{"abstract":"Values are wrong for every maturity other than one year.","category":"Options payoff and settlement","checks":8,"contract":"Inputs kind, spot S, strike K, rate r, dividend yield q, volatility sigma and calendar days to expiry. T = days/365. At days == 0 return intrinsic value. Otherwise d1 = (ln(S/K) + (r - q + sigma^2/2)T)/(sigma sqrt T), d2 = d1 - sigma sqrt T, call = S e^{-qT} N(d1) - K e^{-rT} N(d2), put = K e^{-rT} N(-d2) - S e^{-qT} N(-d1). Round to 6.","evaluation_group":"w2-options_payoff_and_settlement-black-scholes-dividend-yield","failed_approach":"Subtracting sigma^2*sqrt(T) mixes variance and volatility.","family":"w2-options_payoff_and_settlement-black-scholes-dividend-yield-d2-volatility-term","id":"FA-61546","implementations":{"attempt":{"sha256":"487be230165a12e20e5177df8db31e6565cfb00c03f80ff26087e730e2eb3730","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(kind, S, K, r, q, sigma, days):\n    def N(x):\n        return 0.5 * (1 + math.erf(x / math.sqrt(2)))\n    T = days / 365\n    if days == 0:\n        return round(max(S - K, 0.0) if kind == 'C' else max(K - S, 0.0), 6)\n    d1 = (math.log(S / K) + (r - q + 0.5 * sigma ** 2) * T) / (sigma * math.sqrt(T))\n    d2 = d1 - sigma ** 2 * math.sqrt(T)\n    if kind == 'C':\n        v = S * math.exp(-q * T) * N(d1) - K * math.exp(-r * T) * N(d2)\n    else:\n        v = K * math.exp(-r * T) * N(-d2) - S * math.exp(-q * T) * N(-d1)\n    return round(v, 6)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression d2 volatility term 1', ['C', 90.0, 95.0, 0.02, 0.03, 0.35, 30], 1.69956], ['regression d2 volatility term 2', ['C', 90.0, 100.0, 0.02, 0.015, 0.2, 182], 1.805544], ['partial repair probe 1', ['C', 100.0, 100.0, 0.02, 0.03, 0.35, 365], 13.067027], ['partial repair probe 2', ['C', 100.0, 100.0, 0.02, 0.0, 0.1, 365], 5.016981], ['boundary control 1', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['P', 100.0, 95.0, 0.05, 0.0, 0.1, 1], 0.0], ['normal control 2', ['P', 90.0, 100.0, 0.0, 0.0, 0.2, 0], 10.0]], [['regression d2 volatility term 1', ['P', 90.0, 95.0, 0.05, 0.0, 0.35, 91], 8.491395], ['regression d2 volatility term 2', ['P', 100.0, 95.0, 0.05, 0.03, 0.1, 30], 0.035336], ['partial repair probe 1', ['C', 100.0, 95.0, 0.05, 0.0, 0.2, 365], 13.346465], ['partial repair probe 2', ['C', 110.0, 95.0, 0.0, 0.015, 0.35, 365], 21.78191], ['boundary control 1', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['P', 90.0, 95.0, 0.02, 0.03, 0.2, 0], 5.0], ['normal control 2', ['P', 90.0, 105.0, 0.0, 0.03, 0.35, 1], 15.007397]], [['regression d2 volatility term 1', ['C', 100.0, 105.0, 0.0, 0.03, 0.35, 7], 0.399252], ['regression d2 volatility term 2', ['P', 110.0, 100.0, 0.02, 0.03, 0.1, 91], 0.063955], ['partial repair probe 1', ['C', 110.0, 100.0, 0.05, 0.015, 0.1, 365], 13.698166], ['partial repair probe 2', ['P', 110.0, 95.0, 0.02, 0.0, 0.1, 365], 0.200779], ['boundary control 1', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['C', 100.0, 100.0, 0.05, 0.015, 0.35, 0], 0.0], ['normal control 2', ['C', 90.0, 105.0, 0.0, 0.0, 0.35, 0], 0.0]], [['regression d2 volatility term 1', ['C', 110.0, 105.0, 0.02, 0.03, 0.2, 91], 7.012004], ['regression d2 volatility term 2', ['P', 90.0, 95.0, 0.05, 0.03, 0.35, 30], 6.596833], ['partial repair probe 1', ['P', 100.0, 95.0, 0.05, 0.03, 0.1, 365], 1.30802], ['partial repair probe 2', ['C', 90.0, 100.0, 0.0, 0.03, 0.1, 365], 0.378908], ['boundary control 1', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['P', 100.0, 95.0, 0.05, 0.03, 0.1, 0], 0.0], ['normal control 2', ['C', 100.0, 105.0, 0.05, 0.03, 0.35, 0], 0.0]], [['regression d2 volatility term 1', ['P', 110.0, 105.0, 0.02, 0.015, 0.2, 182], 3.745196], ['regression d2 volatility term 2', ['P', 100.0, 95.0, 0.05, 0.03, 0.2, 7], 0.032572], ['partial repair probe 1', ['C', 90.0, 95.0, 0.02, 0.0, 0.2, 365], 5.838977], ['partial repair probe 2', ['P', 110.0, 95.0, 0.02, 0.03, 0.2, 365], 2.923685], ['boundary control 1', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['C', 90.0, 100.0, 0.02, 0.015, 0.35, 1], 0.0], ['normal control 2', ['C', 100.0, 105.0, 0.05, 0.03, 0.1, 1], 0.0]]]\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":"ac056318a97d31c94b2b1425c4d8ef2ded928b829e3dfab254cefb970a48de56","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(kind, S, K, r, q, sigma, days):\n    def N(x):\n        return 0.5 * (1 + math.erf(x / math.sqrt(2)))\n    T = days / 365\n    if days == 0:\n        return round(max(S - K, 0.0) if kind == 'C' else max(K - S, 0.0), 6)\n    d1 = (math.log(S / K) + (r - q + 0.5 * sigma ** 2) * T) / (sigma * math.sqrt(T))\n    d2 = d1 - sigma * T\n    if kind == 'C':\n        v = S * math.exp(-q * T) * N(d1) - K * math.exp(-r * T) * N(d2)\n    else:\n        v = K * math.exp(-r * T) * N(-d2) - S * math.exp(-q * T) * N(-d1)\n    return round(v, 6)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression d2 volatility term 1', ['C', 90.0, 95.0, 0.02, 0.03, 0.35, 30], 1.69956], ['regression d2 volatility term 2', ['C', 90.0, 100.0, 0.02, 0.015, 0.2, 182], 1.805544], ['partial repair probe 1', ['C', 100.0, 100.0, 0.02, 0.03, 0.35, 365], 13.067027], ['partial repair probe 2', ['C', 100.0, 100.0, 0.02, 0.0, 0.1, 365], 5.016981], ['boundary control 1', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['P', 100.0, 95.0, 0.05, 0.0, 0.1, 1], 0.0], ['normal control 2', ['P', 90.0, 100.0, 0.0, 0.0, 0.2, 0], 10.0]], [['regression d2 volatility term 1', ['P', 90.0, 95.0, 0.05, 0.0, 0.35, 91], 8.491395], ['regression d2 volatility term 2', ['P', 100.0, 95.0, 0.05, 0.03, 0.1, 30], 0.035336], ['partial repair probe 1', ['C', 100.0, 95.0, 0.05, 0.0, 0.2, 365], 13.346465], ['partial repair probe 2', ['C', 110.0, 95.0, 0.0, 0.015, 0.35, 365], 21.78191], ['boundary control 1', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['P', 90.0, 95.0, 0.02, 0.03, 0.2, 0], 5.0], ['normal control 2', ['P', 90.0, 105.0, 0.0, 0.03, 0.35, 1], 15.007397]], [['regression d2 volatility term 1', ['C', 100.0, 105.0, 0.0, 0.03, 0.35, 7], 0.399252], ['regression d2 volatility term 2', ['P', 110.0, 100.0, 0.02, 0.03, 0.1, 91], 0.063955], ['partial repair probe 1', ['C', 110.0, 100.0, 0.05, 0.015, 0.1, 365], 13.698166], ['partial repair probe 2', ['P', 110.0, 95.0, 0.02, 0.0, 0.1, 365], 0.200779], ['boundary control 1', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['C', 100.0, 100.0, 0.05, 0.015, 0.35, 0], 0.0], ['normal control 2', ['C', 90.0, 105.0, 0.0, 0.0, 0.35, 0], 0.0]], [['regression d2 volatility term 1', ['C', 110.0, 105.0, 0.02, 0.03, 0.2, 91], 7.012004], ['regression d2 volatility term 2', ['P', 90.0, 95.0, 0.05, 0.03, 0.35, 30], 6.596833], ['partial repair probe 1', ['P', 100.0, 95.0, 0.05, 0.03, 0.1, 365], 1.30802], ['partial repair probe 2', ['C', 90.0, 100.0, 0.0, 0.03, 0.1, 365], 0.378908], ['boundary control 1', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['P', 100.0, 95.0, 0.05, 0.03, 0.1, 0], 0.0], ['normal control 2', ['C', 100.0, 105.0, 0.05, 0.03, 0.35, 0], 0.0]], [['regression d2 volatility term 1', ['P', 110.0, 105.0, 0.02, 0.015, 0.2, 182], 3.745196], ['regression d2 volatility term 2', ['P', 100.0, 95.0, 0.05, 0.03, 0.2, 7], 0.032572], ['partial repair probe 1', ['C', 90.0, 95.0, 0.02, 0.0, 0.2, 365], 5.838977], ['partial repair probe 2', ['P', 110.0, 95.0, 0.02, 0.03, 0.2, 365], 2.923685], ['boundary control 1', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['C', 90.0, 100.0, 0.02, 0.015, 0.35, 1], 0.0], ['normal control 2', ['C', 100.0, 105.0, 0.05, 0.03, 0.1, 1], 0.0]]]\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":"114e7c1c57a42438643791e0e6dbd0f5552c22b33bdf5af4561cf2e83502bcc9","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(kind, S, K, r, q, sigma, days):\n    def N(x):\n        return 0.5 * (1 + math.erf(x / math.sqrt(2)))\n    T = days / 365\n    if days == 0:\n        return round(max(S - K, 0.0) if kind == 'C' else max(K - S, 0.0), 6)\n    d1 = (math.log(S / K) + (r - q + 0.5 * sigma ** 2) * T) / (sigma * math.sqrt(T))\n    d2 = d1 - sigma * math.sqrt(T)\n    if kind == 'C':\n        v = S * math.exp(-q * T) * N(d1) - K * math.exp(-r * T) * N(d2)\n    else:\n        v = K * math.exp(-r * T) * N(-d2) - S * math.exp(-q * T) * N(-d1)\n    return round(v, 6)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression d2 volatility term 1', ['C', 90.0, 95.0, 0.02, 0.03, 0.35, 30], 1.69956], ['regression d2 volatility term 2', ['C', 90.0, 100.0, 0.02, 0.015, 0.2, 182], 1.805544], ['partial repair probe 1', ['C', 100.0, 100.0, 0.02, 0.03, 0.35, 365], 13.067027], ['partial repair probe 2', ['C', 100.0, 100.0, 0.02, 0.0, 0.1, 365], 5.016981], ['boundary control 1', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['P', 100.0, 95.0, 0.05, 0.0, 0.1, 1], 0.0], ['normal control 2', ['P', 90.0, 100.0, 0.0, 0.0, 0.2, 0], 10.0]], [['regression d2 volatility term 1', ['P', 90.0, 95.0, 0.05, 0.0, 0.35, 91], 8.491395], ['regression d2 volatility term 2', ['P', 100.0, 95.0, 0.05, 0.03, 0.1, 30], 0.035336], ['partial repair probe 1', ['C', 100.0, 95.0, 0.05, 0.0, 0.2, 365], 13.346465], ['partial repair probe 2', ['C', 110.0, 95.0, 0.0, 0.015, 0.35, 365], 21.78191], ['boundary control 1', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['P', 90.0, 95.0, 0.02, 0.03, 0.2, 0], 5.0], ['normal control 2', ['P', 90.0, 105.0, 0.0, 0.03, 0.35, 1], 15.007397]], [['regression d2 volatility term 1', ['C', 100.0, 105.0, 0.0, 0.03, 0.35, 7], 0.399252], ['regression d2 volatility term 2', ['P', 110.0, 100.0, 0.02, 0.03, 0.1, 91], 0.063955], ['partial repair probe 1', ['C', 110.0, 100.0, 0.05, 0.015, 0.1, 365], 13.698166], ['partial repair probe 2', ['P', 110.0, 95.0, 0.02, 0.0, 0.1, 365], 0.200779], ['boundary control 1', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['C', 100.0, 100.0, 0.05, 0.015, 0.35, 0], 0.0], ['normal control 2', ['C', 90.0, 105.0, 0.0, 0.0, 0.35, 0], 0.0]], [['regression d2 volatility term 1', ['C', 110.0, 105.0, 0.02, 0.03, 0.2, 91], 7.012004], ['regression d2 volatility term 2', ['P', 90.0, 95.0, 0.05, 0.03, 0.35, 30], 6.596833], ['partial repair probe 1', ['P', 100.0, 95.0, 0.05, 0.03, 0.1, 365], 1.30802], ['partial repair probe 2', ['C', 90.0, 100.0, 0.0, 0.03, 0.1, 365], 0.378908], ['boundary control 1', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['P', 100.0, 95.0, 0.05, 0.03, 0.1, 0], 0.0], ['normal control 2', ['C', 100.0, 105.0, 0.05, 0.03, 0.35, 0], 0.0]], [['regression d2 volatility term 1', ['P', 110.0, 105.0, 0.02, 0.015, 0.2, 182], 3.745196], ['regression d2 volatility term 2', ['P', 100.0, 95.0, 0.05, 0.03, 0.2, 7], 0.032572], ['partial repair probe 1', ['C', 90.0, 95.0, 0.02, 0.0, 0.2, 365], 5.838977], ['partial repair probe 2', ['P', 110.0, 95.0, 0.02, 0.03, 0.2, 365], 2.923685], ['boundary control 1', ['P', 90.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['boundary control 2', ['C', 110.0, 100.0, 0.05, 0.0, 0.2, 0], 10.0], ['normal control 1', ['C', 90.0, 100.0, 0.02, 0.015, 0.35, 1], 0.0], ['normal control 2', ['C', 100.0, 105.0, 0.05, 0.03, 0.1, 1], 0.0]]]\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-black-scholes-dividend-yield-d2-volatility-term","generated_at":"2026-09-29T14:46:56.174003+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 d2 = d1 - sigma*sqrt(T).","root_cause":"d2 subtracts sigma*T instead of sigma*sqrt(T).","sha256":"2aa84aecad2b144bf52e15b9ab31d79c721878ff013aff54c0211d8848bbb570","title":"European option value with continuous dividend yield: d2 subtracts sigma*T · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":40.158,"exit_code":1,"observations":[{"actual":-0.404446,"check":"regression d2 volatility term 1","expected":1.69956,"passed":false},{"actual":-1.581095,"check":"regression d2 volatility term 2","expected":1.805544,"passed":false},{"actual":4.225537,"check":"partial repair probe 1","expected":13.067027,"passed":false},{"actual":1.564997,"check":"partial repair probe 2","expected":5.016981,"passed":false},{"actual":10.0,"check":"boundary control 1","expected":10.0,"passed":true},{"actual":10.0,"check":"boundary control 2","expected":10.0,"passed":true},{"actual":0.0,"check":"normal control 1","expected":0.0,"passed":true},{"actual":10.0,"check":"normal control 2","expected":10.0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression d2 volatility term 1\", \"actual\": -0.404446, \"expected\": 1.69956, \"passed\": false}, {\"check\": \"regression d2 volatility term 2\", \"actual\": -1.581095, \"expected\": 1.805544, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 4.225537, \"expected\": 13.067027, \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": 1.564997, \"expected\": 5.016981, \"passed\": false}, {\"check\": \"boundary control 1\", \"actual\": 10.0, \"expected\": 10.0, \"passed\": true}, {\"check\": \"boundary control 2\", \"actual\": 10.0, \"expected\": 10.0, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 10.0, \"expected\": 10.0, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":38.222,"exit_code":1,"observations":[{"actual":-0.613446,"check":"regression d2 volatility term 1","expected":1.69956,"passed":false},{"actual":0.594633,"check":"regression d2 volatility term 2","expected":1.805544,"passed":false},{"actual":13.067027,"check":"partial repair probe 1","expected":13.067027,"passed":true},{"actual":5.016981,"check":"partial repair probe 2","expected":5.016981,"passed":true},{"actual":10.0,"check":"boundary control 1","expected":10.0,"passed":true},{"actual":10.0,"check":"boundary control 2","expected":10.0,"passed":true},{"actual":0.0,"check":"normal control 1","expected":0.0,"passed":true},{"actual":10.0,"check":"normal control 2","expected":10.0,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression d2 volatility term 1\", \"actual\": -0.613446, \"expected\": 1.69956, \"passed\": false}, {\"check\": \"regression d2 volatility term 2\", \"actual\": 0.594633, \"expected\": 1.805544, \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": 13.067027, \"expected\": 13.067027, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 5.016981, \"expected\": 5.016981, \"passed\": true}, {\"check\": \"boundary control 1\", \"actual\": 10.0, \"expected\": 10.0, \"passed\": true}, {\"check\": \"boundary control 2\", \"actual\": 10.0, \"expected\": 10.0, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 10.0, \"expected\": 10.0, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":41.097,"exit_code":0,"observations":[{"actual":1.69956,"check":"regression d2 volatility term 1","expected":1.69956,"passed":true},{"actual":1.805544,"check":"regression d2 volatility term 2","expected":1.805544,"passed":true},{"actual":13.067027,"check":"partial repair probe 1","expected":13.067027,"passed":true},{"actual":5.016981,"check":"partial repair probe 2","expected":5.016981,"passed":true},{"actual":10.0,"check":"boundary control 1","expected":10.0,"passed":true},{"actual":10.0,"check":"boundary control 2","expected":10.0,"passed":true},{"actual":0.0,"check":"normal control 1","expected":0.0,"passed":true},{"actual":10.0,"check":"normal control 2","expected":10.0,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression d2 volatility term 1\", \"actual\": 1.69956, \"expected\": 1.69956, \"passed\": true}, {\"check\": \"regression d2 volatility term 2\", \"actual\": 1.805544, \"expected\": 1.805544, \"passed\": true}, {\"check\": \"partial repair probe 1\", \"actual\": 13.067027, \"expected\": 13.067027, \"passed\": true}, {\"check\": \"partial repair probe 2\", \"actual\": 5.016981, \"expected\": 5.016981, \"passed\": true}, {\"check\": \"boundary control 1\", \"actual\": 10.0, \"expected\": 10.0, \"passed\": true}, {\"check\": \"boundary control 2\", \"actual\": 10.0, \"expected\": 10.0, \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": 0.0, \"expected\": 0.0, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": 10.0, \"expected\": 10.0, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}