{"abstract":"Surge spreads several hops from a hotspot depending on zone name order.","category":"Ride-hailing fare and surge pricing","checks":7,"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.","contract_signature":"mult, adj","evaluation_group":"w2-ride-hailing-fare-surge-surge-spatial-smoothing","failed_approach":"Reversing the iteration order just changes which zones cascade.","family":"w2-ride-hailing-fare-surge-surge-spatial-smoothing-raw-neighbor-values","id":"FA-85731","implementations":{"attempt":{"sha256":"ff70ebcc32158b41827e9af8e8db82959b094755f602f5d98f71070fc5e15da8","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(mult, adj):\n    out = {}\n    for z in sorted(mult, reverse=True):\n        nbrs = set(adj.get(z, [])) | {a for a, lst in adj.items() if z in lst}\n        best = mult[z]\n        for nb in sorted(nbrs):\n            if nb in mult:\n                best = max(best, out.get(nb, mult[nb]) - 5)\n        out[z] = min(max(best, 10), 30)\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: raw neighbor values',\n   [{'A': 20, 'B': 35, 'C': 35, 'D': 15, 'E': 20},\n    {'A': ['C', 'B'], 'B': ['C', 'E'], 'C': ['B', 'A'], 'D': ['A', 'B'], 'E': []}],\n   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 30}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 15, 'B': 35, 'C': 25}, {'A': ['B'], 'B': [], 'C': [], 'D': ['C', 'E'], 'E': ['A']}],\n   {'A': 30, 'B': 30, 'C': 25}),\n  ('second regression',\n   [{'A': 15, 'B': 35, 'C': 25, 'D': 10}, {'A': ['E'], 'B': ['E'], 'C': ['B'], 'D': [], 'E': ['A']}],\n   {'A': 15, 'B': 30, 'C': 30, 'D': 10}),\n  ('normal control 1',\n   [{'A': 12, 'B': 20, 'C': 25, 'D': 15}, {'A': [], 'B': ['C'], 'C': [], 'D': [], 'E': ['A', 'D']}],\n   {'A': 12, 'B': 20, 'C': 25, 'D': 15}),\n  ('normal control 2',\n   [{'A': 25, 'B': 20, 'C': 25}, {'A': [], 'B': ['C', 'A'], 'C': [], 'D': ['E'], 'E': ['A']}],\n   {'A': 25, 'B': 20, 'C': 25}),\n  ('normal control 3',\n   [{'A': 20, 'B': 25, 'C': 20, 'D': 15, 'E': 12},\n    {'A': ['B'], 'B': ['D', 'A'], 'C': [], 'D': ['C', 'B'], 'E': ['B']}],\n   {'A': 20, 'B': 25, 'C': 20, 'D': 20, 'E': 20}),\n  ('normal control 4',\n   [{'A': 12, 'B': 12, 'C': 20}, {'A': ['B', 'E'], 'B': ['D'], 'C': [], 'D': ['E'], 'E': []}],\n   {'A': 12, 'B': 12, 'C': 20})],\n [('regression: raw neighbor values',\n   [{'A': 25, 'B': 35, 'C': 20}, {'A': ['D'], 'B': ['E'], 'C': ['B'], 'D': [], 'E': ['A']}],\n   {'A': 25, 'B': 30, 'C': 30}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 20, 'B': 25, 'C': 15, 'D': 35}, {'A': ['D'], 'B': ['E'], 'C': ['B'], 'D': ['C'], 'E': ['C']}],\n   {'A': 30, 'B': 25, 'C': 30, 'D': 30}),\n  ('second regression',\n   [{'A': 25, 'B': 20, 'C': 25, 'D': 20, 'E': 35}, {'A': [], 'B': [], 'C': ['B', 'E'], 'D': ['A'], 'E': []}],\n   {'A': 25, 'B': 20, 'C': 30, 'D': 20, 'E': 30}),\n  ('normal control 1',\n   [{'A': 10, 'B': 20, 'C': 10, 'D': 12, 'E': 10}, {'A': [], 'B': [], 'C': [], 'D': ['E'], 'E': []}],\n   {'A': 10, 'B': 20, 'C': 10, 'D': 12, 'E': 10}),\n  ('normal control 2',\n   [{'A': 15, 'B': 12, 'C': 25}, {'A': ['B'], 'B': ['D'], 'C': [], 'D': ['A', 'C'], 'E': []}],\n   {'A': 15, 'B': 12, 'C': 25}),\n  ('normal control 3',\n   [{'A': 10, 'B': 35, 'C': 10, 'D': 20}, {'A': ['C'], 'B': ['E'], 'C': [], 'D': ['E', 'A'], 'E': []}],\n   {'A': 15, 'B': 30, 'C': 10, 'D': 20}),\n  ('normal control 4',\n   [{'A': 35, 'B': 25, 'C': 35}, {'A': ['D'], 'B': [], 'C': [], 'D': ['A', 'C'], 'E': ['B']}],\n   {'A': 30, 'B': 25, 'C': 30})],\n [('regression: raw neighbor values',\n   [{'A': 35, 'B': 15, 'C': 25}, {'A': ['E', 'B'], 'B': [], 'C': [], 'D': ['E'], 'E': ['A']}],\n   {'A': 30, 'B': 30, 'C': 25}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 25, 'B': 35, 'C': 15, 'D': 15, 'E': 35},\n    {'A': ['D'], 'B': [], 'C': [], 'D': ['A', 'C'], 'E': ['A']}],\n   {'A': 30, 'B': 30, 'C': 15, 'D': 20, 'E': 30}),\n  ('second regression',\n   [{'A': 10, 'B': 35, 'C': 25, 'D': 12}, {'A': [], 'B': ['C'], 'C': [], 'D': ['A'], 'E': []}],\n   {'A': 10, 'B': 30, 'C': 30, 'D': 12}),\n  ('normal control 1',\n   [{'A': 25, 'B': 15, 'C': 35, 'D': 35}, {'A': [], 'B': [], 'C': ['D'], 'D': [], 'E': []}],\n   {'A': 25, 'B': 15, 'C': 30, 'D': 30}),\n  ('normal control 2',\n   [{'A': 15, 'B': 10, 'C': 12}, {'A': [], 'B': ['C'], 'C': [], 'D': ['C'], 'E': ['B', 'D']}],\n   {'A': 15, 'B': 10, 'C': 12}),\n  ('normal control 3',\n   [{'A': 15, 'B': 12, 'C': 10, 'D': 10}, {'A': [], 'B': [], 'C': ['E'], 'D': ['A', 'E'], 'E': ['B', 'C']}],\n   {'A': 15, 'B': 12, 'C': 10, 'D': 10}),\n  ('normal control 4',\n   [{'A': 20, 'B': 15, 'C': 15}, {'A': [], 'B': ['C', 'D'], 'C': [], 'D': ['C'], 'E': ['C']}],\n   {'A': 20, 'B': 15, 'C': 15})],\n [('regression: raw neighbor values',\n   [{'A': 10, 'B': 10, 'C': 35, 'D': 10, 'E': 25}, {'A': ['E'], 'B': ['D'], 'C': ['B'], 'D': [], 'E': ['D']}],\n   {'A': 20, 'B': 30, 'C': 30, 'D': 20, 'E': 25}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 12, 'B': 25, 'C': 10, 'D': 12, 'E': 35}, {'A': [], 'B': ['E', 'A'], 'C': [], 'D': [], 'E': []}],\n   {'A': 20, 'B': 30, 'C': 10, 'D': 12, 'E': 30}),\n  ('second regression',\n   [{'A': 25, 'B': 12, 'C': 35}, {'A': ['B', 'C'], 'B': [], 'C': ['B'], 'D': ['E'], 'E': ['D']}],\n   {'A': 30, 'B': 30, 'C': 30}),\n  ('normal control 1',\n   [{'A': 25, 'B': 25, 'C': 15, 'D': 15}, {'A': ['D'], 'B': ['D'], 'C': [], 'D': [], 'E': ['B']}],\n   {'A': 25, 'B': 25, 'C': 15, 'D': 20}),\n  ('normal control 2',\n   [{'A': 10, 'B': 20, 'C': 20, 'D': 25, 'E': 35}, {'A': [], 'B': [], 'C': ['A', 'D'], 'D': [], 'E': []}],\n   {'A': 15, 'B': 20, 'C': 20, 'D': 25, 'E': 30}),\n  ('normal control 3',\n   [{'A': 15, 'B': 12, 'C': 35}, {'A': ['D', 'B'], 'B': ['E'], 'C': [], 'D': [], 'E': ['B', 'D']}],\n   {'A': 15, 'B': 12, 'C': 30}),\n  ('normal control 4',\n   [{'A': 20, 'B': 25, 'C': 25, 'D': 20}, {'A': ['B'], 'B': ['D', 'E'], 'C': ['E'], 'D': ['C'], 'E': []}],\n   {'A': 20, 'B': 25, 'C': 25, 'D': 20})],\n [('regression: raw neighbor values',\n   [{'A': 25, 'B': 15, 'C': 12, 'D': 15, 'E': 15},\n    {'A': [], 'B': ['A'], 'C': ['B'], 'D': [], 'E': ['A', 'B']}],\n   {'A': 25, 'B': 20, 'C': 12, 'D': 15, 'E': 20}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 15, 'B': 20, 'C': 35, 'D': 15}, {'A': [], 'B': [], 'C': ['E', 'B'], 'D': ['C'], 'E': ['A']}],\n   {'A': 15, 'B': 30, 'C': 30, 'D': 30}),\n  ('second regression',\n   [{'A': 25, 'B': 12, 'C': 20, 'D': 15, 'E': 12},\n    {'A': ['B'], 'B': ['A'], 'C': ['D', 'A'], 'D': ['B'], 'E': ['B']}],\n   {'A': 25, 'B': 20, 'C': 20, 'D': 15, 'E': 12}),\n  ('normal control 1',\n   [{'A': 12, 'B': 10, 'C': 10, 'D': 35}, {'A': [], 'B': ['A', 'E'], 'C': ['B'], 'D': [], 'E': []}],\n   {'A': 12, 'B': 10, 'C': 10, 'D': 30}),\n  ('normal control 2',\n   [{'A': 10, 'B': 15, 'C': 20, 'D': 15}, {'A': ['E', 'D'], 'B': ['D'], 'C': ['E'], 'D': [], 'E': []}],\n   {'A': 10, 'B': 15, 'C': 20, 'D': 15}),\n  ('normal control 3',\n   [{'A': 15, 'B': 25, 'C': 20}, {'A': [], 'B': [], 'C': [], 'D': ['C'], 'E': ['C', 'A']}],\n   {'A': 15, 'B': 25, 'C': 20}),\n  ('normal control 4', [{'A': 25, 'B': 10, 'C': 25}, {'A': [], 'B': [], 'C': ['E'], 'D': ['A'], 'E': ['D']}],\n   {'A': 25, 'B': 10, 'C': 25})]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"18ac97f6e54846fbf521b308be76b939e46f5e141773d899dcfbc1e4181f623b","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(mult, adj):\n    out = {}\n    for z in sorted(mult):\n        nbrs = set(adj.get(z, [])) | {a for a, lst in adj.items() if z in lst}\n        best = mult[z]\n        for nb in sorted(nbrs):\n            if nb in mult:\n                best = max(best, out.get(nb, mult[nb]) - 5)\n        out[z] = min(max(best, 10), 30)\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: raw neighbor values',\n   [{'A': 20, 'B': 35, 'C': 35, 'D': 15, 'E': 20},\n    {'A': ['C', 'B'], 'B': ['C', 'E'], 'C': ['B', 'A'], 'D': ['A', 'B'], 'E': []}],\n   {'A': 30, 'B': 30, 'C': 30, 'D': 30, 'E': 30}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 15, 'B': 35, 'C': 25}, {'A': ['B'], 'B': [], 'C': [], 'D': ['C', 'E'], 'E': ['A']}],\n   {'A': 30, 'B': 30, 'C': 25}),\n  ('second regression',\n   [{'A': 15, 'B': 35, 'C': 25, 'D': 10}, {'A': ['E'], 'B': ['E'], 'C': ['B'], 'D': [], 'E': ['A']}],\n   {'A': 15, 'B': 30, 'C': 30, 'D': 10}),\n  ('normal control 1',\n   [{'A': 12, 'B': 20, 'C': 25, 'D': 15}, {'A': [], 'B': ['C'], 'C': [], 'D': [], 'E': ['A', 'D']}],\n   {'A': 12, 'B': 20, 'C': 25, 'D': 15}),\n  ('normal control 2',\n   [{'A': 25, 'B': 20, 'C': 25}, {'A': [], 'B': ['C', 'A'], 'C': [], 'D': ['E'], 'E': ['A']}],\n   {'A': 25, 'B': 20, 'C': 25}),\n  ('normal control 3',\n   [{'A': 20, 'B': 25, 'C': 20, 'D': 15, 'E': 12},\n    {'A': ['B'], 'B': ['D', 'A'], 'C': [], 'D': ['C', 'B'], 'E': ['B']}],\n   {'A': 20, 'B': 25, 'C': 20, 'D': 20, 'E': 20}),\n  ('normal control 4',\n   [{'A': 12, 'B': 12, 'C': 20}, {'A': ['B', 'E'], 'B': ['D'], 'C': [], 'D': ['E'], 'E': []}],\n   {'A': 12, 'B': 12, 'C': 20})],\n [('regression: raw neighbor values',\n   [{'A': 25, 'B': 35, 'C': 20}, {'A': ['D'], 'B': ['E'], 'C': ['B'], 'D': [], 'E': ['A']}],\n   {'A': 25, 'B': 30, 'C': 30}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 20, 'B': 25, 'C': 15, 'D': 35}, {'A': ['D'], 'B': ['E'], 'C': ['B'], 'D': ['C'], 'E': ['C']}],\n   {'A': 30, 'B': 25, 'C': 30, 'D': 30}),\n  ('second regression',\n   [{'A': 25, 'B': 20, 'C': 25, 'D': 20, 'E': 35}, {'A': [], 'B': [], 'C': ['B', 'E'], 'D': ['A'], 'E': []}],\n   {'A': 25, 'B': 20, 'C': 30, 'D': 20, 'E': 30}),\n  ('normal control 1',\n   [{'A': 10, 'B': 20, 'C': 10, 'D': 12, 'E': 10}, {'A': [], 'B': [], 'C': [], 'D': ['E'], 'E': []}],\n   {'A': 10, 'B': 20, 'C': 10, 'D': 12, 'E': 10}),\n  ('normal control 2',\n   [{'A': 15, 'B': 12, 'C': 25}, {'A': ['B'], 'B': ['D'], 'C': [], 'D': ['A', 'C'], 'E': []}],\n   {'A': 15, 'B': 12, 'C': 25}),\n  ('normal control 3',\n   [{'A': 10, 'B': 35, 'C': 10, 'D': 20}, {'A': ['C'], 'B': ['E'], 'C': [], 'D': ['E', 'A'], 'E': []}],\n   {'A': 15, 'B': 30, 'C': 10, 'D': 20}),\n  ('normal control 4',\n   [{'A': 35, 'B': 25, 'C': 35}, {'A': ['D'], 'B': [], 'C': [], 'D': ['A', 'C'], 'E': ['B']}],\n   {'A': 30, 'B': 25, 'C': 30})],\n [('regression: raw neighbor values',\n   [{'A': 35, 'B': 15, 'C': 25}, {'A': ['E', 'B'], 'B': [], 'C': [], 'D': ['E'], 'E': ['A']}],\n   {'A': 30, 'B': 30, 'C': 25}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 25, 'B': 35, 'C': 15, 'D': 15, 'E': 35},\n    {'A': ['D'], 'B': [], 'C': [], 'D': ['A', 'C'], 'E': ['A']}],\n   {'A': 30, 'B': 30, 'C': 15, 'D': 20, 'E': 30}),\n  ('second regression',\n   [{'A': 10, 'B': 35, 'C': 25, 'D': 12}, {'A': [], 'B': ['C'], 'C': [], 'D': ['A'], 'E': []}],\n   {'A': 10, 'B': 30, 'C': 30, 'D': 12}),\n  ('normal control 1',\n   [{'A': 25, 'B': 15, 'C': 35, 'D': 35}, {'A': [], 'B': [], 'C': ['D'], 'D': [], 'E': []}],\n   {'A': 25, 'B': 15, 'C': 30, 'D': 30}),\n  ('normal control 2',\n   [{'A': 15, 'B': 10, 'C': 12}, {'A': [], 'B': ['C'], 'C': [], 'D': ['C'], 'E': ['B', 'D']}],\n   {'A': 15, 'B': 10, 'C': 12}),\n  ('normal control 3',\n   [{'A': 15, 'B': 12, 'C': 10, 'D': 10}, {'A': [], 'B': [], 'C': ['E'], 'D': ['A', 'E'], 'E': ['B', 'C']}],\n   {'A': 15, 'B': 12, 'C': 10, 'D': 10}),\n  ('normal control 4',\n   [{'A': 20, 'B': 15, 'C': 15}, {'A': [], 'B': ['C', 'D'], 'C': [], 'D': ['C'], 'E': ['C']}],\n   {'A': 20, 'B': 15, 'C': 15})],\n [('regression: raw neighbor values',\n   [{'A': 10, 'B': 10, 'C': 35, 'D': 10, 'E': 25}, {'A': ['E'], 'B': ['D'], 'C': ['B'], 'D': [], 'E': ['D']}],\n   {'A': 20, 'B': 30, 'C': 30, 'D': 20, 'E': 25}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 12, 'B': 25, 'C': 10, 'D': 12, 'E': 35}, {'A': [], 'B': ['E', 'A'], 'C': [], 'D': [], 'E': []}],\n   {'A': 20, 'B': 30, 'C': 10, 'D': 12, 'E': 30}),\n  ('second regression',\n   [{'A': 25, 'B': 12, 'C': 35}, {'A': ['B', 'C'], 'B': [], 'C': ['B'], 'D': ['E'], 'E': ['D']}],\n   {'A': 30, 'B': 30, 'C': 30}),\n  ('normal control 1',\n   [{'A': 25, 'B': 25, 'C': 15, 'D': 15}, {'A': ['D'], 'B': ['D'], 'C': [], 'D': [], 'E': ['B']}],\n   {'A': 25, 'B': 25, 'C': 15, 'D': 20}),\n  ('normal control 2',\n   [{'A': 10, 'B': 20, 'C': 20, 'D': 25, 'E': 35}, {'A': [], 'B': [], 'C': ['A', 'D'], 'D': [], 'E': []}],\n   {'A': 15, 'B': 20, 'C': 20, 'D': 25, 'E': 30}),\n  ('normal control 3',\n   [{'A': 15, 'B': 12, 'C': 35}, {'A': ['D', 'B'], 'B': ['E'], 'C': [], 'D': [], 'E': ['B', 'D']}],\n   {'A': 15, 'B': 12, 'C': 30}),\n  ('normal control 4',\n   [{'A': 20, 'B': 25, 'C': 25, 'D': 20}, {'A': ['B'], 'B': ['D', 'E'], 'C': ['E'], 'D': ['C'], 'E': []}],\n   {'A': 20, 'B': 25, 'C': 25, 'D': 20})],\n [('regression: raw neighbor values',\n   [{'A': 25, 'B': 15, 'C': 12, 'D': 15, 'E': 15},\n    {'A': [], 'B': ['A'], 'C': ['B'], 'D': [], 'E': ['A', 'B']}],\n   {'A': 25, 'B': 20, 'C': 12, 'D': 15, 'E': 20}),\n  ('partial repair probe: raw neighbor values',\n   [{'A': 15, 'B': 20, 'C': 35, 'D': 15}, {'A': [], 'B': [], 'C': ['E', 'B'], 'D': ['C'], 'E': ['A']}],\n   {'A': 15, 'B': 30, 'C': 30, 'D': 30}),\n  ('second regression',\n   [{'A': 25, 'B': 12, 'C': 20, 'D': 15, 'E': 12},\n    {'A': ['B'], 'B': ['A'], 'C': ['D', 'A'], 'D': ['B'], 'E': ['B']}],\n   {'A': 25, 'B': 20, 'C': 20, 'D': 15, 'E': 12}),\n  ('normal control 1',\n   [{'A': 12, 'B': 10, 'C': 10, 'D': 35}, {'A': [], 'B': ['A', 'E'], 'C': ['B'], 'D': [], 'E': []}],\n   {'A': 12, 'B': 10, 'C': 10, 'D': 30}),\n  ('normal control 2',\n   [{'A': 10, 'B': 15, 'C': 20, 'D': 15}, {'A': ['E', 'D'], 'B': ['D'], 'C': ['E'], 'D': [], 'E': []}],\n   {'A': 10, 'B': 15, 'C': 20, 'D': 15}),\n  ('normal control 3',\n   [{'A': 15, 'B': 25, 'C': 20}, {'A': [], 'B': [], 'C': [], 'D': ['C'], 'E': ['C', 'A']}],\n   {'A': 15, 'B': 25, 'C': 20}),\n  ('normal control 4', [{'A': 25, 'B': 10, 'C': 25}, {'A': [], 'B': [], 'C': ['E'], 'D': ['A'], 'E': ['D']}],\n   {'A': 25, 'B': 10, 'C': 25})]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"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.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-ride-hailing-fare-surge-surge-spatial-smoothing-raw-neighbor-values","generated_at":"2026-09-29T14:50:43.096242+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Ride-hailing prices are computed per trip at scale; ordering, unit and boundary slips become systematic over- or under-charging.","root_cause":"Neighbor values come from the partially updated output.","sha256":"b33eb969cc00b64409bd2c523ebca2d69be9d215fc0b81c7a91a06f000652423","title":"Smoothing reads already-smoothed neighbors · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":41.105,"exit_code":1,"observations":[{"actual":{"A":25,"B":30,"C":30,"D":30,"E":30},"check":"regression: raw neighbor values","expected":{"A":30,"B":30,"C":30,"D":30,"E":30},"passed":false},{"actual":{"A":25,"B":30,"C":25},"check":"partial repair probe: raw neighbor values","expected":{"A":30,"B":30,"C":25},"passed":false},{"actual":{"A":15,"B":30,"C":30,"D":10},"check":"second regression","expected":{"A":15,"B":30,"C":30,"D":10},"passed":true},{"actual":{"A":12,"B":20,"C":25,"D":15},"check":"normal control 1","expected":{"A":12,"B":20,"C":25,"D":15},"passed":true},{"actual":{"A":25,"B":20,"C":25},"check":"normal control 2","expected":{"A":25,"B":20,"C":25},"passed":true},{"actual":{"A":20,"B":25,"C":20,"D":20,"E":20},"check":"normal control 3","expected":{"A":20,"B":25,"C":20,"D":20,"E":20},"passed":true},{"actual":{"A":12,"B":12,"C":20},"check":"normal control 4","expected":{"A":12,"B":12,"C":20},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: raw neighbor values\", \"actual\": {\"E\": 30, \"D\": 30, \"C\": 30, \"B\": 30, \"A\": 25}, \"expected\": {\"A\": 30, \"B\": 30, \"C\": 30, \"D\": 30, \"E\": 30}, \"passed\": false}, {\"check\": \"partial repair probe: raw neighbor values\", \"actual\": {\"C\": 25, \"B\": 30, \"A\": 25}, \"expected\": {\"A\": 30, \"B\": 30, \"C\": 25}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"D\": 10, \"C\": 30, \"B\": 30, \"A\": 15}, \"expected\": {\"A\": 15, \"B\": 30, \"C\": 30, \"D\": 10}, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": {\"D\": 15, \"C\": 25, \"B\": 20, \"A\": 12}, \"expected\": {\"A\": 12, \"B\": 20, \"C\": 25, \"D\": 15}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"C\": 25, \"B\": 20, \"A\": 25}, \"expected\": {\"A\": 25, \"B\": 20, \"C\": 25}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"E\": 20, \"D\": 20, \"C\": 20, \"B\": 25, \"A\": 20}, \"expected\": {\"A\": 20, \"B\": 25, \"C\": 20, \"D\": 20, \"E\": 20}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"C\": 20, \"B\": 12, \"A\": 12}, \"expected\": {\"A\": 12, \"B\": 12, \"C\": 20}, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":39.09,"exit_code":1,"observations":[{"actual":{"A":30,"B":30,"C":30,"D":25,"E":25},"check":"regression: raw neighbor values","expected":{"A":30,"B":30,"C":30,"D":30,"E":30},"passed":false},{"actual":{"A":30,"B":30,"C":25},"check":"partial repair probe: raw neighbor values","expected":{"A":30,"B":30,"C":25},"passed":true},{"actual":{"A":15,"B":30,"C":25,"D":10},"check":"second regression","expected":{"A":15,"B":30,"C":30,"D":10},"passed":false},{"actual":{"A":12,"B":20,"C":25,"D":15},"check":"normal control 1","expected":{"A":12,"B":20,"C":25,"D":15},"passed":true},{"actual":{"A":25,"B":20,"C":25},"check":"normal 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\"D\": 15}, \"expected\": {\"A\": 12, \"B\": 20, \"C\": 25, \"D\": 15}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"A\": 25, \"B\": 20, \"C\": 25}, \"expected\": {\"A\": 25, \"B\": 20, \"C\": 25}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"A\": 20, \"B\": 25, \"C\": 20, \"D\": 20, \"E\": 20}, \"expected\": {\"A\": 20, \"B\": 25, \"C\": 20, \"D\": 20, \"E\": 20}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"A\": 12, \"B\": 12, \"C\": 20}, \"expected\": {\"A\": 12, \"B\": 12, \"C\": 20}, \"passed\": true}], \"passed\": false}\n"}},"member_only":{"stages":["fixed"],"fields":["implementations.fixed","verification.fixed","harness","repair"],"note":"The verified repair, its recorded checks, the repair description, and the scoring harness are available to members."}}