FA-85596 / Ride-hailing fare and surge pricing / Open access
Flat promo larger than the fare creates negative amount due · case 01
A 25.00 credit code on a 7.00 ride shows -18.00 due.
ROOT CAUSE
The flat discount is not limited to the fare.
VERIFIED REPAIR
Cap flat discounts at the fare.
Unsuccessful approach: Leaving one cent due still misstates a fully covered ride.
Case contract
Validate a promo in order: expired if now_day is after expires_day (the expiry day itself is valid), exhausted if no uses remain, not_first if first-ride-only and the rider has prior rides, min_fare if the fare (cents) is below min_fare. A valid pct promo takes value% of the fare (floored), capped at cap cents when cap is not None (a cap of 0 means a zero discount); a flat promo takes value but never more than the fare. Ride credits then cover up to the remaining fare. Return discount, credit used, amount due and reason.
Why this case matters
Ride-hailing prices are computed per trip at scale; ordering, unit and boundary slips become systematic over- or under-charging.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(promo, ride, now_day):
reason = None
if now_day > promo['expires_day']:
reason = 'expired'
elif promo['uses_left'] <= 0:
reason = 'exhausted'
elif promo['first_ride_only'] and ride['rider_rides'] > 0:
reason = 'not_first'
elif ride['fare'] < promo['min_fare']:
reason = 'min_fare'
disc = 0
if reason is None:
if promo['kind'] == 'pct':
disc = ride['fare'] * promo['value'] // 100
if promo['cap'] is not None:
disc = min(disc, promo['cap'])
else:
disc = promo['value']
credit = min(ride['credits'], ride['fare'] - disc)
return {'discount': disc, 'credit_used': credit, 'due': ride['fare'] - disc - credit, 'reason': reason}
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 0, 'fare': 2400, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 2500},
{'credits': 0, 'fare': 700, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 700, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 2500},
{'credits': 0, 'fare': 1099, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 1,
'value': 1000},
{'credits': 0, 'fare': 1099, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 1000, 'due': 99, 'reason': None}),
('normal control 2',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 0,
'value': 10},
{'credits': 0, 'fare': 1000, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'}),
('normal control 3',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 250, 'fare': 1099, 'rider_rides': 0}, 101],
{'credit_used': 250, 'discount': 0, 'due': 849, 'reason': 'expired'}),
('normal control 4',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': True,
'kind': 'pct',
'min_fare': 1000,
'uses_left': 3,
'value': 10},
{'credits': 0, 'fare': 1000, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'not_first'})],
[('regression: flat promo above fare',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 0, 'fare': 1000, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 250, 'fare': 1000, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 1099, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 3,
'value': 25},
{'credits': 0, 'fare': 700, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 175, 'due': 525, 'reason': None}),
('normal control 2',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 500},
{'credits': 250, 'fare': 700, 'rider_rides': 0}, 101],
{'credit_used': 250, 'discount': 0, 'due': 450, 'reason': 'expired'}),
('normal control 3',
[{'cap': None,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 1000},
{'credits': 5000, 'fare': 1050, 'rider_rides': 5}, 100],
{'credit_used': 1050, 'discount': 0, 'due': 0, 'reason': 'not_first'}),
('normal control 4',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 0,
'uses_left': 0,
'value': 500},
{'credits': 0, 'fare': 1000, 'rider_rides': 5}, 99],
{'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'})],
[('regression: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 1,
'value': 2500},
{'credits': 5000, 'fare': 1342, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 1342, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 821, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 821, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 2400, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 500},
{'credits': 250, 'fare': 1099, 'rider_rides': 0}, 100],
{'credit_used': 250, 'discount': 500, 'due': 349, 'reason': None}),
('normal control 2',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 1,
'value': 1000},
{'credits': 5000, 'fare': 1394, 'rider_rides': 0}, 99],
{'credit_used': 394, 'discount': 1000, 'due': 0, 'reason': None}),
('normal control 3',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 1050,
'uses_left': 3,
'value': 25},
{'credits': 250, 'fare': 1605, 'rider_rides': 1}, 101],
{'credit_used': 250, 'discount': 0, 'due': 1355, 'reason': 'expired'}),
('normal control 4',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 1000,
'uses_left': 0,
'value': 10},
{'credits': 250, 'fare': 700, 'rider_rides': 5}, 101],
{'credit_used': 250, 'discount': 0, 'due': 450, 'reason': 'expired'})],
[('regression: flat promo above fare',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 1,
'value': 2500},
{'credits': 0, 'fare': 2400, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 250, 'fare': 1000, 'rider_rides': 1}, 99],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 1,
'value': 2500},
{'credits': 5000, 'fare': 1262, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 1262, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 1000},
{'credits': 0, 'fare': 1050, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1050, 'reason': 'exhausted'}),
('normal control 2',
[{'cap': None,
'expires_day': 100,
'first_ride_only': True,
'kind': 'pct',
'min_fare': 0,
'uses_left': 1,
'value': 25},
{'credits': 250, 'fare': 1050, 'rider_rides': 0}, 99],
{'credit_used': 250, 'discount': 262, 'due': 538, 'reason': None}),
('normal control 3',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 2500},
{'credits': 5000, 'fare': 1050, 'rider_rides': 0}, 101],
{'credit_used': 1050, 'discount': 0, 'due': 0, 'reason': 'expired'}),
('normal control 4',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 3,
'value': 25},
{'credits': 5000, 'fare': 1099, 'rider_rides': 1}, 100],
{'credit_used': 825, 'discount': 274, 'due': 0, 'reason': None})],
[('regression: flat promo above fare',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 2500},
{'credits': 0, 'fare': 1099, 'rider_rides': 5}, 99],
{'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 5000, 'fare': 1000, 'rider_rides': 5}, 99],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 1050, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 1050, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 500},
{'credits': 0, 'fare': 1099, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1099, 'reason': 'not_first'}),
('normal control 2',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 3,
'value': 10},
{'credits': 250, 'fare': 2400, 'rider_rides': 5}, 101],
{'credit_used': 250, 'discount': 0, 'due': 2150, 'reason': 'expired'}),
('normal control 3',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 1,
'value': 500},
{'credits': 250, 'fare': 1000, 'rider_rides': 5}, 101],
{'credit_used': 250, 'discount': 0, 'due': 750, 'reason': 'expired'}),
('normal control 4',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 2500},
{'credits': 250, 'fare': 855, 'rider_rides': 0}, 100],
{'credit_used': 250, 'discount': 0, 'due': 605, 'reason': 'exhausted'})]]
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: flat promo above fare | {'credit_used': -100, 'discount': 2500, 'due': 0, 'reason': None} | {'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None} | Failed |
| partial repair probe: flat promo above fare | {'credit_used': -1800, 'discount': 2500, 'due': 0, 'reason': None} | {'credit_used': 0, 'discount': 700, 'due': 0, 'reason': None} | Failed |
| second regression | {'credit_used': -1401, 'discount': 2500, 'due': 0, 'reason': None} | {'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None} | Failed |
| normal control 1 | {'credit_used': 0, 'discount': 1000, 'due': 99, 'reason': None} | {'credit_used': 0, 'discount': 1000, 'due': 99, 'reason': None} | Passed |
| normal control 2 | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'} | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'} | Passed |
| normal control 3 | {'credit_used': 250, 'discount': 0, 'due': 849, 'reason': 'expired'} | {'credit_used': 250, 'discount': 0, 'due': 849, 'reason': 'expired'} | Passed |
| normal control 4 | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'not_first'} | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'not_first'} | Passed |
SHA-256 / c9273bc4bae32edee5da579a6f9e68d5c65728d17846354e84bd80271eb4bb21
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(promo, ride, now_day):
reason = None
if now_day > promo['expires_day']:
reason = 'expired'
elif promo['uses_left'] <= 0:
reason = 'exhausted'
elif promo['first_ride_only'] and ride['rider_rides'] > 0:
reason = 'not_first'
elif ride['fare'] < promo['min_fare']:
reason = 'min_fare'
disc = 0
if reason is None:
if promo['kind'] == 'pct':
disc = ride['fare'] * promo['value'] // 100
if promo['cap'] is not None:
disc = min(disc, promo['cap'])
else:
disc = min(promo['value'], ride['fare'] - 1)
credit = min(ride['credits'], ride['fare'] - disc)
return {'discount': disc, 'credit_used': credit, 'due': ride['fare'] - disc - credit, 'reason': reason}
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 0, 'fare': 2400, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 2500},
{'credits': 0, 'fare': 700, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 700, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 2500},
{'credits': 0, 'fare': 1099, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 1,
'value': 1000},
{'credits': 0, 'fare': 1099, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 1000, 'due': 99, 'reason': None}),
('normal control 2',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 0,
'value': 10},
{'credits': 0, 'fare': 1000, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'}),
('normal control 3',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 250, 'fare': 1099, 'rider_rides': 0}, 101],
{'credit_used': 250, 'discount': 0, 'due': 849, 'reason': 'expired'}),
('normal control 4',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': True,
'kind': 'pct',
'min_fare': 1000,
'uses_left': 3,
'value': 10},
{'credits': 0, 'fare': 1000, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'not_first'})],
[('regression: flat promo above fare',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 0, 'fare': 1000, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 250, 'fare': 1000, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 1099, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 3,
'value': 25},
{'credits': 0, 'fare': 700, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 175, 'due': 525, 'reason': None}),
('normal control 2',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 500},
{'credits': 250, 'fare': 700, 'rider_rides': 0}, 101],
{'credit_used': 250, 'discount': 0, 'due': 450, 'reason': 'expired'}),
('normal control 3',
[{'cap': None,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 1000},
{'credits': 5000, 'fare': 1050, 'rider_rides': 5}, 100],
{'credit_used': 1050, 'discount': 0, 'due': 0, 'reason': 'not_first'}),
('normal control 4',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 0,
'uses_left': 0,
'value': 500},
{'credits': 0, 'fare': 1000, 'rider_rides': 5}, 99],
{'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'})],
[('regression: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 1,
'value': 2500},
{'credits': 5000, 'fare': 1342, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 1342, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 821, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 821, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 2400, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 500},
{'credits': 250, 'fare': 1099, 'rider_rides': 0}, 100],
{'credit_used': 250, 'discount': 500, 'due': 349, 'reason': None}),
('normal control 2',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 1,
'value': 1000},
{'credits': 5000, 'fare': 1394, 'rider_rides': 0}, 99],
{'credit_used': 394, 'discount': 1000, 'due': 0, 'reason': None}),
('normal control 3',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 1050,
'uses_left': 3,
'value': 25},
{'credits': 250, 'fare': 1605, 'rider_rides': 1}, 101],
{'credit_used': 250, 'discount': 0, 'due': 1355, 'reason': 'expired'}),
('normal control 4',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 1000,
'uses_left': 0,
'value': 10},
{'credits': 250, 'fare': 700, 'rider_rides': 5}, 101],
{'credit_used': 250, 'discount': 0, 'due': 450, 'reason': 'expired'})],
[('regression: flat promo above fare',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 1,
'value': 2500},
{'credits': 0, 'fare': 2400, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 250, 'fare': 1000, 'rider_rides': 1}, 99],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 1,
'value': 2500},
{'credits': 5000, 'fare': 1262, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 1262, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 1000},
{'credits': 0, 'fare': 1050, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1050, 'reason': 'exhausted'}),
('normal control 2',
[{'cap': None,
'expires_day': 100,
'first_ride_only': True,
'kind': 'pct',
'min_fare': 0,
'uses_left': 1,
'value': 25},
{'credits': 250, 'fare': 1050, 'rider_rides': 0}, 99],
{'credit_used': 250, 'discount': 262, 'due': 538, 'reason': None}),
('normal control 3',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 2500},
{'credits': 5000, 'fare': 1050, 'rider_rides': 0}, 101],
{'credit_used': 1050, 'discount': 0, 'due': 0, 'reason': 'expired'}),
('normal control 4',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 3,
'value': 25},
{'credits': 5000, 'fare': 1099, 'rider_rides': 1}, 100],
{'credit_used': 825, 'discount': 274, 'due': 0, 'reason': None})],
[('regression: flat promo above fare',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 2500},
{'credits': 0, 'fare': 1099, 'rider_rides': 5}, 99],
{'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 5000, 'fare': 1000, 'rider_rides': 5}, 99],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 1050, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 1050, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 500},
{'credits': 0, 'fare': 1099, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1099, 'reason': 'not_first'}),
('normal control 2',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 3,
'value': 10},
{'credits': 250, 'fare': 2400, 'rider_rides': 5}, 101],
{'credit_used': 250, 'discount': 0, 'due': 2150, 'reason': 'expired'}),
('normal control 3',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 1,
'value': 500},
{'credits': 250, 'fare': 1000, 'rider_rides': 5}, 101],
{'credit_used': 250, 'discount': 0, 'due': 750, 'reason': 'expired'}),
('normal control 4',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 2500},
{'credits': 250, 'fare': 855, 'rider_rides': 0}, 100],
{'credit_used': 250, 'discount': 0, 'due': 605, 'reason': 'exhausted'})]]
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: flat promo above fare | {'credit_used': 0, 'discount': 2399, 'due': 1, 'reason': None} | {'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None} | Failed |
| partial repair probe: flat promo above fare | {'credit_used': 0, 'discount': 699, 'due': 1, 'reason': None} | {'credit_used': 0, 'discount': 700, 'due': 0, 'reason': None} | Failed |
| second regression | {'credit_used': 0, 'discount': 1098, 'due': 1, 'reason': None} | {'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None} | Failed |
| normal control 1 | {'credit_used': 0, 'discount': 1000, 'due': 99, 'reason': None} | {'credit_used': 0, 'discount': 1000, 'due': 99, 'reason': None} | Passed |
| normal control 2 | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'} | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'} | Passed |
| normal control 3 | {'credit_used': 250, 'discount': 0, 'due': 849, 'reason': 'expired'} | {'credit_used': 250, 'discount': 0, 'due': 849, 'reason': 'expired'} | Passed |
| normal control 4 | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'not_first'} | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'not_first'} | Passed |
SHA-256 / cfbada1ab0f3a19420ea492213b5de170be7913a72b6614bdccd6ed0886bc231
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(promo, ride, now_day):
reason = None
if now_day > promo['expires_day']:
reason = 'expired'
elif promo['uses_left'] <= 0:
reason = 'exhausted'
elif promo['first_ride_only'] and ride['rider_rides'] > 0:
reason = 'not_first'
elif ride['fare'] < promo['min_fare']:
reason = 'min_fare'
disc = 0
if reason is None:
if promo['kind'] == 'pct':
disc = ride['fare'] * promo['value'] // 100
if promo['cap'] is not None:
disc = min(disc, promo['cap'])
else:
disc = min(promo['value'], ride['fare'])
credit = min(ride['credits'], ride['fare'] - disc)
return {'discount': disc, 'credit_used': credit, 'due': ride['fare'] - disc - credit, 'reason': reason}
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 0, 'fare': 2400, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 2500},
{'credits': 0, 'fare': 700, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 700, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 2500},
{'credits': 0, 'fare': 1099, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 1,
'value': 1000},
{'credits': 0, 'fare': 1099, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 1000, 'due': 99, 'reason': None}),
('normal control 2',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 0,
'value': 10},
{'credits': 0, 'fare': 1000, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'}),
('normal control 3',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 250, 'fare': 1099, 'rider_rides': 0}, 101],
{'credit_used': 250, 'discount': 0, 'due': 849, 'reason': 'expired'}),
('normal control 4',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': True,
'kind': 'pct',
'min_fare': 1000,
'uses_left': 3,
'value': 10},
{'credits': 0, 'fare': 1000, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'not_first'})],
[('regression: flat promo above fare',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 0, 'fare': 1000, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 250, 'fare': 1000, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 1099, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 3,
'value': 25},
{'credits': 0, 'fare': 700, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 175, 'due': 525, 'reason': None}),
('normal control 2',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 500},
{'credits': 250, 'fare': 700, 'rider_rides': 0}, 101],
{'credit_used': 250, 'discount': 0, 'due': 450, 'reason': 'expired'}),
('normal control 3',
[{'cap': None,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 1000},
{'credits': 5000, 'fare': 1050, 'rider_rides': 5}, 100],
{'credit_used': 1050, 'discount': 0, 'due': 0, 'reason': 'not_first'}),
('normal control 4',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 0,
'uses_left': 0,
'value': 500},
{'credits': 0, 'fare': 1000, 'rider_rides': 5}, 99],
{'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'})],
[('regression: flat promo above fare',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 1,
'value': 2500},
{'credits': 5000, 'fare': 1342, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 1342, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 821, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 821, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 2400, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 500},
{'credits': 250, 'fare': 1099, 'rider_rides': 0}, 100],
{'credit_used': 250, 'discount': 500, 'due': 349, 'reason': None}),
('normal control 2',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 1,
'value': 1000},
{'credits': 5000, 'fare': 1394, 'rider_rides': 0}, 99],
{'credit_used': 394, 'discount': 1000, 'due': 0, 'reason': None}),
('normal control 3',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 1050,
'uses_left': 3,
'value': 25},
{'credits': 250, 'fare': 1605, 'rider_rides': 1}, 101],
{'credit_used': 250, 'discount': 0, 'due': 1355, 'reason': 'expired'}),
('normal control 4',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 1000,
'uses_left': 0,
'value': 10},
{'credits': 250, 'fare': 700, 'rider_rides': 5}, 101],
{'credit_used': 250, 'discount': 0, 'due': 450, 'reason': 'expired'})],
[('regression: flat promo above fare',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 1,
'value': 2500},
{'credits': 0, 'fare': 2400, 'rider_rides': 0}, 99],
{'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 250, 'fare': 1000, 'rider_rides': 1}, 99],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 1,
'value': 2500},
{'credits': 5000, 'fare': 1262, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 1262, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 1000},
{'credits': 0, 'fare': 1050, 'rider_rides': 5}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1050, 'reason': 'exhausted'}),
('normal control 2',
[{'cap': None,
'expires_day': 100,
'first_ride_only': True,
'kind': 'pct',
'min_fare': 0,
'uses_left': 1,
'value': 25},
{'credits': 250, 'fare': 1050, 'rider_rides': 0}, 99],
{'credit_used': 250, 'discount': 262, 'due': 538, 'reason': None}),
('normal control 3',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 2500},
{'credits': 5000, 'fare': 1050, 'rider_rides': 0}, 101],
{'credit_used': 1050, 'discount': 0, 'due': 0, 'reason': 'expired'}),
('normal control 4',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 3,
'value': 25},
{'credits': 5000, 'fare': 1099, 'rider_rides': 1}, 100],
{'credit_used': 825, 'discount': 274, 'due': 0, 'reason': None})],
[('regression: flat promo above fare',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 2500},
{'credits': 0, 'fare': 1099, 'rider_rides': 5}, 99],
{'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None}),
('partial repair probe: flat promo above fare',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 0,
'uses_left': 1,
'value': 1000},
{'credits': 5000, 'fare': 1000, 'rider_rides': 5}, 99],
{'credit_used': 0, 'discount': 1000, 'due': 0, 'reason': None}),
('second regression',
[{'cap': 0,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 3,
'value': 2500},
{'credits': 5000, 'fare': 1050, 'rider_rides': 0}, 100],
{'credit_used': 0, 'discount': 1050, 'due': 0, 'reason': None}),
('normal control 1',
[{'cap': 800,
'expires_day': 100,
'first_ride_only': True,
'kind': 'flat',
'min_fare': 1000,
'uses_left': 3,
'value': 500},
{'credits': 0, 'fare': 1099, 'rider_rides': 1}, 100],
{'credit_used': 0, 'discount': 0, 'due': 1099, 'reason': 'not_first'}),
('normal control 2',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'pct',
'min_fare': 0,
'uses_left': 3,
'value': 10},
{'credits': 250, 'fare': 2400, 'rider_rides': 5}, 101],
{'credit_used': 250, 'discount': 0, 'due': 2150, 'reason': 'expired'}),
('normal control 3',
[{'cap': 300,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 1,
'value': 500},
{'credits': 250, 'fare': 1000, 'rider_rides': 5}, 101],
{'credit_used': 250, 'discount': 0, 'due': 750, 'reason': 'expired'}),
('normal control 4',
[{'cap': None,
'expires_day': 100,
'first_ride_only': False,
'kind': 'flat',
'min_fare': 1050,
'uses_left': 0,
'value': 2500},
{'credits': 250, 'fare': 855, 'rider_rides': 0}, 100],
{'credit_used': 250, 'discount': 0, 'due': 605, 'reason': 'exhausted'})]]
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: flat promo above fare | {'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None} | {'credit_used': 0, 'discount': 2400, 'due': 0, 'reason': None} | Passed |
| partial repair probe: flat promo above fare | {'credit_used': 0, 'discount': 700, 'due': 0, 'reason': None} | {'credit_used': 0, 'discount': 700, 'due': 0, 'reason': None} | Passed |
| second regression | {'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None} | {'credit_used': 0, 'discount': 1099, 'due': 0, 'reason': None} | Passed |
| normal control 1 | {'credit_used': 0, 'discount': 1000, 'due': 99, 'reason': None} | {'credit_used': 0, 'discount': 1000, 'due': 99, 'reason': None} | Passed |
| normal control 2 | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'} | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'exhausted'} | Passed |
| normal control 3 | {'credit_used': 250, 'discount': 0, 'due': 849, 'reason': 'expired'} | {'credit_used': 250, 'discount': 0, 'due': 849, 'reason': 'expired'} | Passed |
| normal control 4 | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'not_first'} | {'credit_used': 0, 'discount': 0, 'due': 1000, 'reason': 'not_first'} | Passed |
SHA-256 / 65f0c7f1097bcd9612b53d57626e6ae4fb74d4028ff8f4f9cb4f269853624fd4
Verification & scope
A deterministic toy pricing contract stipulated for this example; it does not reproduce the pricing of any real ride-hailing operator or regulator. 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 2026-09-29T14:50:41.838948+00:00.
Case digest / a38d5e7dad84a234abd338f26ab1778e10a4a9a121b63a5ebb5fbde1d1039010