{"abstract":"Mid-schedule disruptions borrow a future price.","category":"Options payoff and settlement","checks":8,"contract":"Inputs kind (price-call, price-put, strike-call), fixings (None = disrupted), strike and final price. A disrupted fixing takes the last preceding filled value; if none precedes, the next valid fixing. avg = mean of the filled fixings. price-call pays max(avg-K,0), price-put max(K-avg,0), strike-call max(final-avg,0). Round to 6.","evaluation_group":"w2-options_payoff_and_settlement-asian-disrupted-fixings","failed_approach":"Averaging neighbours interpolates instead of carrying the previous value.","family":"w2-options_payoff_and_settlement-asian-disrupted-fixings-fallback-priority","id":"FA-61421","implementations":{"attempt":{"sha256":"35b0af2562e043643a737b5815134078478219a0d3dcf4f6dc5ffe4cc0723282","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(kind, fixings, strike, final):\n    vals = list(fixings)\n    filled = []\n    for i, v in enumerate(vals):\n        if v is None:\n            prev = [x for x in filled if x is not None]\n            later = [x for x in vals[i + 1:] if x is not None]\n            v = (prev[-1] + later[0]) / 2 if prev and later else (prev or later)[0]\n        filled.append(v)\n    avg = sum(filled) / len(filled)\n    if kind == 'price-call':\n        pay = max(avg - strike, 0.0)\n    elif kind == 'price-put':\n        pay = max(strike - avg, 0.0)\n    else:\n        pay = max(final - avg, 0.0)\n    return round(pay, 6)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression fallback priority 1', ['price-put', [107.56, 91.47, None, 93.63, 107.09, 85.05], 100, 107.47], 3.955], ['regression fallback priority 2', ['strike-call', [90.82, 116.42, 97.17, None, 102.9], 100, 102.74], 1.844], ['partial repair probe 1', ['strike-call', [119.87, 109.69, None], 110, 116.2], 3.116667], ['partial repair probe 2', ['price-call', [117.31, 109.18, 80.52, 110.93, None], 90, 89.18], 15.774], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-put', [115.48, 83.47, 98.82], 100, 99.98], 0.743333], ['normal control 2', ['strike-call', [111.57, None, None, None, 98.59, 116.83], 110, 84.9], 0.0], ['normal control 3', ['strike-call', [91.38, None, None], 105, 95.03], 3.65]], [['regression fallback priority 1', ['price-call', [98.02, None, 91.49, 95.03, 98.48, 97.35], 90, 119.72], 6.398333], ['regression fallback priority 2', ['price-put', [119.49, 98.97, 101.06, None, 95.58, 113.4, 91.41, 95.29], 105, 88.56], 2.9675], ['partial repair probe 1', ['strike-call', [88.95, 80.84, None], 110, 112.81], 29.266667], ['partial repair probe 2', ['price-put', [119.4, 88.69, 99.38, 103.22, 102.55, None], 110, 112.44], 7.368333], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-put', [85.84, None], 90, 114.04], 4.16], ['normal control 2', ['price-put', [None, 105.9], 105, 82.58], 0.0], ['normal control 3', ['price-put', [111.7, 101.25, 103.45, 114.56, 86.59, None, 114.39], 100, 96.18], 0.0]], [['regression fallback priority 1', ['price-call', [119.01, None, 115.28], 105, 82.02], 12.766667], ['regression fallback priority 2', ['price-call', [84.27, 118.57, None, None, None, 103.89], 100, 80.29], 10.406667], ['partial repair probe 1', ['price-put', [None, 87.07, 89.34, None], 90, 115.78], 1.795], ['partial repair probe 2', ['price-put', [110.48, 85.44, None, None, None], 110, 102.6], 19.552], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-call', [80.8, 102.44, None, 103.49, 106.76, 93.24, None], 110, 93.16], 0.0], ['normal control 2', ['price-call', [96.59, None, 81.5, 86.37, 117.86, 81.57], 100, 80.38], 0.0], ['normal control 3', ['price-put', [93.19, None, None, None, None], 110, 115.13], 16.81]], [['regression fallback priority 1', ['price-put', [85.19, None, 83.45, 104.23, 100.65, None, 102.76], 110, 109.78], 15.411429], ['regression fallback priority 2', ['strike-call', [86.53, 95.55, None, 100.69, 106.44], 90, 104.86], 7.908], ['partial repair probe 1', ['strike-call', [81.55, 101.38, 89.48, None], 100, 100.13], 9.6575], ['partial repair probe 2', ['price-put', [88.01, 87.96, None], 105, 112.32], 17.023333], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-call', [None, 112.37, None, None], 90, 98.65], 22.37], ['normal control 2', ['price-call', [None, 110.4, 80.07], 90, 95.81], 10.29], ['normal control 3', ['price-put', [110.91, None], 100, 116.16], 0.0]], [['regression fallback priority 1', ['strike-call', [100.62, None, 111.91, 86.61, None], 100, 115.98], 18.706], ['regression fallback priority 2', ['price-put', [116.55, 87.44, 91.05, None, 97.68], 110, 114.79], 13.246], ['partial repair probe 1', ['strike-call', [87.08, 93.2, None, None, None, None], 110, 94.72], 2.54], ['partial repair probe 2', ['price-call', [104.79, 89.0, None, None], 100, 101.84], 0.0], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-call', [None, 98.32, 105.85, 84.08], 100, 117.74], 0.0], ['normal control 2', ['price-call', [80.35, 102.5], 105, 119.19], 0.0], ['normal control 3', ['price-call', [97.46, 119.62, 96.51, 117.63, 87.35, 92.18, 101.58, 80.54], 90, 100.37], 9.10875]]]\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":"f316b14fe4e0191f7d80a1e821bb0840b61d7304d7aad99d0cd990d1008b09fe","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(kind, fixings, strike, final):\n    vals = list(fixings)\n    filled = []\n    for i, v in enumerate(vals):\n        if v is None:\n            prev = [x for x in filled if x is not None]\n            later = [x for x in vals[i + 1:] if x is not None]\n            v = later[0] if later else prev[-1]\n        filled.append(v)\n    avg = sum(filled) / len(filled)\n    if kind == 'price-call':\n        pay = max(avg - strike, 0.0)\n    elif kind == 'price-put':\n        pay = max(strike - avg, 0.0)\n    else:\n        pay = max(final - avg, 0.0)\n    return round(pay, 6)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression fallback priority 1', ['price-put', [107.56, 91.47, None, 93.63, 107.09, 85.05], 100, 107.47], 3.955], ['regression fallback priority 2', ['strike-call', [90.82, 116.42, 97.17, None, 102.9], 100, 102.74], 1.844], ['partial repair probe 1', ['strike-call', [119.87, 109.69, None], 110, 116.2], 3.116667], ['partial repair probe 2', ['price-call', [117.31, 109.18, 80.52, 110.93, None], 90, 89.18], 15.774], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-put', [115.48, 83.47, 98.82], 100, 99.98], 0.743333], ['normal control 2', ['strike-call', [111.57, None, None, None, 98.59, 116.83], 110, 84.9], 0.0], ['normal control 3', ['strike-call', [91.38, None, None], 105, 95.03], 3.65]], [['regression fallback priority 1', ['price-call', [98.02, None, 91.49, 95.03, 98.48, 97.35], 90, 119.72], 6.398333], ['regression fallback priority 2', ['price-put', [119.49, 98.97, 101.06, None, 95.58, 113.4, 91.41, 95.29], 105, 88.56], 2.9675], ['partial repair probe 1', ['strike-call', [88.95, 80.84, None], 110, 112.81], 29.266667], ['partial repair probe 2', ['price-put', [119.4, 88.69, 99.38, 103.22, 102.55, None], 110, 112.44], 7.368333], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-put', [85.84, None], 90, 114.04], 4.16], ['normal control 2', ['price-put', [None, 105.9], 105, 82.58], 0.0], ['normal control 3', ['price-put', [111.7, 101.25, 103.45, 114.56, 86.59, None, 114.39], 100, 96.18], 0.0]], [['regression fallback priority 1', ['price-call', [119.01, None, 115.28], 105, 82.02], 12.766667], ['regression fallback priority 2', ['price-call', [84.27, 118.57, None, None, None, 103.89], 100, 80.29], 10.406667], ['partial repair probe 1', ['price-put', [None, 87.07, 89.34, None], 90, 115.78], 1.795], ['partial repair probe 2', ['price-put', [110.48, 85.44, None, None, None], 110, 102.6], 19.552], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-call', [80.8, 102.44, None, 103.49, 106.76, 93.24, None], 110, 93.16], 0.0], ['normal control 2', ['price-call', [96.59, None, 81.5, 86.37, 117.86, 81.57], 100, 80.38], 0.0], ['normal control 3', ['price-put', [93.19, None, None, None, None], 110, 115.13], 16.81]], [['regression fallback priority 1', ['price-put', [85.19, None, 83.45, 104.23, 100.65, None, 102.76], 110, 109.78], 15.411429], ['regression fallback priority 2', ['strike-call', [86.53, 95.55, None, 100.69, 106.44], 90, 104.86], 7.908], ['partial repair probe 1', ['strike-call', [81.55, 101.38, 89.48, None], 100, 100.13], 9.6575], ['partial repair probe 2', ['price-put', [88.01, 87.96, None], 105, 112.32], 17.023333], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-call', [None, 112.37, None, None], 90, 98.65], 22.37], ['normal control 2', ['price-call', [None, 110.4, 80.07], 90, 95.81], 10.29], ['normal control 3', ['price-put', [110.91, None], 100, 116.16], 0.0]], [['regression fallback priority 1', ['strike-call', [100.62, None, 111.91, 86.61, None], 100, 115.98], 18.706], ['regression fallback priority 2', ['price-put', [116.55, 87.44, 91.05, None, 97.68], 110, 114.79], 13.246], ['partial repair probe 1', ['strike-call', [87.08, 93.2, None, None, None, None], 110, 94.72], 2.54], ['partial repair probe 2', ['price-call', [104.79, 89.0, None, None], 100, 101.84], 0.0], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-call', [None, 98.32, 105.85, 84.08], 100, 117.74], 0.0], ['normal control 2', ['price-call', [80.35, 102.5], 105, 119.19], 0.0], ['normal control 3', ['price-call', [97.46, 119.62, 96.51, 117.63, 87.35, 92.18, 101.58, 80.54], 90, 100.37], 9.10875]]]\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"},"fixed":{"sha256":"2c5c22b8f85e355cda5820d337ef2f23b59f28d56e896d75357d27a982166ce1","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(kind, fixings, strike, final):\n    vals = list(fixings)\n    filled = []\n    for i, v in enumerate(vals):\n        if v is None:\n            prev = [x for x in filled if x is not None]\n            later = [x for x in vals[i + 1:] if x is not None]\n            v = prev[-1] if prev else later[0]\n        filled.append(v)\n    avg = sum(filled) / len(filled)\n    if kind == 'price-call':\n        pay = max(avg - strike, 0.0)\n    elif kind == 'price-put':\n        pay = max(strike - avg, 0.0)\n    else:\n        pay = max(final - avg, 0.0)\n    return round(pay, 6)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression fallback priority 1', ['price-put', [107.56, 91.47, None, 93.63, 107.09, 85.05], 100, 107.47], 3.955], ['regression fallback priority 2', ['strike-call', [90.82, 116.42, 97.17, None, 102.9], 100, 102.74], 1.844], ['partial repair probe 1', ['strike-call', [119.87, 109.69, None], 110, 116.2], 3.116667], ['partial repair probe 2', ['price-call', [117.31, 109.18, 80.52, 110.93, None], 90, 89.18], 15.774], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-put', [115.48, 83.47, 98.82], 100, 99.98], 0.743333], ['normal control 2', ['strike-call', [111.57, None, None, None, 98.59, 116.83], 110, 84.9], 0.0], ['normal control 3', ['strike-call', [91.38, None, None], 105, 95.03], 3.65]], [['regression fallback priority 1', ['price-call', [98.02, None, 91.49, 95.03, 98.48, 97.35], 90, 119.72], 6.398333], ['regression fallback priority 2', ['price-put', [119.49, 98.97, 101.06, None, 95.58, 113.4, 91.41, 95.29], 105, 88.56], 2.9675], ['partial repair probe 1', ['strike-call', [88.95, 80.84, None], 110, 112.81], 29.266667], ['partial repair probe 2', ['price-put', [119.4, 88.69, 99.38, 103.22, 102.55, None], 110, 112.44], 7.368333], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-put', [85.84, None], 90, 114.04], 4.16], ['normal control 2', ['price-put', [None, 105.9], 105, 82.58], 0.0], ['normal control 3', ['price-put', [111.7, 101.25, 103.45, 114.56, 86.59, None, 114.39], 100, 96.18], 0.0]], [['regression fallback priority 1', ['price-call', [119.01, None, 115.28], 105, 82.02], 12.766667], ['regression fallback priority 2', ['price-call', [84.27, 118.57, None, None, None, 103.89], 100, 80.29], 10.406667], ['partial repair probe 1', ['price-put', [None, 87.07, 89.34, None], 90, 115.78], 1.795], ['partial repair probe 2', ['price-put', [110.48, 85.44, None, None, None], 110, 102.6], 19.552], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-call', [80.8, 102.44, None, 103.49, 106.76, 93.24, None], 110, 93.16], 0.0], ['normal control 2', ['price-call', [96.59, None, 81.5, 86.37, 117.86, 81.57], 100, 80.38], 0.0], ['normal control 3', ['price-put', [93.19, None, None, None, None], 110, 115.13], 16.81]], [['regression fallback priority 1', ['price-put', [85.19, None, 83.45, 104.23, 100.65, None, 102.76], 110, 109.78], 15.411429], ['regression fallback priority 2', ['strike-call', [86.53, 95.55, None, 100.69, 106.44], 90, 104.86], 7.908], ['partial repair probe 1', ['strike-call', [81.55, 101.38, 89.48, None], 100, 100.13], 9.6575], ['partial repair probe 2', ['price-put', [88.01, 87.96, None], 105, 112.32], 17.023333], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-call', [None, 112.37, None, None], 90, 98.65], 22.37], ['normal control 2', ['price-call', [None, 110.4, 80.07], 90, 95.81], 10.29], ['normal control 3', ['price-put', [110.91, None], 100, 116.16], 0.0]], [['regression fallback priority 1', ['strike-call', [100.62, None, 111.91, 86.61, None], 100, 115.98], 18.706], ['regression fallback priority 2', ['price-put', [116.55, 87.44, 91.05, None, 97.68], 110, 114.79], 13.246], ['partial repair probe 1', ['strike-call', [87.08, 93.2, None, None, None, None], 110, 94.72], 2.54], ['partial repair probe 2', ['price-call', [104.79, 89.0, None, None], 100, 101.84], 0.0], ['boundary control 1', ['price-call', [None, 100.0, 110.0], 100, 100.0], 3.333333], ['normal control 1', ['price-call', [None, 98.32, 105.85, 84.08], 100, 117.74], 0.0], ['normal control 2', ['price-call', [80.35, 102.5], 105, 119.19], 0.0], ['normal control 3', ['price-call', [97.46, 119.62, 96.51, 117.63, 87.35, 92.18, 101.58, 80.54], 90, 100.37], 9.10875]]]\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 contract stated explicitly in the contract field; no claim of conformance to any exchange or clearing rulebook. 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-options_payoff_and_settlement-asian-disrupted-fixings-fallback-priority","generated_at":"2026-09-29T14:46:55.059710+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Option expiry, exercise and settlement engines move cash and shares; a wrong branch misstates obligations.","repair":"Use the last preceding filled value; look forward only when nothing precedes.","root_cause":"The fallback checks later fixings before earlier ones.","sha256":"392e78a2d1430a85bb192f4dc7f2c5a39167d901e9a8ef191b717425bd2cc5e9","title":"Arithmetic Asian payoff with disrupted fixings: disruptions prefer the next valid fixing over the previous one · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":40.936,"exit_code":1,"observations":[{"actual":3.775,"check":"regression fallback priority 1","expected":3.955,"passed":false},{"actual":1.271,"check":"regression fallback priority 2","expected":1.844,"passed":false},{"actual":0.0,"check":"partial repair probe 1","expected":3.116667,"passed":false},{"actual":17.05,"check":"partial repair probe 2","expected":15.774,"passed":false},{"actual":3.333333,"check":"boundary control 1","expected":3.333333,"passed":true},{"actual":0.743333,"check":"normal control 1","expected":0.743333,"passed":true},{"actual":0.0,"check":"normal control 2","expected":0.0,"passed":true},{"actual":3.65,"check":"normal control 3","expected":3.65,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression fallback priority 1\", \"actual\": 3.775, \"expected\": 3.955, \"passed\": false}, {\"check\": \"regression fallback priority 2\", \"actual\": 1.271, \"expected\": 1.844, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 0.0, \"expected\": 3.116667, \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": 17.05, \"expected\": 15.774, \"passed\": false}, {\"check\": \"boundary control 1\", \"actual\": 3.333333, \"expected\": 3.333333, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 0.743333, \"expected\": 0.743333, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 3.65, \"expected\": 3.65, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":39.253,"exit_code":1,"observations":[{"actual":3.595,"check":"regression fallback priority 1","expected":3.955,"passed":false},{"actual":0.698,"check":"regression fallback priority 2","expected":1.844,"passed":false},{"actual":3.116667,"check":"partial repair probe 1","expected":3.116667,"passed":true},{"actual":15.774,"check":"partial repair probe 2","expected":15.774,"passed":true},{"actual":3.333333,"check":"boundary control 1","expected":3.333333,"passed":true},{"actual":0.743333,"check":"normal control 1","expected":0.743333,"passed":true},{"actual":0.0,"check":"normal control 2","expected":0.0,"passed":true},{"actual":3.65,"check":"normal control 3","expected":3.65,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression fallback priority 1\", \"actual\": 3.595, \"expected\": 3.955, \"passed\": false}, {\"check\": \"regression fallback priority 2\", \"actual\": 0.698, \"expected\": 1.844, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 3.116667, \"expected\": 3.116667, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 15.774, \"expected\": 15.774, \"passed\": true}, {\"check\": \"boundary control 1\", \"actual\": 3.333333, \"expected\": 3.333333, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 0.743333, \"expected\": 0.743333, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 3.65, \"expected\": 3.65, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":40.321,"exit_code":0,"observations":[{"actual":3.955,"check":"regression fallback priority 1","expected":3.955,"passed":true},{"actual":1.844,"check":"regression fallback priority 2","expected":1.844,"passed":true},{"actual":3.116667,"check":"partial repair probe 1","expected":3.116667,"passed":true},{"actual":15.774,"check":"partial repair probe 2","expected":15.774,"passed":true},{"actual":3.333333,"check":"boundary control 1","expected":3.333333,"passed":true},{"actual":0.743333,"check":"normal control 1","expected":0.743333,"passed":true},{"actual":0.0,"check":"normal control 2","expected":0.0,"passed":true},{"actual":3.65,"check":"normal control 3","expected":3.65,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression fallback priority 1\", \"actual\": 3.955, \"expected\": 3.955, \"passed\": true}, {\"check\": \"regression fallback priority 2\", \"actual\": 1.844, \"expected\": 1.844, \"passed\": true}, {\"check\": \"partial repair probe 1\", \"actual\": 3.116667, \"expected\": 3.116667, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 15.774, \"expected\": 15.774, \"passed\": true}, {\"check\": \"boundary control 1\", \"actual\": 3.333333, \"expected\": 3.333333, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 0.743333, \"expected\": 0.743333, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": 3.65, \"expected\": 3.65, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}