90 only hits by rate.

VERIFIED REPAIR

Restore `n >= 90 or r < rate` at the hard pity guarantee step.

Unsuccessful approach: Testing the stored pity instead of the pull number moves hard pity to pull 91.

Case contract

Each roll is 0..999. Pull number n = pity+1. Top-rarity rate is 6 per mille, plus 50*(n-73) from n >= 74 (soft pity); n >= 90 always hits. On a hit pity resets to 0; the item is featured ("F") if guarantee is set or the roll is even, otherwise lost ("L") and the guarantee is set; a featured hit clears the guarantee. Misses ("-") set pity = n.

Why this case matters

Game economies leak or destroy currency when one crafting or pricing rule is off by one boundary, rounding stage or state update; the defect is observable in exact integer outcomes.

1 / The failure

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

N = 1
observations = []
def solve(rolls, state):
    pity = state['pity']
    guarantee = state['guarantee']
    out = []
    for r in rolls:
        n = pity + 1
        rate = 6
        if n >= 74:
            rate += 50 * (n - 73)
        if n > 90 or r < rate:
            pity = 0
            if guarantee or r % 2 == 0:
                out.append('F')
                guarantee = False
            else:
                out.append('L')
                guarantee = True
        else:
            pity = n
            out.append('-')
    return {'results': ''.join(out), 'pity': pity, 'guarantee': guarantee}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[935, 90, 29, 166, 937, 997, 903, 315, 848, 1, 893, 36, 218, 730, 858, 726, 972, 10],
    {'pity': 89, 'guarantee': True}],
   {'results': 'F--------L--------', 'pity': 8, 'guarantee': True}),
  ('regression hard pity guarantee #2',
   [[986], {'pity': 89, 'guarantee': True}],
   {'results': 'F', 'pity': 0, 'guarantee': False}),
  ('regression hard pity guarantee #3',
   [[879, 933, 335, 968, 23, 554, 957, 37, 960, 47, 35, 24, 892, 11, 52, 851, 334, 43, 807, 808],
    {'pity': 88, 'guarantee': False}],
   {'results': '-L------------------', 'pity': 18, 'guarantee': True}),
  ('regression hard pity guarantee #4',
   [[812, 997, 899, 10], {'pity': 88, 'guarantee': False}],
   {'results': '-L--', 'pity': 2, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[15, 31, 302, 259, 332, 886, 12, 851, 55, 45, 6, 903, 946, 869, 725], {'pity': 88, 'guarantee': True}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[986], {'pity': 89, 'guarantee': True}],
   {'results': 'F', 'pity': 0, 'guarantee': False}),
  ('regression hard pity guarantee #2',
   [[879, 933, 335, 968, 23, 554, 957, 37, 960, 47, 35, 24, 892, 11, 52, 851, 334, 43, 807, 808],
    {'pity': 88, 'guarantee': False}],
   {'results': '-L------------------', 'pity': 18, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[812, 997, 899, 10], {'pity': 88, 'guarantee': False}],
   {'results': '-L--', 'pity': 2, 'guarantee': True}),
  ('regression hard pity guarantee #4',
   [[941, 855, 955], {'pity': 89, 'guarantee': False}],
   {'results': 'L--', 'pity': 2, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[15, 31, 302, 259, 332, 886, 12, 851, 55, 45, 6, 903, 946, 869, 725], {'pity': 88, 'guarantee': True}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[812, 997, 899, 10], {'pity': 88, 'guarantee': False}],
   {'results': '-L--', 'pity': 2, 'guarantee': True}),
  ('regression hard pity guarantee #2',
   [[941, 855, 955], {'pity': 89, 'guarantee': False}],
   {'results': 'L--', 'pity': 2, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[866, 716, 336, 806, 719, 971, 56, 858, 215, 881, 854, 21, 997, 459, 240],
    {'pity': 89, 'guarantee': False}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False}),
  ('regression hard pity guarantee #4',
   [[835, 921, 31, 855, 841, 35, 966, 806, 957, 858, 42, 57, 921], {'pity': 88, 'guarantee': False}],
   {'results': '-L-----------', 'pity': 11, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[15, 31, 302, 259, 332, 886, 12, 851, 55, 45, 6, 903, 946, 869, 725], {'pity': 88, 'guarantee': True}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[866, 716, 336, 806, 719, 971, 56, 858, 215, 881, 854, 21, 997, 459, 240],
    {'pity': 89, 'guarantee': False}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False}),
  ('regression hard pity guarantee #2',
   [[835, 921, 31, 855, 841, 35, 966, 806, 957, 858, 42, 57, 921], {'pity': 88, 'guarantee': False}],
   {'results': '-L-----------', 'pity': 11, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[890, 52, 19, 184, 980], {'pity': 89, 'guarantee': False}],
   {'results': 'F----', 'pity': 4, 'guarantee': False}),
  ('regression hard pity guarantee #4',
   [[929, 229, 908, 987, 916, 982, 868, 899, 703, 873, 474, 54, 48, 190, 47, 959, 85],
    {'pity': 89, 'guarantee': False}],
   {'results': 'L----------------', 'pity': 16, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[507, 965, 27, 525, 851], {'pity': 73, 'guarantee': True}],
   {'results': '--F--', 'pity': 2, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[890, 52, 19, 184, 980], {'pity': 89, 'guarantee': False}],
   {'results': 'F----', 'pity': 4, 'guarantee': False}),
  ('regression hard pity guarantee #2',
   [[929, 229, 908, 987, 916, 982, 868, 899, 703, 873, 474, 54, 48, 190, 47, 959, 85],
    {'pity': 89, 'guarantee': False}],
   {'results': 'L----------------', 'pity': 16, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[860, 578, 19, 809, 175, 896, 995, 51, 817, 955, 882, 623, 519, 962, 886, 900, 785, 824, 15],
    {'pity': 89, 'guarantee': False}],
   {'results': 'F------------------', 'pity': 18, 'guarantee': False}),
  ('regression hard pity guarantee #4',
   [[999, 955, 867, 824, 299, 243, 930, 89, 25, 397, 757, 7, 112, 301, 716, 703, 998, 888, 950, 816],
    {'pity': 88, 'guarantee': True}],
   {'results': '-F------------------', 'pity': 18, 'guarantee': False}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[480, 489, 823, 13, 936, 776, 44, 409, 26, 974, 9, 54, 911, 804, 433, 47, 942, 847],
    {'pity': 89, 'guarantee': True}],
   {'results': 'F-----------------', 'pity': 17, 'guarantee': False})]]
for label, args, expected in cases[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
hard pity pull #1{'guarantee': True, 'pity': 0, 'results': '-L'}{'guarantee': True, 'pity': 1, 'results': 'L-'}Failed
regression hard pity guarantee #1{'guarantee': True, 'pity': 8, 'results': '-F-------L--------'}{'guarantee': True, 'pity': 8, 'results': 'F--------L--------'}Failed
regression hard pity guarantee #2{'guarantee': True, 'pity': 90, 'results': '-'}{'guarantee': False, 'pity': 0, 'results': 'F'}Failed
regression hard pity guarantee #3{'guarantee': True, 'pity': 17, 'results': '--L-----------------'}{'guarantee': True, 'pity': 18, 'results': '-L------------------'}Failed
regression hard pity guarantee #4{'guarantee': True, 'pity': 1, 'results': '--L-'}{'guarantee': True, 'pity': 2, 'results': '-L--'}Failed
first soft pity pull #1{'guarantee': False, 'pity': 0, 'results': '-F'}{'guarantee': False, 'pity': 0, 'results': '-F'}Passed
lost fifty fifty then featured #1{'guarantee': False, 'pity': 0, 'results': 'L-F'}{'guarantee': False, 'pity': 0, 'results': 'L-F'}Passed
control #1{'guarantee': False, 'pity': 14, 'results': 'F--------------'}{'guarantee': False, 'pity': 14, 'results': 'F--------------'}Passed

SHA-256 / a0e24a984b1ad7a66fdd83e673f5a2de6ad33e4935e704aaa962d90af2f9f57a

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(rolls, state):
    pity = state['pity']
    guarantee = state['guarantee']
    out = []
    for r in rolls:
        n = pity + 1
        rate = 6
        if n >= 74:
            rate += 50 * (n - 73)
        if pity >= 90 or r < rate:
            pity = 0
            if guarantee or r % 2 == 0:
                out.append('F')
                guarantee = False
            else:
                out.append('L')
                guarantee = True
        else:
            pity = n
            out.append('-')
    return {'results': ''.join(out), 'pity': pity, 'guarantee': guarantee}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[935, 90, 29, 166, 937, 997, 903, 315, 848, 1, 893, 36, 218, 730, 858, 726, 972, 10],
    {'pity': 89, 'guarantee': True}],
   {'results': 'F--------L--------', 'pity': 8, 'guarantee': True}),
  ('regression hard pity guarantee #2',
   [[986], {'pity': 89, 'guarantee': True}],
   {'results': 'F', 'pity': 0, 'guarantee': False}),
  ('regression hard pity guarantee #3',
   [[879, 933, 335, 968, 23, 554, 957, 37, 960, 47, 35, 24, 892, 11, 52, 851, 334, 43, 807, 808],
    {'pity': 88, 'guarantee': False}],
   {'results': '-L------------------', 'pity': 18, 'guarantee': True}),
  ('regression hard pity guarantee #4',
   [[812, 997, 899, 10], {'pity': 88, 'guarantee': False}],
   {'results': '-L--', 'pity': 2, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[15, 31, 302, 259, 332, 886, 12, 851, 55, 45, 6, 903, 946, 869, 725], {'pity': 88, 'guarantee': True}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[986], {'pity': 89, 'guarantee': True}],
   {'results': 'F', 'pity': 0, 'guarantee': False}),
  ('regression hard pity guarantee #2',
   [[879, 933, 335, 968, 23, 554, 957, 37, 960, 47, 35, 24, 892, 11, 52, 851, 334, 43, 807, 808],
    {'pity': 88, 'guarantee': False}],
   {'results': '-L------------------', 'pity': 18, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[812, 997, 899, 10], {'pity': 88, 'guarantee': False}],
   {'results': '-L--', 'pity': 2, 'guarantee': True}),
  ('regression hard pity guarantee #4',
   [[941, 855, 955], {'pity': 89, 'guarantee': False}],
   {'results': 'L--', 'pity': 2, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[15, 31, 302, 259, 332, 886, 12, 851, 55, 45, 6, 903, 946, 869, 725], {'pity': 88, 'guarantee': True}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[812, 997, 899, 10], {'pity': 88, 'guarantee': False}],
   {'results': '-L--', 'pity': 2, 'guarantee': True}),
  ('regression hard pity guarantee #2',
   [[941, 855, 955], {'pity': 89, 'guarantee': False}],
   {'results': 'L--', 'pity': 2, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[866, 716, 336, 806, 719, 971, 56, 858, 215, 881, 854, 21, 997, 459, 240],
    {'pity': 89, 'guarantee': False}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False}),
  ('regression hard pity guarantee #4',
   [[835, 921, 31, 855, 841, 35, 966, 806, 957, 858, 42, 57, 921], {'pity': 88, 'guarantee': False}],
   {'results': '-L-----------', 'pity': 11, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[15, 31, 302, 259, 332, 886, 12, 851, 55, 45, 6, 903, 946, 869, 725], {'pity': 88, 'guarantee': True}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[866, 716, 336, 806, 719, 971, 56, 858, 215, 881, 854, 21, 997, 459, 240],
    {'pity': 89, 'guarantee': False}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False}),
  ('regression hard pity guarantee #2',
   [[835, 921, 31, 855, 841, 35, 966, 806, 957, 858, 42, 57, 921], {'pity': 88, 'guarantee': False}],
   {'results': '-L-----------', 'pity': 11, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[890, 52, 19, 184, 980], {'pity': 89, 'guarantee': False}],
   {'results': 'F----', 'pity': 4, 'guarantee': False}),
  ('regression hard pity guarantee #4',
   [[929, 229, 908, 987, 916, 982, 868, 899, 703, 873, 474, 54, 48, 190, 47, 959, 85],
    {'pity': 89, 'guarantee': False}],
   {'results': 'L----------------', 'pity': 16, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[507, 965, 27, 525, 851], {'pity': 73, 'guarantee': True}],
   {'results': '--F--', 'pity': 2, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[890, 52, 19, 184, 980], {'pity': 89, 'guarantee': False}],
   {'results': 'F----', 'pity': 4, 'guarantee': False}),
  ('regression hard pity guarantee #2',
   [[929, 229, 908, 987, 916, 982, 868, 899, 703, 873, 474, 54, 48, 190, 47, 959, 85],
    {'pity': 89, 'guarantee': False}],
   {'results': 'L----------------', 'pity': 16, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[860, 578, 19, 809, 175, 896, 995, 51, 817, 955, 882, 623, 519, 962, 886, 900, 785, 824, 15],
    {'pity': 89, 'guarantee': False}],
   {'results': 'F------------------', 'pity': 18, 'guarantee': False}),
  ('regression hard pity guarantee #4',
   [[999, 955, 867, 824, 299, 243, 930, 89, 25, 397, 757, 7, 112, 301, 716, 703, 998, 888, 950, 816],
    {'pity': 88, 'guarantee': True}],
   {'results': '-F------------------', 'pity': 18, 'guarantee': False}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[480, 489, 823, 13, 936, 776, 44, 409, 26, 974, 9, 54, 911, 804, 433, 47, 942, 847],
    {'pity': 89, 'guarantee': True}],
   {'results': 'F-----------------', 'pity': 17, 'guarantee': False})]]
for label, args, expected in cases[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
hard pity pull #1{'guarantee': True, 'pity': 0, 'results': '-L'}{'guarantee': True, 'pity': 1, 'results': 'L-'}Failed
regression hard pity guarantee #1{'guarantee': True, 'pity': 8, 'results': '-F-------L--------'}{'guarantee': True, 'pity': 8, 'results': 'F--------L--------'}Failed
regression hard pity guarantee #2{'guarantee': True, 'pity': 90, 'results': '-'}{'guarantee': False, 'pity': 0, 'results': 'F'}Failed
regression hard pity guarantee #3{'guarantee': True, 'pity': 17, 'results': '--L-----------------'}{'guarantee': True, 'pity': 18, 'results': '-L------------------'}Failed
regression hard pity guarantee #4{'guarantee': True, 'pity': 1, 'results': '--L-'}{'guarantee': True, 'pity': 2, 'results': '-L--'}Failed
first soft pity pull #1{'guarantee': False, 'pity': 0, 'results': '-F'}{'guarantee': False, 'pity': 0, 'results': '-F'}Passed
lost fifty fifty then featured #1{'guarantee': False, 'pity': 0, 'results': 'L-F'}{'guarantee': False, 'pity': 0, 'results': 'L-F'}Passed
control #1{'guarantee': False, 'pity': 14, 'results': 'F--------------'}{'guarantee': False, 'pity': 14, 'results': 'F--------------'}Passed

SHA-256 / ecc60c2d0d8ed07a0a19a8983090a7d6745b15e2af520b19d9625c49b2df1d25

3 / The verified repair

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

N = 1
observations = []
def solve(rolls, state):
    pity = state['pity']
    guarantee = state['guarantee']
    out = []
    for r in rolls:
        n = pity + 1
        rate = 6
        if n >= 74:
            rate += 50 * (n - 73)
        if n >= 90 or r < rate:
            pity = 0
            if guarantee or r % 2 == 0:
                out.append('F')
                guarantee = False
            else:
                out.append('L')
                guarantee = True
        else:
            pity = n
            out.append('-')
    return {'results': ''.join(out), 'pity': pity, 'guarantee': guarantee}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[935, 90, 29, 166, 937, 997, 903, 315, 848, 1, 893, 36, 218, 730, 858, 726, 972, 10],
    {'pity': 89, 'guarantee': True}],
   {'results': 'F--------L--------', 'pity': 8, 'guarantee': True}),
  ('regression hard pity guarantee #2',
   [[986], {'pity': 89, 'guarantee': True}],
   {'results': 'F', 'pity': 0, 'guarantee': False}),
  ('regression hard pity guarantee #3',
   [[879, 933, 335, 968, 23, 554, 957, 37, 960, 47, 35, 24, 892, 11, 52, 851, 334, 43, 807, 808],
    {'pity': 88, 'guarantee': False}],
   {'results': '-L------------------', 'pity': 18, 'guarantee': True}),
  ('regression hard pity guarantee #4',
   [[812, 997, 899, 10], {'pity': 88, 'guarantee': False}],
   {'results': '-L--', 'pity': 2, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[15, 31, 302, 259, 332, 886, 12, 851, 55, 45, 6, 903, 946, 869, 725], {'pity': 88, 'guarantee': True}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[986], {'pity': 89, 'guarantee': True}],
   {'results': 'F', 'pity': 0, 'guarantee': False}),
  ('regression hard pity guarantee #2',
   [[879, 933, 335, 968, 23, 554, 957, 37, 960, 47, 35, 24, 892, 11, 52, 851, 334, 43, 807, 808],
    {'pity': 88, 'guarantee': False}],
   {'results': '-L------------------', 'pity': 18, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[812, 997, 899, 10], {'pity': 88, 'guarantee': False}],
   {'results': '-L--', 'pity': 2, 'guarantee': True}),
  ('regression hard pity guarantee #4',
   [[941, 855, 955], {'pity': 89, 'guarantee': False}],
   {'results': 'L--', 'pity': 2, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[15, 31, 302, 259, 332, 886, 12, 851, 55, 45, 6, 903, 946, 869, 725], {'pity': 88, 'guarantee': True}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[812, 997, 899, 10], {'pity': 88, 'guarantee': False}],
   {'results': '-L--', 'pity': 2, 'guarantee': True}),
  ('regression hard pity guarantee #2',
   [[941, 855, 955], {'pity': 89, 'guarantee': False}],
   {'results': 'L--', 'pity': 2, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[866, 716, 336, 806, 719, 971, 56, 858, 215, 881, 854, 21, 997, 459, 240],
    {'pity': 89, 'guarantee': False}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False}),
  ('regression hard pity guarantee #4',
   [[835, 921, 31, 855, 841, 35, 966, 806, 957, 858, 42, 57, 921], {'pity': 88, 'guarantee': False}],
   {'results': '-L-----------', 'pity': 11, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[15, 31, 302, 259, 332, 886, 12, 851, 55, 45, 6, 903, 946, 869, 725], {'pity': 88, 'guarantee': True}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[866, 716, 336, 806, 719, 971, 56, 858, 215, 881, 854, 21, 997, 459, 240],
    {'pity': 89, 'guarantee': False}],
   {'results': 'F--------------', 'pity': 14, 'guarantee': False}),
  ('regression hard pity guarantee #2',
   [[835, 921, 31, 855, 841, 35, 966, 806, 957, 858, 42, 57, 921], {'pity': 88, 'guarantee': False}],
   {'results': '-L-----------', 'pity': 11, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[890, 52, 19, 184, 980], {'pity': 89, 'guarantee': False}],
   {'results': 'F----', 'pity': 4, 'guarantee': False}),
  ('regression hard pity guarantee #4',
   [[929, 229, 908, 987, 916, 982, 868, 899, 703, 873, 474, 54, 48, 190, 47, 959, 85],
    {'pity': 89, 'guarantee': False}],
   {'results': 'L----------------', 'pity': 16, 'guarantee': True}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[507, 965, 27, 525, 851], {'pity': 73, 'guarantee': True}],
   {'results': '--F--', 'pity': 2, 'guarantee': False})],
 [('hard pity pull #1',
   [[999, 999], {'pity': 89, 'guarantee': False}],
   {'results': 'L-', 'pity': 1, 'guarantee': True}),
  ('regression hard pity guarantee #1',
   [[890, 52, 19, 184, 980], {'pity': 89, 'guarantee': False}],
   {'results': 'F----', 'pity': 4, 'guarantee': False}),
  ('regression hard pity guarantee #2',
   [[929, 229, 908, 987, 916, 982, 868, 899, 703, 873, 474, 54, 48, 190, 47, 959, 85],
    {'pity': 89, 'guarantee': False}],
   {'results': 'L----------------', 'pity': 16, 'guarantee': True}),
  ('regression hard pity guarantee #3',
   [[860, 578, 19, 809, 175, 896, 995, 51, 817, 955, 882, 623, 519, 962, 886, 900, 785, 824, 15],
    {'pity': 89, 'guarantee': False}],
   {'results': 'F------------------', 'pity': 18, 'guarantee': False}),
  ('regression hard pity guarantee #4',
   [[999, 955, 867, 824, 299, 243, 930, 89, 25, 397, 757, 7, 112, 301, 716, 703, 998, 888, 950, 816],
    {'pity': 88, 'guarantee': True}],
   {'results': '-F------------------', 'pity': 18, 'guarantee': False}),
  ('first soft pity pull #1',
   [[100, 3], {'pity': 73, 'guarantee': True}],
   {'results': '-F', 'pity': 0, 'guarantee': False}),
  ('lost fifty fifty then featured #1',
   [[1, 999, 0], {'pity': 10, 'guarantee': False}],
   {'results': 'L-F', 'pity': 0, 'guarantee': False}),
  ('control #1',
   [[480, 489, 823, 13, 936, 776, 44, 409, 26, 974, 9, 54, 911, 804, 433, 47, 942, 847],
    {'pity': 89, 'guarantee': True}],
   {'results': 'F-----------------', 'pity': 17, 'guarantee': False})]]
for label, args, expected in cases[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
hard pity pull #1{'guarantee': True, 'pity': 1, 'results': 'L-'}{'guarantee': True, 'pity': 1, 'results': 'L-'}Passed
regression hard pity guarantee #1{'guarantee': True, 'pity': 8, 'results': 'F--------L--------'}{'guarantee': True, 'pity': 8, 'results': 'F--------L--------'}Passed
regression hard pity guarantee #2{'guarantee': False, 'pity': 0, 'results': 'F'}{'guarantee': False, 'pity': 0, 'results': 'F'}Passed
regression hard pity guarantee #3{'guarantee': True, 'pity': 18, 'results': '-L------------------'}{'guarantee': True, 'pity': 18, 'results': '-L------------------'}Passed
regression hard pity guarantee #4{'guarantee': True, 'pity': 2, 'results': '-L--'}{'guarantee': True, 'pity': 2, 'results': '-L--'}Passed
first soft pity pull #1{'guarantee': False, 'pity': 0, 'results': '-F'}{'guarantee': False, 'pity': 0, 'results': '-F'}Passed
lost fifty fifty then featured #1{'guarantee': False, 'pity': 0, 'results': 'L-F'}{'guarantee': False, 'pity': 0, 'results': 'L-F'}Passed
control #1{'guarantee': False, 'pity': 14, 'results': 'F--------------'}{'guarantee': False, 'pity': 14, 'results': 'F--------------'}Passed

SHA-256 / b11ab144bd7ec78de822e2145292a33125a6e797dbfb93dd138f362919fb3a26

Verification & scope

Deterministic toy contract stipulated for this model; integer or exact arithmetic only, not a reproduction of any specific game engine. 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 2026-09-29T14:50:44.858338+00:00.

Case digest / 23b4e45d4a733f9a930cdc6380a99d35a2c84f182b613f2d48d01c2c7b64d71f