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FA-85741 / Ride-hailing fare and surge pricing / Open access

Published multiplier exceeds the 3.0x cap · case 01

A raw 3.5x zone publishes 3.5x.

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

ROOT CAUSE

The upper clamp is missing.

VERIFIED REPAIR

Clamp the published multiplier to at most 30.

Unsuccessful approach: Capping only neighbor-derived values lets raw values above the cap through.

Case contract

Smooth zone multipliers (tenths): each zone publishes the max of its own raw multiplier and each neighbor's raw multiplier minus 5, clamped to [10, 30]. Adjacency is symmetric even when listed once; neighbors without a raw multiplier are ignored; all reads use raw values, never already-smoothed ones. Return zone -> published multiplier.

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(mult, adj):
    out = {}
    for z in sorted(mult):
        nbrs = set(adj.get(z, [])) | {a for a, lst in adj.items() if z in lst}
        best = mult[z]
        for nb in sorted(nbrs):
            if nb in mult:
                best = max(best, mult[nb] - 5)
        out[z] = max(best, 10)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: publication cap',
   [{'A': 35, 'B': 25, 'C': 15, 'D': 25, 'E': 10},
    {'A': [], 'B': ['C'], 'C': ['E'], 'D': [], 'E': ['B', 'C']}],
   {'A': 30, 'B': 25, 'C': 20, 'D': 25, 'E': 20}),
  ('partial repair probe: publication cap',
   [{'A': 35, 'B': 10, 'C': 25, 'D': 25, 'E': 25}, {'A': [], 'B': ['D'], 'C': [], 'D': [], 'E': ['D']}],
   {'A': 30, 'B': 20, 'C': 25, 'D': 25, 'E': 25}),
  ('second regression',
   [{'A': 20, 'B': 35, 'C': 10, 'D': 12, 'E': 15},
    {'A': ['C'], 'B': ['E', 'C'], 'C': ['D'], 'D': [], 'E': ['D']}],
   {'A': 20, 'B': 30, 'C': 30, 'D': 12, 'E': 30}),
  ('normal control 1',
   [{'A': 25, 'B': 20, 'C': 10, 'D': 10}, {'A': ['E', 'D'], 'B': ['C'], 'C': ['A'], 'D': ['A'], 'E': ['D']}],
   {'A': 25, 'B': 20, 'C': 20, 'D': 20}),
  ('normal control 2', [{'A': 10, 'B': 20, 'C': 12}, {'A': [], 'B': [], 'C': [], 'D': [], 'E': ['C']}],
   {'A': 10, 'B': 20, 'C': 12}),
  ('normal control 3',
   [{'A': 12, 'B': 10, 'C': 20}, {'A': [], 'B': ['C'], 'C': ['A'], 'D': ['C'], 'E': ['B']}],
   {'A': 15, 'B': 15, 'C': 20}),
  ('normal control 4',
   [{'A': 20, 'B': 10, 'C': 15, 'D': 12}, {'A': [], 'B': ['D'], 'C': [], 'D': ['C', 'E'], 'E': ['D', 'C']}],
   {'A': 20, 'B': 10, 'C': 15, 'D': 12})],
 [('regression: publication cap',
   [{'A': 25, 'B': 15, 'C': 25, 'D': 35, 'E': 12},
    {'A': [], 'B': ['D', 'E'], 'C': ['B', 'E'], 'D': ['A', 'B'], 'E': ['A']}],
   {'A': 30, 'B': 30, 'C': 25, 'D': 30, 'E': 20}),
  ('partial repair probe: publication cap',
   [{'A': 15, 'B': 20, 'C': 35}, {'A': ['C', 'E'], 'B': ['E'], 'C': ['E', 'A'], 'D': ['E', 'C'], 'E': ['A']}],
   {'A': 30, 'B': 20, 'C': 30}),
  ('second regression',
   [{'A': 25, 'B': 35, 'C': 15, 'D': 20, 'E': 25},
    {'A': ['D'], 'B': ['A', 'C'], 'C': ['D'], 'D': ['C', 'B'], 'E': []}],
   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 25}),
  ('normal control 1',
   [{'A': 10, 'B': 15, 'C': 20, 'D': 12}, {'A': ['C'], 'B': ['E'], 'C': [], 'D': ['C'], 'E': []}],
   {'A': 15, 'B': 15, 'C': 20, 'D': 15}),
  ('normal control 2',
   [{'A': 25, 'B': 15, 'C': 25}, {'A': ['E', 'C'], 'B': ['D', 'A'], 'C': ['D'], 'D': ['E'], 'E': ['C']}],
   {'A': 25, 'B': 20, 'C': 25}),
  ('normal control 3',
   [{'A': 25, 'B': 12, 'C': 25, 'D': 15, 'E': 10}, {'A': [], 'B': ['A'], 'C': [], 'D': ['E', 'B'], 'E': []}],
   {'A': 25, 'B': 20, 'C': 25, 'D': 15, 'E': 10}),
  ('normal control 4', [{'A': 25, 'B': 10, 'C': 15}, {'A': ['E'], 'B': ['C'], 'C': [], 'D': ['B'], 'E': []}],
   {'A': 25, 'B': 10, 'C': 15})],
 [('regression: publication cap',
   [{'A': 25, 'B': 35, 'C': 35, 'D': 35, 'E': 35},
    {'A': ['E'], 'B': ['E'], 'C': [], 'D': [], 'E': ['A', 'C']}],
   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 30}),
  ('partial repair probe: publication cap',
   [{'A': 35, 'B': 10, 'C': 12, 'D': 25, 'E': 10},
    {'A': ['C', 'D'], 'B': ['A', 'D'], 'C': [], 'D': [], 'E': ['D']}],
   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 20}),
  ('second regression',
   [{'A': 25, 'B': 12, 'C': 12, 'D': 35, 'E': 12}, {'A': ['B'], 'B': [], 'C': [], 'D': [], 'E': ['A']}],
   {'A': 25, 'B': 20, 'C': 12, 'D': 30, 'E': 20}),
  ('normal control 1',
   [{'A': 12, 'B': 25, 'C': 10}, {'A': [], 'B': [], 'C': [], 'D': ['A', 'E'], 'E': ['D']}],
   {'A': 12, 'B': 25, 'C': 10}),
  ('normal control 2',
   [{'A': 20, 'B': 12, 'C': 10, 'D': 12}, {'A': ['C', 'B'], 'B': [], 'C': [], 'D': ['E'], 'E': []}],
   {'A': 20, 'B': 15, 'C': 15, 'D': 12}),
  ('normal control 3',
   [{'A': 25, 'B': 12, 'C': 25, 'D': 12}, {'A': ['E', 'B'], 'B': ['D', 'A'], 'C': [], 'D': [], 'E': ['D']}],
   {'A': 25, 'B': 20, 'C': 25, 'D': 12}),
  ('normal control 4',
   [{'A': 15, 'B': 25, 'C': 12, 'D': 15}, {'A': ['E'], 'B': [], 'C': ['A'], 'D': ['E'], 'E': ['A', 'C']}],
   {'A': 15, 'B': 25, 'C': 12, 'D': 15})],
 [('regression: publication cap',
   [{'A': 12, 'B': 35, 'C': 25}, {'A': ['D'], 'B': ['E', 'D'], 'C': ['A'], 'D': ['B'], 'E': []}],
   {'A': 20, 'B': 30, 'C': 25}),
  ('partial repair probe: publication cap',
   [{'A': 12, 'B': 20, 'C': 35, 'D': 20, 'E': 12},
    {'A': ['B', 'E'], 'B': [], 'C': ['A'], 'D': ['C'], 'E': ['B', 'D']}],
   {'A': 30, 'B': 20, 'C': 30, 'D': 30, 'E': 15}),
  ('second regression',
   [{'A': 12, 'B': 15, 'C': 35, 'D': 12, 'E': 25}, {'A': [], 'B': ['E', 'C'], 'C': ['D'], 'D': [], 'E': []}],
   {'A': 12, 'B': 30, 'C': 30, 'D': 30, 'E': 25}),
  ('normal control 1',
   [{'A': 20, 'B': 12, 'C': 15}, {'A': ['D'], 'B': [], 'C': ['A'], 'D': ['C', 'E'], 'E': []}],
   {'A': 20, 'B': 12, 'C': 15}),
  ('normal control 2',
   [{'A': 12, 'B': 12, 'C': 12, 'D': 15}, {'A': [], 'B': [], 'C': ['B', 'E'], 'D': ['C'], 'E': []}],
   {'A': 12, 'B': 12, 'C': 12, 'D': 15}),
  ('normal control 3',
   [{'A': 12, 'B': 20, 'C': 15, 'D': 20}, {'A': [], 'B': [], 'C': ['E', 'B'], 'D': ['C', 'A'], 'E': []}],
   {'A': 15, 'B': 20, 'C': 15, 'D': 20}),
  ('normal control 4',
   [{'A': 15, 'B': 15, 'C': 12}, {'A': [], 'B': ['D'], 'C': [], 'D': ['C'], 'E': ['B', 'A']}],
   {'A': 15, 'B': 15, 'C': 12})],
 [('regression: publication cap',
   [{'A': 35, 'B': 10, 'C': 10, 'D': 10}, {'A': ['D'], 'B': [], 'C': ['B'], 'D': ['B', 'E'], 'E': ['D']}],
   {'A': 30, 'B': 10, 'C': 10, 'D': 30}),
  ('partial repair probe: publication cap',
   [{'A': 35, 'B': 10, 'C': 12, 'D': 20}, {'A': [], 'B': ['D', 'E'], 'C': [], 'D': ['A'], 'E': ['D']}],
   {'A': 30, 'B': 15, 'C': 12, 'D': 30}),
  ('second regression',
   [{'A': 10, 'B': 35, 'C': 25, 'D': 12}, {'A': [], 'B': [], 'C': [], 'D': [], 'E': ['A']}],
   {'A': 10, 'B': 30, 'C': 25, 'D': 12}),
  ('normal control 1',
   [{'A': 12, 'B': 20, 'C': 12, 'D': 25, 'E': 12}, {'A': [], 'B': [], 'C': [], 'D': ['C'], 'E': ['A', 'B']}],
   {'A': 12, 'B': 20, 'C': 20, 'D': 25, 'E': 15}),
  ('normal control 2', [{'A': 25, 'B': 20, 'C': 10}, {'A': [], 'B': ['E'], 'C': [], 'D': ['A'], 'E': []}],
   {'A': 25, 'B': 20, 'C': 10}),
  ('normal control 3',
   [{'A': 10, 'B': 25, 'C': 12, 'D': 15, 'E': 20},
    {'A': ['D', 'B'], 'B': [], 'C': [], 'D': ['C', 'E'], 'E': ['C', 'D']}],
   {'A': 20, 'B': 25, 'C': 15, 'D': 15, 'E': 20}),
  ('normal control 4',
   [{'A': 25, 'B': 20, 'C': 25}, {'A': [], 'B': ['D'], 'C': ['D', 'A'], 'D': [], 'E': []}],
   {'A': 25, 'B': 20, 'C': 25})]]
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: publication cap{'A': 35, 'B': 25, 'C': 20, 'D': 25, 'E': 20}{'A': 30, 'B': 25, 'C': 20, 'D': 25, 'E': 20}Failed
partial repair probe: publication cap{'A': 35, 'B': 20, 'C': 25, 'D': 25, 'E': 25}{'A': 30, 'B': 20, 'C': 25, 'D': 25, 'E': 25}Failed
second regression{'A': 20, 'B': 35, 'C': 30, 'D': 12, 'E': 30}{'A': 20, 'B': 30, 'C': 30, 'D': 12, 'E': 30}Failed
normal control 1{'A': 25, 'B': 20, 'C': 20, 'D': 20}{'A': 25, 'B': 20, 'C': 20, 'D': 20}Passed
normal control 2{'A': 10, 'B': 20, 'C': 12}{'A': 10, 'B': 20, 'C': 12}Passed
normal control 3{'A': 15, 'B': 15, 'C': 20}{'A': 15, 'B': 15, 'C': 20}Passed
normal control 4{'A': 20, 'B': 10, 'C': 15, 'D': 12}{'A': 20, 'B': 10, 'C': 15, 'D': 12}Passed

SHA-256 / 794d9cfed5dc2c33687fe8d34585ff3ff2d2303c0c6d4502a59abd35f84a18d5

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(mult, adj):
    out = {}
    for z in sorted(mult):
        nbrs = set(adj.get(z, [])) | {a for a, lst in adj.items() if z in lst}
        best = mult[z]
        for nb in sorted(nbrs):
            if nb in mult:
                best = max(best, mult[nb] - 5)
        out[z] = min(max(best, 10), 30) if best != mult[z] else best
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: publication cap',
   [{'A': 35, 'B': 25, 'C': 15, 'D': 25, 'E': 10},
    {'A': [], 'B': ['C'], 'C': ['E'], 'D': [], 'E': ['B', 'C']}],
   {'A': 30, 'B': 25, 'C': 20, 'D': 25, 'E': 20}),
  ('partial repair probe: publication cap',
   [{'A': 35, 'B': 10, 'C': 25, 'D': 25, 'E': 25}, {'A': [], 'B': ['D'], 'C': [], 'D': [], 'E': ['D']}],
   {'A': 30, 'B': 20, 'C': 25, 'D': 25, 'E': 25}),
  ('second regression',
   [{'A': 20, 'B': 35, 'C': 10, 'D': 12, 'E': 15},
    {'A': ['C'], 'B': ['E', 'C'], 'C': ['D'], 'D': [], 'E': ['D']}],
   {'A': 20, 'B': 30, 'C': 30, 'D': 12, 'E': 30}),
  ('normal control 1',
   [{'A': 25, 'B': 20, 'C': 10, 'D': 10}, {'A': ['E', 'D'], 'B': ['C'], 'C': ['A'], 'D': ['A'], 'E': ['D']}],
   {'A': 25, 'B': 20, 'C': 20, 'D': 20}),
  ('normal control 2', [{'A': 10, 'B': 20, 'C': 12}, {'A': [], 'B': [], 'C': [], 'D': [], 'E': ['C']}],
   {'A': 10, 'B': 20, 'C': 12}),
  ('normal control 3',
   [{'A': 12, 'B': 10, 'C': 20}, {'A': [], 'B': ['C'], 'C': ['A'], 'D': ['C'], 'E': ['B']}],
   {'A': 15, 'B': 15, 'C': 20}),
  ('normal control 4',
   [{'A': 20, 'B': 10, 'C': 15, 'D': 12}, {'A': [], 'B': ['D'], 'C': [], 'D': ['C', 'E'], 'E': ['D', 'C']}],
   {'A': 20, 'B': 10, 'C': 15, 'D': 12})],
 [('regression: publication cap',
   [{'A': 25, 'B': 15, 'C': 25, 'D': 35, 'E': 12},
    {'A': [], 'B': ['D', 'E'], 'C': ['B', 'E'], 'D': ['A', 'B'], 'E': ['A']}],
   {'A': 30, 'B': 30, 'C': 25, 'D': 30, 'E': 20}),
  ('partial repair probe: publication cap',
   [{'A': 15, 'B': 20, 'C': 35}, {'A': ['C', 'E'], 'B': ['E'], 'C': ['E', 'A'], 'D': ['E', 'C'], 'E': ['A']}],
   {'A': 30, 'B': 20, 'C': 30}),
  ('second regression',
   [{'A': 25, 'B': 35, 'C': 15, 'D': 20, 'E': 25},
    {'A': ['D'], 'B': ['A', 'C'], 'C': ['D'], 'D': ['C', 'B'], 'E': []}],
   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 25}),
  ('normal control 1',
   [{'A': 10, 'B': 15, 'C': 20, 'D': 12}, {'A': ['C'], 'B': ['E'], 'C': [], 'D': ['C'], 'E': []}],
   {'A': 15, 'B': 15, 'C': 20, 'D': 15}),
  ('normal control 2',
   [{'A': 25, 'B': 15, 'C': 25}, {'A': ['E', 'C'], 'B': ['D', 'A'], 'C': ['D'], 'D': ['E'], 'E': ['C']}],
   {'A': 25, 'B': 20, 'C': 25}),
  ('normal control 3',
   [{'A': 25, 'B': 12, 'C': 25, 'D': 15, 'E': 10}, {'A': [], 'B': ['A'], 'C': [], 'D': ['E', 'B'], 'E': []}],
   {'A': 25, 'B': 20, 'C': 25, 'D': 15, 'E': 10}),
  ('normal control 4', [{'A': 25, 'B': 10, 'C': 15}, {'A': ['E'], 'B': ['C'], 'C': [], 'D': ['B'], 'E': []}],
   {'A': 25, 'B': 10, 'C': 15})],
 [('regression: publication cap',
   [{'A': 25, 'B': 35, 'C': 35, 'D': 35, 'E': 35},
    {'A': ['E'], 'B': ['E'], 'C': [], 'D': [], 'E': ['A', 'C']}],
   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 30}),
  ('partial repair probe: publication cap',
   [{'A': 35, 'B': 10, 'C': 12, 'D': 25, 'E': 10},
    {'A': ['C', 'D'], 'B': ['A', 'D'], 'C': [], 'D': [], 'E': ['D']}],
   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 20}),
  ('second regression',
   [{'A': 25, 'B': 12, 'C': 12, 'D': 35, 'E': 12}, {'A': ['B'], 'B': [], 'C': [], 'D': [], 'E': ['A']}],
   {'A': 25, 'B': 20, 'C': 12, 'D': 30, 'E': 20}),
  ('normal control 1',
   [{'A': 12, 'B': 25, 'C': 10}, {'A': [], 'B': [], 'C': [], 'D': ['A', 'E'], 'E': ['D']}],
   {'A': 12, 'B': 25, 'C': 10}),
  ('normal control 2',
   [{'A': 20, 'B': 12, 'C': 10, 'D': 12}, {'A': ['C', 'B'], 'B': [], 'C': [], 'D': ['E'], 'E': []}],
   {'A': 20, 'B': 15, 'C': 15, 'D': 12}),
  ('normal control 3',
   [{'A': 25, 'B': 12, 'C': 25, 'D': 12}, {'A': ['E', 'B'], 'B': ['D', 'A'], 'C': [], 'D': [], 'E': ['D']}],
   {'A': 25, 'B': 20, 'C': 25, 'D': 12}),
  ('normal control 4',
   [{'A': 15, 'B': 25, 'C': 12, 'D': 15}, {'A': ['E'], 'B': [], 'C': ['A'], 'D': ['E'], 'E': ['A', 'C']}],
   {'A': 15, 'B': 25, 'C': 12, 'D': 15})],
 [('regression: publication cap',
   [{'A': 12, 'B': 35, 'C': 25}, {'A': ['D'], 'B': ['E', 'D'], 'C': ['A'], 'D': ['B'], 'E': []}],
   {'A': 20, 'B': 30, 'C': 25}),
  ('partial repair probe: publication cap',
   [{'A': 12, 'B': 20, 'C': 35, 'D': 20, 'E': 12},
    {'A': ['B', 'E'], 'B': [], 'C': ['A'], 'D': ['C'], 'E': ['B', 'D']}],
   {'A': 30, 'B': 20, 'C': 30, 'D': 30, 'E': 15}),
  ('second regression',
   [{'A': 12, 'B': 15, 'C': 35, 'D': 12, 'E': 25}, {'A': [], 'B': ['E', 'C'], 'C': ['D'], 'D': [], 'E': []}],
   {'A': 12, 'B': 30, 'C': 30, 'D': 30, 'E': 25}),
  ('normal control 1',
   [{'A': 20, 'B': 12, 'C': 15}, {'A': ['D'], 'B': [], 'C': ['A'], 'D': ['C', 'E'], 'E': []}],
   {'A': 20, 'B': 12, 'C': 15}),
  ('normal control 2',
   [{'A': 12, 'B': 12, 'C': 12, 'D': 15}, {'A': [], 'B': [], 'C': ['B', 'E'], 'D': ['C'], 'E': []}],
   {'A': 12, 'B': 12, 'C': 12, 'D': 15}),
  ('normal control 3',
   [{'A': 12, 'B': 20, 'C': 15, 'D': 20}, {'A': [], 'B': [], 'C': ['E', 'B'], 'D': ['C', 'A'], 'E': []}],
   {'A': 15, 'B': 20, 'C': 15, 'D': 20}),
  ('normal control 4',
   [{'A': 15, 'B': 15, 'C': 12}, {'A': [], 'B': ['D'], 'C': [], 'D': ['C'], 'E': ['B', 'A']}],
   {'A': 15, 'B': 15, 'C': 12})],
 [('regression: publication cap',
   [{'A': 35, 'B': 10, 'C': 10, 'D': 10}, {'A': ['D'], 'B': [], 'C': ['B'], 'D': ['B', 'E'], 'E': ['D']}],
   {'A': 30, 'B': 10, 'C': 10, 'D': 30}),
  ('partial repair probe: publication cap',
   [{'A': 35, 'B': 10, 'C': 12, 'D': 20}, {'A': [], 'B': ['D', 'E'], 'C': [], 'D': ['A'], 'E': ['D']}],
   {'A': 30, 'B': 15, 'C': 12, 'D': 30}),
  ('second regression',
   [{'A': 10, 'B': 35, 'C': 25, 'D': 12}, {'A': [], 'B': [], 'C': [], 'D': [], 'E': ['A']}],
   {'A': 10, 'B': 30, 'C': 25, 'D': 12}),
  ('normal control 1',
   [{'A': 12, 'B': 20, 'C': 12, 'D': 25, 'E': 12}, {'A': [], 'B': [], 'C': [], 'D': ['C'], 'E': ['A', 'B']}],
   {'A': 12, 'B': 20, 'C': 20, 'D': 25, 'E': 15}),
  ('normal control 2', [{'A': 25, 'B': 20, 'C': 10}, {'A': [], 'B': ['E'], 'C': [], 'D': ['A'], 'E': []}],
   {'A': 25, 'B': 20, 'C': 10}),
  ('normal control 3',
   [{'A': 10, 'B': 25, 'C': 12, 'D': 15, 'E': 20},
    {'A': ['D', 'B'], 'B': [], 'C': [], 'D': ['C', 'E'], 'E': ['C', 'D']}],
   {'A': 20, 'B': 25, 'C': 15, 'D': 15, 'E': 20}),
  ('normal control 4',
   [{'A': 25, 'B': 20, 'C': 25}, {'A': [], 'B': ['D'], 'C': ['D', 'A'], 'D': [], 'E': []}],
   {'A': 25, 'B': 20, 'C': 25})]]
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: publication cap{'A': 35, 'B': 25, 'C': 20, 'D': 25, 'E': 20}{'A': 30, 'B': 25, 'C': 20, 'D': 25, 'E': 20}Failed
partial repair probe: publication cap{'A': 35, 'B': 20, 'C': 25, 'D': 25, 'E': 25}{'A': 30, 'B': 20, 'C': 25, 'D': 25, 'E': 25}Failed
second regression{'A': 20, 'B': 35, 'C': 30, 'D': 12, 'E': 30}{'A': 20, 'B': 30, 'C': 30, 'D': 12, 'E': 30}Failed
normal control 1{'A': 25, 'B': 20, 'C': 20, 'D': 20}{'A': 25, 'B': 20, 'C': 20, 'D': 20}Passed
normal control 2{'A': 10, 'B': 20, 'C': 12}{'A': 10, 'B': 20, 'C': 12}Passed
normal control 3{'A': 15, 'B': 15, 'C': 20}{'A': 15, 'B': 15, 'C': 20}Passed
normal control 4{'A': 20, 'B': 10, 'C': 15, 'D': 12}{'A': 20, 'B': 10, 'C': 15, 'D': 12}Passed

SHA-256 / bad32bd79cc389e0a2149ebb2eb256034ec17fe27112a1e1f87d0f7a247b9fa1

3 / The verified repair

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

N = 1
observations = []
def solve(mult, adj):
    out = {}
    for z in sorted(mult):
        nbrs = set(adj.get(z, [])) | {a for a, lst in adj.items() if z in lst}
        best = mult[z]
        for nb in sorted(nbrs):
            if nb in mult:
                best = max(best, mult[nb] - 5)
        out[z] = min(max(best, 10), 30)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: publication cap',
   [{'A': 35, 'B': 25, 'C': 15, 'D': 25, 'E': 10},
    {'A': [], 'B': ['C'], 'C': ['E'], 'D': [], 'E': ['B', 'C']}],
   {'A': 30, 'B': 25, 'C': 20, 'D': 25, 'E': 20}),
  ('partial repair probe: publication cap',
   [{'A': 35, 'B': 10, 'C': 25, 'D': 25, 'E': 25}, {'A': [], 'B': ['D'], 'C': [], 'D': [], 'E': ['D']}],
   {'A': 30, 'B': 20, 'C': 25, 'D': 25, 'E': 25}),
  ('second regression',
   [{'A': 20, 'B': 35, 'C': 10, 'D': 12, 'E': 15},
    {'A': ['C'], 'B': ['E', 'C'], 'C': ['D'], 'D': [], 'E': ['D']}],
   {'A': 20, 'B': 30, 'C': 30, 'D': 12, 'E': 30}),
  ('normal control 1',
   [{'A': 25, 'B': 20, 'C': 10, 'D': 10}, {'A': ['E', 'D'], 'B': ['C'], 'C': ['A'], 'D': ['A'], 'E': ['D']}],
   {'A': 25, 'B': 20, 'C': 20, 'D': 20}),
  ('normal control 2', [{'A': 10, 'B': 20, 'C': 12}, {'A': [], 'B': [], 'C': [], 'D': [], 'E': ['C']}],
   {'A': 10, 'B': 20, 'C': 12}),
  ('normal control 3',
   [{'A': 12, 'B': 10, 'C': 20}, {'A': [], 'B': ['C'], 'C': ['A'], 'D': ['C'], 'E': ['B']}],
   {'A': 15, 'B': 15, 'C': 20}),
  ('normal control 4',
   [{'A': 20, 'B': 10, 'C': 15, 'D': 12}, {'A': [], 'B': ['D'], 'C': [], 'D': ['C', 'E'], 'E': ['D', 'C']}],
   {'A': 20, 'B': 10, 'C': 15, 'D': 12})],
 [('regression: publication cap',
   [{'A': 25, 'B': 15, 'C': 25, 'D': 35, 'E': 12},
    {'A': [], 'B': ['D', 'E'], 'C': ['B', 'E'], 'D': ['A', 'B'], 'E': ['A']}],
   {'A': 30, 'B': 30, 'C': 25, 'D': 30, 'E': 20}),
  ('partial repair probe: publication cap',
   [{'A': 15, 'B': 20, 'C': 35}, {'A': ['C', 'E'], 'B': ['E'], 'C': ['E', 'A'], 'D': ['E', 'C'], 'E': ['A']}],
   {'A': 30, 'B': 20, 'C': 30}),
  ('second regression',
   [{'A': 25, 'B': 35, 'C': 15, 'D': 20, 'E': 25},
    {'A': ['D'], 'B': ['A', 'C'], 'C': ['D'], 'D': ['C', 'B'], 'E': []}],
   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 25}),
  ('normal control 1',
   [{'A': 10, 'B': 15, 'C': 20, 'D': 12}, {'A': ['C'], 'B': ['E'], 'C': [], 'D': ['C'], 'E': []}],
   {'A': 15, 'B': 15, 'C': 20, 'D': 15}),
  ('normal control 2',
   [{'A': 25, 'B': 15, 'C': 25}, {'A': ['E', 'C'], 'B': ['D', 'A'], 'C': ['D'], 'D': ['E'], 'E': ['C']}],
   {'A': 25, 'B': 20, 'C': 25}),
  ('normal control 3',
   [{'A': 25, 'B': 12, 'C': 25, 'D': 15, 'E': 10}, {'A': [], 'B': ['A'], 'C': [], 'D': ['E', 'B'], 'E': []}],
   {'A': 25, 'B': 20, 'C': 25, 'D': 15, 'E': 10}),
  ('normal control 4', [{'A': 25, 'B': 10, 'C': 15}, {'A': ['E'], 'B': ['C'], 'C': [], 'D': ['B'], 'E': []}],
   {'A': 25, 'B': 10, 'C': 15})],
 [('regression: publication cap',
   [{'A': 25, 'B': 35, 'C': 35, 'D': 35, 'E': 35},
    {'A': ['E'], 'B': ['E'], 'C': [], 'D': [], 'E': ['A', 'C']}],
   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 30}),
  ('partial repair probe: publication cap',
   [{'A': 35, 'B': 10, 'C': 12, 'D': 25, 'E': 10},
    {'A': ['C', 'D'], 'B': ['A', 'D'], 'C': [], 'D': [], 'E': ['D']}],
   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 20}),
  ('second regression',
   [{'A': 25, 'B': 12, 'C': 12, 'D': 35, 'E': 12}, {'A': ['B'], 'B': [], 'C': [], 'D': [], 'E': ['A']}],
   {'A': 25, 'B': 20, 'C': 12, 'D': 30, 'E': 20}),
  ('normal control 1',
   [{'A': 12, 'B': 25, 'C': 10}, {'A': [], 'B': [], 'C': [], 'D': ['A', 'E'], 'E': ['D']}],
   {'A': 12, 'B': 25, 'C': 10}),
  ('normal control 2',
   [{'A': 20, 'B': 12, 'C': 10, 'D': 12}, {'A': ['C', 'B'], 'B': [], 'C': [], 'D': ['E'], 'E': []}],
   {'A': 20, 'B': 15, 'C': 15, 'D': 12}),
  ('normal control 3',
   [{'A': 25, 'B': 12, 'C': 25, 'D': 12}, {'A': ['E', 'B'], 'B': ['D', 'A'], 'C': [], 'D': [], 'E': ['D']}],
   {'A': 25, 'B': 20, 'C': 25, 'D': 12}),
  ('normal control 4',
   [{'A': 15, 'B': 25, 'C': 12, 'D': 15}, {'A': ['E'], 'B': [], 'C': ['A'], 'D': ['E'], 'E': ['A', 'C']}],
   {'A': 15, 'B': 25, 'C': 12, 'D': 15})],
 [('regression: publication cap',
   [{'A': 12, 'B': 35, 'C': 25}, {'A': ['D'], 'B': ['E', 'D'], 'C': ['A'], 'D': ['B'], 'E': []}],
   {'A': 20, 'B': 30, 'C': 25}),
  ('partial repair probe: publication cap',
   [{'A': 12, 'B': 20, 'C': 35, 'D': 20, 'E': 12},
    {'A': ['B', 'E'], 'B': [], 'C': ['A'], 'D': ['C'], 'E': ['B', 'D']}],
   {'A': 30, 'B': 20, 'C': 30, 'D': 30, 'E': 15}),
  ('second regression',
   [{'A': 12, 'B': 15, 'C': 35, 'D': 12, 'E': 25}, {'A': [], 'B': ['E', 'C'], 'C': ['D'], 'D': [], 'E': []}],
   {'A': 12, 'B': 30, 'C': 30, 'D': 30, 'E': 25}),
  ('normal control 1',
   [{'A': 20, 'B': 12, 'C': 15}, {'A': ['D'], 'B': [], 'C': ['A'], 'D': ['C', 'E'], 'E': []}],
   {'A': 20, 'B': 12, 'C': 15}),
  ('normal control 2',
   [{'A': 12, 'B': 12, 'C': 12, 'D': 15}, {'A': [], 'B': [], 'C': ['B', 'E'], 'D': ['C'], 'E': []}],
   {'A': 12, 'B': 12, 'C': 12, 'D': 15}),
  ('normal control 3',
   [{'A': 12, 'B': 20, 'C': 15, 'D': 20}, {'A': [], 'B': [], 'C': ['E', 'B'], 'D': ['C', 'A'], 'E': []}],
   {'A': 15, 'B': 20, 'C': 15, 'D': 20}),
  ('normal control 4',
   [{'A': 15, 'B': 15, 'C': 12}, {'A': [], 'B': ['D'], 'C': [], 'D': ['C'], 'E': ['B', 'A']}],
   {'A': 15, 'B': 15, 'C': 12})],
 [('regression: publication cap',
   [{'A': 35, 'B': 10, 'C': 10, 'D': 10}, {'A': ['D'], 'B': [], 'C': ['B'], 'D': ['B', 'E'], 'E': ['D']}],
   {'A': 30, 'B': 10, 'C': 10, 'D': 30}),
  ('partial repair probe: publication cap',
   [{'A': 35, 'B': 10, 'C': 12, 'D': 20}, {'A': [], 'B': ['D', 'E'], 'C': [], 'D': ['A'], 'E': ['D']}],
   {'A': 30, 'B': 15, 'C': 12, 'D': 30}),
  ('second regression',
   [{'A': 10, 'B': 35, 'C': 25, 'D': 12}, {'A': [], 'B': [], 'C': [], 'D': [], 'E': ['A']}],
   {'A': 10, 'B': 30, 'C': 25, 'D': 12}),
  ('normal control 1',
   [{'A': 12, 'B': 20, 'C': 12, 'D': 25, 'E': 12}, {'A': [], 'B': [], 'C': [], 'D': ['C'], 'E': ['A', 'B']}],
   {'A': 12, 'B': 20, 'C': 20, 'D': 25, 'E': 15}),
  ('normal control 2', [{'A': 25, 'B': 20, 'C': 10}, {'A': [], 'B': ['E'], 'C': [], 'D': ['A'], 'E': []}],
   {'A': 25, 'B': 20, 'C': 10}),
  ('normal control 3',
   [{'A': 10, 'B': 25, 'C': 12, 'D': 15, 'E': 20},
    {'A': ['D', 'B'], 'B': [], 'C': [], 'D': ['C', 'E'], 'E': ['C', 'D']}],
   {'A': 20, 'B': 25, 'C': 15, 'D': 15, 'E': 20}),
  ('normal control 4',
   [{'A': 25, 'B': 20, 'C': 25}, {'A': [], 'B': ['D'], 'C': ['D', 'A'], 'D': [], 'E': []}],
   {'A': 25, 'B': 20, 'C': 25})]]
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: publication cap{'A': 30, 'B': 25, 'C': 20, 'D': 25, 'E': 20}{'A': 30, 'B': 25, 'C': 20, 'D': 25, 'E': 20}Passed
partial repair probe: publication cap{'A': 30, 'B': 20, 'C': 25, 'D': 25, 'E': 25}{'A': 30, 'B': 20, 'C': 25, 'D': 25, 'E': 25}Passed
second regression{'A': 20, 'B': 30, 'C': 30, 'D': 12, 'E': 30}{'A': 20, 'B': 30, 'C': 30, 'D': 12, 'E': 30}Passed
normal control 1{'A': 25, 'B': 20, 'C': 20, 'D': 20}{'A': 25, 'B': 20, 'C': 20, 'D': 20}Passed
normal control 2{'A': 10, 'B': 20, 'C': 12}{'A': 10, 'B': 20, 'C': 12}Passed
normal control 3{'A': 15, 'B': 15, 'C': 20}{'A': 15, 'B': 15, 'C': 20}Passed
normal control 4{'A': 20, 'B': 10, 'C': 15, 'D': 12}{'A': 20, 'B': 10, 'C': 15, 'D': 12}Passed

SHA-256 / ad3d2387add00e6df777947c862b6aba6acabe63aa7503909fd97f717d957f25

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 2026-09-29T14:50:43.138628+00:00.

Case digest / f7366c8d2b87863018d1c0a9f1afa3fd3d17c3923633468d40d495f91cd7f238