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FA-67411 / Elevator dispatch scheduling / Open access

Load weighing dispatch modes: overload boundary · case 01

A car loaded exactly to the overload limit refuses to depart, or a heavy overload departs.

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

ROOT CAUSE

The overload comparison is inclusive.

VERIFIED REPAIR

Hold the car only when the load exceeds 110% of the rating.

Unsuccessful approach: Adding 110 kg instead of 10% is only right for a 1100 kg rating.

Case contract

Overload (load above 110% of rating) keeps the car at the floor: no departure, no hall service, no cancellation. Otherwise the car departs; at 80% or more it runs in bypass (ignores hall calls). Anti-nuisance cancels all car calls when the load is below 10% of rating and more than three car calls are registered. Percentages are exact integer comparisons.

Why this case matters

Lift group controllers make these decisions many times per minute; a wrong answer strands passengers, wastes trips or overrides a safety rule.

1 / The failure

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

N = 1
observations = []
def solve(x):
    r = x['rated_kg']
    w = x['load_kg']
    if w * 100 >= r * 110:
        return {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}
    full = w * 100 >= r * 80
    nuisance = w * 100 < r * 10 and len(x['car_calls']) > 3
    return {'mode': 'bypass' if full else 'normal', 'depart': True, 'serve_hall': not full, 'cancel_car_calls': nuisance}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 7', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': [7, 6, 9, 4]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: exactly 80 percent', {'rated_kg': 630, 'load_kg': 504, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 1', {'rated_kg': 1000, 'load_kg': 800, 'car_calls': [0]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 4', {'rated_kg': 1000, 'load_kg': 0, 'car_calls': [1, 6]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 10', {'rated_kg': 630, 'load_kg': 504, 'car_calls': [3, 6, 2, 8, 5, 7]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: exactly 80 percent', {'rated_kg': 630, 'load_kg': 504, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just under 80 percent', {'rated_kg': 630, 'load_kg': 503, 'car_calls': []}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 12', {'rated_kg': 1000, 'load_kg': 100, 'car_calls': [6, 7, 4, 3, 9, 0]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('sampled regression 15', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [7, 4, 0]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 18', {'rated_kg': 450, 'load_kg': 45, 'car_calls': []}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 78', {'rated_kg': 630, 'load_kg': 694, 'car_calls': [5, 4]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: empty car with four calls', {'rated_kg': 675, 'load_kg': 0, 'car_calls': [0, 1, 2, 3]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': True}), ('control 23', {'rated_kg': 675, 'load_kg': 539, 'car_calls': [0, 7, 5, 9, 8, 4]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 26', {'rated_kg': 675, 'load_kg': 540, 'car_calls': [9, 6, 0]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 29', {'rated_kg': 675, 'load_kg': 66, 'car_calls': [3, 5]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 65', {'rated_kg': 450, 'load_kg': 496, 'car_calls': [6, 0, 7]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: fractional ten percent threshold', {'rated_kg': 675, 'load_kg': 67, 'car_calls': [0, 1, 2, 3, 4]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': True}), ('control 34', {'rated_kg': 1275, 'load_kg': 126, 'car_calls': [7, 3, 1, 0, 2, 4]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': True}), ('control 37', {'rated_kg': 1000, 'load_kg': 100, 'car_calls': [0]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 40', {'rated_kg': 450, 'load_kg': 30, 'car_calls': []}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 59', {'rated_kg': 675, 'load_kg': 750, 'car_calls': [2, 3, 6]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: exactly 80 percent', {'rated_kg': 630, 'load_kg': 504, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 45', {'rated_kg': 630, 'load_kg': 464, 'car_calls': [8, 7, 5, 9, 2]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 48', {'rated_kg': 675, 'load_kg': 153, 'car_calls': [1, 7, 4, 5, 6, 3]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 51', {'rated_kg': 450, 'load_kg': 330, 'car_calls': [6, 0, 7, 9]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression: exactly 110 percent{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Failed
boundary: just over 110 percent{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}Passed
sampled regression 22{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Failed
control 7{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}Passed
boundary: exactly 80 percent{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
control 1{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
control 4{'cancel_car_calls': False, 'depart': True, 'mode': 'normal', 'serve_hall': True}{'cancel_car_calls': False, 'depart': True, 'mode': 'normal', 'serve_hall': True}Passed
control 10{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed

SHA-256 / f53ec7d09982325efaf362e9deb9a1ef80fe1023f74e4255df07f8642a49dc7f

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(x):
    r = x['rated_kg']
    w = x['load_kg']
    if w > r + 110:
        return {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}
    full = w * 100 >= r * 80
    nuisance = w * 100 < r * 10 and len(x['car_calls']) > 3
    return {'mode': 'bypass' if full else 'normal', 'depart': True, 'serve_hall': not full, 'cancel_car_calls': nuisance}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 7', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': [7, 6, 9, 4]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: exactly 80 percent', {'rated_kg': 630, 'load_kg': 504, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 1', {'rated_kg': 1000, 'load_kg': 800, 'car_calls': [0]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 4', {'rated_kg': 1000, 'load_kg': 0, 'car_calls': [1, 6]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 10', {'rated_kg': 630, 'load_kg': 504, 'car_calls': [3, 6, 2, 8, 5, 7]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: exactly 80 percent', {'rated_kg': 630, 'load_kg': 504, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just under 80 percent', {'rated_kg': 630, 'load_kg': 503, 'car_calls': []}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 12', {'rated_kg': 1000, 'load_kg': 100, 'car_calls': [6, 7, 4, 3, 9, 0]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('sampled regression 15', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [7, 4, 0]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 18', {'rated_kg': 450, 'load_kg': 45, 'car_calls': []}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 78', {'rated_kg': 630, 'load_kg': 694, 'car_calls': [5, 4]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: empty car with four calls', {'rated_kg': 675, 'load_kg': 0, 'car_calls': [0, 1, 2, 3]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': True}), ('control 23', {'rated_kg': 675, 'load_kg': 539, 'car_calls': [0, 7, 5, 9, 8, 4]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 26', {'rated_kg': 675, 'load_kg': 540, 'car_calls': [9, 6, 0]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 29', {'rated_kg': 675, 'load_kg': 66, 'car_calls': [3, 5]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 65', {'rated_kg': 450, 'load_kg': 496, 'car_calls': [6, 0, 7]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: fractional ten percent threshold', {'rated_kg': 675, 'load_kg': 67, 'car_calls': [0, 1, 2, 3, 4]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': True}), ('control 34', {'rated_kg': 1275, 'load_kg': 126, 'car_calls': [7, 3, 1, 0, 2, 4]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': True}), ('control 37', {'rated_kg': 1000, 'load_kg': 100, 'car_calls': [0]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 40', {'rated_kg': 450, 'load_kg': 30, 'car_calls': []}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 59', {'rated_kg': 675, 'load_kg': 750, 'car_calls': [2, 3, 6]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: exactly 80 percent', {'rated_kg': 630, 'load_kg': 504, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 45', {'rated_kg': 630, 'load_kg': 464, 'car_calls': [8, 7, 5, 9, 2]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 48', {'rated_kg': 675, 'load_kg': 153, 'car_calls': [1, 7, 4, 5, 6, 3]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 51', {'rated_kg': 450, 'load_kg': 330, 'car_calls': [6, 0, 7, 9]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression: exactly 110 percent{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
boundary: just over 110 percent{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}Failed
sampled regression 22{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
control 7{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}Failed
boundary: exactly 80 percent{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
control 1{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
control 4{'cancel_car_calls': False, 'depart': True, 'mode': 'normal', 'serve_hall': True}{'cancel_car_calls': False, 'depart': True, 'mode': 'normal', 'serve_hall': True}Passed
control 10{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed

SHA-256 / 937d2e1802fe3a13d76896c7597f8199a01d6df5488cd6788aebb1aecc89faa4

3 / The verified repair

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

N = 1
observations = []
def solve(x):
    r = x['rated_kg']
    w = x['load_kg']
    if w * 100 > r * 110:
        return {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}
    full = w * 100 >= r * 80
    nuisance = w * 100 < r * 10 and len(x['car_calls']) > 3
    return {'mode': 'bypass' if full else 'normal', 'depart': True, 'serve_hall': not full, 'cancel_car_calls': nuisance}
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 7', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': [7, 6, 9, 4]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: exactly 80 percent', {'rated_kg': 630, 'load_kg': 504, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 1', {'rated_kg': 1000, 'load_kg': 800, 'car_calls': [0]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 4', {'rated_kg': 1000, 'load_kg': 0, 'car_calls': [1, 6]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 10', {'rated_kg': 630, 'load_kg': 504, 'car_calls': [3, 6, 2, 8, 5, 7]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: exactly 80 percent', {'rated_kg': 630, 'load_kg': 504, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just under 80 percent', {'rated_kg': 630, 'load_kg': 503, 'car_calls': []}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 12', {'rated_kg': 1000, 'load_kg': 100, 'car_calls': [6, 7, 4, 3, 9, 0]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('sampled regression 15', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [7, 4, 0]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 18', {'rated_kg': 450, 'load_kg': 45, 'car_calls': []}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 78', {'rated_kg': 630, 'load_kg': 694, 'car_calls': [5, 4]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: empty car with four calls', {'rated_kg': 675, 'load_kg': 0, 'car_calls': [0, 1, 2, 3]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': True}), ('control 23', {'rated_kg': 675, 'load_kg': 539, 'car_calls': [0, 7, 5, 9, 8, 4]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 26', {'rated_kg': 675, 'load_kg': 540, 'car_calls': [9, 6, 0]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 29', {'rated_kg': 675, 'load_kg': 66, 'car_calls': [3, 5]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 65', {'rated_kg': 450, 'load_kg': 496, 'car_calls': [6, 0, 7]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: fractional ten percent threshold', {'rated_kg': 675, 'load_kg': 67, 'car_calls': [0, 1, 2, 3, 4]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': True}), ('control 34', {'rated_kg': 1275, 'load_kg': 126, 'car_calls': [7, 3, 1, 0, 2, 4]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': True}), ('control 37', {'rated_kg': 1000, 'load_kg': 100, 'car_calls': [0]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 40', {'rated_kg': 450, 'load_kg': 30, 'car_calls': []}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})], [('regression: exactly 110 percent', {'rated_kg': 1000, 'load_kg': 1100, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: just over 110 percent', {'rated_kg': 1000, 'load_kg': 1101, 'car_calls': []}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('sampled regression 22', {'rated_kg': 630, 'load_kg': 693, 'car_calls': [9, 7, 3]}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 59', {'rated_kg': 675, 'load_kg': 750, 'car_calls': [2, 3, 6]}, {'mode': 'overload', 'depart': False, 'serve_hall': False, 'cancel_car_calls': False}), ('boundary: exactly 80 percent', {'rated_kg': 630, 'load_kg': 504, 'car_calls': []}, {'mode': 'bypass', 'depart': True, 'serve_hall': False, 'cancel_car_calls': False}), ('control 45', {'rated_kg': 630, 'load_kg': 464, 'car_calls': [8, 7, 5, 9, 2]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 48', {'rated_kg': 675, 'load_kg': 153, 'car_calls': [1, 7, 4, 5, 6, 3]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False}), ('control 51', {'rated_kg': 450, 'load_kg': 330, 'car_calls': [6, 0, 7, 9]}, {'mode': 'normal', 'depart': True, 'serve_hall': True, 'cancel_car_calls': False})]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression: exactly 110 percent{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
boundary: just over 110 percent{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}Passed
sampled regression 22{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
control 7{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}{'cancel_car_calls': False, 'depart': False, 'mode': 'overload', 'serve_hall': False}Passed
boundary: exactly 80 percent{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
control 1{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed
control 4{'cancel_car_calls': False, 'depart': True, 'mode': 'normal', 'serve_hall': True}{'cancel_car_calls': False, 'depart': True, 'mode': 'normal', 'serve_hall': True}Passed
control 10{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}{'cancel_car_calls': False, 'depart': True, 'mode': 'bypass', 'serve_hall': False}Passed

SHA-256 / 4dec272911fed4e3799d0423469e5caf67a64c8c10e4e8ffcf62d6ccadcaa8e1

Verification & scope

Stipulated toy lift-control contract for a bounded teaching model; it makes no claim of conformance to any lift code or vendor dispatcher and omits real safety cases. 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 2026-09-29T14:47:52.619551+00:00.

Case digest / 79245a2f5c9b85c1d66eacafb98badca6882f4a547ea0331f6a25a39f5b00d0d